As AI adoption continues to ramp up exponentially, so is the discussion around — and concern for — accountable AI.
While tech leaders and field researchers understand the importance of developing AI that is ethical, safe and inclusive, they still grapple with issues around regulatory frameworks and concepts of “ethics washing” or “ethics shirking” that diminish accountability.
Perhaps most importantly, the concept is not yet clearly defined. While many sets of suggested guidelines and tools exist — from the U.S. National Institute of Standards and Technology’s Artificial Intelligence Risk Management Framework to the European Commission’s Expert Group on AI, for example — they are not cohesive and are very often vague and overly complex.
