Executive summary: An evidence-based comparative analysis of Anthropic’s Responsible Scaling Policy, Google DeepMind’s Frontier Safety Framework, and OpenAI’s Preparedness Framework (all updated in 2025) finds broadly similar, misuse-focused approaches to monitoring dangerous capabilities (bio/chem, cyber, and AI self-improvement) but highlights weakening commitments, governance differences, and persistent vagueness about concrete “if-then” actions—leaving substantial uncertainty about whether these policies would prevent catastrophic outcomes.

Key points:

1. Common architecture, different labels: All three frameworks commit to testing for dangerous capabilities and gating deployment behind safeguards; they track broadly the same areas (CBRN/bio-chem, cyber, and AI self-improvement), emphasize misuse over misalignment, and use threshold concepts (Anthropic “Capability Thresholds”/ASLs, DeepMind CCLs, OpenAI high/critical risk tiers).
2. How risks are evaluated: Anthropic triggers comprehensive assessments after step-change indicators and tests “safety-off” variants; DeepMind runs Early Warning Evaluations with alert thresholds and brings in external experts; OpenAI relies on scalable automated proxies validated by deep-dive red-teaming and domain tests.
3. What happens at the thresholds: Anthropic pairs thresholds with ASL-3/4 deployment and security safeguards plus executive/board signoffs; DeepMind requires a governance-approved “safety case” and RAND-style security levels but is explicit that some measures need field-wide coordination; OpenAI allows deployment of “high-risk” models only with safeguards and pledges to pause training for “critical-risk” models.
4. Governance and posture differences: Anthropic foregrounds internal roles, whistleblowing, and public capability reports; DeepMind spreads authority across multiple councils and stresses industry co-adoption; OpenAI routes decisions through a Safety Advisory Group and board committee, with a notable (but high-level) training-pause commitment.
5. 2025 regressions and recalibrations: Labs added process detail but also softened parts of earlier commitments—e.g., conditional adoption tied to competitors, reduced safeguards for some CBRN/cyber cases, OpenAI removing “persuasion” from its tracked categories, and Anthropic stepping back from pre-defining ASL-N+1 evaluations—raising doubts about robustness under competitive pressure.
6. Unresolved crux: will this avert catastrophe? The documents remain more specification-plus-tests than operational plans with hard triggers; senior leaders’ stated P(doom) still diverge markedly (e.g., ~25% vs. ~2%), underscoring real uncertainty about whether these frameworks, even if followed, meaningfully reduce existential risk and suggesting a need for stronger, coordinated standards and regulation.

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.

Executive summary: OpenAI’s transformation from a nonprofit-controlled organization to a for-profit public benefit corporation has now been approved by California and Delaware attorneys general and Microsoft, ending months of legal and political wrangling. The final structure preserves some governance safeguards under nonprofit oversight but eliminates profit caps—cementing a win for investors and a profound shift away from the company’s founding altruistic mission.

Key points:

1. Regulatory approval: The California and Delaware attorneys general conditionally approved OpenAI’s conversion to a public benefit corporation, provided it adheres to strict governance and transparency requirements; Microsoft also agreed in exchange for a $135 billion stake and new partnership terms.
2. Governance safeguards: The nonprofit retains formal control, including appointing and removing PBC directors, oversight of safety and security decisions, and mandated check-ins with regulators—but most directors serve on both boards, limiting true independence.
3. Safety mechanisms: A new Safety and Security Committee (SSC), led by Zico Kolter and answerable to the nonprofit, can demand mitigation measures or halt releases over safety concerns—one of the few meaningful checks on commercial pressure.
4. Profit caps removed: The restructuring abolishes OpenAI’s previous profit limits, granting the nonprofit a 26% equity stake and potential bonuses if valuations soar; critics argue this forfeits trillions in public benefit and transforms OpenAI into a conventional profit-driven firm.
5. Political context: The decision reflects political calculation as much as legal judgment; despite expert consensus that the restructuring contradicts OpenAI’s nonprofit mission, elected AGs opted for a compromise amid pressure from one of the world’s most powerful companies.
6. Reactions and implications: Observers see modest wins for accountability but a decisive loss for public ownership; the nonprofit may be nominally “in control,” yet practical authority and incentives now align with investors—raising doubts about OpenAI’s continued commitment to benefiting humanity.

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.

Executive summary: Drawing on over a decade of experience as a hiring manager and grantmaker in the EA ecosystem, the author outlines unconventional but effective hiring practices—such as unstructured interviews, flexible work tests, and informal or conflicted references—arguing that context-sensitive, information-rich, and adaptable approaches outperform standardized “best practices” borrowed from other industries.

Key points:

1. Unstructured interviews can yield deeper insight than rigid formats, allowing hiring managers to adapt questions to each candidate’s strengths, weaknesses, and reasoning style—especially valuable for high-skill roles.
2. Work tests are underused for roles requiring soft skills but can be powerful when tailored to mimic real work; they provide richer signals than traditional interviews despite being harder to design.
3. Informal and wide-ranging references—including from peers or acquaintances outside formal referee lists—often offer the most candid and useful information, especially in small ecosystems like EA.
4. Conflicted sources shouldn’t be ignored entirely; instead, evaluators should weigh their input proportionally, since people with conflicts often also have the best information.
5. Quantification in hiring can help clarify priorities and trade-offs but should guide rather than dictate decisions, as numerical models rarely capture all relevant qualities.
6. For applicants, the author advises discreetly seeking candid feedback from potential colleagues or former employees, since manager fit strongly influences job satisfaction.
7. Overall hiring philosophy: adapt best practices to EA’s small, high-stakes environment; borrow selectively from startup culture; and consult experienced hirers to refine bespoke approaches.

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.

Executive summary: A marketer reflecting on three years in the EA community shares lessons learned from running campaigns at ClearerThinking.org—arguing that EA marketing requires niche-targeted creatives, realistic metrics, and novel outreach methods, while promoting interactive tools as the most effective strategy for engagement and growth.

Key points:

1. “Filter through the creative” for niche audiences: Conventional ad targeting is weak, so effective campaigns rely on creatives that both attract and screen for the right audience segments.
2. Targeting existing EAs through ads rarely works: Experiments show very low conversion rates, likely due to the community’s small size, skepticism toward ads, and use of blockers.
3. Beware early high-engagement audiences: Initial EA-based mailing lists or networks create inflated benchmarks; scaling to broader audiences will naturally reduce engagement rates.
4. Long-term goals still need measurable milestones: Even slow-to-convert causes should set concrete timeframes to assess effectiveness and enable iterative learning.
5. Outbound marketing remains underused in EA: Ethical, personalized outreach (email or phone) to new audiences can be a valuable but overlooked channel.
6. Interactive tools outperform landing pages: Tools that engage users before collecting emails generate higher-quality leads; ClearerThinking’s branded tools have shown strong results and are available for EA org partnerships.

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.

Executive summary: The author argues that politically oriented donations in the U.S. are far less fungible than many assume: money restricted to charitable use (e.g., via a donor-advised fund) is significantly less effective for influencing political outcomes than unrestricted “flex” funds, with timing and legal structure greatly affecting real-world leverage.

Key points:

1. Charitable funds face strict limits in politics: 501(c)(3) organizations can fund research and nonpartisan education but cannot support candidates or conduct substantial lobbying, making such funds poorly suited for direct political impact.
2. Campaign donations are uniquely powerful: Direct campaign contributions (“hard money”) can be 2–3× more valuable than PAC funds because they qualify for cheaper ad rates and are spent at the most decisive times.
3. Timing amplifies effectiveness: Early donations—especially before primaries—are far more valuable than last-minute ones; delayed gifts may lose most of their influence.
4. Legal structures determine flexibility: 501(c)(4)s can lobby and use unrestricted money, while PACs can campaign but not coordinate with candidates. Each step toward more political freedom roughly doubles effectiveness, albeit without tax deductibility.
5. Cumulative effect is dramatic: Combining tax restrictions, organizational preferences, campaign leverage, and timing can make unrestricted early donations over ten times more impactful than equivalent charitable giving.
6. Implication for donors: Those aiming for political influence should avoid locking funds in donor-advised or 501(c)(3)-restricted vehicles and instead consider direct, flexible contributions to campaigns, PACs, or possibly parties.

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.

Executive summary: A year-long experiment teaching rationality workshops to EAs in the Netherlands found that while attendance and measurable impact were modest, the sessions were engaging, well-received, and occasionally life-changing; the author concludes that sustaining energy, experimenting with formats, and training good instructors are key to scaling such programs.

Key points:

1. The author taught 16 rationality and decision-making workshops over 12 months, attended by 119 EAs (243 total attendances), and developed five new workshops covering topics like productivity, disagreement, groupthink, and moral action.
2. Feedback showed workshops were consistently rated as engaging and useful, with anecdotes suggesting real personal impact (e.g. attendees addressing health issues).
3. The author emphasizes “fueling yourself” — teaching topics that excite you and maintaining personal energy and humor — as central to effectiveness and sustainability.
4. Effective outreach involved letting the community vote on workshop topics, starting with popular ones to build trust and word-of-mouth momentum.
5. Iterative experimentation was crucial: online formats reduced attendance, while exercise-heavy and multi-workshop “EAxRationality days” performed well.
6. Scaling is challenging because success depends heavily on instructor quality; the author suggests creating training or retreat-style programs to teach others how to run rationality workshops effectively.

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.

Executive summary: This exploratory analysis argues that return migration—where roughly one-third to one-half of migrants eventually go back to their home countries—is a vital but underappreciated part of the global migration system, generating economic, social, and institutional benefits for both origin and destination countries through “brain circulation” rather than simple brain drain or gain.

Key points:

1. Between 30% and 60% of migrants return to their home country within ten years, a pattern remarkably consistent across time, skill levels, and regions—migration is often temporary rather than permanent.
2. Return likelihood depends on both home and host country conditions: people are more likely to go home if their origin country is relatively prosperous or culturally similar, but individual outcomes also matter—less successful migrants tend to return sooner.
3. This “negative selection” means destination countries retain especially successful migrants, while home countries lose some talent but gain returnees with new skills, networks, and entrepreneurial energy.
4. Empirical evidence suggests return migrants earn more, start more businesses, and transfer valuable knowledge to their home economies, fueling innovation in sectors like IT, textiles, and manufacturing.
5. The author proposes “brain circulation” as a more accurate model than “brain drain,” emphasizing how migration raises incentives for education and creates pathways for skill acquisition that ultimately benefit both sides.
6. Beyond economics, return migration also spreads democratic and accountability norms, as migrants bring political expectations from more democratic societies back to their home countries.

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.

Executive summary: An exploratory, steelmanning critique argues that contemporary longtermism risks amplifying a broader cultural drift toward safetyism and centralized control, is skewed by a streetlight effect toward extinction-risk work, and—when paired with hedonic utilitarian framings—can devalue individual human agency; the author proposes a more empowerment-focused, experimentation-friendly, pluralistic longtermism that also treats stable totalitarianism and “flourishing futures” as first-class priorities.

Key points:

1. Historical context & “cultural longtermism”: Longtermism is situated within a centuries-long rise in societal risk-aversion (post-WW2 liberalism, 1970s environmentalism/anti-nuclear). This tide brings real benefits but also stagnation risks that critics plausibly attribute to over-regulation and homogenizing global governance.
2. Reconciling perceptions of power: Even if explicit longtermist budgets are small, the indirect, often unseen costs of safetyist policy—slower medical progress, blocked nuclear power, NIMBY housing constraints, tabooed research—create “invisible graveyards,” making a de facto “strict culturally-longtermist state” more feasible than analysts assume.
3. Streetlight effect inside longtermism: Because extinction risks are unusually amenable to analysis and messaging, they crowd out harder-to-measure priorities—s-risks (e.g., stable totalitarianism), institutional quality, social technology, and positive-vision “flourishing futures”—potentially causing large path-dependent misallocations.
4. Utilitarian framings and the individual: Widespread (often implicit) reliance on total hedonic utilitarianism dissolves the moral salience of unique persons into interchangeable “qualia-moments” while elevating the survival of civilization as a whole—fueling totalitarian vibes and explaining why deaths of individuals (e.g., aging) receive less emphasis than civilization-level x-risk.
5. Risk of over-centralization: If longtermist x-risk agendas unintentionally bolster global regulation and control, they may increase the probability of totalitarian lock-in—the very kind of non-extinction catastrophe that longtermism underweights because it runs through messy socio-political channels.
6. Toward a more humanistic longtermism: Prioritize empowerment, experimentation, and credible-neutral social technologies (e.g., prediction markets, algorithmic policy rules, liability schemes); invest in governance concepts that reduce politicization, expand policy VOI via pluralism (charter-city-like diversity), and explicitly target anti-totalitarian interventions (propaganda/censorship-resistance, offense-defense mapping for control-enabling tech).

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.

Executive summary: In this exploratory dialogue between Audrey Tang and Plex, they probe whether “symbiogenesis” (hyperlocal, community-first cooperation that scales up) can stably beat convergent, power-seeking consequentialism, with Plex remaining skeptical that bounded/steerable systems can survive competitive pressure without a unifying, theory-level alignment that scales to superintelligence, and Audrey arguing that practicing alignment on today’s systems, strengthening defense-dominant communities, and iterating hyperlocal “civic care” and Coherent Blended Volition (CBV) may bootstrap a viable path—while both endorse improved sensemaking, shared vocabularies, and cautious experimentation.

Key points:

1. Core crux: Can complex cooperation (“symbiogenesis”) remain stable against selection for unbounded optimizers? Plex doubts boundedness survives competitive dynamics without a top-level, enforceable norm; Audrey thinks hyperlocal alignment plus defense-dominant coordination can scale and police defectors.
2. Economic pressure vs. safety: Plex argues unbounded systems will outcompete bounded/steerable ones (profit and influence gradients), making mere norms or lip service insufficient; Audrey counters with Montreal-Protocol-style, technology-forcing governance and claims steerable systems can deliver value and thus win investment.
3. Robustness requirement: Plex maintains that before strong agentic AIs, we likely need a general alignment theory that “tiles” through self-improvement (avoids sharp left turns and Goodharted proxies); Audrey frames robustness as strategy-proof rules and bounded “Kamis” (local stewards) loyal to relationships and communities.
4. Hyperlocal morality as scaffold: Audrey claims solving morality locally (quasi-utilitarianism/care ethics, subsidiarity/Ostrom) can recurse up via “dividuals” to produce stable higher-level coherence; Audrey worries local wins may aggregate into alien global outcomes that today’s humans wouldn’t endorse.
5. Coordination + sensemaking now: Both see immediate value in aligning current recommender systems, building shared vocabularies across alignment subfields, and running safe simulations (e.g., Metta’s “Clips vs. Cogs”) to test group-dynamics claims—while noting experiments won’t replace a theory expected to scale.
6. Practical implications: Focus on defense-dominant pods, transparent dashboards with awareness of Goodhart risks, participatory “utopiography”/clustered-volition processes (Weval/Global Dialogue), and cross-ontology translation; plex recommends engaging with MIRI and similar communities, and he remains cautiously supportive of AudreyThis 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.’s approach as a pathway to buy time and improve global strategy.

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.

Executive summary: This retrospective details how EAGxNigeria 2025—Africa’s largest Effective Altruism conference to date—successfully convened nearly 300 attendees from 15+ countries to strengthen EA community growth and regional engagement, while highlighting logistical, technical, and volunteer coordination lessons for future events.

Key points:

1. Scale and impact: Held in Abuja from July 11–13, 2025, EAGxNigeria hosted 295 attendees from 15+ countries, supported by $61k in expenditures and $63k in travel grants. It achieved strong satisfaction, new Giving What We Can pledges, and an average of nearly 11 new connections per participant.
2. Strategic goals: The event aimed to deepen EA engagement across Africa by connecting local and international members, emphasizing regionally relevant cause areas, and fostering collaboration on global problems.
3. Content and participation: The program included 29 sessions, 8 meetups, 21 office hours, and a popular Opportunity Fair, with attendees rating 1-1 meetings and talks as most valuable. Cause areas spanned global health, animal welfare, AI safety, and biosecurity.
4. Community outcomes: Participants reported intentions to start EA-aligned projects and organizations, apply for grants, and make giving commitments; 18 took or planned to take the Giving What We Can pledge.
5. Operational challenges: The team faced issues with badge printing, navigation, volunteer training, and minor technical faults, leading to specific recommendations such as earlier preparation, stronger AV partnerships, and more realistic volunteer simulations.
6. Volunteer coordination: 45 volunteers supported logistics, speaker liaison, and first aid, with later improvements like daily stand-ups enhancing teamwork; 44 respondents rated the experience highly despite initial confusion.
7. Lessons learned: Early planning, clearer wayfinding, and improved tech readiness were identified as key improvements for future EAGx events, along with continued investment in local leadership and volunteer capacity across Africa.

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.