WORKING FOR MORE TRANSPARENT, OPEN AND ACCOUNTABLE TECHNOLOGY
The Bar's use of AI resulted in low quality questions and was seen to threaten the integrity of professional standards and public trust in the USΒ legal system.
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Get to grips with incidents and controversies driven by and associated with AI and related technologies, and the implications of the technology and governance systems behind them for individuals, society and the environment.
Equipping researchers, civil society organisations and the general public to better understand and take action on AI and related technology harms and violations.
AIAAIC publishes AI and algorithmic harm and risk taxonomy review working paper
AIAAIC publishes AI, algorithmic and automation harms taxonomy v1.8
AIAAIC launches Slack channel for community members
AIAAIC updates AIAAIC Repository user guide
AIAAIC publishes Values and Code of Conduct
Brazil's Nucleo charts AI incidents using AIAAIC data
AIAAIC cited in ACLU/EPIC/EFF response to trade secrecy protections under California's proposed Risk Assessments and Automated Decisionmaking Technology Regulations
AIAAIC cited as an 'Authority' (pdf) in US Supreme Court mistaken identity case
AIAAIC cited in testimony to US Commission on Civil Rights briefing on government use of facial recognition
AIAAIC cited in Apple (pdf), Disney (pdf) and Paramount (pdf) shareholder AI transparency report proposals
Elliott, M. T. J., & MacCarthaigh, M. Accountability and AI: Redundancy, Overlaps and Blind-Spots
Hadan H. et al. Who is Responsible When AI Fails? Mapping Causes, Entities, and Consequences of AI Privacy and Ethical Incidents
Bengio Y. et al. International AI Safety Report (pdf)
Knight, S., McGrath, C., Viberg, O. et al. Learning about AI ethics from cases: a scoping review of AI incident repositories and cases
Jurowetzki R., Hain DS., Wirtz K., Bianchini S. The private sector is hoarding AI researchers: what implications for science?
AIAAIC is an independent, non-partisan, grassroots public interest initiative that examines and makes the case for real AI, algorithmic and automation transparency, openness and accountability. More
Transparency is often approached in a partial, piecemeal and reactive manner. Here's what we believe the meaningful transparency and openness of AI, algorithmic and automation systems should look like. More
AIAAIC is committed to ensuring that it thinks and acts in a manner consistent with its politically and technologically non-partisan, public interest status. More
AIAAIC content is available to use, copy, adapt, and redistribute under a CC BY-SA 4.0 licence. More
