Week of 9 June 2025
Good Ancestors' June 2025 newsletter covers four lead items and a broad 'in case you missed it' roundup of AI policy developments.
Key points
- Australian-relevant items include the Albanese-AWS $20B data centre deal, the government's 'light-touch' regulatory posture, and AI workforce concerns.
- International items cover California's AI policy working group report, G7 AI-for-prosperity statement, and tech giants' superintelligence pivot.
Week of 2 June 2025
AI Now Institute's 2025 annual report frames AI as a power concentration problem, not a technology problem.
Key points
- Report argues AI harms are structural and calls for regulatory intervention, antitrust action, and community organising.
- Primarily a US-oriented advocacy document; APS relevance is indirect but useful for understanding critical-AI discourse.
A researcher argues that multimodal scaling cannot achieve human-level AGI, citing limits in embodied cognition.
Key points
- The piece challenges assumptions underlying some AI capability forecasts - relevant to how agencies assess AGI risk timelines.
- Primarily an academic-conceptual argument; limited direct operational relevance for APS practitioners right now.
Week of 12 May 2025
MIT AI Risk Repository spotlights a 2022 Google DeepMind taxonomy of LLM risks across six domains and 20 subdomains.
Key points
- The taxonomy covers discrimination, information hazards, misinformation, malicious use, HCI harms, and socioeconomic harms - directly relevant to APS AI risk assessment work.
- The underlying paper is from 2022; the MIT blog post is a summary spotlight, not new research.
Week of 5 May 2025
Good Ancestors' May 2025 newsletter covers three distinct developments: US AI safety rollbacks, OpenAI's Stargate global expansion, and Federal Court GenAI consultations.
Key points
- The Federal Court of Australia item is directly relevant to APS practitioners - submissions were open until 13 June 2025.
- US deregulation under Trump is framed as increasing pressure on Australia and other middle powers to fill the governance gap.
Week of 21 April 2025
MIT's AI Risk Repository updated to 1,612 unique risk entries across 65 frameworks, now including multi-agent risks.
Key points
- The repository provides causal and domain taxonomies designed to support policy, auditing, and governance processes.
- A credible reference resource for APS agencies developing AI risk frameworks or audit criteria - freely accessible.
MIT AI Risk Repository spotlights the 2022 MLSR framework, categorising ML risks into first-order and second-order types.
Key points
- The framework offers a structured taxonomy integrating impact assessments, incident reports, and ML literature - useful for risk assessment design.
- This is a 2022 academic paper being surfaced via a blog digest; it is reference material rather than new guidance.
AI Now Institute report argues industry-led AI safety frameworks are weakening established military and defence evaluation standards.
Key points
- Report draws parallels with Cold War-era nuclear governance frameworks, calling for democratic oversight of military AI deployment.
- Australian federal agencies are not the primary audience; relevance is indirect, through international AI safety governance discourse.
Week of 7 April 2025
MIT AI Risk Repository maps 11 frameworks bridging traditional risk management and AI safety, all published 2023 or later.
Key points
- Frameworks span maturity models, probabilistic risk assessment, and cybersecurity adaptations useful for agency AI governance work.
- UK DSIT's 'Emerging Processes for Frontier AI Safety' is among the 11 - a directly accessible government reference.
Week of 31 March 2025
MIT AI Risk Repository Version 3 now covers over 1,600 coded AI risks drawn from 65 published frameworks.
Key points
- Nine newly added frameworks include the final International Scientific Report on the Safety of Advanced AI and multi-agent risk taxonomies.
- APS risk and governance teams can use this as a structured reference to benchmark agency AI risk frameworks against global practice.
MIT AI Risk Repository v3 now includes a public Google Slides deck covering 65 source frameworks and documents.
Key points
- The deck provides excerpts, taxonomies, and citations from academic, industry, and policy AI risk literature.
- Useful reference for APS governance professionals building or auditing AI risk taxonomies and frameworks.
Week of 17 March 2025
The Alan Turing Institute's Project Aardvark applies machine learning to improve weather prediction for underserved regions.
Key points
- The initiative targets communities in the Global South and Arctic where forecasting gaps create real safety and economic risks.
- Limited direct relevance to APS AI governance work; may interest agencies with climate, emergency management, or geospatial remits.
Week of 3 March 2025
MIT AI Risk Repository spotlights a 2022 taxonomy classifying AI risk sources into ethical and reliability/robustness clusters.
Key points
- The framework integrates AI risk sources into formal risk assessment processes, distinguishing ML systems from classical software.
- This is a 2022 academic paper surfaced via a blog spotlight - not new guidance or a regulatory development.
Alan Turing Institute report calls for balancing academic freedom with research security in AI.
Key points
- State-sponsored threats to AI research are a growing concern for UK universities and research institutions.
- Limited direct applicability to APS; Australian universities and CSIRO/Data61 face analogous pressures.
MIT AI Risk Repository was presented at the inaugural IASEAI conference in Paris, February 2025.
Key points
- The Paris AI Action Summit convened researchers, industry, press, and policy representatives amid a fragmented global AI governance landscape.
- This is a conference recap with limited direct APS policy or operational content - context only.
NIST has finalised SP 800-226, guidelines for evaluating differential privacy guarantees in data analytics.
Key points
- Differential privacy is a privacy-enhancing technology relevant to data sharing and de-identification, including in government contexts.
- This is a US standards publication; no direct Australian regulatory parallel exists yet, limiting immediate APS applicability.
Week of 24 February 2025
MIT AI Risk Repository spotlights a 2023 framework for evaluating generative AI social impacts across eleven categories.
Key points
- Framework covers both technical system-level evaluation and broader societal impacts, with modality-specific mitigation guidance.
- Useful reference material for agencies developing AI risk or impact assessment frameworks, though not APS-specific.
Week of 17 February 2025
AI Now Institute co-published a report on how algorithmic surveillance of prices and wages harms the public.
Key points
- The report covers AI-enabled price and wage surveillance - a consumer and labour-market governance concern relevant to Australian regulators.
- Extracted text is minimal; full substance requires reading the underlying report directly.
Alan Turing Institute's Chief Scientist highlights seven sessions at the AI UK 2025 conference.
Key points
- Content is promotional event guidance from a UK think tank - no substantive policy or research findings included.
- Low signal for APS readers; limited extracted content makes substantive analysis impossible.
Week of 3 February 2025
The Alan Turing Institute examines 'Humanity's Last Exam', a new benchmark designed to test frontier LLMs at expert level.
Key points
- Benchmark saturation is an emerging governance concern - when AI passes the hardest tests, evaluation frameworks need rethinking.
- Limited direct APS applicability from this blog post alone; useful background for capability-tracking teams.
Week of 13 January 2025
Sherman and Eisenberg propose a nine-category AI risk taxonomy as a pre-deployment disclosure standard.
Key points
- The framework is applied to Claude, GPT APIs, Microsoft Copilot, GitHub Copilot, and Midjourney as worked examples.
- The taxonomy aims to bridge technical and non-technical stakeholders - useful for procurement and regulatory contexts.
A 2023 peer-reviewed taxonomy classifies algorithmic harms into five categories and 20 subcategories across micro, meso, and macro levels.
Key points
- MIT AI Risk Repository spotlights this as one of its indexed risk frameworks, making it more accessible to practitioners.
- Published in 2023 and now featured in a repository blog - substantive but not a new or urgent development for APS readers.
MIT AI Risk Repository was selected among 50 projects from 770 applications to present at the 2025 Paris AI Action Summit.
Key points
- The repository compiles over 1,000 AI risks from 56 frameworks into two structured taxonomies - causal and domain-based.
- The resource is publicly accessible and already adopted by governments and researchers globally, making it potentially useful for APS risk work.
Week of 30 December 2024
MIT AI Risk Repository adds 13 new frameworks in its December 2024 update, now covering over 1,000 AI risks from 56 sources.
Key points
- Newly added frameworks include NIST AI 600-1, China's AI Safety Governance Framework, and the UK Government Office for Science frontier AI report.
- Australian contributors are among the authoring jurisdictions; the repository commits to quarterly updates through 2025.
MIT AI Risk Repository has reached 90,000+ users since August 2024, used by governments and companies globally.
Key points
- A new AI Risk Index project launching Q1 2025 will evaluate how key actors respond to high-priority AI risks.
- Planned crosswalking of the repository's taxonomies against NIST AI RMF and EU AI Act is directly useful for APS risk practitioners.