Thanks! I wasnāt aware of the great work that https://āāwelfarefootprint.org/āā is doing, and your attempt to bring it to a total value is exactly what I was looking for. From what I understand the ābestā scenarios (cage free hens and reformed broilers) are still below the example standard I discussed here. Would you agree?
Christoph Hartmann šø
Karma: 168
Thanks for taking the time to write this! I think it aligns well with what somebody else had shared with me as well privately.
Let me start with where I disagree: I donāt share your view that it is unethical under all circumstances to create āhumans to be slaughteredā. If my life ended painlessly without me knowing and affecting nobody around me in a few years because, plot twist, our universe is just one big farm of some aliens, then that would be a pity because I wouldāve preferred to live another fourty years but Iām also grateful for the fourty years of life until that point that I wouldnāt have experienced otherwise. From conversations with friends I do understand that this is not a common view and I understand if yours is different. One reason āit would be a pityā is that of course I had plans for my life and those vanish but here I share the thinking you mentioned that animals probably live a lot less in the future than we do so this might ācount lessā.
On your false dichotomy argument: āOf course it is better to have a net-positive life then not to be born at all. But it is even better to have a net-positive and not to be killed after some (rather short) time.ā I agree but realistically the options are āno lifeā or ālimited lifeā (becuase animals are expensive), and if those are the options then I think ālimited lifeā is better. And if the animals truely have no concept of the future, isnāt ātwo animals for half the timeā somewhat similar to āone animal for the full timeā?
I love how you went from these philosophical points to more practical points at the end, so let me also come back to those. I think no matter the disagreement on the points above, we can both agree that a world without net-negative factory farmed lives is a better world. I personally donāt think that alt-protein will result in everybody stopping to eat meat, it is too deeply culturally engrained in so many cultures. At the same time nobody who sees the suffering of animals is supporting these practices. So going from a messaging of āideally everybody should be vegan and letās trust tech to solve itā to āideally everybody should treat animal products as something sacred and really care for how they are treatedā is something that probably the majority of people could get on board with.
In practice that would probably mean supporting organizations that try communicating along those lines and see if that has a better effect than advocating for a vegan diet. I could also imagine that it has the opposite effect: Normalising animal protein and a slippery slope in the direction of also eating net-negative animal protein.
Thanks! Indeed thinking along the same lines although I have a much stronger intuition that most human and wild animal lives are lives worth living.
From the comment section I likedThe link to the talk on wild animal welfareāwhile it makes the point that evolution is complicated and not guranteed to increase welfare welfare for all animals, I think I share their assumption that pain is an evolutionary tool for animals to stop doing things that will harm them (which would stop working if it would be overly abundant). In a similar way pleasure can be argued to encourage taking actions to achieve fitness-improving goals, so youād expect them to always somewhat balance out unless in niche cases where pain/āpleasure donāt have an effect on reproductive success (like an especially painful death, or a factory farm where activities from the animals donāt have an effect on their fitness).
The link to the neutral point discussion although most considerations seem more relevant for human lives (e.g., the ethical issues around legalising assisted suicide) I found it interesting that the estimated neutral point moves ādownā as people have lower average life satisfaction (e.g., 2 for UK and 0.5 for Ghana and Kenya).
Somewhat unrelated to this but I read your work for Animal Advocacy Africa. How do you look at the welfare of animals farmed in more traditional settings there? E.g., chickens in a village or small cattle herds by roaming tribes like the Kenyan Maasai? Just from looking at them I always guessed that they have a āgood lifeā but curious what you think! From some conversations I understood that factory farming also becomes more prominent in Kenya but the majority still seems to be farmed in more traditional settings.
Yes I heard the same. I had a brief look at their regulation and saw that āNo more than 3,000 laying hens may be kept in any one shedā which seems pretty high even if they have more space per hen than with other regulations.
Iāll see if I can talk to some experts and get their thoughts on these questions.
Thanks for your thoughts!
On your question: I chose organic because I had initially planned to take the EU Organic one because itās so wide spread here and has some animal welfare standards. In the end I chose Naturland though because it seems to be stronger on animal welfare, and I wanted to make a strong case.
I am not aware of any reported malpractices as the one you cited for that label but of course there is always a chance to have these outliers.
Thanks for tagging me! Fully agree with you Joseph that an easier way to socialise with strangers at conferences would be great and thatās exactly what Iām trying to do with this app. Let me know if you know anybody organising conferences or communities for whom this could be helpful.
Thanks so much for steelmanning my argument and looking for some research yourself! And I share your intuition that some consumption seems zero-sum around status. I do think though that my smartphone is giving me tons of value but thatās a different discussion probably haha
Thanks for that! And for making the ideological ickyness visible. I think a lot of people, me included, feel like this. And thanks also for acknowledging the accounting part of the framework. It does rely on a similar relationship though that money spent represents value delivered. So we would have to assume that companies are more rational in their spending choices.
If I understand you correctly, you are questioning three things
1) That there is a marginal relationship between income and life satisfaction at high incomes
2) If there were a relationship, that consumption is a good predictor of contribution to life satisfaction
3) That Elon Musk could be the most impactful person alive
Let me try to address each one1) For this I will just defer to the studies referenced in Our World In Data: āHigher personal incomes go together with higher self-reported life satisfactionā suggests to me that also at high incomes there is a marginal relationship between income and life satisfaction.
2) If we accept 1), then itās very likely that your spending will be predictive of your life satisfaction. I share your intuition that spending becomes more volatile and impulsive, but if we consider similar amounts on a percentage level, and thereby a similar level of contribution to the WELLBY measure, I think itās fair to assume that somebody who earns $100k will be as diligent about spending $1k as a person earning $1k will be about spending $10.
3) You make the point that Elon relies on government spending. I think this is a valid one because that is far far away from actual consumer life satisfaction and the influence of each citizen and the effect on them is only very very indirect. So maybe the government just spent the money badly (Iād argue though that itās much better spent than on NASA). If, however, he would not rely on these and make most of his money directly from consumers, I think accepting 2) would have to lead us to accept 3) unless he were in some industry that tricks our consumer choices, like the addictions you mentioned, I think he doesnāt.
Hm, not sure. If there is an opportunity for innovation, Iād expect either the incumbent to pursue this to expand the addressable market (and thereby make more revenue /ā have more impact) or/āand a competitor to innvoate, thereby reducing the price and capturing market share /ā prevent the incumbent from increasing profits (and increasing revenue /ā imapct for the competitor).
On second reading I assume you are referring to the issue that when a product gets cheaper through innvoation it might look like the product would be less impactful because it now gets less share of the total WELLBYs of the customer. I guess, though, what would happen at the same time is that overall life satisfaction of the customer will go slightly up as they now have more disposable income (just saved some money from spending less on that product), and that increased life satisfaction would be distributed across all purchases, including the one that just got cheaper. On a micro level those wonāt perfectly balance of course but on the coarsness level of this analysis I think weād be fineāsee the section on first dollar vs last dollar spent in Appendix 1.
But Iām not an economist or anything like that by training so very curious about your further thoughts! I very likely missed things.
I addressed the counterfactual impact a bit in Appendix 1 in the section on absolute vs relative impact.
Thanks for taking the time to share this great anecdote. Exactly what this framework would predict. If any more thoughts come up as you think through it, Iād be curious!
Thanks so much! Interesting that they count GiftAid and not employer ones, that seems contradictory.
Agree on the counterfactual impact of the person offering donation matching otherwise donating to other effective charities.
Finding stability in your life should always be first priority and it sounds like youāre on a good path. Wishing you lots of empathy and compassion also for yourself on the way!
Glad you liked it and great that you posted your postāit takes some courage here sometimes haha. Itās still something I keep thinking aboutāmy main concern is how tractable it is though. I feel itās incredibly hard to significantly change peopleās character traits, including empathy. If I would spend more time on this Iād probably start there, interview a few psychology professors (like Tania Singer) on their view on if this is even possible, and if thatās a yes then start to brainstorm interventions. I donāt have much time the next few months but if you have a thesis or something coming up I think it could be a great topic.
Thanks for taking the time to formalizing this a bit more. I think youāre capturing my ideas quite well and indeed I canāt think of ways how this would scale exponentially. Your point on āletās remove the human bottleneckā goes a bit in the direction of the last simulation paragraph where I suggest that you could parallelize knowledge acquisition. But as I argue there I think thatās unrealistic to scale exponentially.
In general, I think I focused too much on the robotics examples when trying to illustrate that generating new knowledge takes time and is difficult but the same applies of course also to performing any kind of other experiment that an AI would have to do such as generating knowledge on human psychology by doing experiments with us, testing new training algorithms, performing experiments on quantum physics for chip research, etc.
Hi Harrison, thanks for stating what I guess a few people are thinkingāitās a bit of a clickbait title. I do think though that the non-exponential growth is much more likely than exponential growth just becuase exponential takeoff would require no constraints on growth while itās enough if one constraint kicks in (maybe even one I didnāt consider here) to stop exponential growth.
Iād be curious on the methodological overhang though. Are you aware of any posts /ā articles discussing this further?
Thanks for this, Thomas! See my answer to titotal addressing the algorithm efficiency question in general. Note that if we would follow the hand-wavy āevolutional transfer learningā argument that would weaken the existence proof for sample-efficiency of the human brain. The brain isnāt a āgeneral-purpose Tabula Rasaā. But I do agree with you that probably weāll find a better algorithm that doesnāt scale this badly with data and can extract knowledge more efficiently.
However, Iād argue that as before, even if we find a much much more efficient algorithm, we are in the end limited by the growth of knowledge and the predictability of our world. Epoch estimates that weāll run out of high-quality text data next year, which I would argue is the most knowledge-dense data we have. Even if we find more efficient algorithms, once AI has learnt all this text, itāll have to start generating new knowledge itself, which is much more cumbersome thant ājustā absorbing existing knowledge.
Hey Steve, thanks for those thoughts! I think Iām not more qualified than the wikipedia community to argue for or against Mooreās law, thatās why I just quoted them. So canāt give more thoughts on that unfortunately.
But even if Mooreās law would continue forever, I think that the data argument would kick in. If we have infinite compute but limited information to learn from, thatās still a limited model. Applying infinite compute to the MNIST dataset will give you a model that wonāt be much better than the latest Kaggle competitor on that dataset.
So then we end up again at the more hand-wavy arguments for limits to the growth of knowledge and predictability of our world in general. Would be curious where Iām losing you there.
Thanks for your thoughts! When writing this up I also felt that the algorithm one is the weakest one, so let me answer from two perspectives:
From the room to invent new algorithms: Convolutional neural networks have been around since the 80s, weāve been using GPUs to run them since about 10 years. If there really would be huge potential left, Iād be a bit surprised that we didnāt find it in the last 40 years alreadyāwe certainly had incentives because hardware was so slow and people had to optimize, but of course you never know. I tried to find a paper reviewing efficiency improvements of non-negative matrix factorization over time, I think that could be a fun guide, but couldnāt find one.
From the brain perspective: Yes, itās puzzling that the brain can do all this on 12 watts power while OpenAI is using server farms that consume much much more than that. So somewhere there must be huge efficiency gains. Note that thatās mostly on the training sideāāevaluatingā a network is pretty efficient as far as I know. For training, there could be different reasons:
Transfer learning: Maybe the ācomputation of evolutionā just āpre-programmedā our brain similar to how we use transfer learning. Itās already pretty close to where we want it and we just need to fine tune. Transfer learning on neural networks is already pretty cheap today. One argument supporting this would be that many animals are perfectly functional from day 1 of their life without much learning. Of course not same level of intelligence, but still.
Hardware: The brain doesnāt run on silicone. We use a very very abstracted version of our brain and there is much more going on biologically. Some people argue that a lot of computation is already happening in the dendrites, maybe the morphology of neurons has effects on computation, maybe the specific nonlinearity applied by the neurons is more relevant than we think, ā¦ . One way to try to adress this would be to build chips that are more similar (āneuromorphicā) but I havenāt seen much progress there
Architecture: The brain isnāt a CNN. This might be a good approximation for our sensory cortices but even there itās not the same. The brain is very recurrent, not feed-forward, and it canāt send signals back through itās synapses and therefore canāt implement backpropagation. Maybe weāre just using the wrong architecture and if we find the right one itās going to go much faster. I did my PhD on something related to this and I gave up haha, but of course, Iām sure there are lots of things to be discovered here.
Thanks so much for writing out all of this!
I am really surprised by the 60% number. Will update my internal model ;)
And fully agree that highly intensive farming with no regulation is the worst of both worlds and very worthwhile to work on. Thank you for that work!!