About the AIAAIC Repository
The AIAAIC Repository (standing for 'AI, Algorithmic, and Automation Incidents and Controversies') is an open resource that details incidents and controversies driven by and relating to artificial intelligence, algorithms, and automation.
By collecting, dissecting, and surfacing incidents and issues from a responsible, ethical 'outside-in' perspective in an objective and balanced manner, the Repository enables users to identify, examine, and understand the nature, risks, and impacts of AI, algorithms, and automation.
The AIAAIC Repository is available as a Google Sheet and is being added to this website.
Approach
The AIAAIC Repository is intended to help fulfil AIAAIC’s mission by systematically collecting, classifying, and surfacing AI and AI-related incidents and issues to key audiences, notably researchers, teachers, policymakers, and citizens/consumers.
Some other open/public databases and registers take a narrow, technical view of technology systems (eg. aviation accidents, cybersecurity). However, it is clear that many factors other than the technical components play important roles in driving AI, algorithmic, and automation incidents and controversies.
These include:
Issues such as: Job displacements/losses, Employment offshoring, Environmental damage, Misleading/hyped marketing, Anthromophorism, Unethical data use.
External triggers including: Research studies, NGO research reports/campaigns, Media investigations, Legal threats, Whistleblower reports, Political backlashes.
AIAAIC Repository uses
The AIAAIC Repository can be used to:
Conduct qualitative or quantitative research
Inform and enhance analysis and commentary
Develop case studies
Devise training and education programmes
Desogn products and services
Inform policy.
Here are some research studies citing and mentioning the AIAAIC Repository.
The repository helps answer the following kinds of questions:
What are the top risks of AI, algorithms and automation?
Which sectors and countries are most exposed to AI incidents and controversies?
Which AI, algorithmic and automation technologies are most likely to result in incidents or controversies?
What forms do AI, algorithmic and automation incidents take?
What are the principal triggers that turn an AI or algorithmically-driven or related problem or issue into a public incident or controversy?
Which kinds of incidents and controversies result from inadequate, poor, inaccurate or misleading AI transparency and openness?
Further information
Contact us for further information about the AIAAIC Repository.
Equally, if you are already using it, we'd love to hear how and to what effect. Drop us a line and let us know.