Adding 5+5 is an example of a computation. Why? By definition. "Computation" is a word which refers to calculating stuff like sums, matrix multiplication, binary logic operations, derivatives, etc.

Are all computations math? Sorta. Consider this computation:

(concatenate "cat" "dog")

Which outputs: "catdog"

The format I used is: (function data-1 data-2). That's the best format programmers have invented so far. There can be any number of pieces of data including zero. Quotes indicate a string. And for data you can also put a function which returns data. That's nesting, e.g:

(concatenate "meow" (concatenate "cat" "dog"))

Which outputs: "meowcatdog"

Is that math? It can be done by math. E.g. you can assign each letter a number and manipulate lists of numbers, which is what a Mac or PC would do to deal with this. If you're interested in this topic, you might like reading Godel, Escher, Bach which discusses numeric representations.

But a human might calculate string concatenation in a different way, e.g. by writing each string on a piece of paper and then computing concatenations by taping pieces of paper together.

Humans have a lot of ways to do sums too. E.g. you can compute 5+5 using groups of marbles. If you want to know more about this, you should read David Deutsch's discussion of roman numerals in The Beginning of Infinity, as well as the rest of his books.

Moving on, computation is sorta like math but not exactly. You can think of computation as math or stuff that could be done with math.

A computer is a physical object which can do computations.

We can see that human intelligence involves computation because I can ask you "what is 5+5?" and you can tell me without even using a tool like a calculator. You can do it mentally. So either brains are computers or brains contain computers plus something else. There has to be a computer there somewhere because anything that can add 5+5 is a computer.

But we don't really care about an object which can add 5+5 but which can't compute anything else.

We're interested in computers which can do many different computations. Add lots of different numbers, multiply any matrices, find primes, and even do whatever math or math-equivalent it takes to write and send emails!

We want a general purpose computer. And human intelligence has that too. Humans can mentally compute all sorts of stuff like integrals, factoring, finding the area of shapes, or logic operations like AND, NOT, OR, XOR.

When we say "computer" we normally refer to general purpose computers. Specifically, universal classical computers.

A universal computer is a computer than can compute anything that can be computed. "Classical" refers to computers which don't use quantum physics. Quantum physics allows some additional computations if you build a special quantum computer.

A universal computer sounds really amazing and difficult to create. It sounds really special. But there's something really interesting. All general purpose computers are universal. It only takes a tiny bit of basic functionality to reach universality.

Every iPhone, Android phone, Mac, or PC is a universal computer. Even microwaves and dishwashers use universal computers to control them. The computer in a microwave can do any computation that a $100,000 supercomputer can do. (The microwave computer would take longer and you'd have to plug in extra disks periodically for computations that deal with a lot of data.)

All it takes to be a universal computer is being able to compute one single function: NAND. NAND takes two inputs, each of which is a 1 or 0, and it computes one output, a 1 or 0. NAND stands for "not and" and the rule is: return a 1 if not both inputs are 1.

That's it. You can use NAND to do addition, matrix multiplication, and send emails. You just have to build up the complexity step by step.

There are many other ways to achieve universality. For example, a computer which can compute AND and NOT, individually, is also universal. Being able to do NOT and OR also works. (Again these are simple functions which only have 1's and 0's as inputs and outputs.) If you want to see how they work, there are "truth tables" here which show lists of what the outputs are for all possible inputs: Wikipedia Link.

We can see that the computer aspect of humans is universal because humans can mentally compute NAND, AND and NOT. That's more than enough to indicate universal computation.

To make this more concrete, you can ask me what (AND 1 1) is and I can tell you 1. You can ask me (NOT 0) and I can tell you 1. You can ask me (NAND 1 1) and I can tell you 0. I can do that in my head, no problem. You could too (at least if you learned how). You're capable.

So human thinking works by either:

1. Universal classical computation; or

2. Universal classical computation as well as something else.

I don't think there's a something else because there's nothing humans do, think, say, etc, which requires something else to explain how it's possible. And because no one has proposed any something else that makes sense. I don't believe in magical souls, and I'm certainly not going to start believing in them in order to say, "Humans have a universal classical computer plus a soul, which lets them do exactly the same things a universal classical computer with no soul can do.". That'd be silly. And I don't think an iPhone has a soul in the silicon.

The brains of dogs, cats, parrots and monkeys are also universal classical computers. Remember, that's a low bar. It's actually really hard to make a computer do much of anything without making it universal. You can read about Universal Cellular Automata and how little it takes to get universality if you're interested. How easy universality is to achieve, and how there's an abrupt jump to it (rather than there being half-universal computers) is also explained in The Beginning of Infinity.

I won't go into arguing that cat brains are universal computers here. What I will say, briefly, is in what way humans are different than cats. It's kinda like how a PC is different than an iPhone. It has a different operating system and different apps. That's the basic difference between a person and a cat: different software. The hardware is different too, but the hardware fundamentally has the same capabilities, just like iPhones and PCs have different hardware with the same fundamental capabilities: they can do exactly the same computations. Humans have intelligence software of some sort – software which does intelligent thinking. Cats don't.

I began organizing the current state of the animal rights debate into a discussion tree diagram. I started with Peter Singer because he's a well known intellectual with pro animal rights writing. I will update the diagram or create additional diagrams if some pro animal rights people point me to literature which addresses my unanswered arguments and questions, or make important arguments in the comments below. I hope they'll do that. I prefer pointers to specific parts of literature unless someone wants to first concede that key arguments for animal rights haven't been written down anywhere (and explain why they haven't been).

The diagram is just an outline. For details about a particular part, ask in comments below. The diagram is meant to show (a piece of) the structure of the debate/discussion. It selectively focuses on points Singer raised and points I consider important. I'm sure other people have written relevant things, but I don't know where to find that, I've done some Bing searches unsuccessfully, and I have other research priorities (such as how to have a rational discussion – this is an experiment for that purpose). My relevant expertise is primarily about epistemology, software and science, not the animal rights literature. I've debated ~25 people on these issues but they typically bring up sources like a YouTube video about how an animal did something that seems intelligent to them.

Click the diagram to expand or view the PDF for selectable text. The source links are clickable in the PDF and are Animal Liberation and Animal Liberation at 30.

Update: I explain more of my position, and do some research, in the comments below, and in Discussion about Animal Rights and Popper

Update 2: I wrote Animal Rights Issues Regarding Software and AGI

This discussion is from the Fallible Ideas Discord. Join link.

Context: Discussion Tree: State of Animal Rights Debate and in the comments you'll see that I went to some animal rights forums and asked for responses. And, after they had no literature to refer me to, I got banned from the Ask Yourself vegan debate Discord for not responding fast enough while troubleshooting an audio issue.

TheRat: curi, re the vegan thing. How could science demonstrate that animals can suffer (interpret pain as bad etc...) or how could we falsify that animals are not robots? Would this not require us to understand consciousness first? Would this not be in the realm of philosophy vs science? btw I think you're right but I don't know what would change my mind.
curi: knowledge creating animals. humans routinely do things we can't explain as non-AGI algorithms. let's see an animal do one. it's clearer if you get several different sorts of things, e.g. poetry, engineering, art, chess.
curi: you have to be careful about what counts cuz e.g. beavers do something that could be called engineering. but only a specific type that is encoded in their genes, they don't do it more generally.
curi: i'm not aware of any animal researcher with a halfway sophisticated understanding of what non-AGI software can do who has carefully observed and documented animals to try to show they do anything intelligent.
curi: i am aware of ppl observing carefully and noticing animals being much more algorithmic (or simpler algos) than ppl would naively, unscientifically expect: http://curi.us/272-algorithmic-animal-behavior
curi: i think the reason ppl don't care about this is they assume intelligence is a matter of degree and/or suffering is possible without intelligence
curi: so they consider it an uncontroversial non-issue that e.g. a dolphin is somewhere between 0.1% and 70% as intelligence as a human
curi: rather than understanding there at least might be a jump to universality for intelligence and so you can't just safely assume stuff has medium intelligence anymore than a computer can have a medium computational repertoire
curi: the jump to universality is what polarizes the issue into a binary intelligent or non-intelligent. but ppl don't know about it. so they aren't even trying to show a single thing that any animal has ever done which is incompatible with non-intelligence.
curi: so they haven't.
curi: alternatively they could argue for dualism, animal souls, non-intelligent suffering and differentiate that from information processing and computation, or several other things.
curi: i haven't seen anything that understands software stuff which tries to differentiate suffering from information processing in general without intelligence.
TheRat: Is it possible for animals to suffer without having that universality?
curi: there are no arguments to establish some way that would be possible afaik. i think suffering is related to preference, opinions, values, judgments. i think you have to want, prefer or value X, and be able to form judgments about better and worse, in order to suffer. something along those lines.
curi: if you never consider alternatives, like a rooma algorithm doesn't, then how can you be bothered by the outcome?
TheRat: I've read about Dolphins in captivity that seem to "go insane" and commit suicide. What do you think is going on there?
curi: chess algorithms consider alternative moves in some sense but it's mechanistic, it isn't a value judgment, they just do math about each outcome on the board and play the move that leads to the highest evaluation (or sometimes use a random algorithm among the top few moves to avoid predictability).
curi: re dolphins: sounds like algorithm bugs. animals have plenty of those. it's probably an evolutionary useful thing in some scenarios, like a failsafe where it tries to stop repeating the same actions that aren't working.
curi:

Only after thirty or forty repetitions will the wasp finally drag the caterpillar into its nest without further inspection.

curi: even digger wasps have failsafes where they change behavior after 30-40 repetitions.
curi: (whether an action works being defined in some algorithmic way, not as a value judgment or opinion, and in particular not as something where the creature can create new knowledge and new opinions that aren't in its genes)
curi: my position on animals is awkward to use in debates because it's over 80% background knowledge rather than topical stuff.
curi: that's part of why i wanted to question their position and ask for literature that i could respond to and criticize, rather than focusing on trying to lay out my position which would require e.g. explaining KP and DD which is hard and indirect.
curi: if they'll admit they have no literature which addresses even basic non-CR issues about computer stuff, i'd at that point be more interested in trying to explain CR to them.
TheRat: Yes. I've had that issue when trying to debate people. I'll say something and it flies right past them because they don't have cr background. Most of the time not realizing there is a disagreement there.
curi: it's worse for me in general b/c it's CR and Objectivism and Austrian econ/classical liberalism as major background knowledge ppl don't have. and sometimes other stuff but especially those 3.
curi: i should perhaps add my own additions to CR, especially debating methodology stuff, as an additional thing.
curi: they are within the CR tradition so could go either way on separating. i don't like to separate DD from CR.
curi: programming is another big background knowledge which is relevant in this case but doesn't come up tooooo often.
TheRat: Yes I have no programming knowledge at all so I struggle with the computation stuff from CR and DD.
curi: i don't think it's realistic to have serious opinions about animal rights without knowing how to code, knowing how various video game "AI" algorithms work, stuff like that. also some physics knowledge is important like about what information is and some conception of how computation aka information processing is part of reality.
curi: i don't even know good sources for that physics stuff. i kinda got bits here and there over time from DD. his information flow in the multiverse paper is both technical and largely off topic or unnecessary cuz of the multiverse focus.
TheRat:

i don't think it's realistic to have serious opinions about animal rights without knowing how to code

That sucks. Everytime I have attempted to learn how to code I give up after 1 day. I get bored.
curi: you can't really compare animals to robots if you don't know how robots work. harsh but i don't know a good workaround.
curi: i don't even know where to find one animal rights writer who knows how to code and tries to analyze that stuff.
curi: i don't think most animal rights advocates know of one either...
curi: i imagine i would have gotten replies by now somewhere if ppl actually had answers.
curi: ppl like answering reasonable-seeming opponents who ask for a particular thing and they totally have that covered.
curi: it's like if you go to a Popperian forum and ask if anyone knows any Popper chapters that refute induction, ppl will be happy to answer.
curi: or if you ask for anyone other than Popper with good anti-induction args, someone will want to recommend DD.
curi: but if no one knows any answers then you may be ignored.
curi: like if you go to a Popper forum and ask for his arguments against capitalism and why he rejected Mises, you may not get an answer b/c no1 has an easy or good answer to give. the answer, afaik, is Popper was wrong and actually irrational about that.
curi: if you don't bring up Mises they may point you to some non-technical kinda vague comments here and there that he made, but if you do bring up Mises' treatises Popper certainly made no attempt to answer those and nevertheless formed opinions in contradiction to them, so that's awkward, so it'll be hard to get ppl to engage with that issue.
curi: someone might try claiming that maybe Popper didn't know about Mises or didn't have time to read every possibly-dumb idea and it wasn't his speciality. but that kind of thing is dangerous and in this case will actually get you rekt by documented facts about Popper's awareness of Mises and exposure to ideas of that nature.
curi: so safer not to respond.
TheRat: Popper was friends with Hayek right? Did he disagree with Hayek too? I am very unfamiliar with Popper's political views. What I've read in OSE is actually more epistemology than poli sci or econ.
curi: yes he disagreed with Hayek significantly re capitalism/econ stuff. But hayek was also somewhat of a statist and socialist sympathizer, whereas Mises wasn't.
curi: Hayek was the leader of the Mount Pelerin society meetings which Mises and Popper both went to.
curi: there's a comment in a book by a popper student about Popper disliking and dismissing libertarian-type arguments like Mises, but it doesn't give arguments, nor did Popper. but he wasn't just unaware.
curi: his irrationality on these issues was enough to contradict himself, IMO quite blatantly. advocated freedom ... and TV censorship. advocated freedom and peace ... and the government forcibly taking 51% of all public companies.
curi: he says milder stuff in that direction in OSE. haven't read for ages but he talks about social technology by which he means something along the lines of governments improving at figuring out how to be effective at their policy goals. which sure aren't freedom.
curi: he's of course right that governments do tons of counterproductive and inefficient actions, and that's a big problem, and there's tons of room for improvement there. but he was also making some statist assumptions.

Claim: Animal rights may be refuted by advanced Critical Rationalist (CR) epistemology, including the jump to universality, but most people (pro or anti animal rights) haven’t read and understood The Beginning of Infinity and have a different view of epistemology. Given that ignorance of CR, their belief in animal rights is reasonable. And their failure to understand my questions and challenges of their beliefs is also reasonable. (This claim is based on a comment by TheRat on Discord.)

I disagree with that claim. The purpose of this post is to restate my main question/challenge for animal rights and then to argue that it should be understandable, and be seen as an issue worth answering, by someone who has never heard of CR. The issue is related to software not CR. I will further claim that a non-programmer should be able to understand the question/problem/issue and see that it matters (even though he’ll have a hard time reaching a conclusion about the answer without being able to understand code).

Note: I do have other arguments against animal rights which rely on CR.

The Programmer’s Challenge to Animal Rights

Claim: Animals are complex robots. Humans are different because they have general intelligence – the thing that AGI (Artificial General Intelligence) researchers are trying to program but haven’t yet been able to. All known and documented animal behavior is compatible with animals lacking general intelligence (example).

Animals are built with with different materials (more carbon, less metal). This difference is irrelevant. Similarly, the “artificial” in Artificial General Intelligence doesn’t matter either.

Animals are fundamentally similar to a self-driving car, to board game playing software in a robot with (or without) an arm that can move the pieces around the board, and to “AI” controlled video game characters. Those, like all human-written software that exists today, are all examples of non-AGI (non-general intelligence) algorithms. And the lack of a physical body in some cases important (a robot body could be built and added without changing the intelligence of the software).

Brains of both animals and humans are universal classical computers (Turing complete), just like Macs and iPhones, which run software. The relevant differences are software algorithm differences. People who deny this are ignorant and/or unscientific.

Further Explanation

All software we know how to write today is inadequate to achieve general intelligence. So to claim animals have moral rights like humans, people should argue that animals do things which fundamentally differ from current software. So far I have been unable to find any serious attempt to do this.

Alternatively, someone could come up with a distinguishing feature of software algorithms other than having or lacking general intelligence, show that some animals have that feature, and explain why that feature has moral relevance. I’ve also been unable to find any serious attempt to do this.

Whether general intelligence has moral relevance is non-obvious. Regardless, a reasonable person should agree it might have major moral relevance and therefore this is an issue worth investigating for those curious about animal rights. If there is no animal rights literature trying to do this sort of analysis, and addressing these issues, that’s a significant gap in their arguments.

People denying that general intelligence has moral relevance should specify what else humans have, which robots lack, which they think has moral relevance. A common answer to that is the capacity to suffer. I have been unable to find any animal rights literature that tries to differentiate humans or AGIs from self-driving cars and non-AGI software in terms of ability to suffer. What is it about a human’s software, what trait matters other than general intelligence, that grants the capacity to suffer? If they answered that, then we could investigate whether animal software has that trait or not.

I think capacity to suffer is related to general intelligence because suffering involves making value judgments like not wanting a particular outcome or thinking something is bad. Suffering involves having preferences/wants which you then don’t get. I don’t think it’s possible without the ability to consider alternatives and make value judgments about which you prefer, which requires creative thought and the ability to create new knowledge, think of new things. This is a very brief argument which I’m not going to elaborate on here. My main goal is to challenge animal rights advocates. What is their position on this matter and where are their arguments?

What I’ve mostly found is that people don’t want to think about computer algorithms. They don’t know how to program and they aren’t scientists. They don’t know (or deny without educated arguments) that brains are literally universal classical computers (Turing complete), that information and computation is part of physical reality and physics, that human minds are literally equivalent to some sort of software, and other things like that. That’s OK. Not everyone is an expert.

That’s why I’ve been asking (see the comments in addition to the post) to be referred to literature from someone who does know how to program, understands some of these basic issues, and then makes a case for animal rights. Where are the people with relevant expertise about computers and AGI who favor animal rights and write arguments? I can’t find any. That’s bad for the case for animal rights!

Note: My relevant views on AGI are mainstream for the field. I disagree with the mainstream views in the AGI field on some advanced details, but the basic stuff I’m discussing here is widely agreed on. That doesn’t prove it’s true or anything, but a mainstream view merits some analysis and argument rather than being ignored. (Even obscure views often merit a reply, but I won’t get into that.) If animal rights advocates have failed to consider mainstream AGI ideas, that’s bad.

Consciousness

Besides suffering and general intelligence, the other main trait brought up in animal rights discussions is consciousness. If animals are conscious, that gives them moral value. These three traits are related, e.g. consciousness seems to be a prerequisite of suffering, and consciousness may be a prerequisite or consequence of general intelligence.

What computations, what information processing, what inputs or outputs to what algorithms, what physical states of computer systems like brains indicates or is consciousness? I have the same question for suffering too.

Similar questions can be asked about general intelligence. My answer to that is we don’t entirely know. We haven’t yet written an AGI. So what should we think in the meantime? We can look at whether all animal behavior is consistent with non-AGI, non-conscious, non-suffering robots with the same sorts of features and design as present day software and robots that we have created and do understand. Is there any evidence to differentiate an animal from non-AGI software? I’m not aware of any, although I’ve had many people point me to examples of animal behavior that are blatantly compatible with non-AGI programming algorithms. Humans are different because lots of their behavior is not explainable in terms of current software algorithms. Humans create new knowledge, e.g. about spaceships and vaccines, that isn’t programmed in their genes. And humans do that regarding many different topics, seemingly all, hence the idea of “general” intelligence. I have yet to see evidence that any animal does that on even one topic, let alone generally.

Many of the arguments about consciousness involve the rejection of what I regard as science. E.g. they advocate dualism – they claim that there is something other than the material world. They claim that consciousness is a fundamental, non-physical part of reality. They deny that physics can explain and account for everything that exists.

I regard dualism as bad philosophy but I won’t go into that. I’ll just say that if the case for animal rights relies on the rejection of modern physics and the scientific-materialist view of the world, they’ve got a serious problem which they should address. Where can I read literature telling me why I should change my view of science and accept claims like theirs, which addresses the kind of doubts an atheist who believes in objective physical reality would have? I haven’t gotten any answers to that so far. Instead I’m told assertions which I regard as factually false, e.g. that information is not physical. People who say things like that seem to be unfamiliar with standard views in physics (example paper).

The Argument for Conservatism

Animal rights advocates claim that, if in doubt, we should err on the side of caution. If the science and philosophy of mind isn’t fully figured out, then we should assume animals have moral value just in case they do. Even if there’s only a 1% chance that animals have rights, it’s a bad idea to slaughter them by the millions. I agree.

Pro-life (anti-abortion) advocates make the same argument regarding human fetuses. The science and philosophy aren’t fully settled, so when in doubt we should avoid the chance of murdering millions of human beings, even if it’s a low chance. I agree with that too. I think most animal rights advocates disagree with that or refuse to take it into account so that they can favor abortion. I think this indicates some political bias and double standards. I imagine there are some pro-life animal rights activists, but I think most aren’t, which I think is screwy.

Despite agreeing with these arguments, I’m pro-abortion and pro-slaughtering-farm-animals. The reason I favor abortion is I don’t have any significant doubt about whether a 3 month old fetus, which doesn’t not yet have a brain with electrical activity, is intelligence. I haven’t carefully researched the scientific details about abortion (I would if I was actually deciding the law), but from what I’ve seen, banning third trimester abortions is a reasonable and conservative option.

The reason I favor slaughtering cows is that I have no significant doubt about whether a cow has general intelligence. I’ve seen zero indicators that it does, and I’ve debated many people about this, asked many animal rights advocates for things to read which argue their case, asked for examples of animals doing things which are different than what a non-AGI robot could do, and so on. The total lack of relevant counter-argument from the other side is just the same as with abortion and is about equally conclusive. When all the arguments go one way, one can reasonably reach a conclusion and act on it instead of endlessly doubting. (When argument X has logical priority over Y, then Y is excluded from “all the arguments”. And when argument P is conclusively refuted by argument Q, then P is excluded from “all the arguments”.)

My Expertise

Because I’m asking for arguments from someone familiar with software and AGI rather than from just anyone, I think it’s fair that I share my own background.

I’m a philosopher and programmer. My speciality is epistemology (the philosophy of knowledge, including how to think, learn and reason, and how to evaluate ideas and arguments). I study and contribute to the Critical Rationalist epistemology of Karl Popper and David Deutsch, which I believe is important to making progress on AGI. David Deutsch, a physicist, philosopher and programmer, was my mentor and taught me a lot about philosophy and physics. He’s an award-winning pioneer of quantum computing, a Fellow of the Royal Society, and an author.

I’m a professional programmer with over a decade of work experience, but the software I work on isn’t related to AGI. I’ve read books about AI, watched talks, learned and coded some of the algorithms, talked with people in the field, etc.

Conclusion

Non-programmer animal rights advocates ought to be able to see that someone, some expert, should address the issue of whether humans are animals are differentiated by general intelligence. They should argue that animals have general intelligence (or argue that humans don’t have it) or explain some other sort of software/algorithm/code difference between animals and present day, non-AGI robots and software. If no one can do that and address the computational issues, the remaining option in favor of animal rights is to reject science.

I’m seeking thoughtful, competent written arguments addressing these issues. Blog posts are OK, not just academic material. I challenge anyone who favors animal rights to refer me to such literature in the comments below.

The Cambridge Declaration on Consciousness (2012):

The field of Consciousness research is rapidly evolving. Abundant new techniques and strategies for human and non-human animal research have been developed. Consequently, more data is becoming readily available, and this calls for a periodic reevaluation of previously held preconceptions in this field.

ok

Studies of non-human animals have shown that homologous brain circuits correlated with conscious experience and perception can be selectively facilitated and disrupted to assess whether they are in fact necessary for those experiences. Moreover, in humans, new non-invasive techniques are readily available to survey the correlates of consciousness.

No. Wrong just in this summary, unsourced, and focusing on correlation instead of causation.

You can’t tell what is “necessary” by turning some things on and off. You turn off X and then Y doesn’t happen. Does that mean X is necessary to Y? No, some Z you didn’t consider could cause or allow Y. So they’re making a basic logic error.

And how can you do a correlation study involving “conscious experience” in non-human animals? How do you know if or when they have any conscious experience at all?

The neural substrates of emotions do not appear to be confined to cortical structures.

These people don’t seem to understand the hardware independence of computation. Or they think emotions are non-computational or something. But they don’t explain what they think and address the computer science issues.

In fact, subcortical neural networks aroused during affective states in humans are also critically important for generating emotional behaviors in animals.

Wait lol, after they brought up emotions the next sentence (this one) switches from emotions to “emotional behaviors”. Emotional behaviors are behaviors which look emotional according to some cultural intuitions of some researchers. This ain’t science.

The rest is more of the same crap that doesn’t address the issues or give sources, so I’m stopping now.

In the comments below, reply saying which is the first sentence you disagree with, and why you disagree.

Minds are software. Suffering is a state of mind. Physical information signals, whether from the eyes or from pain nerves, have to be processed by the software before they can cause suffering, be liked or disliked, etc. Before that they're just raw data and no meaning has been determined yet by the conscious mind.

Brains (both human and animal) are universal classical computers. The hardware between humans and some animals is similar. Hardware similarity doesn't tell you about software similarity. Computation is hardware independent. Similar or even identical hardware can run totally different computations. Studying hardware and comparing hardware similarities is a red herring.

All animal behavior follows algorithms specified by their genes. Human genes specify a different type of algorithm – general intelligence – which involves the ability to create/design new knowledge, just as biological evolution created/designed the knowledge of optics in our eyes, the knowledge for how to build a computer out of neurons, the knowledge for what situations a rabbit should run away in, etc. General intelligence is the ability to evolve new knowledge. It’s the ability to replicate ideas with variation and selection, just as biological evolution proceeds by replicating genes with variation and selection. With animals, all the knowledge comes from biological evolution. Humans can do evolution of ideas inside their brains to create new knowledge, animals can’t.

This is a discussion tree based on many discussions with animal welfare advocates related to my Peter Singer discussion tree.

Is it missing an important argument? Comment below about what should be added.

Click the diagram to expand or view the PDF for selectable text.

See also: Posts about animals.

I made Discussion Tree: State of Animal Rights Debate. My tree diagram summarizes pro-animal-rights arguments from Peter Singer and asks some questions about major issues he didn’t cover. It reveals that his arguments were incomplete. The incompleteness I’ve focused on is that they don’t address issues related to computers and software. Maybe animals are like self-driving cars with some extra features, not like humans. Self-driving cars aren’t intelligent, conscious or capable of suffering. Singer doesn’t try to address that issue.

I did additional research to find arguments to add to my discussion tree. I found no answers to basic computer science questions from the animal welfare advocates.

I posted to five pro animal rights forums asking for links to written material (like books, articles, or blog posts) making arguments that Singer didn’t make, so I could read about why they’re right. I received no relevant responses and almost zero interest.

Later, I and others posted to eleven more places. Although this resulted in a bunch of discussion, I was not referred to a single piece of relevant literature. No one had a single piece of evidence to differentiate animals from fancy self-driving cars, nor any substantive argument. Many people insulted me. None had a scientific, materialist worldview, incorporating computer science principles, and could give any argument against my position which is compatible with that type of worldview. Nor did they give arguments that that kind of worldview is false. No one said anything that could plausibly have changed my mind. And people didn’t quote from my discussion tree and respond, nor suggest text for a new node. I linked and documented lots of the discussion on this page.

I was referred to dozens of pieces of literature, but none were relevant. In general, searching for terms like “software”, “hardware”, “algorithm” and “compu” immediately showed the source was irrelevant.

I also went to a vegan Discord for a YouTube debater to ask if they could help me improve my discussion tree diagram. I streamed what happened. Summary: They laughed at my view, then asked me to debate in voice chat (instead of giving literature), then banned me for not responding in 30 seconds while they knew I was busy fixing an audio issue.

This illustrates several things. First, my discussion tree shows how you can begin researching a topic in an organized way. You can pick a topic and create something similar. If you want to learn, it’s a great approach.

Second, there’s a serious lack of interest in discussion or debate in the world, and most people are quite ignorant and don’t even know of sources which argue why their beliefs are correct. They have some sources for why they’re right and rival views X and Y are wrong, but no answer to view Z, and will just keep giving you their answers to X and Y. Are you better or do you know of anyone who is better? Speak up.

Third, animal rights advocates broadly don’t know anything about computers and software and haven’t tried to update their thinking to take that stuff into account. Sad!

I encourage people to try creating a discussion tree on a topic that interests them, then ask for help finding sources and adding arguments to it. See what people, with what conclusions, have anything they’re willing to contribute, or not. You’ll learn a lot about the topic and about the rationality of the advocates of each viewpoint. It’ll help you judge issues yourself instead of deferring to the conclusions of experts (rather than their arguments). Even if you were happy to defer to expert opinions, it’s hard because experts disagree with each other; a discussion tree can help you organize those expert arguments.

You can also use discussion trees to organize and keep track of debates/discussions you have – as the conversation goes along, keep notes in a tree diagram.

I made a video covering these events and more. It’s from when I’d gotten almost no answers, rather than a bunch of bad answers. And I streamed a bunch of my discussions when I got bad answers.

While discussing, I wrote several additional blog posts, including a second discussion tree.

This content was borrowed from my free email newsletter. Sign up here.

TheCriticalRat posted my article Animal Rights Issues Regarding Software and AGI on the Debate A Vegan SubReddit.

This post shares a discussion highlight where I wrote something I consider interesting and important. The main issue is about the inadequacy of academia.

The two large blockquotes are messages from pdxthehunted and the non-quotes are me. I made judgment calls about newline spacing for reproducing pdxthehunted's messages and I changed the format for the two footnotes.

This came up a few weeks ago, when u/curi was posing questions on this subreddit. I looked through some of Elliot's work then and did so again just now. I'm not accusing them of being here in bad faith--they seem like they are legitimately interested in thinking about this topic and are asking interesting questions/making interesting claims.

That being said, they also seem to have little or no formal education in philosophy of mind or AGI. All of their links to who they are circle back to their own commercial website/blog, where they sell their services as a rationalist philosopher/consultant. It appears that they are (mostly) self-taught. Their (supposed)[1] connection to David Deutsch is why I bothered even to look further.

I don't think you need to have a degree to understand even advanced tenets in philosophy of mind or artificial intelligence. The problem here is that Elliot seems to have written an enormous amount--possibly thousands of pages--but has never been published in any peer-reviewed journal (at least none that I have access to through my community college) and so their credibility is questionable. Judging from their previous interactions on this sub, Elliot seems to have created their own curriculum and field of expertise.

I was impressed by the scope and seriousness of their work (the little I took the time to read). Still, it's very problematic for debate: they seem to be looking for someone who has the exact same intellectual background as they do--but without any kind of standardization, it's very hard to know what that is without investing possibly hundreds of hours into reading his corpus. This is the benefit of academic credentials; we can engage with someone under the assumption that they know what they're talking about. Most of Elliot's citations and links are to their own blog--not to any peer-reviewed, actual science. I suspect that's why they've left the caveat that "blog posts are okay."

A very quick browse through Academic Search Premier found over 100 published peer-reviewed journal articles on nonhuman animals and general intelligence. I browsed the abstracts of the first three, all of which discuss general intelligence in nonhuman animals. General intelligence is hard to define--especially in a way that doesn't immediately bias it in favor of humans--but even looking at the usual suspects in cognition demonstrate that many animals possess it unless we move the goalposts to human-specific achievements like writing symphonies or building spacecraft (which of course leaves the vast majority of all humans who've ever existed in the cold).

In short--not to be rude or dismissive--but the reason that animal rights activists aren't concerned about the "algorithms" that animals have that "give them the capacity to suffer" (forgive me if I'm misquoting) is that it is a non-issue. No serious biologists doubt that nonhuman animals (at least mammals and birds) can have preferences for or against different mental states and that those preferences can be frustrated or thwarted. Pain and suffering are fitness-selecting traits that allowed animals to avoid danger and seek nourishment and mates. I'm not an expert in any of your claimed domains; that being said, to believe that consciousness and the capacity to suffer evolved only in one species of primate demonstrates a shockingly naive understanding of evolution, philosophy of mind, cognitive science/neuroscience, and biology.

Similar questions can be asked about general intelligence. My answer to that is we don’t entirely know. We haven’t yet written an AGI. So what should we think in the meantime? We can look at whether all animal behavior is consistent with non-AGI, non-conscious, non-suffering robots with the same sorts of features and design as present day software and robots that we have created and do understand. Is there any evidence to differentiate an animal from non-AGI software? I’m not aware of any, although I’ve had many people point me to examples of animal behavior that are blatantly compatible with non-AGI programming algorithms.

There is no "scoop" here. There are a few serious philosophers I've read--Daniel Dennett, for instance--who I think make similar arguments as you're making here, which we can call the "animals as automata" meme. The very fact that you believe that cows show no more intelligence than a self-driving car makes me feel very suspicious that you don't know what you're talking about. Nick Bostrum basically states in his AI opus Superintelligence that if humans managed to emulate a rodent mind, we would have mostly solved human-level AGI.

To claim that there are "no examples" of an animal doing something that a non-AGI robot couldn't[2] do discredits your entire thesis--you're either woefully misinformed, or disingenuous. Again, I'm very impressed by your (Elliot's) obvious dedication to learning and thinking. Still, I don't think this argument is even to the point where it's refined enough to take seriously. There's so much wrong with it that betrays not just a lack of competence in adjacent disciplines but also an arrogance around the author's imagined brilliance that it feels awkward and unrewarding to engage with.

EDIT 12/2: [1] Connection to Deutsch--though not necessarily relevant to this argument--is not overstated.

[2] Changed would to couldn't

Suppose I'm right about ~everything. What should I do that would fix these problems?

Thanks for the response. Also, I checked the Beginning of Infinity and saw that you don't seem to be exaggerating your claim (obviously you know this--I'm mentioning it for any skeptics). Elliot Temple is not only listed in the acknowledgments of BOI, but they are given special thanks from the author. That's very cool, regardless of anything else. Congratulations. I'm hesitant to do too much cognitive work for you on how to fix your problems--it sounds like you're used to charging people a fair amount of money to do the same. Still, I engaged with you here, so I'll let you know what I think.

Read More

You need to become better read in adjacent fields--cognitive neuroscience, ethology, evolutionary biology, ethics--these are just a few that come up off the top of my head. If you're right about more or less everything, peer-reviewed research done by actual scientists in most of these fields should agree with your thesis. If it doesn't, make a weaker claim.

Publish

Right now, your argument is formatted as a blog post. Anyone with access to a computer is technically capable of self-publishing thousands of pages of their thoughts. Write an article and submit it to an academic journal for peer review. Any publication that survives the peer-review process will give you more credibility. I'm not saying that's fair, but it is a useful heuristic for nonexperts to decide whether or not you are worth their time. An alternative would be to see your blog posts cited in books by experts (for instance, Eliezer Yudkowsky has no formal secondary education, but his ideas are good enough that he is credited by other experts in his field).

Empiricism/Falsifiability

As it currently stands, you're essentially making a claim and insisting that others disprove it. This, of course, is acceptable as a Reddit discussion or a blog post--but is not suitable for uncovering the truth. I can insist that my pet rock has a subjective experience and refuse to believe otherwise unless someone can prove it to me, but I won't be taken seriously (nor should I be). Could you design an experiment that tests a falsifiable claim about nonhuman animal general intelligence? (Or, alternatively, find one that has already been published demonstrating that only humans possess it?) What would it look like?

What computations, what information processing, what inputs or outputs to what algorithms, what physical states of computer systems like brains indicates or is consciousness? I have the same question for suffering too.

We don't know the answer to these questions. Staking your thesis on possible answers to open questions might be a way to stalemate internet debates, but won't deepen your or anyone else's understanding.

Gatekeeping

You're widely read and the depth of your knowledge/understanding in some areas is significant. You need to recognize that some people will have different foundations than yours--they might be very well-read on evolutionary biology--but have less of an understanding of Turing computability. Instead of rudely dismissing arguments that are outside of the disciplines you're most comfortable with, try to meet these people on their level. What do they have to teach you? What thinkers can they expose you to? Your self-curated curriculum is impressive but uneven and far from comprehensive. Try a little humility. Assuming you're right about everything, you should be able to communicate it to experts outside of your field.

Closing

I think that advice is good whether or not you're correct; if you are, people far more intelligent than I should start to recognize it. If you aren't, you might be able to clarify where you went wrong and either abandon your claim or reformulate it to make a weaker--but possibly true--version.

Lastly, I encourage anyone observing from the sidelines to use Google Scholar or similar if you have an interest in animal general intelligence. I linked an article above; here it is again. The article references 60 others and has been cited in 14. This does not mean that the authors' findings are replicable or ironclad, but again--it is a useful heuristic in deciding what kind of probability we want to assign to the likelihood it is on the right track, especially when the alternative is trying to read through hundreds of pages of random blog posts so that we can meet an interlocutor on their level.

To find that article, I searched for "general intelligence in animals" using Academic Search Premier. Pubmed and Google Scholar might find similar results. I filtered out all articles that were not subject to peer review or were published before 2012. It was the 4th search result out of over 50 published in the last seven years. Science may never be finished or solvable, but nonhuman animal's capacity to learn, have intentional states, preferences, and experience pain are not really still open questions in relevant disciplines.

If I'm right about ~everything, that includes my views of the broad irrationality of academia and the negative value of current published research in many of the fields in question.

For example, David Deutsch's static meme idea, available in BoI, was rejected for academic publication ~20 years earlier. Academia gatekeeps to keep out ideas they don't want to hear, and they don't really debate what's true much in journals. It's like a highly moderated forum with biased moderators following unwritten and inconsistent rules (like reddit but stricter!).

My arguments re animals are largely Deutsch's. He taught me his worldview. The reason he doesn't write it up and publish it in a journal is because (he believes that) it either wouldn't be published or wouldn't be listened to (and it would alienate people who will listen to his physics papers). The same goes for many other important ideas he has. Being in the Royal Society, etc., is inadequate to effectively get past the academic gatekeeping (to get both published and seriously, productively engaged with). I don't think a PhD and 20 published papers would help either (especially not with issues involving many fields at once). I don't think people would, at that point, start considering and learning different ideas than what they already have, e.g. learning Critical Rationalism so they could apply that framework to animal rights to reach a conclusion like "If Critical Rationalism is true, then animal rights is wrong." (And CR is not the only controversial premise I use that people are broadly ignorant of, so it's harder than that.) People commonly dismiss others, despite many credentials, if they don't like the message. I don't think playing the game of authority and credentials – an irrational game – will solve the problem of people's disinterest in truth-seeking. This is view of academia is, again, a view Deutsch taught me.

Karl Popper published a ton but was largely ignored. Thomas Szasz too. There are many other examples. Even if I got published, I could easily be treated like e.g. Richard Lindzen who has published articles doubting some claims about global warming.

Instead of rudely dismissing arguments that are outside of the disciplines you're most comfortable with, try to meet these people on their level.

If I'm right about ~everything (premise), that includes that I'm right about my understanding of evolutionary biology, which is an area I've studied a lot (as has Deutsch). That's not outside my comfort zone.

I think that advice is good whether or not you're correct; if you are, people far more intelligent than I should start to recognize it.

We disagree about the current state of the world. How many smart people exist, how many competent people exist in what fields, how reasonable are intellectuals, what sort of things do they do, etc. You mention Eliezer Yudkowsky, who FYI agrees with me about this something like this particular issue, e.g. he denies "civilizational adequacy", and says the world is on fire, in Hero Licenscing. OTOH, he's also the same guy who took moderator action to suppress discussion of Critical Rationalism on his site because – according to him – it was downvoted a lot (factually there were lots of downvotes, but I mean he actually said that was his reason for taking moderator action – so basically just suppressing unpopular ideas on the basis that they are unpopular). He has publicly claimed Critical Rationalism is crap but has never written anything substantive about that and won't debate, answer counter-arguments, or endorse any criticism of Critical Rationalism written by someone else (and I'm pretty confident there is no public evidence that he knows much about CR).

The reason I asked about how to fix this is I think your side of the debate, including academic institutions and their alleged adequacy, are blocking error correction. They don't allow any reasonable or realistic way that, if I'm right, it gets fixed. FYI I've written about the general topic of how intellectuals are closed to ideas and what rational methods of truth seeking look like, e.g. Paths Forward. The basic theme of that article is about doing intellectual activities in such a way that, if you're wrong, and someone knows you're wrong, and they're willing to tell you, you don't prevent them from correcting you. Currently ~everyone is doing that wrong. (Of course there are difficulties like how to do this in a time-efficient manner, which I go into. It's not an easy problem to solve but I think it is solvable.)

Lastly, I encourage anyone observing from the sidelines to use Google Scholar or similar if you have an interest in animal general intelligence. I linked an article above; here it is again.

PS, FYI it's readily apparent from the first sentence of the abstract of that article that it's based on an intellectual framework which contradicts the one in The Beginning of Infinity. It views intelligence in a different way than we do, which must be partly due to some epistemology ideas which are not stated or cited in the paper. And it doesn't contain the string "compu" so it isn't engaging with our framework re computation either (instead it's apparently making unstated, uncited background assumptions again, which I fear may not even be thought through).

I guess you'll think that, in that case, I should debate epistemologists, not animal rights advocates. Approach one of the biggest points of disagreements more directly. I don't object to that. I do focus a lot on epistemology and issues closer to it. The animal welfare thing is a side project. But the situation in academic epistemology has the same problems I talked about in my sibling post and is, overall, IMO, worse. Also, even if I convinced many epistemologists, that might not help much, considering lots of what I was saying about computation is already a standard (sorta, see quote) view among experts. Deutsch actually complains about that last issue in The Fabric of Reality (bold text emphasized by me):

The Turing principle, for instance, has hardly ever been seriously doubted as a pragmatic truth, at least in its weak forms (for example, that a universal computer could render any physically possible environment). Roger Penrose's criticisms are a rare exception, for he understands that contradicting the Turing principle involves contemplating radically new theories in both physics and epistemology, and some interesting new assumptions about biology too. Neither Penrose nor anyone else has yet actually proposed any viable rival to the Turing principle, so it remains the prevailing fundamental theory of computation. Yet the proposition that artificial intelligence is possible in principle, which follows by simple logic from this prevailing theory, is by no means taken for granted. (An artificial intelligence is a computer program that possesses properties of the human mind including intelligence, consciousness, free will and emotions, but runs on hardware other than the human brain.) The possibility of artificial intelligence is bitterly contested by eminent philosophers (including, alas, Popper), scientists and mathematicians, and by at least one prominent computer scientist. But few of these opponents seem to understand that they are contradicting the acknowledged fundamental principle of a fundamental discipline. They contemplate no alternative foundations for the discipline, as Penrose does. It is as if they were denying the possibility that we could travel to Mars, without noticing that our best theories of engineering and physics say that we can. Thus they violate a basic tenet of rationality — that good explanations are not to be discarded lightly.

But it is not only the opponents of artificial intelligence who have failed to incorporate the Turing principle into their paradigm. Very few others have done so either. The fact that four decades passed after the principle was proposed before anyone investigated its implications for physics, and a further decade passed before quantum computation was discovered, bears witness to this. People were accepting and using the principle pragmatically within computer science, but it was not integrated with their overall world-view.

I think we live in a world where you can be as famous as Turing, have ~everyone agree you're right, and still have many implications of your main idea substantively ignored for decades (or forever. Applying Turing to physics is a better result than has happened with many other ideas, and Turing still isn't being applied to AI adequately). As Yudkowsky says, it's not an adequate world.

Update: Read more of this discussion at Discussing Animal Intelligence

I explained on Reddit [one typo is fixed in this post] that intelligence isn't a matter of computing hardware speed.

Sounds like the IQ vs Universality thing is just two camps talking past each other.

Suppose we do believe in the basic premise of universality, that all computers are equally "powerful" in a specific way, namely that there's no problem a sophisticated computer can solve that a simple computer cannot, provided we just give the simple computer a long enough time frame to solve it in.

Fair enough. But surely we're also interested in how fast the computer can solve the problems. That's not a trivial factor, especially when we consider that human computers are prone to getting bored, frustrated, confused, or forgetful.

So maybe when we talk about IQ we're not talking about computational power, but maybe something like computational speed. Or, more likely, computational speed combined with some other personality traits.

I think computational universality helps change the primary point of interest (re intelligence) to software that is created and modified after birth. You think maybe it makes hardware speed the key place to look re intelligence. FYI, your view is something I've already considered and taken into account.

You also think some other (genetic) personality traits may be important to intelligence. I don't think so partly because of a different type of universality: universal intelligence (or universal learning, universal knowledge creating, universal problem solving, same things). Universalities are discussed in The Beginning of Infinity by David Deutsch. It's important, in these discussions, to keep the two types of universalities separate (universal computer; universal learning/thinking software). I won't go into this point further right now. I'm going to talk about the hardware speed issue.

Suppose my brain is 100% faster than yours (which sounds like an unrealistically high difference). You will still outperform me, by far, if you use a better algorithm than I do. E.g. if you use an O(N) algorithm to think about something while I'm using O(N^2).

That's called Big O notation, which basically means how many steps it takes to complete the algorithm. N is the number of data points. In this example, you need time proportional to the amount of data. I need time proportional to the square of the amount of data. So for decent sized data sets, you win even if my hardware is twice as fast. E.g. with 10 data points, you win by a a factor of 5. Taking 2 seconds per step, you need 10 * 2 = 20 seconds. I, doing steps in 1 second, need 10^2 = 100 seconds. How does it scale? With 100 data points, you need 200 seconds and I need 100^2 = 10,000 seconds. Now you won by a factor of 50. That factor will go up if there's more data. And the world has a lot of data.

Exponential differences in Big O complexity between algorithms are common and routinely make a huge difference in processing time – far more than CPU speed. In software we write, lots of work goes into using algorithms that are only sub-optimal by a linear or constant amount.

If people think at different speeds, you should probably blame their thinking method (software) rather than their hardware for well over 99% of the difference. Especially because hardware variation between humans is pretty small.

But most differences in intelligence are not speed differences anyway. For example, often one human solves a problem and another doesn't solve it at all. The second guy doesn't solve it slower, he fails. He gets stuck and gives up, or won't even begin because he knows he doesn't understand how to do it. This is partly because of what knowledge people have or lack (learned information that wasn't inborn), and partly because of thinking methods (e.g. algorithms which could be fast or exponentially slow depending on how well they're designed). With bad algorithms, the time to finish can be a million years while a good algorithm can do the same task in minutes on a slower CPU.

There are other crucial non-hardware issues too, e.g. error correction. If you make a thinking mistake, can you recover from that, identify that something has gone wrong, find the problem, and fix it? Some ways of thinking can accomplish that pretty reliably for a wide variety of errors. But some ways of thinking are quite fragile to error. This is leads to wildly different thinking results that aren't due to hardware speed.

I'll close with an explanation of these issues from David Deutsch, from my interview with him:

David: As to innate intelligence: I don't think that can possibly exist because of the universality of computation. Basically, intelligence or any kind of measure of quality of thinking is a measure of quality of software, not hardware. People might say, "Well, what hardware you have might affect how well your software can address problems." But because of universality, that isn't so: we know that hardware can at most affect the speed of computation. The thing that people call intelligence in everyday life — like the ability of some people like Einstein or Feynman to see their way through to a solution to a problem while other people can't — simply doesn't take the form that the person you regard as 'unintelligent' would take a year to do something that Einstein could do in a week; it's not a matter of speed. What we really mean is the person can't understand at all what Einstein can understand. And that cannot be a matter of (inborn) hardware, it is a matter of (learned) software.

This post replies to pdxthehunted from Reddit (everything he said there is included in quotes below). There is also previous discussion before this exchange, see here. This post will somewhat stand on its own without reading context, but not 100%. Topics include about whether animals can suffer, the nature of intelligence and the flaws of academia.

[While writing this response, the original post was removed. I think that’s unfortunate, but what’s done is done. I’d still love a quick response—just to see if I understand you correctly.]

Hi, Elliot. Thanks for your response. I want to say off the bat that I don’t think I’m equipped to debate the issue at hand with you past this point. (Mostly based off your sibling post; I’m not claiming you’re wrong, but just that I think I—finally—realize that I don’t understand where you’re coming from, entirely (or possibly at all). I’m willing to concede that—if you’re right about everything—you probably do need to have this conversation with programmers or physicists. If the general intelligence on display in the article I cited is categorically different from what you’re talking about when you talk about G.I. than I’m out of my depth.

Yes, what that article is studying is different and I don't think it should be called "general intelligence". General means general purpose, but the kind of "intelligence" in the article can't build a spaceship or write a philosophy treatise, so it's limited to only some cases. They are vague about this matter. They suggest they are studying general intelligence because their five learning tasks are "diverse". Being able to do 5 different learning tasks is a great sign if they are diverse enough, but I don't think they're diverse with respect to the set of all possible learning tasks, I think they're actually all pretty similar.

This is all more complicated because they think intelligence comes in degrees, so they maybe believe a mouse has the right type of intelligence to build a spaceship, just not enough of it. But their research is not about whether that premise (intelligence comes in degrees) is true, nor do they write philosophical arguments about it.

That being said, I’d love to continue the conversation for a little while, if you’re up for it, either here or possibly on your blog if that works better for you. I have some questions and would like to try and understand your perspective.

If I'm right about ~everything, that includes my views of the broad irrationality of academia and the negative value of current published research in many of the fields in question.

For example, David Deutsch's static meme idea, available in BoI, was rejected for academic publication ~20 years earlier. Academia gatekeeps to keep out ideas they don't want to hear, and they don't really debate what's true much in journals. It's like a highly moderated forum with biased moderators following unwritten and inconsistent rules (like reddit but stricter!).

My arguments re animals are largely Deutsch's. He taught me his worldview. The reason he doesn't write it up and publish it in a journal is because (he believes that) it either wouldn't be published or wouldn't be listened to (and it would alienate people who will listen to his physics papers). The same goes for many other important ideas he has. Being in the Royal Society, etc., is inadequate to effectively get past the academic gatekeeping (to get both published and seriously, productively engaged with). I don't think a PhD and 20 published papers would help either (especially not with issues involving many fields at once).

For what it’s worth, I think this is a fair criticism and concern, especially for someone—like you—who is trying to distill specific truths out of many fields at once. If your (and Deutsch’s) worldview conflicts with the prevailing academic worldview, I concede that publishing might be difficult or impossible and not the best use of your energy.

I asked for a solution but I'm happy with that response. I find it a very hard problem.

Sadly, Deutsch has given up on the problem to the point that he's focusing on physics (Constructor Theory) not philosophy now. Physics is one of the best academic fields to interact with, and one of the most productive and rational, while philosophy is one of the worst. Deutsch used to e.g. write about the implications of Critical Rationalism for parenting and education. The applications are pretty direct from philosophy of knowledge to how people learn, but the conclusions are extremely offensive to ~everyone because, basically, ~all parents and teachers are doing a bad job and destroying children's minds (which is one of the main underlying reasons for why academia and many other intellectual things are broken). Very important issues but people shoot messengers... The messenger shooting is bad enough that Deutsch refused me permission to post archived copies of hundreds of things he wrote publicly online but which are no longer available at their original locations. A few years earlier he had said he would like the archives posted. He changed his mind because he became more pessimistic about people reaction's to ideas.

I, by contrast, am pursuing a different strategy of speaking truth to power without regard for offending people. I don't want to hold back, but I also don't have a very large fanbase because even if someone agrees with me about many issues, I have like two dozen different ideas that would alienate many people, so pretty much everyone can find something to hate.

I don't think people would, at that point, start considering and learning different ideas than what they already have, e.g. learning Critical Rationalism so they could apply that framework to animal rights to reach a conclusion like "If Critical Rationalism is true, then animal rights is wrong." (And CR is not the only controversial premise I use that people are broadly ignorant of, so it's harder than that.) People commonly dismiss others, despite many credentials, if they don't like the message. I don't think playing the game of authority and credentials – an irrational game – will solve the problem of people's disinterest in truth-seeking. This is view of academia is, again, a view Deutsch taught me.

Karl Popper published a ton but was largely ignored. Thomas Szasz too. There are many other examples. Even if I got published, I could easily be treated like e.g. Richard Lindzen who has published articles doubting some claims about global warming.

Fair enough.

I’m not going to respond to the rest of your posts line-by-line because I think most of what you’re saying is uncontroversial or is not relevant to the OP (it was relevant to my posts; thank you for the substantial, patient responses).

I think most people would deny most of it. I wasn’t expecting a lot of agreement. But OK, great.

For any bystanders who are interested and have made it this far, I think that this conversation between OP and Elliot is helpful in understanding their argument (at least it was for me).

Without the relevant CS or critical rationality background, I can attempt to restate their argument in a way that seems coherent (to me). Elliot or OP can correct me if I’m way off base.

The capacity for an organism to suffer may be binary; essentially, at a certain level of general intelligence, the capacity to suffer may turn on.

I don’t think there are levels of general intelligence, I think it’s present or not present. This is analogous to there not being levels of computers: it’s either a universal classical computer or it’s not a computer and can compute ~nothing. The jump from ~nothing to universality is discussed in BoI.

Otherwise, close enough.

(I imagine suffering to exist on a spectrum; a human’s suffering may be “worse” than a cow’s or a chicken’s because we have the ability to reflect on our suffering and amplify it by imagining better outcomes, but I’m not convinced that—if I experienced life from the perspective of a cow—that I wouldn’t recognize the negative hallmarks of suffering, and prefer it to end. My thinking is that a sow in a gestation crate could never articulate to herself “I’m uncomfortable and in pain; I wish I were comfortable and pain-free,” but that doesn’t preclude a conscious preference for circumstances to be otherwise, accompanied by suffering or its nonhuman analog.)

I think suffering comes in degrees if it’s present at all. Some injuries hurt more than others. Some bad news is more upsetting than other bad news.

Similarly, how smart people are comes in degrees when intelligence is present. They have the same basic capacity but vary in thinking quality due to having e.g. different ideas and different thinking methods (e.g. critical rationalist thinking is more effective than superstition).

Roughly there are three levels like this:

1. Computer (brain)
2. Intelligent Mind (roughly: an operating system (OS) for the computer with the feature that it allows creating and thinking about ideas)
3. Ideas within the mind.

Each level requires the previous level.

Sand fails to match humans at level 1. No brain.

Apes fail to match humans at level 2. They run a different operating system with features more similar to Windows or Mac than to intelligence. It doesn’t have support for ideas.

Self-driving cars have brains (CPUs) which are adequately comparable to an ape or human, but like apes they differ from humans at level 2.

When Sue is cleverer than Joe, that’s a level 3 difference. She doesn’t have a better brain (level 1), nor a better operating system (level 2), she has better ideas. She has some knowledge he doesn’t. That includes not just knowledge of facts but also knowledge about rationality, about how to think effectively. E.g. she knows some stuff about how to avoid bias, how to find and correct errors effectively, how to learn from criticism instead of getting angry, or how to interpret disagreements as disagreements instead of as other things like heresy, bad faith, or “not listening”.

Small hardware differences between people are possible. Sue’s brain might be a 5% faster computer than Joe’s. But this difference is unimportant relative to the impact of culture, ideas, rationality, bias, education, etc. Similarly, small OS differences are possible but they wouldn’t matter much either.

There are some complications. E.g. imagine a society which extensively tested children on speed of doing addition problems in their head. They care a ton about this. The best performers get educated to be scientists and lower performers do unskilled laborer. Someone with a slightly faster brain or slightly different OS might do better on those tests. Those tests limit the role of ideas. So, in this culture, a small hardware speed advantage could make a huge difference in life outcome including how clever the person is as an adult (due to huge educational differences which were caused by differences in arithmetic speed). But the same hardware difference could have totally different results in a different culture, and in a rational culture it wouldn’t matter much. What differentiates knowledge workers IRL, including scientists and philosophers, is absolutely nothing like that the 99th percentile successful guys are able to get equal quality work done 5% faster than the 20th percentile guys.

Our actual culture has some stuff kinda like this hypothetical culture, but much more accidental and with less control over your life (there are many different paths to success, so even if a few get blocked, you don’t have to do unskilled labor). It also has similar kinda things based on non-mental attributes like skin color, height, hair color, etc, though again with considerably smaller consequences than the hypothetical where your whole fate is determined just by addition tests.

Back to my interpretation of the argument: Beneath a certain threshold of general intelligence, pain—or the experience of having any genetically preprogrammed preference frustrated—may not be interpreted as suffering in the way humans understand it and may not constitute suffering in any meaningful or morally relevant way (even if you otherwise think we have a moral obligation to prevent suffering where we can).

It’s possible that suffering requires uniquely human metacognition; without the ability to think about pain and preference frustration abstractly, animals might not suffer in any meaningful sense.

This is a reasonable approximation except that I think preferences are ideas and I don’t think animals have them at all (not even preprogrammed).

So far (I hope) all I’ve done is restate what’s already been claimed by Elliot in his original post. Whether I’ve helped make it any clearer is probably an open question. Hopefully, Elliot can correct me if I’ve misinterpreted anything or if I’ve dumbed it down to a level where it’s fundamentally different from the original argument.

This is where I think it gets tricky and where a lot of miscommunication and misunderstanding has been going on. Here is a snippet of the conversation I linked earlier:

curi: my position on animals is awkward to use in debates because it's over 80% background knowledge rather than topical stuff.

curi: that's part of why i wanted to question their position and ask for literature that i could respond to and criticize, rather than focusing on trying to lay out my position which would require e.g. explaining KP and DD which is hard and indirect.

curi: if they'll admit they have no literature which addresses even basic non-CR issues about computer stuff, i'd at that point be more interested in trying to explain CR to them.

I’m willing to accept that Elliot is here in good faith; nothing I’ve read on their blog thus far looks like an attempt to “own the soyboys” or “DESTROY vegan arguments.” They’re reading Singer (and Korsgaard) and are legitimately looking for literature that compares or contrasts nonhuman animals with AI.

The problem is—whether they’re right or not—it seems like the foundation of their argument requires a background in CR and theoretical computer science.

Yes.

My view: if you want to figure out what’s true, a lot of ideas are relevant. Gotta learn it yourself and/or find a way to outsource some of the work. So e.g. Singer needs to read Popper and Deutsch or contact some people competent to discuss whether CR is correct and its implications. And Singer also needs to contact some computer people and ask them and try to meet them in the middle by explaining some of what he does to them so they understand the problems he’s working on, and then they explain some CS principles to him and how they apply to his problems. Something like that.

That is not happening.

It ought to actually be easier than that. Instead of contacting people Singer or anyone else could look at the literature. What criticisms of CR have been written? What counter-arguments to those criticisms have CR advocates written? How did those discussions end? You can look at the literature and get a picture of the state of the debate and draw some conclusions from that.

I find people don’t do this much or well. It often falls apart in a specific way. Instead of evaluating the pro-CR and anti-CR arguments – seeing what answers what, what’s unanswered, etc. – they give up on understanding the issues and just decide to assume the correctness of whichever side has a significant lead in popularity and prestige.

The result is, whenever some bad ideas and irrational thinkers become prestigious in a field, it’s quite hard to fix because people outside the field largely refuse to examine the field and see if a minority view’s arguments are actually superior.

Also, often people just use common sense about what they assume would be true of other fields instead of consulting literature. So e.g. rather than reading actual inductivist literature (induction is mainstream and is one of the main things CR rejects), most animal researchers and others rely on what they’ve picked up about induction, here and there, just from being part of an intellectual subculture. Hence there exist e.g. academic papers studying animal intelligence that don’t cite even mainstream epistemology books or papers.

The current state of the CR vs. induction debate, in my considered and researched opinion, is there don’t actually exist criticisms of CR from anyone who has understood it, and there’s very little willingness to engage in debate by any inductivists. Inductivists are broadly uninterested in learning about a rival idea which they have not understood or refuted. I think ignoring ideas that no one has criticized is something of a maximum for a type of irrationality. And people outside the field (and in the field too) mostly assume that some inductivists somewhere did learn and criticize CR, though people usually don’t have links to specific criticisms, which is a problem. I think it’s important to have sources in other fields that aren’t your own so that if your sources are incorrect they can be criticized and corrected and you can change your mind, whereas if you just say “people in the field generally conclude X” without citing any particular arguments then it’s very hard to continue the discussion and correct you about X from there.

From my POV, (a) the argument that suffering may be binary vs. occurring on a spectrum is possible but far from settled and might be unfalsifiable. From my POV, it’s far more likely that animals do suffer in a way that is very different from human suffering but still ethically and categorically relevant.

That’s a reasonable place to start. What I can say is that if you investigate the details, I think they come out particular way rather conclusively. (Actually the nature of arguments, and what is conclusive vs. unsettled – how to evaluate and think about that – is a part of epistemology, it’s one of the issues I think mainstream epistemology is wrong about. That’s actually the issue where I made my largest personal contribution to CR.)

If you don’t want to investigate the details, has anyone else done so as your proxy or representative? Has Singer or any other person or group done that work for you? Who has investigated, reached a conclusion, written it up, and you’re happy with what they did? If no one has done that, that suggests something is broken with all the intellectuals on your side – there may be a lot of them, but between all of them they aren’t doing much relevant thinking.

In some ways, the more people believe something and still no one writes detailed arguments and addresses rival ideas well, the more damning it is. In other words, CR has the excuse of not having essays to cover every little detail of every mainstream view because there aren’t many of us to write all that and we have ~no funding. The other side has no such excuse yet they’re the side, between all those people, has no representatives who will debate! They have plenty of people to have some specialists in refuting CR but they don’t have any.

Sadly, the same pattern repeats in other areas, e.g. The Failure of the 'New Economics’ by Henry Hazlitt is a point-by-point book-length refutation of Keynes’ main book. It uses tons of quotes from Keynes, similar to how I’m replying his this comment using quotes from pdxthehunted. As far as I know, Hazlitt’s criticisms went unanswered. Note: I think Hazlitt’s level of fame/prestige was loosely comparable to Popper and more than Deutsch; it’s not like he was ignored for being a nobody (which I’d object to too, but that isn’t what happened).

Large groups of people ignore critical arguments. What does it mean for intellectuals to rationally engage with critics and how can we get people to actually do that? I think it’s one of the world’s larger problems.

new_grass made a few posts that more eloquently describe that perspective; humans, yelping dogs, and so on evolved from a common ancestor and it seems unlikely that suffering is a uniquely human feature when so many of our other cognitive skills seem to be continuous with other animals.

New_grass says:

link

But this isn't the relevant proposition, unless you think the probability that general intelligence (however you are defining it) is required for the ability to suffer or be conscious is one. And that is absurd, given our current meager understanding of consciousness.

The relevant question is what the probability is that other animals are conscious, or, if you are a welfarist, whether they can suffer. And that probability is way higher than zero, for the naturalistic reasons I have cited.

But according to Elliot, our judgment of the conservatism argument hinges on our understanding of CR and Turing computability.

Does the following sound fair?

Yeah, I have arguments here covering other cases (the cases of the main issue being suffering or consciousness rather than intelligence) and linking the other cases to the intelligence issue. I think it’s linked.

If pdxthehunted had an adequate understanding of the Turing principle and CR and their implications on intelligence and suffering, their opinion on *(a)** would change; they would understand why suffering certainly does occur as a binary off/on feature of sufficiently intelligent life.*

In short, yes. Might have to add a few more pieces of background knowledge.

Please let me know if I’ve managed to at least get a clearer view of the state of the debate and where communication issues are popping up.

Frankly, I’ve enjoyed this thread. I’ve learned a lot. I bought DD’s BOI a couple of years ago after listening to his two podcasts with Sam Harris, but never got around to reading it. I’ve bumped it up to next on my reading list and am hoping that I’m in a better position to understand your argument afterward.

Yeah, comprehensive understanding of DD’s two books covers most of the main issues. That’s hard though. I run the forums where people reading those books (or Popper) can ask questions (it’s this website and an email group with a 25 year history, where DD used to write thousands of posts, but he doesn’t post anymore).

Finally--if capacity for suffering hinges on general intelligence, is consciousness relevant to the argument at all?

To a significant extent, I leave claims about consciousness out of my arguments. I think consciousness is relevant but isn’t necessary to say much about to reach a conclusion. I do have to make some claims about consciousness, which some people find pretty easy to accept, but others do deny. These claims include:

1. Dualism is false.
2. People don’t have souls and there’s no magic involved with minds.
3. Consciousness is an emergent property of some computations.
4. Computation is a purely physical process that is part of physics and obeys the laws of physics. Computers are regular matter like rocks.
5. Computation takes information as input and outputs information. Information is a physical quantity. It’s part of the physical world.
6. Some additional details about computation, along similar lines, to further rule out views of consciousness that are incompatible with my position. Like I don’t think consciousness can be a property of particular hardware (like organic molecules – molecules with carbon instead of silicon) because of the hardware independence of computation.
7. I believe that consciousness is an emergent property of (general) intelligence. That claim makes things more convenient, but I don’t think it’s necessary. It’s a stronger claim than necessary. But it’s hard to explain or discuss a weaker and adequate claim. There aren’t currently any known alternative claims which make sense given my other premises including CR.

One more thing. The “general intelligence” terminology comes from the AI field which calls a Roomba’s algorithms AI and then differentiates human-type intelligence from that by calling it AGI. The concept is that a Roomba is intelligent regarding a few specific tasks while a human is able to think intelligently about anything. I’d prefer to say humans are intelligent and a Roomba or mouse is not intelligent. This corresponds to how I don’t call my text editor intelligent even though, e.g., it “intelligently” renumbered the items in the above list when I moved dualism to the top. In my view, there’s quite a stark contrast between humans – which can learn, can have ideas, can think about ideas, etc. – and everything else which can’t do that at all and has nothing worthy of the name “intelligence”. The starkness of this contrast helps explain why I reach a conclusion rather than wanting to err on the side of caution re animal welfare. A different and more CR-oriented explanation of the difference is that all knowledge creation functions via evolution (not induction) and only humans have the (software) capacity to do evolution of ideas within their brains. (Evolution = replication with variation and selection.)

That’s just the current situation. I do think we can program an AGI which will be just like us, a full person. And yes I do care about AGI welfare and think AGIs should have full rights, freedoms, citizenship, etc. (I’m also, similarly, a big advocate of children’s rights/welfare and I think there’s something wrong with many animal rights/welfare advocates in general that they are more concerned about animal suffering than the suffering of human children. This is something I learned from DD.) I think it’s appalling that in the name of safety (maybe AGIs will want to turn us into paperclips for some reason, and will be able to kill us all due to being super-intelligent) many AGI researchers advocate working on “friendly AI” which is an attempt to design an AGI with built-in mind control so that, essentially, it’s our slave and is incapable of disagreeing with us. I also think these efforts are bound to fail on technical grounds – AGI researchers don’t understand BoI either, neither its implications for mind control (which is an attempt to take a universal system and limit it with no workarounds, which is basically a lost cause unless you’re willing to lose virtually all functionality) nor its implications for super intelligent AGIs (they’ll just be universal knowledge creators like us, and if you give one a CPU that is 1000x as powerful as a human brain then that’ll be very roughly as good as having 1000 people work on something which is the same compute power.). This, btw, speaks to the importance of some interdisciplinary knowledge. If they understood classical liberalism better, that would help them recognize slavery and refrain from advocating it.

curi: The trait that differentiates humans from non-human animals, in a veganism-relevant way, is (general, universal) intelligence, which is the ability to learn (aka create knowledge), which is the ability to do evolution of ideas within one's mind.

This is a binary trait, not a matter of degree.

This is not a complete explanation, e.g. it doesn't say how that trait relates to other issues vegans may bring up like consciousness or suffering.

Vegans: What about mentally handicapped people. If they have less intellectual capacity than a cow, is it OK to kill them?

curi: Yes, in principle. They're (by premise) on the wrong side of the intelligence/non-intelligence asymmetry.

However, we should begin our discussion with cases which are easier to understand and potentially agree about, not hard cases or edge cases. If you understand and agree with my way of differentiating most humans from cows, then it'd make sense to discuss edge cases in detail.

Vegans: How do you tell if a normal person or cow is intelligent?

curi: Primarily behavior: people have intelligent conversations, write blog posts demonstrating that they understand TV show plots, act according to learned jobs skills, develop new science, etc. That is best explained by knowledge the person created in his mind rather than by genetic knowledge. Animals behave in simplistic, algorithmic ways which are best explained by the knowledge in their genes.

I think careful analysis of animal behavior, and trying to differentiate it from the capabilities of stuff like video game enemies and self-driving cars, is one of the more productive ways to continue this discussion. People have strong intuitions that animals are somewhat intelligent and are clearly different, in terms of intelligence, than current robots and "AI" software algorithms. Relatedly, people believe intelligence is a matter of degree. Looking at rigorous information of animal behavior, from scientists, and carefully considering the simplest ways it could be achieved, can be informative.

This is an answer to Name That Trait which asks what trait differentiates humans from animals. The named trait should justify vegan-objectionable activities such as slaughtering animals for food.

Short answer: the trait is being a universal knowledge creator. This answer relies on lots of non-standard background knowledge such as The Beginning of Infinity.

This post gives a different argument which I think is easier to understand with less background knowledge. It will still require going over some background.

The Problem of Design

An important problem in the history of philosophy is the problem of design, famously argued by William Paley. It says some objects (such as an animal or pocket watch) have the appearance of design which requires explanation. Paley’s explanation was that a pocket watch has an intelligent, human designer, and animals were designed by God.

Plants, animals and pocket watches have the appearance of design. They’re complex. Stones, crystals, dirt and stars don’t. This is a big difference. Stones and stars are worth explaining in terms of fundamental physics like the big bang, but plants merit additional explanation. Plants e.g. have chloroplasts which do photosynthesis, which are nothing like rocks and wouldn’t be created randomly or purposelessly.

The above is widely accepted. What’s not widely known is that “appearance of design” is knowledge. Knowledge is information adapted to a purpose.

The underlying problem is how knowledge can be created starting with non-knowledge. Where can new knowledge come from? How can it originate?

This is a hard problem and not many answers have been proposed. The bad answers include magic, knowledge is just created sometimes out of thin air, and designers. Saying that a designer created the knowledge doesn’t explain how the designer created the knowledge (using intelligence – but how does intelligence work?), nor where that designer’s intelligence came from. If you say knowledge comes from God who already has tons of knowledge, then where did God come from?

A single good answer has been developed. It’s the only known answer that makes much sense. It’s the theory of evolution. Replication with variation and selection is able to adapt information to a purpose and thereby create new knowledge. The appearance of design, in plants and animals, was created by evolution.

Where did eyes come from? Evolution. Why does a rabbit run away from danger? It evolved to do that. Why are trees structured in an organized way with the leaves on top where they can better receive light? Because that structure has better survival and replication value for trees (survival and replication value is the short answer for what biological evolution selects for). Etc. This is widely accepted.

With this background in mind:

Intelligence

How does intelligence work and create new knowledge? I believe intelligence works by evolution, literally, not as an analogy. (Seriously I find that 90% of people assume I mean an analogy even though I just told them I didn’t.) This is not a mainstream view. It’s been developed by Critical Rationalist philosophers, especially David Deutsch.

Biological evolution does replication with variation and selection of genes. Intellectual evolution does replication with variation and selection of ideas. Genes and ideas are both things which it’s possible to make copies of – replicators – so evolution applies to them.

FYI, the view that evolution applies to replicators is a fairly standard view in the field even though most of the public is ignorant of it. It’s held by e.g. Richard Dawkins and is why he developed the idea of a “meme” (which means an idea that replicates). A meme plays the role in the evolution of ideas that a gene plays in the evolution of plants and animals.

Name That Trait

Lots of animal behavior has the appearance of design (or the appearance of intelligence or purposefulness). This indicates knowledge is involved. I think that knowledge comes from the animal’s genes and was created by biological evolution. I think it’s this appearance of intelligent behavior that is the primary reason people (correctly) differentiate animals from rocks.

Human behavior also has the appearance of design, so what’s the difference? Humans create new knowledge that isn’t in their genes. Instead of relying only on biological evolution for knowledge, humans do intelligent evolution of ideas within their minds. This is a capacity that no animal has and explains why only humans were able to invent philosophy and science.

When an animal does intelligent-appearing behavior, the designer was biological evolution. When a human does intelligent-appearing behavior, the designer is usually a human being who created ideas using mental evolution of ideas.

Animals have one source of knowlege: genetic evolution. Humans have two sources of knowledge: genetic and memetic evolution.

People commonly assume that the appearance of design in animal behavior is an indicator of intelligence, while the appearance of design in an animal’s eyes and claws is not. The primary mechanism by which genes control animal behavior is through creating the animal’s brain according to a design detailed in the animal’s genes. The animal brain is a computer which the genes build and configure with behavioral algorithms. Humans work differently because they’re capable of doing evolution within their minds to create new algorithms, new behaviors, new ideas. etc.

Getting from these claims to a full case against animal welfare or rights requires additional arguments. I won’t detail them here but see this post for some explanation. The basic issue is that animals aren’t differentiated from rocks in a relevant way because genes (which are where the knowledge is) are not conscious and can’t suffer (like rocks), and animals behave according to algorithms in conceptually the same way as a robot like a self-driving car.

For more info, see e.g. Evolution and Knowledge, Evolution, and the books of David Deutsch and Richard Dawkins.

Is animal welfare a key issue that we should work on? If so, what are productive things to do about it?

This article is a fairly high level overview of some issues, which doesn’t attempt to explain e.g. the details of Popperian epistemology.

Human Suffering

Humans suffer and die, today, a lot. Look at what’s going on in Iran, Ukraine, Yemen, North Korea, Venezuela and elsewhere. This massive human suffering should, in general, be our priority before worrying about animals much.

People lived in terrible conditions, and died, building stadiums for the World Cup in Qatar. Here’s a John Oliver video about it. They were lied to, exploited, defrauded, and basically (temporarily) enslaved etc. People sometimes die in football (soccer) riots too. I saw a headline recently that a second journalist died in Qatar for the World Cup. FIFA is a corrupt organization that likes dictators. Many people regard human death as an acceptable price for sports entertainment, and many more don’t care to know the price.

There are garment workers in Los Angeles (USA) working in terrible conditions for illegally low wages. There are problems in other countries too. Rayon manufacturing apparently poisons nearby children enough to damage their intelligence due to workers washing off toxic chemicals in local rivers. (I just read that one article; I haven’t really researched this but it seems plausible and I think many industries do a lot of bad things. There are so many huge problems in human civilization that even reading one article per issue would take a significant amount of time and effort. I don’t have time to do in-depth research on most of the issues. Similarly, I have not done in-depth research on the Qatar World Cup issues.)

India has major problems with orphans. Chinese people live under a tyrannical government. Human trafficking continues today. Drug cartels exist. Millions of people live in prisons. Russia uses forced conscription for its war of aggression in Ukraine.

These large-scale, widespread problems causing human suffering seem more important than animal suffering. Even if you hate how factory farms treat animals, you should probably care more that a lot of humans live in terrible conditions including lacking their freedom in major ways.

Intelligence

Humans have general, universal intelligence. They can do philosophy and science.

Animals don’t. All the knowledge involved in animal behavior comes from genetic evolution. They’re like robots created by their genes and controlled by software written by their genes.

Humans can do evolution of ideas in their minds to create new, non-genetic knowledge. Animals can’t.

Evolution is the only known way of creating knowledge. It involves replication with variation and selection.

Whenever there is an appearance of design (e.g. a wing or a hunting behavior), knowledge is present.

People have been interested in the sources of knowledge for a long time, but it’s a hard problem and there have been few proposals. Proposals include evolution, intelligent design, creationism, induction, deduction and abduction.

If non-evolutionary approaches to knowledge creation actually worked, it would still seem that humans can do them and animals can’t – because there are human scientists and philosophers but no animal scientists or philosophers.

Human learning involves guessing or brainstorming (replication with variation) plus criticism and rejecting refuted ideas (selection). Learning by evolution means learning by error correction, which we do by creating many candidate ideas (like a gene pool) and rejecting ideas that don’t work well (like animals with bad mutations being less likely to have offspring).

Also, since people very commonly get this wrong: Popperian epistemology says we literally learn by evolution. It is not a metaphor or analogy. Evolution literally applies to both genes and memes. It’s the same process (replication with variation and selection). Evolution could also work with other types of replicators. For general knowledge creation, the replicator has to be reasonably complex, interesting, flexible or something (the exact requirements aren’t known).

Types of Algorithms

All living creatures with brains have Turing-complete computers for brains. A squirrel is a reasonable example animal. Let’s not worry about bacteria or worms. (Earthworms apparently have some sort of brain with only around 300 neurons. I haven’t researched it.)

Humans have more neurons, but the key difference between humans and squirrels is the software our brains run.

We can look at software algorithms in three big categories.

1. Fixed, innate algorithm
2. “Learning” algorithms which read and write data in long-term memory
3. Knowledge-creation algorithm (evolution, AGI)

Fixed algorithms are inborn. The knowledge comes from genes. They’re complete and functional with no practice or experience.

If you keep a squirrel in a lab and never let it interact with dirt, and it still does behaviors that seem designed for burying nuts in dirt, that indicates a fixed, innate algorithm. These algorithms can lead to nonsensical behavior when taken out of context.

There are butterflies which do multi-generation migrations. How do they know where to go? It’s in their genes.

Why do animals “play”? To “learn” hunting, fighting, movement, etc. During play, they try out different motions and record data about the results. Later, their behavioral algorithms read that data. Their behavior depends partly on what that data says, not just on inborn, genetic information.

Many animals record data for navigation purposes. They look around, then can find their way back to the same spot (long-term memory). They can also look around, then avoid walking into obstacles (short-term memory).

Chess-playing software can use fixed, innate algorithms. A programmer can specify rules which the software follows.

Chess-playing software can also involve “learning”. Some software plays many practice games against itself, records a bunch of data, and uses that data in order to make better moves in the future. The chess-playing algorithm takes into account data that was created after birth (after the programmer was done).

I put “learning” in scare quotes because the term often refers to knowledge creation (evolution) which is different than an algorithm that writes data to long-term data storage then uses it later. When humans learn at school, it’s not the same thing as e.g. a “reinforcement learning” AI algorithm or what animals do.

People often confuse algorithms involving long-term memory, which use information not available at birth, with knowledge creation. They call both “learning” and “intelligent”.

They can be distinguished in several ways. Is there replication with variation and selection, or not? If you think there’s evolution, can it create a variety of types of knowledge, or is it limited to one tiny niche? If you believe a different epistemology, you might look for the presence of inductive thinking (but Popper and others have refuted induction). There are other tests and methods that can be used to identify new knowledge as opposed to the downstream consequences of existing knowledge created by genetic evolution, by a programmer, or by some other sort of designer.

Knowledge

What is knowledge? It’s information which is adapted to a purpose. When you see the appearance of design, knowledge is present. Understanding the source of that knowledge is often important. Knowledge is one of the more important and powerful things in the universe.

Binary Intelligence or Degrees?

The word “intelligence” is commonly used with two different meanings.

One is a binary distinction. I’m intelligent but a rock or tree isn’t.

The other meaning is a difference in degree or amount of intelligence: Alice is smarter than Joe but dumber than Feynman.

Degrees of intelligence can refer to a variety of different things that we might call logical skill, wisdom, cleverness, math ability, knowledge, being well spoken, scoring well on tests (especially IQ tests, but others too), getting high grades, having a large vocabulary, being good at reading, being good at scientific research or being creative.

There are many different ways to use your intelligence. Some are more effective than others. Using your intelligence effectively is often called being highly intelligent.

Speaking very roughly, many people believe a chimpanzee or dog is kind of like a 50 IQ person – intelligent, but much less intelligent than almost all humans. They think a squirrel passes the binary intelligence distinction to be like a human not a rock, but just has less intelligence. However, they usually don’t think a self-driving car, chat bot, chess software or video game enemy is intelligent at all – that’s just an algorithm which has a lot of advantages compared to a rock but isn’t intelligent. Some other people do think that present-day “AI” software is intelligent, just with a low degree of intelligence.

My position is that squirrels are like self-driving cars: they aren’t intelligent but the software algorithm can do things that a rock can’t. A well designed software algorithm can mimic intelligence without actually having it.

The reason algorithms are cleverer than rocks is they have knowledge in them. Creating knowledge is the key thing intelligence does that makes it seem intelligent. An algorithm uses built-in knowledge, while intelligences can create their own knowledge.

Basically, anything with knowledge seems either intelligent or intelligently-designed to us (speaking loosely and counting evolution as an intelligent designer). People tend to assume animals are intelligent rather than intelligently-designed because they don’t understand evolution or computation very well, and because the animals seem to act autonomously, and because of the similarities between humans and many animals.

Where does knowledge come from? Evolution. To get knowledge, algorithms need to either evolve or to have an intelligent designer. An intelligent designer, such a human software developer, creates the knowledge by evolving ideas about the algorithm within his brain. So the knowledge always comes from evolution. Evolution is the only known solution to how new knowledge can be created which isn’t refuted.

(General intelligence may be an “algorithm” in the same kind of sense that e.g. “it’s all just math”. If you want to call it an algorithm, then whenever I write “algorithm” you can read it as e.g. “algorithm other than general intelligence”.)

Universality

There are philosophical reasons to believe that humans are universal knowledge creators – meaning they can create any knowledge that any knowledge creator can create. The Popperian David Deutsch has written about this.

This parallels how the computer I’m typing on can compute anything that any computer can compute. It’s Turing-complete, a.k.a. universal. (Except quantum computers have extra abilities, so actually my computer is a universal classical computer.)

This implies a fundamental similarity between everything intelligent (they all have the same repertoire of things they can learn). There is no big, bizarre, interesting mind design space like many AGI researchers believe. Instead, there are universally intelligent minds and not much else of note, just like there are universal computers and little else of interest. If you believe in mind design space like Eliezer Yudkowsky does, it’s easy to imagine animals are in it somewhere. But if the only options for intelligence are basically universality or nothing, then animals have to be like humans or else unintelligent – there’s no where else in mind design space for them to be. If the only two options are basically that animals are intelligent in the same way as humans (universal intelligence), or aren’t intelligent, then most people will agree that animals aren’t intelligent.

This also has a lot of relevance to concerns about super-powerful, super-intelligent AGIs turning us all into paperclips. There’s actually nothing in mind design space that’s better than human intelligence, because human intelligence is already universal. Just like how there’s nothing in classical computer design space that’s better than a universal computer or Turing machine.

A “general intelligence” is a universal intelligence. A non-general “intelligence” is basically not an intelligence, like a non-universal or non-Turing-complete “computer” basically isn’t a computer.

Pain

Squirrels have nerves, “pain” receptors, and behavioral changes when “feeling pain”.

Robots can have sensors which identify damage and software which outputs different behaviors when the robot is damaged.

Information about damage travels to a squirrel’s brain where some behavior algorithms use it as input. It affects behavior. But that doesn’t mean the squirrel “feels pain” anymore than the robot does.

Similarly, information travels from a squirrel’s eyes to its brain where behavioral algorithms take it into account. A squirrel moves around differently depending on what it sees.

Unconscious robots can do that too. Self-driving car prototypes today use cameras to send visual information to a computer which makes the car behave differently based on what the camera sees.

Having sensors which transmit information to the brain (CPU), where it is used by behavior-control software algorithms, doesn’t differentiate animals from present-day robots.

Suffering

Humans interpret information. We can form opinions about what is good or bad. We have preferences, values, likes and dislikes.

Sometimes humans like pain. Pain does not automatically equate to suffering. Whether we suffer due to pain, or due to anything else, depends on our interpretation, values, preferences, etc.

Sometimes humans dislike information that isn’t pain. Although many people like it, the taste of pizza can result in suffering for someone.

Pain and suffering are significantly different concepts.

Pain is merely a type of information sent from sensors to the CPU. This is true for humans and animals both. And it’d be true for robots too if anyone called their self-damage related sensors “pain” sensors.

It’s suffering that is important and bad, not pain. Actually, being born without the ability to feel pain is dangerous. Pain provides useful information. Being able to feel pain is a feature, not a bug, glitch or handicap.

If you could disable your ability to feel pain temporarily, that’d be nice sometimes if used wisely, but permanently disabling it would be a bad idea. Similarly, being able to temporarily disable your senses (smell, touch, taste, sight or hearing) is useful, but permanently disabling them is a bad idea. We invent things like ear and nose plugs to temporarily disable senses, and we have built-in eyelids for temporarily disabling our sight (and, probably more importantly, for eye protection).

Suffering involves wanting something and getting something else. Reality violates what you want. E.g. you feel pain that you don’t want to feel. Or you taste a food that you don’t want to taste. Or your spouse dies when you don’t want them to. (People, occasionally, do want their spouse to die – as always, interpretation determines whether one suffers or not).

Karl Popper emphasized that all observation is theory-laden, meaning that all our scientific evidence has to be interpreted and if we get the interpretation wrong then our scientific conclusions will be wrong. Science doesn’t operate on raw data.

Suffering involves something happening and you interpreting it negatively. That’s another way to look at wanting something (that you would interpret positively or neutrally) but getting something else (that you interpret negatively).

Animals can’t interpret like this. They can’t create opinions of what is good and bad. This kind of thinking involves knowledge creation.

Animals do not form preferences. They don’t do abstract thinking to decide what to value, compare differential potential values, and decide what they like. Just like self-driving cars have no interpretation of crashing and do not feel bad about it when they crash. They don’t want to avoid crashing. Their programmers want them to avoid crashing. Evolution doesn’t want things like people do, but it does design animals to (mostly) minimize dying. That involves various more specific designs, like behavior algorithms designed to prevent an animal from starving to death. (Those algorithms are pretty effective but not perfect.)

Genetic evolution is the programmer and designer for animals. Does genetic evolution have values or preferences? No. It has no mind.

Genetic evolution also created humans. What’s different is it gave them the ability to do their own evolution of ideas, thus creating evolved knowledge that wasn’t in their genes, including knowledge about interpretations, preferences, opinions and values.

Animal Appearances

People often assume animals have certain mental states due to superficial appearance. They see facial expressions on animals and think those animals have corresponding emotions, like a human would. They see animals “play” and think it’s the same thing as human play. They see an animal “whimper in pain” and think it’s the same as a human doing that.

People often think their cats or dogs have complex personalities, like an adult human. They also commonly think that about their infants. And they also sometimes think that about chatbots. Many people are fooled pretty easily.

It’s really easy to project your experiences and values onto other entities. But there’s no evidence that animals do anything other than follow their genetic code, which includes sometimes doing genetically-programmed information-gathering behaviors, then writing that information into long-term memory, then using that information in behavior algorithms later in exactly the way the genes say to. (People also get confused by indirection. Genes don’t directly tell animals what to do like slave-drivers. They’re more like blueprints for the physical structure and built-in software of animals.)

Uncertainty

Should we treat animals partially or entirely like humans just in case they can suffer?

Let’s first consider a related question. Should we treat trees and 3-week-old human embryos partially or entirely like humans just in case they can suffer? I say no. If you agree with me, perhaps that will help answer the question about animals.

In short, we have to live by our best understanding of reality. You’re welcome to be unsure, but I have studied stuff, debated and reached conclusions. I have conclusions both about my personal debates and also the state of the debate involving all expert literature.

Also, we’ve been eating animals for thousands of years. It’s an old part of human life, not a risky new invention. Similarly, the mainstream view of human intellectuals, for thousands of years, has been to view animals as incapable of reason or irrational, and as very different than humans. (You can reason with other humans and form e.g. peace treaties or social contracts. You can resolve conflicts with persuasion. You can’t do that with animals.)

But factory farms are not a traditional part of human life. If you just hate factory farms but don’t mind people eating wild animals or raising animals on non-factory farms, then … I don’t care that much. I don’t like factory farms either because I think they harm human health (but so do a lot of other things, including vegetable oil and bad political ideas, so I don’t view factory farms as an especially high priority – the world has a ton of huge problems). I’m a philosopher who mostly cares about the in-principle issue of whether or not animals suffer, which is intellectually interesting and related to epistemology. It’s also relevant to issues like whether or not we should urgently try to push everyone to be vegan, which I think would be a harmful mistake.

Activism

Briefly, most activism related to animal welfare is tribalist, politicized fighting related to local optima. It’s inadequately intellectual, inadequately interested in research and debate about the nature of animals or intelligence, and has inadequate big picture planning about the current world situation and what plan would be very effective and high leverage for improving things. There’s inadequate interest in persuading other humans and reaching agreement and harmony, rather than trying to impose one’s values (like treating animals in particular ways) on others.

Before trying to make big changes, you need e.g. a cause-and-effect diagram about how society works and what all the relevant issues are. And you need to understand the global and local optima well. See Eli Goldratt for more information on project planning.

Also, as is common with causes, activists tend to be biased about their issue. Many people who care about the (alleged) suffering of animals do not care much about the suffering of human children, and vice versa. And many advocates for animals or children don’t care much about the problems facing elderly people in old folks homes, and vice versa. It’s bad to have biased pressure groups competing for attention. That situation makes the world worse. We need truth seeking and reasonable organization, not competitions for attention and popularity. A propaganda and popularity contest isn’t a rational, truth seeking way to organize human effort to make things better.

This article discusses why mistreating animals is bad even if they’re incapable of suffering.

I don’t think animals can suffer, but I’m not an activist about it. I’m not trying to change how the world treats animals. I’m not asking for different laws. I don’t emphasize this issue. I don’t generally bring it up. I care more about epistemology. Ideas about how minds work are an application of some of my philosophy.

On the whole, I think people should treat animals better, not worse. People should also treat keyboards, phones, buildings and their own bodies better. It’s (usually) bad to smash keyboards, throw phones, cause and/or ignore maintenance problems in buildings, or ingest harmful substances like caffeine, alcohol or smoke.

Pets

Legalizing animal abuse would have a variety of negative consequences if nothing else about the world changed. People would do it more because legalizing it would make it more socially legitimate. I don’t see much upside. Maybe more freedom to do scientific testing on animals would be good but, if so, that could be accomplished with a more targeted change that only applies to science – and lab animals should be treated well in ways compatible with the experiment to avoid introducing extra variables like physiological stress.

On the other hand, legalizing animal abuse would actually kill human children. Abused dogs are more likely to bite both humans and dogs.

When spouses fight, one can vandalize the other’s car because it’s shared property. Vandalizing a spouse’s dog would be worse. A dog isn’t replaceable like a car. If vandalizing a dog was treated like regular property damage, the current legal system wouldn’t protect against it well enough.

Why aren’t dogs replaceable? Because they have long-term memory which can’t be backed up and put into a new dog (compare with copying all your data to a new phone). If you’ve had a dog for five years and spent hundreds of hours around it, that’s a huge investment, but society doesn’t see that dog as being worth tens of thousands of dollars. If you were going to get rid of animal abuse laws, you’d have to dramatically raise people’s perception of the monetary value of pets, which is currently way too low.

Dogs, unlike robots we build, cannot have their memory reset. If a dog starts glitching out (e.g. becomes more aggressive) because someone kicks it, you can’t just reinstall and start over, and you wouldn’t want to because the dog has valuable data in it. Restoring a backup from a few days before the abuse would work pretty well but isn’t an option.

You’d be more careful with how you use your Mac or phone if you had no backups of your data and no way to undo changes. You’d be more careful with what software you installed if you couldn’t uninstall it or turn it off. Dogs are like that. And people can screw up your dog’s software by hitting your dog.

People commonly see cars and homes as by far the most valuable things that they own (way ahead of e.g. jewelry, watches and computers for most people). They care about their pets but they don’t put them on that list. They can buy a new dog for a few hundred dollars and they know that (many of them wouldn’t sell their dog for $10,000, but they haven’t all considered that). They don’t want to replace their dog, but many people don’t calculate monetary value correctly. The reason they don’t want to replace their dog is that their current dog has far more value than a new one would. People get confused about it because they can’t sell their dog for anywhere near its value to them. Pricing unique items with no market for them is problematic. Also, if they get a new dog, it will predictably gain value over time.

It’s like how it’s hard to put a price on your diary or journal. If someone burned it, that would be really bad. But how many dollars of damages is that worth? It’s hard to say. A diary has unique, irreplaceable data in it, but there’s no accurate market price because it’s worth far more to the owner than to anyone else.

Similarly, if someone smashes your computer and you lose a bunch of data, you will have a hard time getting appropriate compensation in court today. Being paid the price of a new computer is something the courts understand. And courts will take into account emotional suffering and trauma. They’re worse at taking into account the hassle and time cost of dealing with the whole problem, including going to court. And courts are bad at taking into account the data loss for personal files with no particular commercial value. A dog is like that – it contains a literal computer that literally contains personal data files with no backups. But we also have laws against animal abuse which help protect pet owners, because we recognize in some ways that pets are important. Getting rid of those laws without changing a bunch of other things would make things worse.

Why would you want to abuse a pet anyway? People generally abuse pets because they see the animals as proxies for humans (it can bleed and yelp) or they want to harm the pet’s owner. So that’s really bad. They usually aren’t hitting a dog in the same way they punch a hole in their wall. They know the dog matters more than the wall or their keyboard.

Note: I am not attempting to give a complete list of reasons that animal abuse is bad even if animals are incapable of suffering. I’m just making a few points. There are other issues too.

Factory Farms

Factory farms abuse animals for different reasons. They’re trying to make money. They’re mostly callous not malicious. Let’s consider some downsides of factory farms that apply even if animals cannot suffer.

When animals are sick or have stress hormones, they’re worse for people to eat. This is a real issue involving e.g. cortisol. Tuna fishing reality shows talk about it affecting the quality and therefore price of their catch, and the fishermen go out of their way to reduce fish’s physiological stress.

When animals eat something – like corn or soy – some of it may stay in their body and affect humans who later eat that animal. It can e.g. change the fatty acid profile of the meat.

I don’t like to eat at restaurants with dirty kitchens. I don’t want to eat from dirty farms either. Some people are poor enough for that risk to potentially be worth it, but many aren’t. And in regions where people are poorer, labor is generally cheaper too, so keeping things clean and well-maintained is cheaper there, so reasonably clean kitchens and factories broadly make sense everywhere. (You run into problems in e.g. poorer areas of the U.S. that are stuck with costly laws designed for richer areas of the U.S. They can have a bunch of labor-cost-increasing laws without enough wealth to reduce the impact of the laws.)

I don’t want cars, clothes, books, computers or furniture from dirty factories. Factories should generally be kept neat, tidy and clean even if they make machine tools, let alone consumer products, let alone food. Reasonable standards for cleanliness differ by industry and practicality, but some factory farms are like poorly-kept factories. And they produce food, which is one of the products where hygiene matters most.

On a related note, E. coli is a problem mainly because they mix together large amounts of e.g. lettuce or beef. One infected head of lettuce can contaminate hundreds of other heads of lettuce due to mixing (for pre-made salad mixes rather than buying whole heads of lettuce). They generally don’t figure out which farm had the problem and make them clean up their act. And the government spends money to trace E. coli problems in order to protect public health. This subsidizes having dirtier farms and then mixing lettuce together in processing. The money the government spends on public health, along with the lack of accountability, helps enable farms to get away with being dirtier.

These are just a sample of the problems with factory farms that are separate issues from animal suffering. I’d suggest that animal activists should emphasize benefits for humans more. Explain to people how changes can be good for them, instead of being a sacrifice for the sake of animals. And actually focus reforms on pro-human changes. Even if animals can suffer, there are lots of changes that could be made which would be better for both humans and animals; reformers should start with those.

This is a followup for my article “Small” Errors, Frauds and Violences. It discusses a specific example of “small” fraud.

Tyson is a large meat processing company that gets meat from factory farms. Tyson’s website advertises that their meat that passes objective inspections and audits (mirror) from unbiased third parties.

Tyson makes these claims because these issues matter to consumers and affect purchasing. For example, a 2015 survey found that “56 percent of US consumers stop buying from companies they believe are unethical” and 35% would stop buying even if there is no substitute available. So if Tyson is lying to seem more ethical, there is actual harm to consumers who bought products they wouldn’t have bought without being lied to, so it’d qualify legally as fraud.

So if Tyson says (mirror) “The [third party] audits give us rigorous feedback to help fine tune our food safety practices.”, that better be true. They better actually have internal documents containing text which a reasonable person could interpret as “rigorous feedback”. And if Tyson puts up a website section about animal welfare on their whole website about sustainability, their claims better be true.

I don’t think this stuff is false in a “big” way. E.g., they say they audited 50 facilities in 2021 just for their “Social Compliance Auditing program”. Did they actually audit 0 facilities? Are they just lying and making stuff up? I really doubt it.

But is it “small” fraud? Is it actually true that the audits give them rigorous feedback? Are consumers being misled?

I am suspicious because they get third party audits from Food Safety Net Services, an allegedly independent company that posts partisan meat propaganda (mirror) on their own public website.

How rigorous or independent are the audits from a company that markets (mirror) “Establishing Credibility” as a service they provide while talking about how you need a “non-biased, third-party testing facility” (themselves) and saying they’ll help you gain the “trust” of consumers? They obviously aren’t actually non-biased since they somehow think posting partisan meat propaganda on their website is fine while trying to claim non-bias.

Food Safety Net Services don’t even have a Wikipedia page or other basic information about them available, but they do say (mirror) that their auditing:

started as a subset of FSNS Laboratories in 1998. The primary focus of the auditing group was product and customer-specific audits for laboratory customers. With a large customer base in the meat industry, our auditing business started by offering services specific to meat production and processing. … While still heavily involved in the meat industry, our focus in 2008 broadened to include all food manufacturing sites.

The auditing started with a pre-existing customer base in the meat industry, and a decade later expanded to cover other types of food. It sounds independent like how Uber drivers are independent contractors or how many Amazon delivery drivers work for independent companies. This is the meat industry auditing itself, displaying their partisan biases in public, and then claiming they have non-biased, independent auditing. How can you do a non-biased audit when you have no other income and must please your meat customers? How can you do a non-biased meat audit when you literally post meat-related propaganda articles on your website?

How can you do independent, non-biased audits when your meat auditing team is run by meat industry veterans? Isn’t it suspicious that your “Senior Vice President of Audit Services” “spent 20 years in meat processing facilities, a majority of the time in operational management. Operational experience included steak cutting, marinating, fully cooked meat products, par fry meat and vegetables, batter and breaded meat and vegetables, beef slaughter and fabrication, ground beef, and beef trimmings.” (source). Why exactly is she qualified to be in charge of non-biased audits? Did she undergo anti-bias training? What has she done to become unbiased about meat after her time in the industry? None of the her listed credentials actually say anything about her ability to be unbiased about meat auditing. Instead of trying to establish her objectivity in any way, they brag about someone with “a strong background in the meat industry” performing over 300 audits.

Their Impartiality Statement is one paragraph long and says “Team members … have agreed to operate in an ethical manner with no conflict or perceived conflict of interest.” and employees have to sign an ethics document promising to disclose conflicts of interest. That’s it. Their strategy for providing non-biased audits is to make low-level employees promise to be non-biased in writing, that way if anything goes wrong management can put all the blame on the workers and claim the workers defrauded them by falsely signing the contracts they were required to sign to be hired.

Is this a ridiculous joke, lawbreaking, or a “small” fraud that doesn’t really matter, or a “small” fraud that actually does matter? Would ending practices like this make the industry better and lead to more sanitary conditions for farm animals, or would it be irrelevant?

I think ending fraud would indirectly result better conditions for animals and reducing their suffering (on the premise that animals can suffer). Companies would have to make changes, like using more effective audits, so that their policies are followed more. And they’d have to change their practices to better match what the public thinks is OK.

This stuff isn’t very hard to find, but in a world where even some anti-factory-farm activists don’t care (and actually express high confidence about the legal innocence of the factory farm companies), it’s hard to fix.

Though some activists actually have done some better and more useful work. For example, The Humane League has a 2021 report about slaughterhouses not following the law. Despite bias, current auditing practices already show many violations. That’s not primarily about fraud, but it implies fraud because the companies tell the public that their meat was produced in compliance with the law.