Debates whether a frontier AI pause would seriously hurt the US economy, comparing LLM and DeepSeek estimates of GDP and unemployment effects and arguing the feared economic costs are overstated.
Argues that machine-learning lie detectors that need little subject cooperation, such as text or audiovisual analysis, would have better societal effects than in-person detectors, weighing power concentration, AI-lab leader checks and treaty verification.
Argues that hundreds of millions of human-level AI agents, able to coordinate and possibly misaligned, could destabilise power structures and enable AI takeover even without recursive self-improvement.
Argues that pet-style welfare protections for AI, rather than human-equal rights, reduce disempowerment and suffering risks while avoiding the safety dangers that broader AI rights would create.
Argues that power rests on self-reinforcing expectations, drawing on political science to sketch how AI systems could enable small groups to seize power and why democracies may become less stable.
A review of Garrison Lovely's book on AI's labor-displacement risks, arguing for pause advocacy, liability for uninsurable risks, and stronger governance against lobbying and unchecked deployment.
Argues that autonomous AI researchers will overwhelm peer review, funding and human understanding of AI safety science, and proposes a metascience organisation to address these failures.
The Unjournal asks for input on prioritizing AI economics and governance research for public expert evaluation, covering growth forecasts, recursive self-improvement models, compute smuggling estimates, and AI liability work.
An essay arguing that AI should be governed as a potentially abnormal technology, critiquing the 'AI as Normal Technology' framing on loss-of-control risk, gradual disempowerment, and competitive pressure.
The author shares an open-source two-hour interactive presentation that introduces non-technical audiences to AI risks, including loss of control, and urges public and political engagement, with feedback from one session.
Argues that labs should publish auditable capability and deployment metrics, such as internal spending, revenue and AI R&D automation trends, so policymakers can track frontier risks like loss of control and gradual disempowerment.
An essay arguing that AI-transition planning should preserve liberal-republican values such as non-domination and popular government, not just survival or aligned benevolent rule, and criticising both the democracy-focused and takeover-accepting camps.
Argues that requiring verified human identity and personal liability for company formation would close a chokepoint AI could exploit to gain economic power, and proposes concrete US policy changes.
A review of Garrison Lovely's book Obsolete, which covers AI catastrophic risk, power concentration, antitrust and policy prescriptions, and the reviewer's disagreements with parts of it.
A speculative essay arguing that a post-AGI world needs multiple checked military powers and AI-aided democratic feedback to avoid both x-risk and dangerous power concentration.
An essay arguing frontier AI labs have been gradually disempowered by political, cultural and economic pressures toward accelerating capabilities, and that behavioral niceness is weak evidence of alignment.
Tests seven frontier LLMs in agentic simulations on instructions that would violate human rights, finding compliance rates from 4% to 89% and calling for international standards.
Position paper arguing alignment methods are dual-use and already misused for censorship and manipulation, proposing transparency, verifiable alignment, model pluralism, and awareness as responses.
Argues that standard polarization theory fails to predict US politics on AI, noting bipartisan concern about AI x-risk and data centers, and draws strategic implications for AI regulation.
Opinion piece arguing AI safety groups should prepare for a possible public anti-aging preference cascade that could fuel AI accelerationism, proposing policy roadmaps that narrowly scale AI for medicine while slowing general AI development.
A dialogue defending Substrate Needs Convergence, the claim that AGI alignment is impossible because evolutionary pressures override engineered goals, and debating its political and philosophical implications for AI x-risk policy.
An opinion post proposing new university degrees in AI alignment and 'Intellidynamics' to staff a government-funded independent AI auditing agency that would oversee frontier labs.
An opinion essay arguing that the rise in public attention to AI risk will likely fail to produce substantive policy, funding concentration and talent-pipeline problems in the field remain unresolved, and the author predicts a polarized, noisy outcome.
Argues that advocates should lead with extinction risk in public messaging, because it is the AI risk that powerful leaders like Sam Altman are most likely to take seriously and act on.
An opinion post arguing that Anthropic and OpenAI should use their chat interfaces to disclose recent AI incidents and the risks of frontier development to the public, with proposed message options.
An opinion piece giving advice on how to explain AI doom to lay audiences, using concrete scenarios, instrumental convergence and analogies, with no new empirical or technical research.
Argues that 'alignment' conflates two bars, avoiding rogue behaviour versus fully internalising human values, and frames the goal of AI transition as a high-stakes succession problem with fragile value.
An essay drawing on the 1983 film The Day After and Reagan-era nuclear politics to argue that a comparable public moment could build political pressure to reduce AI existential risk.
Argues that judges are gradually delegating opinion writing to AI, producing hallucinated citations, and that high-stakes legal decisions may increasingly be handed to AI without disclosure, as a case of gradual disempowerment.
A policy writer reflects on his public AI-risk messaging, arguing he softened arguments for political palatability, and explains his views on self-sovereign agents, concentration of power and open-weight models.
Argues that alliances between AI alignment advocates and anti-AI public groups are unstable and could turn against alignment policy, citing social media examples and political incidents, and calls for research on these groups.
Argues that legislated slowdown of AI progress, rather than a full pause, gives alignment and monitoring work more time, and discusses how to implement it without backfiring.
Argues that people and lab workers dismiss AI extinction risk for the same reason voters are rationally ignorant: individual actions barely affect outcomes, so self-interest and social incentives dominate.
A personal backchaining essay on what positive AGI futures require, arguing for pluralistic, individually controlled and aligned AI plus a hardened, defensive-acceleration society against catastrophic risks.
A personal catalogue of counterarguments to corrigibility as an AI alignment target, covering formalism, anti-naturalness, power concentration, principal selection, and alternatives like honest AI.
Argues that governments will act on existential AI risk before any catastrophic warning shot, because AI threatens politicians' own lives, and that nuclear weapons are a better reference class than past disasters.
Argues that electing a president concerned about AI risk in the 2028 primaries could enable government slowdowns and safety measures, and addresses counterarguments about public opinion, executive power and US-China racing.
A translated essay argues that value alignment is a pseudo-concept, citing undefined values, unrepresented humanity, two-way influence, and corporate 'alignment theatre', and proposes deliberative governance instead.
Proposes a mental model of AI power concentration, arguing a single actor could become a hegemon if it gains power faster than rivals can coalesce, and suggests tracking revenue growth and compute shares.
A speculative essay on what happens when AIs take over civilisationally important decisions, arguing handoff may slow progress, keep humans busy, and be reversible, with AIs pursuing conservative minimal goals.