Research / Topics
Labour and economic impact, concentration of power, democracy, the information ecosystem, public opinion.
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.
Proposes the PAAI framework for who controls AI evaluation infrastructure and independence, applying it to African evaluation projects and AI Safety Institute joint testing, finding participation alone doesn't confer authority.
Codes public documents from 200 large companies against the MIT AI Risk Repository, finding most do not acknowledge AI risks, especially severe ones like power centralization, to inform disclosure rules.
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.
Interview-based STS and Black Feminist Technoscience analysis of Canada's AI governance infrastructure, examining expertise politics, strategic ignorance, and accountability for AI harms.
Analyses 139 CivitAI guides to show how general-purpose image-generation workflows, mostly built on open-weight models, can be configured into non-consensual intimate imagery, and argues safeguards should target identity generation and align with EU regulation.
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.
Analyzes documented AI harms across the human lifespan and proposes lifespan design principles and a three-tier external evaluation framework for frontier AI safety.
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.
Codes 1331 public child-related AI incidents into a sociotechnical harm taxonomy, finding harms cluster in deployment, governance and misuse failures, so model-level evaluations are insufficient.
A book proposing a unified data governance framework for LLM, RAG and agentic AI systems, covering law, economics, security and AI regulation across jurisdictions, anchored in Indian law.
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.
Argues that LLM safety governance for anthropomorphic interaction should target vulnerability situations rather than vulnerable groups, proposing a five-part typology and seven principles for response calibration.
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.
Applies contextual integrity to analyze whether major U.S. AI companies' policies on proactively referring dangerous user conversations to law enforcement are justified and transparent, finding key thresholds undisclosed.
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.
Presents a Semantic Web knowledge graph consolidating incident and legal evidence to support EU AI Act fundamental rights impact assessments for high-risk employment and public-service AI; LLM classification performed poorly on the employment domain.
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.
Audits how Instagram, TikTok, X and YouTube label AI and deepfake content under EU law, finding that only 33% of expert-identified systemic-risk deepfakes carried a platform label.
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.
Authors assess evidence that automating AI R&D could trigger an intelligence explosion, analyse its risks including loss of control and eroded checks on power, and propose policy 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.
A blog post defending the Gradual Disempowerment paper against critics, arguing that competitive pressures and misaligned societal systems could cause existential catastrophe even if individual AIs are aligned.
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.