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

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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.

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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.