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Applications are currently open for the next cohort of AIM's Charity Entrepreneurship Incubation Program in August 2025. We've just published our in-depth research reports on the new ideas for charities we're recommending for people to launch through the program. This article provides an introduction to each idea, and a link to the full report. You can learn more about these ideas in our upcoming Q&A with Morgan Fairless, AIM's Director of Research, on February 26th.

 

Advocacy for used lead-acid battery recycling legislation

Full report: https://www.charityentrepreneurship.com/reports/lead-battery-recycling-advocacy 

 

Description

Lead-acid batteries are widely used across industries, particularly in the automotive sector. While recycling these batteries is essential because the lead inside them can be recovered and reused, it is also a major source of lead exposure—a significant environmental health hazard. Lead exposure can cause severe cardiovascular and cognitive development issues, among other health problems.  

The risk is especially high when used-lead acid batteries (ULABs) are processed at informal sites with inadequate health and environmental protections. At these sites, lead from the batteries is often released into the air, soil, and water, exposing nearby populations through inhalation and ingestion. Though data remain scarce, we estimate that ULAB recycling accounts for 5–30% of total global lead exposure.

This report explores the potential of launching a new charity focused on advocating for stronger ULAB recycling policies in low- and middle-income countries (LMICs). The primary goal of these policies would be to transition the sector from informal, high-pollution recycling to formal, regulated recycling. Policies may also improve environmental and safety standards within the formal sector to further reduce pollution and exposure risks.

 

Counterfactual impact

Cost-effectiveness analysis: We estimate that this charity could generate about 59 income doublings[1] per $1,000 (USD). However, this model carries significantly more uncertainty than our typical estimates due to limited evidence. Our model assumes that the charity would operate in three countries in parallel, with a 20% chance of success per country. If successful, we estimate that it could reduce blood lead levels by 5% in the target country.

Scale this charity could reach: We estimate that, if this charity’s work is successful, it could generate around 14,000 income doublings per year at scale per country of the size of Thailand.

 

Potential for success

Robustness of evidence: This intervention does not have a very strong evidence base, as it largely relies on case studies. Most evidence comes from high-income countries, though around seven LMICs have also made good progress. The most relevant case is Brazil, where implementing the three policies listed above was associated with a shift away from informal recycling, reducing its share from 45% to 10%. Some of the progress made in these countries has been industry-led (like in Brazil) rather than driven by NGOs, indicating potential industry support and opportunities for collaboration.

Additionally, the experience of existing nonprofits working on lead exposure mitigation suggests strong government interest. However, we anticipate that progress on ULAB recycling will be less tractable than for other lead exposure sources due to the complexity of the lead-acid battery market.

 

Theory of change (ToC): The primary ToC focuses on country-level policy advocacy, supported by local data (quantitative and qualitative) collection on the ULAB-recycling market, along with technical assistance to governments on regulatory and enforcement issues. Initially, we propose exploring three main policies: a tax exemption for ULABs to reduce the price difference between formal and informal recycling; extended producer responsibility (EPR), which requires manufacturers or importers to ensure that ULABs are recycled in the formal sector; and the establishment of a producer responsibility organization (PRO) to oversee enforcement of these policies on behalf of the government. However, other policies may also be promising, and solutions will likely require significant country-specific tailoring.

A secondary ToC envisions accelerating global progress on this issue by generating new evidence and advising governments and NGOs on the best practices. Currently, almost no one is filling this role, and experts have emphasized that a team focused specifically on ULAB recycling would be highly valuable.

 

Neglectedness

Neglectedness: We are confident that there is room for a new organization in this space. While major actors working on lead exposure—such as Pure Earth, UNICEF, and UNEP—are addressing ULABs, their efforts appear to be ad hoc rather than a core focus. However, there is some chance this could change in the short to medium funding from the Lead Exposure Action Fund increases.

Geographic assessment: Our analysis prioritizes countries with high lead exposure, a large informal employment sector, a sizeable population, and relatively low fragility and corruption. Based on these criteria, we identify Indonesia, India, Pakistan, Bangladesh, Mexico, Peru, Thailand, Colombia, Argentina, and Egypt, among others, as promising locations for this intervention. In general, we expect the greatest potential in middle-income countries that already have at least one high-quality formal ULAB recycling facility.

 

Additional Considerations

Expert views: We spoke with 13 experts, who we believe represent the majority of those working in this field. Most were enthusiastic about the prospect of a new organization, emphasizing that increasing engagement in this space could generate valuable new insights. The most common concern was that Brazil’s approach may not be directly applicable to other countries, as policy solutions would need to be tailored to local contexts.

Implementation factors: Our main concerns relate to access to information and execution challenges. There is a significant lack of data in this space, which will likely slow progress. Even basic details—such as the scale of lead poisoning from ULAB recycling and the locations of recyclers—are not readily available. Combined with the economic interests of the informal ULAB recycling industry, these factors make us believe that failure is more likely than success, with the probability of successfully reducing lead exposure estimated at around 10–25% per country. However, even if the charity does not achieve policy change, it would still generate highly valuable information for other actors in this space.

 

Scaling up Kangaroo Care

Full report: https://www.charityentrepreneurship.com/reports/kangaroo-care-scaleup 

 

AIM has incubated one organization providing Kangaroo Care (KC) working in India, Ansh (launched in early 2023; see original report here). KC is a package of interventions which involves skin-to-skin contact between a low birth weight baby and a caregiver, exclusive breastfeeding, and close monitoring of the baby and their relevant vital and danger signs. KC is a cheap and easy-to-administer form of neonatal care that is evidenced to be effective at reducing mortality and morbidity.

 

Cost-effectiveness analysis: We updated our 2022 cost-effectiveness analysis using our new template, incorporating data from Ansh’s pilot[2] and revised effect sizes for KC’s impact on mortality and morbidity based on our updated evidence review. Embedding KC capacity in hospitals in Pakistan is expected to be highly cost-effective, surpassing the cost-effectiveness anticipated by our previous model. The updated model estimates that the intervention could avert one DALY for every $50 spent.

 

Potential for success

Robustness of evidence: Overall, we are encouraged by the early-stage success of Ansh in building strong relationships with key stakeholders, which we feel is necessary for success in this space. Despite this update to feasibility, Ansh’s pilot shows that not all parents reach 8 hours of daily skin-to-skin contact. This may decrease the effectiveness of KC, as our understanding of its effects is largely based on evidence of 8 or more hours per day. Considering these factors and new evidence since publication, we have slightly reduced our estimate of KC’s mortality effects, but slightly increased our estimate of its morbidity effects.  

Theory of Change: We still think embedding capacity into the health system is a strong ToC that addresses many barriers to scaling up KC. We also weakly endorse exploring context-specific alternative ToCs, in particular, KC for emergency transport and initiating KC outside hospital settings.

 

Neglectedness

Geographic assessment: KC still remains highly neglected. We updated our assessment using a new template and more recent data. The recommended target countries remain largely the same, with most shifting positions within the top 10.

 

Additional Considerations

Expert views: We spoke with Ansh, GiveWell, and another KC implementation org whose insights mostly gave us positive updates, particularly regarding the value of starting an organization sooner rather than later.

Implementation factors: It would benefit the founding team to have a healthcare/medical background and familiarity with the target country, either through being a local or having previous work experience. We think a local founder would be preferable to make stakeholder relationships and access easier.

 

Differentiated Learning

Full report: https://www.charityentrepreneurship.com/reports/differentiated-learning 

 

Differentiated Learning (DL) is an educational approach that groups children by learning level, rather than their age, providing targeted instruction to improve foundational literacy and numeracy skills. This approach ensures that students who have fallen behind receive tailored instruction, allowing them to catch up on foundational skills. DL has been implemented at scale in multiple countries and evaluated by several randomized controlled trials (RCTs), making it one of the most promising interventions for improving the quality of education in low- and middle-income countries (LMICs).

 

Counterfactual impact

Cost-effectiveness analysis: We estimate the cost-effectiveness of this intervention to be between $12 and $45 (USD) per person doubling their future income. This estimate is based on projected impacts in the Philippines, the most promising country in our geographic assessment. The extent of this effect depends on the assumed relationship between education improvement and income gains.[3] This meets our $30 benchmark in most cases. Additionally, our model indicates that dozens of other countries also meet this cost-effectiveness bar.

Scale potential: A successful charity could operate at a large scale. If expanded to cover 10% of the Philippines, we estimate it could generate 1.6–6.2 million consumption doublings per year.

 

Potential for success

Robustness of evidence: We are highly confident in the effectiveness of this intervention. DL is one of the most studied education interventions in developing countries, with numerous RCTs demonstrating effectiveness.

Theory of Change: The primary Theory of Change (ToC) is to deliver DL—likely in collaboration with the NGO Pratham—in a country where no organization is currently delivering it or where only small local actors are active in limited regions.

There are various delivery models, including:

  • Training teachers to implement DL in their classrooms.
  • Running short-term learning “camps” led by staff or volunteers.

It is unclear to us which model would be most effective, and the best approach may vary by country or region.

An alternative ToC would involve partnering with existing NGOs that already deliver DL, providing them with training and monitoring and evaluation (M&E) to help them scale up and improve delivery quality. This approach could allow the charity to operate even in countries where DL is already present while still having a cost-effective impact.

 

Additional Considerations

Expert views: Experts from Pratham, TaRL Africa, J-PAL, and the World Bank were generally supportive of us working on DL. Some raised concerns about whether we could deliver DL to a high standard, though we suspect these concerns stem from past experiences with low-quality or uncooperative implementers—a challenge unlikely to apply to an AIM charity. Overall, key stakeholders in this space appear highly collaborative and were generally enthusiastic about the prospect of new implementing partners.

Implementation factors: DL is a complex intervention and evidence suggests that both uptake and fidelity of delivery strongly influence its effectiveness. While we expect the charity would be able to implement DL successfully at a small scale, we have some concerns about its ability to maintain high-quality delivery at a larger, sustainable scale.

 

Would this charity be additional?

While DL is not being implemented at scale in many countries, major organizations are already planning expansions, raising concerns that a new charity might provide limited additional value. However, existing actors are capacity-constrained, with more funding available for DL than they can absorb. Additionally, leading organizations such as Pratham and TaRL Africa typically operate via local implementing partners, and an AIM charity could serve in this role. Finally, most experts we consulted supported the entry of new high-quality implementers.

 

Which exact ToC should this charity pursue?

While both a volunteer-led model (more effective but less scalable) and a teacher-led model (more scalable but less effective) are viable approaches, it is also unclear whether the charity should deliver the intervention directly or support existing NGOs in scaling up and improving delivery.

The most suitable approach may depend on the country and context, and we do not yet have strong evidence to recommend one over the other. Potential founders of this charity should conduct follow-up research and consult experts—particularly those with prior experience implementing DL and local expertise in the target country—to determine the best model.

 

How does DL compare with other education interventions, such as structured pedagogy?

AIM previously recommended incubating a charity to deliver Structured Pedagogy (SP), another highly studied and cost-effective education intervention, which led to the creation of the Learning Alliance. This raises the question of how DL and SP compare and whether they could be synergistic. Our models suggest that both interventions have overlapping ranges of cost-effectiveness, though DL may be less cost-effective due to being more labor-intensive.

While SP focuses on improving teaching quality in standard classrooms, DL provides remedial education for students who have fallen behind. Given these distinct aims, the two approaches may be complementary, with a recent study in Morocco showing promising results from a combined approach.[4] In the future, this charity could explore co-delivering SP as a potential expansion.

 

Mass Communication for Education

Full report: https://www.charityentrepreneurship.com/reports/edu-mass-comm 

 

A nonprofit organization that leverages mass-communication strategies (mobile messaging) to provide caregivers and students with information on various aspects of education—including the returns to education, student effort, and institution quality—as a low-cost way to improve both attendance and learning outcomes.

 

Counterfactual impact

Cost-effectiveness analysis: We modeled an SMS-based intervention targeting grades five and six in South Africa and estimated the number of students it would need to reach to meet AIM’s cost-effectiveness bar of $30 (USD) per income doubling[1]. In our conservative model (assuming a 10% income increase from a one standard deviation (SD) improvement in test scores), the intervention would need to reach approximately 58,000 students per year at scale. In an optimistic model (assuming a 40% income increase from a one standard deviation improvement in test scores), it would need to reach approximately 8,700 students per year at scale. For context, this represents roughly 2.0% (conservative) or 0.3% (optimistic) of South Africa’s 10–12-year-old students.

Scale this charity could reach: Because this intervention primarily relies on SMS or other mass messaging, which are inexpensive per individual reached, we believe its potential scale is comparable to other nonprofits we have incubated, such as Family Empowerment Media (FEM).

 

Potential for success

Robustness of evidence: This intervention design has been evaluated many times with generally positive findings—however, it is less studied as a mobile intervention and has not been evaluated as a radio intervention. It is endorsed by the Global Education Evidence Advisory Panel’s 2023 Cost-effective Approaches to Improve Global Learning Report (GEEAP, 2023). More recently, researchers from the Centre for Global Development published a meta-analysis on the effects of providing information on the returns to education to parents and students, finding positive and significant average impacts on school participation and student learning (Evans & Acosta, 2024).

Theory of Change (ToC): The ToC behind this intervention is that providing persuasive and informative messaging on education can lead to increased caregiver and student engagement, resulting in higher attendance and improved learning outcomes. The specific design of a new nonprofit’s intervention will depend on contextual factors such as the suitability of different delivery mechanisms, and the availability of key information, such as test scores and data on school quality.

 

Neglectedness

Neglectedness: We identified one organization that works in this area as a for-profit focused on tertiary education in Brazil. Our understanding of the field leads us to believe that this intervention is popular but lacks implementers delivering at scale, mostly remaining as an evaluative pilot or delivered sporadically through government programs.

Geographic assessment: Our geographic assessment suggests that several countries would be strong candidates for an intervention. We are confident that a new nonprofit could identify countries where its work would be additional.

 

Additional Considerations

Fit for the CEIP: Our best guess is that this idea fits the typical CEIP participant profile since it does not require specialized expertise, has historically been attractive to participants, and is well-supported by the international education and development community. However, the founding team must be comfortable with an intervention that depends on large-scale implementation for cost-effectiveness and has weak feedback loops.

Expert views: We spoke with Guilherme Lichand, who founded a nonprofit that initially used SMS delivery before pivoting to work in tertiary education. He was generally positive about SMS interventions as part of a wider package of support to education. Other experts we briefly consulted were also generally supportive but expressed reservations about radio delivery.

Implementation factors: Overall, we see this intervention as similar to others being tested or delivered by past cohorts, including FEM, No Violence at Home, Learning Alliance, Notify Health, and Suvita. We did not identify any major concerns, such as risks of harm or lack of funding. However, our main concern is the challenge of measuring impact. Given that the expected effect on student test scores is likely to be small, any impact evaluation would require a large sample size to detect significant effects. Monitoring intermediate outcomes, such as attendance and drop-out rates, may be more feasible.

 

Establishing a Livelihoods Evaluator

Full report: https://www.charityentrepreneurship.com/reports/livelihood-charity-evaluator 

 

Incubating a new evaluator which would approach evaluation from a livelihoods perspective (‘improving lives, not averting deaths’, i.e., focusing on incomes, education, etc.). The evaluator is expected to be rigorous and produce public recommendations, like GiveWell.

 

Counterfactual impact

Cost-effectiveness analysis: We conducted a fairly conservative back-of-the-envelope calculation (56% chance of success; 70% discount on the average money moved per year by other evaluators in their first five years; average donation around 5x GiveDirectly).

Scale this charity could reach: We are highly uncertain where a reasonable estimate for a peak in funds moved for a successful evaluator could be. Nevertheless, we expect any ceiling to be well in excess of an organization's operating expenses, and as such, do not expect this to reduce an evaluator’s cost-effectiveness below our target bar.

 

Potential for success

Robustness of evidence: Non-profit evaluators can be categorized as “giving multipliers,” organizations that aim to increase the amount of money going to non-profits. To that end, we note several anecdotal cases of evaluators who direct between 6 and 31 times their operating budget to non-profit organizations. We think their success is a marginal positive update that other actors can also achieve. Still, we suspect that early movers in the space benefitted from the relative dearth of competition.

We also note with caution that the literature examining the psychology of effective giving is mixed and tends to find that information on effectiveness does not motivate donors to give more. We think this should continue to be evaluated and used to tailor strategies for converting donors.

 

Theory of Change: The theory of change for this intervention is relatively straightforward and reflects the approach of established players like GiveWell, Giving Green, and Animal Charity Evaluators. The organization will produce and market rigorous evaluations designed to appeal to a wide audience. These credible and persuasive analyses are expected to enhance donors’ understanding of what constitutes a high-impact non-profit and increase their motivation to direct funds towards effective organizations. Ultimately, this should result in more funding for impactful charities and improved well-being for their beneficiaries.

The greatest uncertainties in this ToC relate to the evaluator's ability to gain recognition and transform its research into donations. While existing organizations have demonstrated success in these areas, smaller actors often struggle to establish visibility and communicate the value of their work. Additionally, producing rigorous evaluations requires a high level of research expertise, as evidenced by the challenges and errors documented by evaluators in the past.

 

Additional Considerations

Is there a gap in the market?

We think that many gaps in the market could draw attention from prospective funders: there are only a handful of evaluators, and arguably only one or two very large and popular ones. Increasing the number of evaluators in the field will likely improve viewpoint diversity and plurality of approaches.

Livelihoods emerged as a strong option among the handful we considered. We think existing evaluators in this space give much greater moral weight to health-focused interventions—especially life-saving ones—over income-focused interventions. Many experts were excited by the idea of increased evaluation in this space. However, some felt the space was already well covered by existing organizations.

 

Will there be sufficient donor interest?

We are unsure but marginally confident that there will be sufficient early interest in the outputs of an evaluator's work. We have already received some informal interest from two or three foundations and/or individuals who have suggested they would be interested in either funding or consuming the research produced to inform their donations. It should be noted that given more time, we would have scoped the donor market more for this type of moral view and interest. However, we note the existence of several potentially aligned funders, such as the Livelihood Impact Fund, the Agency Fund (and potentially those listed on their site as partners), and other large philanthropic donors.

 

Will the new organization be successful in gaining an audience?

By audience, we mean attention from the broader public. We think gaining traction within aligned audiences, such as effective altruism-aligned individuals and organizations, would account for earlier and more tractable success for the organization. However, we have a strong expectation that the organization seeks to broaden the types of funders and individuals it appeals to. GiveWell and Giving Green have succeeded in becoming “household brands” in the charity evaluation sector which gives us some confidence. However, other evaluators have remained relatively unknown and have adopted approaches to reaching out to high-net-worth individuals or donors.

 

Expert views: We carried out several informal consultations with individuals who have expertise in the field of non-profit evaluation and affiliated efforts, including a survey consultation (n = 11). Livelihoods was marginally the most favored option among the three we considered. Yet, there was considerable disagreement about potential funding sources, talent availability, and other implementation factors.

Implementation factors: We are most concerned about talent and tractability—we think that to achieve early success, an evaluator will need an early-stage team with strong research skills and resilience. We view non-profit evaluation as a highly technical skill, and expect that marketing those evaluations will also take considerable effort to get right.

 

Excited about these ideas?

We’d love to see you apply to found a new organisation based on one of these ideas through the Charity Entrepreneurship Incubation Program. 

There are no specific qualifications or previous expertise that we require - what we care about is finding talented, ambitious, mission-driven individuals. Our training and mentorship will give you the specific skills you need.

Applications are open until March 24th. To answer questions you may have, we’ve organised a series of online Q&A sessions with:

  1. ^

     An income doubling refers to an increase in a person’s lifetime earnings equivalent to twice what they would have earned in a single year without the intervention, based on projected career earnings and adjusted for present value.

  2. ^

     Our CEA relies on pilot data from work in two hospitals in Rajasthan from January to March 2024, but Ansh is now in their scale-up phase so specific numbers used in this model could already be out of date.

  3. ^

     At AIM, we model the relationship between one standard-deviation improvement in test scores (a meaningful academic gain relative to peers) and income to be between 10% and 40%, based on our review of the literature.

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I'm surprised to see no ideas that incorporate AI. Y-Combinator, the for-profit equivalent of AIM, is now ~75% AI startups. If AIM has looked into relevant ideas, I'd be curious to know what deterred them. 

I'm quite pro-AI.

At the same time, I think one challenge here is that it's hard to imagine many worldviews and corresponding projects where the following would be simultaneously true:

1. Global health charities are more efficient than AI-safety charities. 
2. The AI project in question wouldn't become obsolete after a few years, due to much better LLMs or TAI.
3. The project itself is highly exciting, perhaps in part because of advances in LLMs that are expected in a few years.

So basically, I think this might require a fairly narrow worldview that not too many people fall into. The people highly AI-pilled are focused on projects more specific to AI progress, and the least AI-pilled aren't very bought into the use of AI. 

(Correspondingly, my personal position is that I'm more on the AI-pilled side, and can't think of many AI-related global welfare projects that would excite me now over other AI projects.)

Although I think there probably are some great AI ideas that could help the world's poorest people, it's not easy to think of these or implement them. Usually the economies of the poorest people involve surprisingly little technology and are based around hand powered agriculture, basic goods and basic services. Internet where it is strong is often surprisingly expensive. 

Y combinator startups aim to make money from the richest people in earth, people's who's economy and lives are tied to technology and the Internet.

So the economic reality and ecosystems are completely different and it's hard for AI tools to penetrate super poor systems, while there's endless ways to capture value in high income countries.

I think there may be some super valuable AI ideas that could change the game for the world's poorest, but it's not obvious or clear yet. 

And where there are good ideas, convincing governments and NGOs to take on new ideas is super difficult. We at OneDay health have made a cool healthcare mapping tool based on AI generated population and road data which has transformed our ability to target our healthcare, and  has potential to help improve healthcare on the margins in multiple ways. NGOs and government showing some interest but besides a small USAID pilot in Pakistan it has been quite hard to get uptake.

https://forum.effectivealtruism.org/posts/GpAngpFmn3HFrBLnt/health-aim-a-mapping-tool-helping-health-providers-reach

I'm a sample size one who lives in a more income context and e been thinking hard about it, but I'm struggling to come up with too maybe potentially useful AI ideas right now.

YC aims at making VCs money; the Charity Entrepreneurship programme focuses on helping poor people and animals. I don't think the best ideas for helping poor people and animals are as likely to involve generative content creation as the best ideas for developed world B2B services and consumer products. The EA ecosystem isn't exactly as optimistic about the impact of developing LLM agents as VCs either...

YC aims at making VCs money; the Charity Entrepreneurship programme focuses on helping poor people and animals

I think both are trying to create value at scale. YC cares about what percentage of that value they're able to capture. AIM doesn't.  I suspect one ought, by default, assume a large overlap between the two. 

I don't think the best ideas for helping poor people and animals are as likely to involve generative content creation as the best ideas for developed world B2B services and consumer products

As every charity listed is focused on human wellbeing, let's focus on that. I think access to generative AI is better placed to help poorer people than it is to help richer people - it produces lower quality outputs than otherwise available to rich people, but dramatically better than those accessible to poor people. For example, the poorest can't afford medical advice while the rich get doctors appointments the same week.

 

The EA ecosystem isn't exactly as optimistic about the impact of developing LLM agents as VCs either..

It think the type of agent matters. It's unclear how a chatGPT wrapper aimed at giving good advice to subsistence farmers, for example, would pose an existential threat to humanity

 



The more I think about it, the more I suspect the gap is actually more to do with the type of person running / applying to each organisation, than the relative merit of the ideas.

I think both are trying to create value at scale. YC cares about what percentage of that value they're able to capture. AIM doesn't.  I suspect one ought, by default, assume a large overlap between the two. 

Not really. YC doesn't just care about percentage of value capture, it also cares about the total amount of value available to capture. This tends towards its target market being deep-pocketed corporations and consumers with disposable income to spend on AI app platforms or subscriAI tools for writing better software, and completely ignoring the Global South and people who don't use the internet much.

AIM cares about the opposite: people that don't have access to basics in life and its cost-effectiveness is measured on non-financial returns

I think access to generative AI is better placed to help poorer people than it is to help richer people - it produces lower quality outputs than otherwise available to rich people, but dramatically better than those accessible to poor people. For example, the poorest can't afford medical advice while the rich get doctors appointments the same week.

But if the advice is bad it might actually be net negative (and AI trained on an internet dominated by the developed world is likely to be suboptimal at generating responses to people with limited literacy on medical conditions specific to their region and poverty level in a language that features relatively little in OpenAI's corpus). And training generative AI to be good at specialised tasks to life-or-death levels of reliability is definitely not cheap (and nor is getting that chatbot in front of people who tend not to be prolific users of the internet)

It think the type of agent matters. It's unclear how a chatGPT wrapper aimed at giving good advice to subsistence farmers, for example, would post an existential threat to humanity

Unlike many EAs, I agree that the threat to humanity posed by ChatGPT is negligible, but there's a difference between that and trusting OpenAI enough to think building products piggybacking on their infrastructure is potentially one of the most effective uses of donor funds.  Even if I did trust them, which I don't for reasons EAs are generally aware of, I'm also not at all optimistic that their chatbot would be remotely useful at advising subsistence farmers on market and soil conditions in their locality. 

And especially not remotely confident it'd be better than an information website, which might not be VC-fundable, but would be a whole lot cheaper to create and keep bullshit-free

The more I think about it, the more I suspect the gap is actually more to do with the type of person running / apply to each organisation

I agree this is also a significant factor

Quite a few development and EA adjacent organisations think AI will be quite important, if not the most important factor for future development. It is already being used by many companies, charities and governments around the world.

Executive summary: AIM's Charity Entrepreneurship Incubation Program has identified five new high-impact charity ideas, including lead battery recycling advocacy, differentiated learning, kangaroo care expansion, education-focused mass communication, and a new livelihoods evaluator, each targeting significant gaps in public health, education, and economic development.

Key points:

  1. Lead Battery Recycling Advocacy – Aims to reduce lead exposure in low- and middle-income countries by advocating for policies that formalize lead-acid battery recycling, with potential health benefits but significant implementation challenges due to data limitations and industry resistance.
  2. Differentiated Learning (DL) – Proposes expanding a proven education intervention that groups students by learning level rather than age, improving foundational skills and future earnings; uncertainties remain about scaling quality and the best delivery model.
  3. Kangaroo Care (KC) Expansion – Seeks to embed KC—a cost-effective neonatal care method—in hospital systems, particularly in Pakistan, with evidence suggesting strong potential for reducing infant mortality but concerns about parents meeting the recommended daily skin-to-skin contact hours.
  4. Mass Communication for Education – Leverages SMS-based messaging to inform caregivers and students about the benefits of education, aiming to boost attendance and learning outcomes; cost-effective at scale but with challenges in measuring long-term impact.
  5. Livelihoods Evaluator – Proposes a new evaluator focused on income-boosting charities rather than life-saving interventions, addressing a gap in charity assessment; key uncertainties include donor interest and the ability to establish credibility and influence funding decisions.

 

 

This comment was auto-generated by the EA Forum Team. Feel free to point out issues with this summary by replying to the comment, and contact us if you have feedback.

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Hey everyone, I’ve been going through the EA Introductory Program, and I have to admit some of these ideas make sense, but others leave me with more questions than answers. I’m trying to wrap my head around certain core EA principles, and the more I think about them, the more I wonder: Am I misunderstanding, or are there blind spots in EA’s approach? I’d really love to hear what others think. Maybe you can help me clarify some of my doubts. Or maybe you share the same reservations? Let’s talk. Cause Prioritization. Does It Ignore Political and Social Reality? EA focuses on doing the most good per dollar, which makes sense in theory. But does it hold up when you apply it to real world contexts especially in countries like Uganda? Take malaria prevention. It’s a top EA cause because it’s highly cost effective $5,000 can save a life through bed nets (GiveWell, 2023). But what happens when government corruption or instability disrupts these programs? The Global Fund scandal in Uganda saw $1.6 million in malaria aid mismanaged (Global Fund Audit Report, 2016). If money isn’t reaching the people it’s meant to help, is it really the best use of resources? And what about leadership changes? Policies shift unpredictably here. A national animal welfare initiative I supported lost momentum when political priorities changed. How does EA factor in these uncertainties when prioritizing causes? It feels like EA assumes a stable world where money always achieves the intended impact. But what if that’s not the world we live in? Long termism. A Luxury When the Present Is in Crisis? I get why long termists argue that future people matter. But should we really prioritize them over people suffering today? Long termism tells us that existential risks like AI could wipe out trillions of future lives. But in Uganda, we’re losing lives now—1,500+ die from rabies annually (WHO, 2021), and 41% of children suffer from stunting due to malnutrition (UNICEF, 2022). These are preventable d
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TL;DR In a sentence:  We are shifting our strategic focus to put our proactive effort towards helping people work on safely navigating the transition to a world with AGI, while keeping our existing content up. In more detail: We think it’s plausible that frontier AI companies will develop AGI by 2030. Given the significant risks involved, and the fairly limited amount of work that’s been done to reduce these risks, 80,000 Hours is adopting a new strategic approach to focus our efforts in this area.   During 2025, we are prioritising: 1. Deepening our understanding as an organisation of how to improve the chances that the development of AI goes well 2. Communicating why and how people can contribute to reducing the risks 3. Connecting our users with impactful roles in this field 4. And fostering an internal culture which helps us to achieve these goals We remain focused on impactful careers, and we plan to keep our existing written and audio content accessible to users. However, we are narrowing our focus as we think that most of the very best ways to have impact with one’s career now involve helping make the transition to a world with AGI go well.   This post goes into more detail on why we’ve updated our strategic direction, how we hope to achieve it, what we think the community implications might be, and answers some potential questions. Why we’re updating our strategic direction Since 2016, we've ranked ‘risks from artificial intelligence’ as our top pressing problem. Whilst we’ve provided research and support on how to work on reducing AI risks since that point (and before!), we’ve put in varying amounts of investment over time and between programmes. We think we should consolidate our effort and focus because:   * We think that AGI by 2030 is plausible — and this is much sooner than most of us would have predicted 5 years ago. This is far from guaranteed, but we think the view is compelling based on analysis of the current flow of inputs into AI
Recent opportunities in Global health & development
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Eva
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