EA Forum Podcast (All audio)

Hundreds of billions of animals are trapped in the food industry or suffer in the wild. Our goal is to help you make a bigger positive difference for animals by providing you with impactful giving opportunities that can reduce animal suffering to the greatest extent possible. We are excited to tell you about the five charities we recommend this year!

Animal Charity Evaluators (ACE) spends several months each year evaluating animal advocacy organizations to identify those that can do the most good with additional donations. In 2024, our team of researchers conducted comprehensive evaluations of the 10 animal advocacy organizations that seemed to be doing the most promising work for animals based on what they shared in their evaluation applications. We are grateful to all the charities that applied and agreed to participate in this year's charity evaluations. We believe that each of the charities we chose to evaluate [...]

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Outline:

(02:07) Recommended in 2024

(14:14) Recommended in 2023

(26:22) Support our Recommended Charities

(27:17) Final Thoughts

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Thanks to the generous EA community, it looks like Legal Impact for Chickens (LIC), has a real chance to make cruelty a liability.

Sometimes it can feel like the burden rests entirely on activists to beg Big Ag companies to give animals mercy. But an animal's owner is the one with the obligation to care for the animal. Animal cruelty and neglect are crimes.

So LIC aims for a world where Big Ag companies themselves will proactively ensure their treatment of animals complies with the law. Company executives and general counsels should make sure the company's animals have proper food and clean water. Companies should refrain from animal torture on their own, simply because the law says so.

Below I give you a background on who we are, describe our most recent work, discuss an objection to LIC's work, and lay out how we’d use marginal [...]

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Outline:

(01:02) I. LIC works to make cruelty a liability.

(03:32) II. LIC's most recent work:

(05:35) III. An objection to LIC's work

(07:17) IV. LIC aims to fill ~$90,000 gap by EOY.

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On November 9, it's been a year since the passing of Sebastian Lodemann. In a vigil, his former colleagues and friends from the EA community shared what they learned from him at the end of last year. We’re sharing some of these statements anonymously in slightly edited form.

Humility Paired with Exceptional Competence

"I have never worked with someone whose humility matched such immense intelligence and effectiveness. Sebastian was incredibly skilled in many areas but never spoke about his accomplishments. In my experience, he was humble and quiet, always saying the right thing at the right time to encourage and include others. He ensured we considered important matters and stayed on the right track without ever drawing attention to himself. I deeply admire this quality and aspire to emulate it. There's so much I have to learn from him in this regard."

"Among the many professionals I've met, Sebastian [...]

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Outline:

(00:25) Humility Paired with Exceptional Competence

(01:59) Generosity and Mentorship

(03:35) Encouragement and Empowerment

(04:28) Open-Mindedness and Genuine Curiosity

(05:38) Balancing Personal and Professional Life

(06:43) Sense of Humor and Light-Heartedness

(07:32) Commitment to Self-Improvement and Well-Being

(08:52) Inspiring Others Through Action

(09:32) A Grounded Approach to Lifes Challenges

(10:05) Lasting Impressions and Farewell

(11:03) Continuing Sebastians Legacy

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Observatorio de Riesgos Catastróficos Globales (ORCG) is dedicated to safeguarding humanity's future by addressing the full spectrum of global catastrophic risks. This includes crucial work in Artificial Intelligence, where we have secured funding and achieved significant results in 2024, with even greater impact expected in 2025. You can explore our key AI publications in the (Appendix). However, while AI risk is a critical concern, other urgent threats demand our attention, and these areas are currently facing significant funding challenges. In 2024 and 2025, ORCG needs your support to continue tackling these neglected yet crucial areas:

• Pandemic preparednes: The COVID-19 pandemic exposed deep vulnerabilities in our global systems. We need to learn from this crisis and invest in robust mechanisms for recovery and future preparedness. This includes strengthening healthcare infrastructure, developing equitable vaccine distribution strategies, and addressing the long-term social and economic consequences of pandemics.
• Food Security During ASRS [...]

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Outline:

(02:15) Why Support ORCG in 2024-2025?

(03:48) How Your Donation Will Make a Difference:

(08:55) Appendix

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TL;DR

Healthier Hens (HH) was started to improve cage-free hen welfare, focusing on key neglected issues such as keel bone fractures (KBFs). Throughout the last three years, the HH team:

• chose a pilot country (Kenya),
• looked into a promising dietary intervention aimed at Global North cage-free farms (negative outcomes),
• scoped the state of feed quality, farmer and vet awareness in Kenya (feed quality can be poor and inconsistent; farmers are unaware yet eager to learn; vets do not have the capacity to develop and practice hen welfare assessment skills),
• looked into the prevalence and severity of KBFs on cage-free farms in Kenya (40%, relatively low severity),
• quantified the potential cost-effectiveness of other prevalent on-farm welfare issues (thermal stress: 256x, access to water: 27x, access to feed: 28x lower than additional global corporate cage-free work).

Despite struggling with efficient fundraising, the team raised and used $297k to do the [...]

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Outline:

(00:06) TL;DR

(02:17) Decision to Close

(03:05) Notable Accomplishments

(05:15) Lessons Learned

(06:24) Financial Overview

(07:17) Team Update

(07:56) Knowledge Transfer

(08:43) Future of Hen Welfare Work

(09:22) Gratitude and Acknowledgments

(09:43) Getting in touch

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It's been just over a year since ARMoR launched through the CE/AIM incubation program! In that time, we’ve worked hard to push for policies that will help tackle the rising threat of antimicrobial resistance (AMR) and made some strong progress towards this aim.

As part of our anniversary, we want to take the opportunity to:

1. Explain why AMR is so important
2. Share a little about how our first year has gone
3. Make the case for why our work is worth supporting

Please contact us at [email protected] if you have any questions, comments, feedback, or are interested in donating!

TL;DR 

1. Antimicrobial resistance is a serious global health threat. 
2. We need a continuous pipeline of new antimicrobials coming to market to replace those which are no longer effective. 
3. Market incentives have failed to stimulate the needed innovation. 
4. Significant analysis has suggested that ‘pull incentives’ could be a highly [...]

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Outline:

(00:49) TL;DR

(02:05) Antimicrobial resistance is a looming global health crisis

(02:11) The growing health burden of antimicrobial resistance

(04:01) The market failure preventing antibiotic development

(06:24) Fixing the market failure with pull incentives

(08:33) Global Access and Stewardship Conditionalities

(09:12) Our first year: research, advocacy, and informational lobbying

(13:57) Programs, Progress, and Next Steps

(22:41) Cost-effectiveness of AMR advocacy

(24:39) The impact of Marginal Funds

(26:06) Conclusion

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PauseAI US needs your donations! We were very fortunate not to have to do much dedicated fundraising up until this point, but I was caught off-guard by receiving nothing in the SFF main round (after receiving multiple speculation grants), so we're in a crunch and only fully-funded the end of 2024.

If you're sold, you can donate right now via PauseAI's general support Manifund project, the text of which I'll share here below the dots.

If you're open but you have questions, or you just thought of a great question you know other people are wondering about, ask them in the comments below! I'll answer them before or on 11/19/24.

Project summary

PauseAI US's funding fell short of expected, and now we are only funded until the end of 2024! Money donated to this project will go to fund the operations of PauseAI US until midyear 2025.

[...]

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Outline:

(00:59) Project summary

(01:17) What are this projects goals? How will you achieve them?

(04:46) How will this funding be used?

(07:04) Who is on your team? Whats your track record on similar projects?

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Overview 

With Marginal Funding Week, we want to share key updates on the EA Animal Welfare Fund (AWF). We'll cover what we've accomplished so far in 2024, our impact this year, recent changes, and where we're headed next - including current constraints to our impact. We think this info will be helpful for anyone considering year-end donations.

Since its founding in 2017, AWF has distributed $23.3M across 347 grants. This year, we’ve distributed $3.7M across 51 grants. We made grants across multiple intervention categories and aimed to impact a variety of species. Our most frequently funded strategic area was welfare campaigns, policy advocacy and research. The most frequently targeted species were egg-laying hens followed by multiple farmed animals, wild animals, and shrimps.

While the impact of many of our 2024 grants is still unclear, our previous grants have made significant progress, reflecting our ability to identify opportunities with [...]

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Outline:

(00:08) Overview

(02:12) 1. Background

(03:43) 2. A year in review

(03:47) Key Numbers and Reach

(04:14) Grant Distribution

(05:27) By intervention type

(06:25) By species

(09:04) Highlighted Grants

(13:36) 3. Organizational updates

(18:47) 4. Future plans

(21:58) 5. Room for more funding

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High Impact Professionals (HIP) has already driven at least 20 career transitions and inspired 17 effective giving pledges in 2024 alone, generating over $1 million in counterfactual impact. To sustain this work, HIP requires a minimum budget of $136,000 for an additional year of operations; however, a preferred baseline budget of $191,000 will enable HIP to expand its work and impact. Our current runway extends to February 2025. With your support, we can continue empowering experienced professionals to make high-impact career changes across diverse causes. Contact us or make a donation here.

2024 Achievements & Impact

In 2024, HIP has achieved the following:

• At least 20 career transitions: Through the Impact Accelerator Program (IAP) and Talent Directory (TD), HIP guided experienced professionals into high-impact roles.
• 17 pledges inspired: HIP motivated 8 lifetime 🔸10% Pledges and 9 🔹Trial Pledges, fostering a culture of effective giving.
• Over $1 million in [...]

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Outline:

(00:52) 2024 Achievements and Impact

(01:39) Goals for 2025 and Beyond

(02:26) Case Studies

(03:53) Funding Priorities

(04:34) Why Support HIP?

(05:23) How to Support HIP?

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Rethink Priorities' Worldview Investigations Team is sharing research agendas that provide overviews of some key research areas as well as projects in those areas that we would be keen to pursue. This is the second of three such agendas to be posted in November 2024. It describes our view of the digital welfare research landscape and the kinds of questions that we’re interested in taking up.

Our team is currently working on a model of the probabilities of consciousness in contemporary AI systems that touches on a variety of the questions posed here. We plan to release research related to the issues raised by that project as we go. We're interested in other projects related to the questions below, and we have some specific ideas about what we'd like to work on, but this is a fast-moving space and so we would recommend that prospective donors reach out [...]

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Outline:

(01:02) Introduction

(06:03) 1. Questions of Systems

(08:06) Significant system divisions

(08:16) Deep Learning Models vs Other AI Paradigms

(09:33) Transformers vs Other Deep Learning Models

(10:35) Training Phases vs Deployment Phases

(11:57) Scaffolded vs Pure Models

(13:07) General vs Task-Specific Models

(14:29) Embodied, Agentic, and Oracle Models

(15:59) Digital vs Neuromorphic Implementation

(16:31) Sample questions

(17:37) 2. Questions of Capabilities and Mechanisms

(20:12) Sample questions

(20:19) Do LLMs have access to their own internal processes? Can they tell what is going on inside of themselves?

(21:09) Do LLMs or other deep learning models have goals? Are their actions influenced by representations with a world-to-mind direction of fit?

(21:50) For models with goals, do they have decision-making processes? Do they weigh different considerations for alternative options and contrast them with each other?

(22:18) To what extent do AIs (LLMs or other deep learning models) use internal models for generating predictions? Are there many such models within a single system, and if so, do they have a heterogeneous structure? What aspects of training encourage the formation of such models?

(23:13) What are the limitations on deep learning model creativity?

(23:57) Do LLMs have special representations for the true relationships between concepts as opposed to false but widely believed relationships?

(24:56) How do LLM or other deep learning model representations map onto the conceptual/non-conceptual distinction from the philosophy of mind?

(25:36) To what extent can LLMs reason about possibilities in order to choose text continuations? Are the limits of that reasoning constrained to the structure of outputted text?

(26:54) 3. Questions of Cognitive Assessment

(28:14) Important traits

(29:36) Sample questions

(29:46) Is the case for AI possessing this trait primarily dependent on computational functionalism?

(30:22) How plausible is computational functionalism for this trait, as opposed to other nearby theories (e.g., non-computationalist functionalism), or other kinds of metaphysical theories altogether?

(31:08) What theories of this trait are taken seriously by experts? Which are most plausible?

(32:10) How well is the space of viable theories of this trait covered by existing proposals? If we just evaluate systems according to the specifics of existing proposals, are we likely to be missing out on a number of other equally viable theories?

(33:07) What should we think of minimal implementations of each theory's proposed criteria? How do we judge when we have substantial enough implementation to truly be conscious?

(34:06) For each of the major theories, what capacities or mechanisms are most important to look for? Are they satisfied by any existing models? Should we expect them to be soon?

(34:59) Are there any trends among popular theories that might be useful for assessing the presence of the trait even if we are skeptical that any theory is precisely correct?

(35:49) Are there plausible theory-independent indicators / proxies for this trait?

(36:24) Does this trait exist categorically or does it have a vague / indeterminate extension?

(37:04) 4. Questions of Value

(38:46) Sample questions on the value of consciousness

(39:10) Is consciousness intrinsically valuable?

(40:09) Is it simply wrong to end the lives of conscious beings?

(41:00) Could non-conscious beings have welfare?

(41:29) Could non-conscious mental states contribute to welfare?

(42:04) Are there other states in the ballpark of consciousness that might matter?

(42:47) What should we think about the value of indeterminate or partial consciousness?

(43:34) Sample questions on the value of valenced experiences

(44:43) What determines the value of valenced experiences?

(45:56) How should we trade off between positive and negative experiences?

(46:55) How should we distinguish positive from negative valenced experiences?

(48:23) What is the connection between temporal duration and value?

(49:45) How do we value experiences that are shared between minds?

(50:40) Sample questions on the value of desires

(51:12) Do all desires matter or only specific kinds? Does it matter whether those desires are conscious? Does it matter if they are reflected upon or otherwise endorsed?

(51:49) How do we weigh desires?

(52:35) Other welfare contributors

(53:48) 5. Questions of Domain Epistemology

(55:17) Sample questions

(55:24) Is expert opinion biased toward any specific answers?

(56:43) How confident are experts about our best answers to the relevant questions?

(57:32) How should we aggregate our uncertainties across different questions into an overall assessment of the moral status of AI systems?

(58:18) Acknowledgments

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