THE INDEPENDENT, GRASSROOTS PUBLIC INTEREST INITIATIVE WORKING FOR TRANSPARENT, OPEN, AND ACCOUNTABLE TECHNOLOGY
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OpenAI launched its AI video generator with restrictions on deepfakes, copyright violations, and other misuses. Critics accuse the tool of eroding creativity and the firm of selective opacity and outright hypocrisy.
Featured dataset 🔢
Common Crawl democratises access to massive web datasets that fuel AI innovation and open research. But it also propagates systemic biases, toxic content, and potential copyright infringements due to its uncurated nature and the inclusion of sensitive or proprietary data.
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 joins IASEAI Affiliate Programme
AIAAIC publishes News Trigger, Ethical Issue, External Harm, and Consequence taxonomies
AIAAIC publishes AI harm and risk taxonomy review working paper
AIAAIC publishes AI and algorithmic harms taxonomy v1.8
AIAAIC updates AIAAIC Repository user guide
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
Bengio Y., et al. International AI Safety Report 2026
ICAAD, King & Wood Mallesons. Artificial Intelligence Harm and Human Rights
Xiao, S., et al. What Comes After Harm? Mapping Reparative Actions in AI Through Justice Frameworks
Venkatasubramanian K., Hardie H., Ranalli T-M. Toward a taxonomy of negative outcomes from the use of AI-driven systems for people with disabilities
Hadan H. et al. Who is Responsible When AI Fails? Mapping Causes, Entities, and Consequences of AI Privacy and Ethical Incidents
AIAAIC content is available to use, copy, adapt, and redistribute under a CC BY-SA 4.0 licence. More
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