Absolutely, thanks for pointing this out! Those long words beginning with A - I wouldn't mind, but I have a whole folder in my email about "alternative proteins" ... I will fix this now ...
This is really frustrating - I wrote an article and the EA Forum server crashed and the whole text was lost ... this server seems to be crashing quite a bit recently ... I will try again later.
For what it's worth, the gist of the post was that I looked at the new job-board from the High-Impact Professionals site, and was amazed to see that there were over 1000 full-time positions, but only 12 part-time.
And IMHO, in many smaller orgs especially, it makes a lot more sense to look at hiring experienced people part-time, primarily because many small orgs do not need the unique skills these people bring for 40 hours per week.
So I believe that too many orgs in the impact space are defaulting to full-time roles because maybe that's what the young people and new grads they mostly deal with are looking for. But for a senior professional, maybe they can provide 80/20 the value they can bring to a new, smaller org in one afternoon per week - and this option would enable them to avoid having to take major career risks and pivots at a time in their lives where they are dealing with kids and mortgages and not a lot of flexibility ...
This highlights the massive importance of EA's grasping this moment where we are a bit in the spotlight and using it to gain credibility as a dependable and thorough source of accurate information about AI Safety.
We need the right people to be taking, or at least informing the decisions about AI Safety and Alignment over the next few decades. The AI and LessWrong communities would be ideal. We need to have a world where nobody will take a vital policy decision about AI Safety if it is strongly opposed by the EA community, because we have proven to be prescient in the past, and we have a deep understanding of the subject matter.
This is not the time for weirdness. As more magazines like the Economist profile the EA movement, we need to ensure that they don't get to focus on the arguments that they find ridiculous, be that longtermism or AI sentience or shrimp welfare. Not because these arguments are not important, not because EA's are wrong, but because right now the most important thing may be "do not appear weird!" and also "do not give those who disagree with us easy ways to discount our arguments."
If you want a role-model for how not to do this: We have a president in the US who has probably done more harm to EA-supported causes than any human being in history because some morons in the Democratic party insisted that trans-women should be allowed to compete in high-level women's sports - an issue that probably impacted less than 5 people, each of whom now suffer much more under this administration. Somebody needed to tell them to shut the fuck up, at least until after the election, because FOX news was running this story every night to prove that Democrats were a threat to women. We need to think the same way - when there are things that 99% of the public think are weird, let's not allow our movement to be defined by them so that people can say "yes, the EA's say we're not ready to unpause yet, but aren't they the guys who say that we should take decisions based on the welfare of machines on other planets thousands of years from now rather than what's good for people today?" (yes, they will misrepresent arguments too, of course).
We need to stick to the script: EA's are people who care intensely about people, about animals, about humanity, who devote their lives to helping people in very poor countries or to averting animal suffering, who study risks to humanity and think deeply about what we need to do to avert them - who have been consistently proven right - on poverty and development, on climate, on AI ...
I know this is very anti-EA mentality. But I'm not talking about internal EA discussions. I'm talking about when EA representatives (and this is another vital point: we NEED EA representatives, people who are chosen by the EA community to speak for us, so that journalists cannot just talk to random people and claim their views are representative).
I'm a member of Pause AI, and I find it super valuable to have all the arguments that I (presumably should) disagree with clearly stated to give me pause for thought.
We do this far too little.
I still think we should pause (at least, after one quick read-through), but I also think that if we pause, we need to look at each argument like this seriously to find solutions or mitigations.
IMHO the world has to make Alternative Protein work - for animals, for climate, for poverty, for nutrition. It is the win/win/win/win solution we all need.
I am still deeply frustrated by the lack of political support - especially compared to the massive support given to farmers which makes it far from a level playing-field even trying to reach parity.
When I worked on direct air capture of CO2, there was always an analogous discussion of whether the (or a) technology could work, could be industrialised, could be price-competitive (in that case, with the projected price/tonne of carbon trading markets). The technology is so far from maturity, and the scale needed is so massive that it's difficult to predict accurately from experience or first principles.
But there was a very interesting analysis which I saw presented by Katrien Sievert, in which they predicted likely rates of technological evolution and cost-reduction based on the complexity involved. For example, solar panels could be rapidly improved by one "invention" (e.g. a more efficient surface that could absorb light efficiently at two different energies), so it was realistic to see efficiency increasing and price / kWh dropping rapidly. On the other hand, for a mature and complex technology (e.g. a plane engine), it wasn't obvious that one simple invention could suddenly improve efficiency or reduce cost - rather it would require a suite of inventions.
I wonder would an analogous analysis make sense for cultivated protein, to get a realistic idea of possible timelines, but also maybe to identify the most promising route for massive scaling and cost-reduction. Or would you say that the technology is already mature enough to be past this stage?
I would love to see a JFK-like commitment to this - by 2040 at least half the world will feed itself a nutritious diet rich in meat and fish, without having to kill any animals - allied with a genuine commitment to make it happen. I love that people like you keep pushing the narrative (which I also fully believe) that this is fully technically within reach, and lacking only the political will to make it happen - ideally sooner rather than later.
A tiny minority of vegans seem to give non-vegans who don't care about animals a pass, but to put a lot of energy into finding fault with people who work to improve animal-welfare but are not vegans.
I find this attitude both misguided and counter-productive.
I think there a many people who, if veganism did not exist, would work in animal-charities, but who today would feel to embarrassed to do so without being vegan. (I would feel that way!) Ultimately, it is the animals who suffer because of this.
I really like the mentality of FarmKind, who, among other great things they do, have created a calculator which enables non-vegans (like me) to estimated the donation I would need to make to enable me to have an overall net-positive impact on animal welfare.
I think vegans are deeply admirable - despite their claims to the contrary, it is not easy, there are sacrifices, even if there is also the moral clarity that comes from feeling that you live your principles.
I believe, as the post says, that the world is not moving towards veganism, BUT that there are win/win solutions out there that we can all fight for. From the short term fight for the welfare of factory-farm animals, to the long-term vision of alternative protein so that you can eat meat & fish without any animals having to suffer - so that we'd all become vegans by default. As a chemical engineer, I'm really excited by the potential of this technology to change the world, and frustrated by the low level of attention it receives, and especially by the way that our lobbyist-driven governments give massive subsidies to factory-farms while actively creating obstacles for alternative protein.
Great, I really applaud this initiative, and it feels to me that it can be a real credibility builder. IMHO there is no question at all that artificial protein will dominate our diets by the end of the century, and hopefully a lot soon. It is difficult, but the current system is so bad, on so many levels, that even imperfect solution will be just so much better, cheaper, safer, more ethical ...
I had one additional though: this week I did a TEA for a new process. I knew quite a bit about the process itself but hadn't done a TEA before. I asked Claude Pro to help, and it was amazing. Both for the insights and for the formatting - it gave me a 10-page Excel with a very flexible TEA.
What I particularly liked was a couple of places where it caught me out ("you didn't include the energy consumption of Step X, which can be significant") or questioned my assumptions ("if you make product X, your TEA will be dominated by Cost Y, which is not realistic, because in that case you would change Condition Z" ... really insightful things).
I would never use an AI-generated TEA as a final model, but it is a great way to get an 80/20 model that people can use as a starting point.
(if this seems useful, happy to go into more detail about this, but my guess is that you can do it yourselves, it's very intuitive once you're very clear about what you want and what you do not want Claude to assume).
(I'm all for slowing down AI, but also astonished by what the AI we have already can do!)
I used to work in Pharma. There are organisations like the FDA which need to approve a drug before it can be put on the market. We need legislation to create something similar for AI models. And the burden of proof is on the drug-maker - prove that your drug is safe. Same is needed for AI.
I am an engineer. If I build a bridge and it collapses, I am responsible. I will pay millions (or my insurance will) and I will spend the rest of my life in jail, unless I can demonstate (burden of proof is on me) that I did everything exactly as it should be done, and the collapse was due to something I could not have foreseen and the regulations did not foresee. Why not something similar for AI developers - proper liability.
When I work, a company pays me. Let's say they pay me $100,000 per year. In most countries, the company pays social security on top of this, and other costs, maybe $20,000 per year, to the government. Then I pay taxes and social security, and local taxes. Maybe another $50,000. So for every net $50,000 I earn, the company pays $70,000 to the government in one form or another. If they use an AI agent, they can just pay $50,000 (or whatever) and the government doesn't take one penny. If AI's replace humans as workers, why should humans pay tax, and employers pay tax to hire humans, but AI's not pay tax, and companies pay not tax to hire AI's?? If AI "workers" were taxed at the same rate as humans, replacing humans with AI would be a lot less financially interesting. The government needs to start taxing AI workers in the same way as they tax human workers.
If I commit a crime, the government punishes me. When an AI agent commits a crime, someone must be punished. Let the AI developer and the AI owner/user fight it out in court, but at least one of them must go to jail. Currently they each just deflect blame and nobody pays.
And so on .... there are so many good and very reasonable and fair ways that AI could be managed so that there is a genuine incentive on AI developers to make their AI's behave.
When I worked at a multi-national, I learned (too late) a concept called PIE, which was eye-opening.
P = Performance - this is what you actually do, the contributions you make.
I = Image - this is how you and your performance are perceived.
E = Exposure - this is who sees your work.
The point of this was that many of us work on the P only, we assume that the I and E will follow. But often they don't unless we actively manage them. A lot of corporate frustration is about people who focus only on P angriliy complaining about people who get ahead while they don't - and often those who get ahead are people who focus on I and E - but also P.
The trainer's central thesis was this: YOU are responsible for your P, your I and your E. If you focus only on your Performance, don't blame anyone else when you don't get promoted. You need to take ownership for how you are perceived and who perceives you.
Here's where it got interesting. People pushed back: that isn't fair! I focus on doing my job, I do it extremely well, why should "image" matter? Why should exposure matter?
And the response was not what they expected. It was not defensive at all. The trainer said: "That is not true. If you are not focused on image and exposure, you are not doing your job as well as you could be. Because you are not setting an example that people follow. You are not sharing your ideas for others to learn from. You are not Influencing enough.
I sometimes think this is a great concept to share within EA. Because within EA, there are some people who do a fantastic job of getting their ideas out there, about getting talked about, about moving the Overton window. And there are others who also do brilliant work, but much of it stays within the EA community.
And in the end, if we're looking at impact, we have to ask: who has the most impact? Not: who wrote the best articles? Not: who put in the most hours? But the impact.
This week, one guy did more for AI Safety than 1000 people have done in 10 years. He resigned (P), but unlike many before him, he somehow grasped the media moment, came across as a very normal, not nerdy guy, who truly cared about humanity (I). And got the exposure via his posts and major interviews. (E) He's surely not the "best" AI Safety person ever, but he had a huge impact by getting the image and exposure right.
I know there was also a lot that was out of his control, the timing, the background and so on. But it should be an example to us.
Hey, I have experience with the preliminary parts of this - chemical engineering, but not in the context of cultivated meat. Happy to help / advise.
I have run industrial workshops where we'd get everyone in a room, start with a blank sheet of paper and end up with an 80/20 process flow diagram, highlighting the certainties and the open questions and the opportunities for further research, and then move on from this (with a different group sometimes) to build an 80/20 TEA.
To be clear, what I have run was not as computationally intense as you propose. The model with Monte-Carlo syntheses etc would typically be a secondary step. The first step would be to get the right information into a flowsheet, then into a TEA, and for each parameter to have a clear idea of the sources of variability and the uncertainties. Then you can even run the Monte Carlo simulation on the TEA itself if it's simple enough.
It's not rocket-surgery, as W would say. Just structure and getting the right people, the right knowledge and the right mentality in the room, and getting the right pre-work done.
Since I don't work in this field, I can't really say to what extent the bit I could help with has already been done ... if not, I'd be happy to help, time permitting. No interest in being paid to help, at least for the first iteration.
Absolutely, thanks for pointing this out! Those long words beginning with A - I wouldn't mind, but I have a whole folder in my email about "alternative proteins" ... I will fix this now ...
This is really frustrating - I wrote an article and the EA Forum server crashed and the whole text was lost ... this server seems to be crashing quite a bit recently ... I will try again later.
For what it's worth, the gist of the post was that I looked at the new job-board from the High-Impact Professionals site, and was amazed to see that there were over 1000 full-time positions, but only 12 part-time.
And IMHO, in many smaller orgs especially, it makes a lot more sense to look at hiring experienced people part-time, primarily because many small orgs do not need the unique skills these people bring for 40 hours per week.
So I believe that too many orgs in the impact space are defaulting to full-time roles because maybe that's what the young people and new grads they mostly deal with are looking for. But for a senior professional, maybe they can provide 80/20 the value they can bring to a new, smaller org in one afternoon per week - and this option would enable them to avoid having to take major career risks and pivots at a time in their lives where they are dealing with kids and mortgages and not a lot of flexibility ...
This highlights the massive importance of EA's grasping this moment where we are a bit in the spotlight and using it to gain credibility as a dependable and thorough source of accurate information about AI Safety.
We need the right people to be taking, or at least informing the decisions about AI Safety and Alignment over the next few decades. The AI and LessWrong communities would be ideal. We need to have a world where nobody will take a vital policy decision about AI Safety if it is strongly opposed by the EA community, because we have proven to be prescient in the past, and we have a deep understanding of the subject matter.
This is not the time for weirdness. As more magazines like the Economist profile the EA movement, we need to ensure that they don't get to focus on the arguments that they find ridiculous, be that longtermism or AI sentience or shrimp welfare. Not because these arguments are not important, not because EA's are wrong, but because right now the most important thing may be "do not appear weird!" and also "do not give those who disagree with us easy ways to discount our arguments."
If you want a role-model for how not to do this: We have a president in the US who has probably done more harm to EA-supported causes than any human being in history because some morons in the Democratic party insisted that trans-women should be allowed to compete in high-level women's sports - an issue that probably impacted less than 5 people, each of whom now suffer much more under this administration. Somebody needed to tell them to shut the fuck up, at least until after the election, because FOX news was running this story every night to prove that Democrats were a threat to women. We need to think the same way - when there are things that 99% of the public think are weird, let's not allow our movement to be defined by them so that people can say "yes, the EA's say we're not ready to unpause yet, but aren't they the guys who say that we should take decisions based on the welfare of machines on other planets thousands of years from now rather than what's good for people today?" (yes, they will misrepresent arguments too, of course).
We need to stick to the script: EA's are people who care intensely about people, about animals, about humanity, who devote their lives to helping people in very poor countries or to averting animal suffering, who study risks to humanity and think deeply about what we need to do to avert them - who have been consistently proven right - on poverty and development, on climate, on AI ...
I know this is very anti-EA mentality. But I'm not talking about internal EA discussions. I'm talking about when EA representatives (and this is another vital point: we NEED EA representatives, people who are chosen by the EA community to speak for us, so that journalists cannot just talk to random people and claim their views are representative).
Great post!
I'm a member of Pause AI, and I find it super valuable to have all the arguments that I (presumably should) disagree with clearly stated to give me pause for thought.
We do this far too little.
I still think we should pause (at least, after one quick read-through), but I also think that if we pause, we need to look at each argument like this seriously to find solutions or mitigations.
Thank you for posting this!
This is great, and I love Ula's build below.
IMHO the world has to make Alternative Protein work - for animals, for climate, for poverty, for nutrition. It is the win/win/win/win solution we all need.
I am still deeply frustrated by the lack of political support - especially compared to the massive support given to farmers which makes it far from a level playing-field even trying to reach parity.
When I worked on direct air capture of CO2, there was always an analogous discussion of whether the (or a) technology could work, could be industrialised, could be price-competitive (in that case, with the projected price/tonne of carbon trading markets). The technology is so far from maturity, and the scale needed is so massive that it's difficult to predict accurately from experience or first principles.
But there was a very interesting analysis which I saw presented by Katrien Sievert, in which they predicted likely rates of technological evolution and cost-reduction based on the complexity involved. For example, solar panels could be rapidly improved by one "invention" (e.g. a more efficient surface that could absorb light efficiently at two different energies), so it was realistic to see efficiency increasing and price / kWh dropping rapidly. On the other hand, for a mature and complex technology (e.g. a plane engine), it wasn't obvious that one simple invention could suddenly improve efficiency or reduce cost - rather it would require a suite of inventions.
I wonder would an analogous analysis make sense for cultivated protein, to get a realistic idea of possible timelines, but also maybe to identify the most promising route for massive scaling and cost-reduction. Or would you say that the technology is already mature enough to be past this stage?
I would love to see a JFK-like commitment to this - by 2040 at least half the world will feed itself a nutritious diet rich in meat and fish, without having to kill any animals - allied with a genuine commitment to make it happen. I love that people like you keep pushing the narrative (which I also fully believe) that this is fully technically within reach, and lacking only the political will to make it happen - ideally sooner rather than later.
Considering technology characteristics to project future costs of direct air capture - ScienceDirect
A tiny minority of vegans seem to give non-vegans who don't care about animals a pass, but to put a lot of energy into finding fault with people who work to improve animal-welfare but are not vegans.
I find this attitude both misguided and counter-productive.
I think there a many people who, if veganism did not exist, would work in animal-charities, but who today would feel to embarrassed to do so without being vegan. (I would feel that way!) Ultimately, it is the animals who suffer because of this.
I really like the mentality of FarmKind, who, among other great things they do, have created a calculator which enables non-vegans (like me) to estimated the donation I would need to make to enable me to have an overall net-positive impact on animal welfare.
I think vegans are deeply admirable - despite their claims to the contrary, it is not easy, there are sacrifices, even if there is also the moral clarity that comes from feeling that you live your principles.
I believe, as the post says, that the world is not moving towards veganism, BUT that there are win/win solutions out there that we can all fight for. From the short term fight for the welfare of factory-farm animals, to the long-term vision of alternative protein so that you can eat meat & fish without any animals having to suffer - so that we'd all become vegans by default. As a chemical engineer, I'm really excited by the potential of this technology to change the world, and frustrated by the low level of attention it receives, and especially by the way that our lobbyist-driven governments give massive subsidies to factory-farms while actively creating obstacles for alternative protein.
Great, I really applaud this initiative, and it feels to me that it can be a real credibility builder. IMHO there is no question at all that artificial protein will dominate our diets by the end of the century, and hopefully a lot soon. It is difficult, but the current system is so bad, on so many levels, that even imperfect solution will be just so much better, cheaper, safer, more ethical ...
I had one additional though: this week I did a TEA for a new process. I knew quite a bit about the process itself but hadn't done a TEA before. I asked Claude Pro to help, and it was amazing. Both for the insights and for the formatting - it gave me a 10-page Excel with a very flexible TEA.
What I particularly liked was a couple of places where it caught me out ("you didn't include the energy consumption of Step X, which can be significant") or questioned my assumptions ("if you make product X, your TEA will be dominated by Cost Y, which is not realistic, because in that case you would change Condition Z" ... really insightful things).
I would never use an AI-generated TEA as a final model, but it is a great way to get an 80/20 model that people can use as a starting point.
(if this seems useful, happy to go into more detail about this, but my guess is that you can do it yourselves, it's very intuitive once you're very clear about what you want and what you do not want Claude to assume).
(I'm all for slowing down AI, but also astonished by what the AI we have already can do!)
I used to work in Pharma. There are organisations like the FDA which need to approve a drug before it can be put on the market. We need legislation to create something similar for AI models. And the burden of proof is on the drug-maker - prove that your drug is safe. Same is needed for AI.
I am an engineer. If I build a bridge and it collapses, I am responsible. I will pay millions (or my insurance will) and I will spend the rest of my life in jail, unless I can demonstate (burden of proof is on me) that I did everything exactly as it should be done, and the collapse was due to something I could not have foreseen and the regulations did not foresee. Why not something similar for AI developers - proper liability.
When I work, a company pays me. Let's say they pay me $100,000 per year. In most countries, the company pays social security on top of this, and other costs, maybe $20,000 per year, to the government. Then I pay taxes and social security, and local taxes. Maybe another $50,000. So for every net $50,000 I earn, the company pays $70,000 to the government in one form or another.
If they use an AI agent, they can just pay $50,000 (or whatever) and the government doesn't take one penny. If AI's replace humans as workers, why should humans pay tax, and employers pay tax to hire humans, but AI's not pay tax, and companies pay not tax to hire AI's?? If AI "workers" were taxed at the same rate as humans, replacing humans with AI would be a lot less financially interesting.
The government needs to start taxing AI workers in the same way as they tax human workers.
If I commit a crime, the government punishes me. When an AI agent commits a crime, someone must be punished. Let the AI developer and the AI owner/user fight it out in court, but at least one of them must go to jail. Currently they each just deflect blame and nobody pays.
And so on .... there are so many good and very reasonable and fair ways that AI could be managed so that there is a genuine incentive on AI developers to make their AI's behave.
I love this post.
When I worked at a multi-national, I learned (too late) a concept called PIE, which was eye-opening.
The point of this was that many of us work on the P only, we assume that the I and E will follow. But often they don't unless we actively manage them. A lot of corporate frustration is about people who focus only on P angriliy complaining about people who get ahead while they don't - and often those who get ahead are people who focus on I and E - but also P.
The trainer's central thesis was this: YOU are responsible for your P, your I and your E. If you focus only on your Performance, don't blame anyone else when you don't get promoted. You need to take ownership for how you are perceived and who perceives you.
Here's where it got interesting. People pushed back: that isn't fair! I focus on doing my job, I do it extremely well, why should "image" matter? Why should exposure matter?
And the response was not what they expected. It was not defensive at all. The trainer said: "That is not true. If you are not focused on image and exposure, you are not doing your job as well as you could be. Because you are not setting an example that people follow. You are not sharing your ideas for others to learn from. You are not Influencing enough.
I sometimes think this is a great concept to share within EA. Because within EA, there are some people who do a fantastic job of getting their ideas out there, about getting talked about, about moving the Overton window. And there are others who also do brilliant work, but much of it stays within the EA community.
And in the end, if we're looking at impact, we have to ask: who has the most impact? Not: who wrote the best articles? Not: who put in the most hours? But the impact.
This week, one guy did more for AI Safety than 1000 people have done in 10 years. He resigned (P), but unlike many before him, he somehow grasped the media moment, came across as a very normal, not nerdy guy, who truly cared about humanity (I). And got the exposure via his posts and major interviews. (E) He's surely not the "best" AI Safety person ever, but he had a huge impact by getting the image and exposure right.
I know there was also a lot that was out of his control, the timing, the background and so on. But it should be an example to us.
Hey, I have experience with the preliminary parts of this - chemical engineering, but not in the context of cultivated meat. Happy to help / advise.
I have run industrial workshops where we'd get everyone in a room, start with a blank sheet of paper and end up with an 80/20 process flow diagram, highlighting the certainties and the open questions and the opportunities for further research, and then move on from this (with a different group sometimes) to build an 80/20 TEA.
To be clear, what I have run was not as computationally intense as you propose. The model with Monte-Carlo syntheses etc would typically be a secondary step. The first step would be to get the right information into a flowsheet, then into a TEA, and for each parameter to have a clear idea of the sources of variability and the uncertainties. Then you can even run the Monte Carlo simulation on the TEA itself if it's simple enough.
It's not rocket-surgery, as W would say. Just structure and getting the right people, the right knowledge and the right mentality in the room, and getting the right pre-work done.
Since I don't work in this field, I can't really say to what extent the bit I could help with has already been done ... if not, I'd be happy to help, time permitting. No interest in being paid to help, at least for the first iteration.