Examining and making the case for real AI, algorithmic and automation transparency and openness
Transparency is regularly cited as a core principle of ethical, reponsible and trustworthy AI. But it is often approached in a partial, piecemeal, and reactive manner.
Here's why genuine, meaningful transparency and openness of AI, algorithmic and automation systems is needed, and what it should look like.
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
AIAAIC's independent, free, open library identifies and assesses 750+ incidents and controversies driven by and relating to AI, algorithms and automation.
New: Xiao Yu deepfake pornography : Moscow Metro Face Pay facial recognition : North Ayrshire school meal payment verification : Amazon Buy Box/Featured Merchant algorithm rigging : Amazon Ring video doorbell neighbour privacy invasion : Wendys voice recognition : Gaggle student behavioural monitoring : More...