Examining and making the case for real AI, algorithmic and automation transparency and openness
AIAAIC's independent, free, open library identifies and assesses 700+ incidents and controversies driven by and relating to AI, algorithms and automation.
AIAAIC repository governance
New: NHS Digital/iProov facial recognition data collection, storage : Facebook/Ray-Ban Stories smart glasses : Alexei Navalny smart voting bot : Mohsen Fakhrizadeh assassination : Facebook, Google abortion 'reversal' ads : Australia COVID-19 facial recognition trials : Curtin University Uyghur, Tibetan facial recognition study : More...
Crowdsourced exploration of current and proposed laws mandating the transparency of AI and algorithmic systems
Baseline review of current government and company AI and algorithmic transparency models, types, and forms
Why genuine, meaningful transparency and openness of AI, algorithmic and automation systems is needed, and what it should look like.