EA Forum Podcast (All audio)

AI in aquaculture research at Rethink Priorities

Rethink Priorities’ How AI is affecting farmed aquatic animals is a three-part series that examines AI technologies being developed to address challenges in the aquaculture industry. As global aquaculture faces economic and technical constraints, this series examines whether and how the industry is turning to AI solutions to facilitate expansion. The series evaluates the innovation, deployment, and animal welfare impacts of these technologies to help animal advocates and funders identify which developments should be endorsed and what actions should be taken to prevent increased animal suffering.

For all queries, please contact [email protected].

Introduction

Artificial intelligence (AI) introduces new capabilities to animal agriculture that could alter production methods, economic structures, and animal welfare outcomes. Responding strategically requires an understanding of how quickly such changes will unfold, whether they will benefit or harm animal welfare, and what interventions will remain relevant. In this three-part series, we take a close look at how AI will be used over the next five years in aquaculture, which collectively farms hundreds of billions of animals each year for food.

Part 2: Deployment

This report analyzes the current state of AI deployment in aquaculture, examining where AI-aquaculture tools are [...]

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Outline:

(00:18) Introduction

(00:52) Part 2: Deployment

(02:06) Executive Summary

(04:43) Background

(05:24) Scope

(08:28) Results

(08:31) Three-Quarters of Companies in Our Database Specialize in Aquaculture

(09:26) Europe Leads Company Presence, Followed by Latin America and Southeast Asia

(11:04) Aquaculture AI Flows Predominantly From Northern Europe into Latin America and the Rest of Europe, With Innovation in Southeast Asia Largely Staying Within Southeast Asia

(12:48) Norway and Scotland Are the Two Largest Net Exporters of Aquaculture AI by Absolute Net Flow.

(14:42) Salmon and Shrimp Have the Largest AI Deployment Footprints

(16:56) Salmon

(18:49) Shrimp

(21:46) Experts Suggest Biomass Tools Lead On-Farm AI Deployment in Salmon, While Feed Optimization Dominates in Shrimp

(25:24) The Primary Barrier to AI Adoption is an Unclear Return on Investment

(29:37) Government Action Contributes to Shaping AI Development and Adoption in Aquaculture

(31:48) Experts Predict That AI Tool Uptake Will Increase Rapidly in the Short-Term

(33:55) Conclusions

(35:42) Acknowledgements

(36:53) Appendix

(36:56) Definitions

(37:41) Expert Profiles

(38:09) Claude-Review of Academic Papers on Barriers to Adoption of AI in Aquaculture

(40:03) Ways in Which We Could Be Wrong

(40:10) How Our Database Could Be Incomplete or Inaccurate

(45:20) Regional Groupings

(46:46) Bibliography

The original text contained 7 footnotes which were omitted from this narration.

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First published:

June 29th, 2026

Source:

https://forum.effectivealtruism.org/posts/i5XMLwHhtLRhSqhM6/how-ai-is-affecting-farmed-aquatic-animals-part-2-deployment

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This is a crosspost from the new Animal Welfare Alignment Newsletter by Anima International. You can subscribe on Substack if you are interested in following these efforts. Audio reading also available on Substack.

The goals of this post are to:

1. Raise a question I see as crucially important to the goal of aligning AI to animal welfare, and to altruistic values generally; and
2. Offer a partial solution to that question—one I am not very confident in—so it can be critiqued.

Summary of important claims/arguments:

• When we talk about aligning AI to animal welfare (or welfare of digital minds, or even human welfare) different ideas may come to mind, such as “not speciesist” or “wants to end factory farming.” These ideas can be arranged on a spectrum from broad values to specific actions or ways the world should be changed.
• Most people thinking about animal welfare alignment agree that we should try to constrain future superintelligent AIs to broad values while deferring to them on more specific actions. But it is not clear where to draw the line between these two.
• Current alignment techniques further complicate this by compressing and distorting the lessons we try to teach AIs. [...]

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Outline:

(01:56) Alignment to what?

(04:20) Does intelligence lead to better moral conclusions?

(06:53) Which questions should we defer to superintelligent AI?

(10:11) Current alignment strategies are imprecise

(12:53) Where does that leave animal welfare alignment?

(13:48) Strategy #1: Train & evaluate a broad distribution of practical decisions

(18:39) Strategy #2: Urgently research unresolved foundational questions

(19:49) Minimum viable values for animal welfare alignment

(20:53) Summary of recommendations

The original text contained 11 footnotes which were omitted from this narration.

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First published:

June 30th, 2026

Source:

https://forum.effectivealtruism.org/posts/mnLqdvnpKiudivyfv/what-would-an-animal-aligned-ai-be-aligned-to

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Narrated by TYPE III AUDIO.

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Poll: Assuming we end factory farming before 2100, which factor will have contributed the most? The scale runs from Alternative proteins to Social moral changes.

Bullet point summary:

• Cultivated meat could have a price between $15/kg and $30/kg according to reputable technoeconomic analysis, which we review and explain.
• We present an interactive demand-side economic model where we translate that price to market share: https://pabloamc.github.io/Cultivated_meat/interactive.html
• Some species, like pork and especially chicken, are tough to replace with cultivated meat. Others, like cows and seafood, are more significantly more tractable. This could be good for shrimp and fish.
• Beachhead products exist, in particular foie-gras and high-end fish.
• Disruptive innovation economic theory says cultivated meat will have a hard time because there is no pressing problem that mainstream people perceive, but it is feasible in the same way electric cars are disrupting petrol cars.
• Some of the main advantages of cultivated meat include significantly addressing vegan attrition rates, by lowering the perceived social or health taxes. Long term, this should make conventional meat less and less socially acceptable: no longer a “necessary evil”.
• If electric cars are a good guide, government (or China) support will be important.
• In the end, the [...]

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Outline:

(03:41) Introduction

(08:10) Technoeconomic analysis

(14:55) My conclusions

(16:01) From price to consumer behaviour

(23:35) Demand and disruption

(29:02) Conclusion

(33:25) Bibliography

(33:31) Appendix: The science of cultivated meat

(35:19) Cell lines

(36:42) Cultivated media

(39:37) Biorreactor

(43:03) Humbird, 2022

(44:14) Negulescu, 2023

(45:30) Pasitka, 2024

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First published:

June 26th, 2026

Source:

https://forum.effectivealtruism.org/posts/ED2ag8hYTWf4kmL3x/cultivating-hope-calibrating-the-expectations-for-cultivated

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Assuming we end factory farming before 2100, which factor will have contributed the most?92 votes so far. Voting closes in 25 days. Place your vote or view results.Alternative proteinsSocial moral changes

Bullet point summary:

• Cultivated meat could have a price between $15/kg and $30/kg according to reputable technoeconomic analysis, which we review and explain.
• We present an interactive demand-side economic model where we translate that price to market share: https://pabloamc.github.io/Cultivated_meat/interactive.html
• Some species, like pork and especially chicken, are tough to replace with cultivated meat. Others, like cows and seafood, are more significantly more tractable. This could be good for shrimp and fish.
• Beachhead products exist, in particular foie-gras and high-end fish.
• Disruptive innovation economic theory says cultivated meat will have a hard time because there is no pressing problem that mainstream people perceive, but it is feasible in the same way electric cars are disrupting petrol cars.
• Some of the main advantages of cultivated meat include significantly addressing vegan attrition rates, by lowering the perceived social or health taxes. Long term, this should make conventional meat less and less socially acceptable: no longer a “necessary evil”.
• If electric cars are a good guide, government (or China) support will be [...]

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Outline:

(05:12) Introduction

(09:43) Technoeconomic analysis

(16:31) My conclusions

(17:37) From price to consumer behaviour

(25:06) Demand and disruption

(30:34) Conclusion

(34:56) Bibliography

(35:02) Appendix: The science of cultivated meat

(36:46) Cell lines

(38:09) Cultivated media

(41:01) Biorreactor

(44:27) Humbird, 2022

(45:38) Negulescu, 2023

(46:55) Pasitka, 2024

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First published:

June 26th, 2026

Source:

https://forum.effectivealtruism.org/posts/ED2ag8hYTWf4kmL3x/cultivating-hope-calibrating-the-expectations-for-cultivated

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Subtitle: How to Ride Without Losing Your Mind

Five years ago, Ajeya Cotra memorably described Effective Altruist reasoning as a “train to crazy town”—with longtermists in particular staying on the train for longer than their nearterm-focused colleagues. It's not a perfect metaphor, but what I suspect resonates for a lot of people is the sense that EA-style abstract reasoning can push you in directions you may not antecedently want to go (i.e., against your natural sympathies), and there's something potentially alienating or even threatening about that.[1]

Earlier still, back in 2015, Scott Alexander wrote about the dilemma that either we shouldn’t care about non-human animals at all, or they should totally swamp every other moral concern. There's no realistic chance that the correct moral weighting conveniently turns out to be that precise value needed to justify a balanced approach on first-order grounds. His response was to “safeword out” of that whole line of abstract reasoning for the sake of his sanity. I actually think that's a pretty good response, but would like to try to give it a more principled backing—one that turns out to carry a surprising upshot: that moral theories may not be meant to guide us [...]

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Outline:

(05:46) Moral Uncertainty

(09:42) Comparing Risks

(15:08) Wrapping up

The original text contained 5 footnotes which were omitted from this narration.

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First published:

June 30th, 2026

Source:

https://forum.effectivealtruism.org/posts/3kFXnGeahhPHy97m6/the-train-to-crazy-town

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Why building and backing Welfare Tech companies may be one of the most promising things we can do for billions of animals.

I used AI to assist in writing this post, but I’ve rewritten it extensively and endorse it.

• Announcing the launch of Spring Innovation Fund, a not-for-profit venture philanthropy studio and fund built specifically for Welfare Tech: technology that improves animal welfare in ways that make commercial sense for producers to adopt.
• We think Welfare Tech is unusually promising: neglected, cost-effective, fast-acting, and scalable, with a large amount of low-hanging fruit; and we address some of the leading objections below.
• Three ways to get involved: Spring Works (engineers & builders), Spring Studio (ideators & entrepreneurs), and Spring Ventures (companies & investors).

1. Why we built Spring

I’m Eitan, a long-time EA who spent most of a decade working on turning cultivated meat from an idea into a real field, including founding Mission Barns. Now, I’ve teamed up with Milo Runkle — co-founder of the Good Food Institute, New Crop Capital, Joyful Ventures, among other groups — to found Spring Innovation Fund, together with Nate Crosser, who spent years as an agtech and biotech VC.

Welfare Tech is [...]

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Outline:

(00:12) Why building and backing Welfare Tech companies may be one of the most promising things we can do for billions of animals.

(01:07) 1. Why we built Spring

(04:14) 2. Why Welfare Tech is high-impact

(11:06) 3. Why for-profit companies?

(12:47) 4. Objections

(18:38) 5. Who Spring is for

(20:57) Notes

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First published:

June 30th, 2026

Source:

https://forum.effectivealtruism.org/posts/CzJoXj6iwYvaMdkg5/announcing-spring-a-venture-studio-and-fund-for-animal

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Narrated by TYPE III AUDIO.

This post presents the executive summary from Giving What We Can's impact evaluation for 2025. At the end of this post we share links to more information, including the full report and working sheet for this evaluation. We look forward to your questions and comments!

Executive summary

Giving What We Can (GWWC) is working towards a world without preventable suffering or existential risk, where everyone is able to flourish. We do this by making effective and significant charitable giving a norm among those who can — primarily through our flagship program: the 🔸10% Pledge, a lifetime commitment to give at least 10% of income to highly effective charities. Annually, our growing community of roughly 20K donors and pledgers records over 80 million dollars USD in charitable donations with GWWC.

As an organisation that advocates for effective giving, we think it is important to hold ourselves to the same standard. This report is our third impact evaluation of this type and examines the cost effectiveness of ourselves as an organisation in 2025.

Our headline findings and estimates:

• Our 2025 giving multiplier was 7x — GWWC produced 16 million dollars in value for highly effective charities in 2025, at a [...]

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Outline:

(00:30) Executive summary

(03:56) Where you can learn more

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First published:

June 30th, 2026

Source:

https://forum.effectivealtruism.org/posts/QarcSn67DvYBPuYm3/gwwc-s-2025-impact-evaluation-executive-summary

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Narrated by TYPE III AUDIO.

This is a link post.

Abstract

We make the case for training AIs to be risk-averse in resources — specifically, to treat resources as having diminishing marginal utility. These AIs would (for example) choose $40 for sure over a half-chance of $100 and a half-chance of $0. We argue that risk aversion can preserve AIs’ usefulness in the event that they turn out aligned, and that it provides an extra line of defense in the event that AIs turn out misaligned: misaligned but risk-averse AIs would prefer a higher chance of modest payments to a lower chance of successful rebellion, so in many circumstances we could pay these AIs not to rebel against us. We sketch out some possible methods of training AIs to be risk-averse, and we give reasons to be cautiously optimistic about these methods’ success. The main reasons are that risk aversion is a broad target and easy to reward accurately. Overall, risk aversion seems like a promising line of defense against threats from misaligned AI. Frontier AI companies should consider trying to make their AIs risk-averse.

Introduction

Future AIs might turn out misaligned, pursuing goals that their developers don’t intend. Just to make things concrete, let's [...]

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Outline:

(00:15) Abstract

(01:20) Introduction

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First published:

June 24th, 2026

Source:

https://forum.effectivealtruism.org/posts/ZvEp2G5xi8kQMgPxd/risk-averse-ais

Linkpost URL:
https://www.forethought.org/research/risk-averse-ais

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This is a link post.

The existential AI safety community needs to take building a civic and social movement seriously as a core intervention. We believe this is a high-value, badly neglected approach to reducing catastrophic/x-risks from AI because it may significantly enhance the likelihood of governance efforts succeeding at keeping humanity safe.

Note: this post is about PauseAI, not PauseAI US, which is a distinct entity with a different leadership team and approach.

This post was written by Matilda da Rui and Maxime Fournes, with significant contributions from Benjamin Schmidt (PauseAI Germany co-lead).

Executive Summary

The existential AI safety community needs to take building a civic and social movement seriously as a core intervention. We believe this is a high-value, badly neglected approach to reducing catastrophic/x-risks from AI because it may significantly enhance the likelihood of governance efforts succeeding at keeping humanity safe. As far as we can tell, only one organisation is building this infrastructure across continents: PauseAI. This post lays out our reasoning and our track record, and makes the case that funding this work is one of the highest value-for-money contributions available to anyone looking to reduce AI risk.

Why don't we already have a pause [...]

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Outline:

(00:53) Executive Summary

(06:37) Introduction

(09:14) 1. Our theory of change

(09:18) Prologue

(11:27) 1. The shape of the problem as we see it

(14:47) 2. Necessary conditions for reaching a pause

(17:45) 2. Our role towards a global treaty and in the AI safety ecosystem

(17:52) 1. Our niche within the ecosystem

(21:55) 2. Policymakers need strong enough incentives to act

(26:04) 3. The path to a treaty

(31:56) 4. How we can grow fast without breaking

(39:29) 5. Failure modes

(40:31) 3. Our path so far and where we're headed

(41:01) 1. Bootstrap phase (2023-2025)

(45:22) 2. New leadership, professionalisation and federation

(48:19) 3. Recent outputs

(54:48) 4. Support us

(54:51) 1. Fund us if you can

(01:00:10) 2. What you can do if you can't fund us

(01:00:52) Conclusion

(01:02:41) Bibliography

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First published:

June 26th, 2026

Source:

https://forum.effectivealtruism.org/posts/dLexMyjhAMmG33KnB/existential-ai-safety-needs-an-effective-social-movement

Linkpost URL:
https://www.lesswrong.com/posts/aoqhszdEWqcFWbnda/existential-ai-safety-needs-an-effective-social-movement

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TLDR: what is the grant round?

grantmaking.ai is launching a 1 million dollars grant round, distributing 5 thousand dollars to 50 thousand dollars per successful application to people and projects working to reduce x-risk from AI.

Applications will be reviewed by Gavin Leech, Ryan Kidd, and Marcus Abramovitch. We aim to make all funding decisions by July 28th. Applications submitted by July 13th are guaranteed a priority review. You can still apply after July 13th, and we will make our best effort to review late submissions as long as funding remains.

Grant applications will be mostly public, though we allow certain sensitive details to be kept private. Even if you are not applying, we invite you to join the platform to review and comment. We have set aside 100 thousand dollars of the budget to be given to top commenters as regranting budgets, so please share your thoughts and help us pick out awesome projects!

Who are we?

grantmaking.ai was initialized by Anton Makiievskyi, who is funding this round and brought the team together, built by Matt Brooks (lead dev) and Melissa Samworth (ui/ux), and advised by Austin Chen with Manifund handling grant distribution.

Why we’re building this platform [...]

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Outline:

(00:16) TLDR: what is the grant round?

(01:16) Who are we?

(01:35) Why we're building this platform & launching a grant round

(02:53) What is grantmaking.ai, and who is it for?

(04:13) Grant round details

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First published:

June 29th, 2026

Source:

https://forum.effectivealtruism.org/posts/AnMtdJfDym8bGjPB2/usd1m-ai-x-risk-grant-round-is-live-on-grantmaking-ai-apply

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Narrated by TYPE III AUDIO.