The Mechanics and Validation of Generative AI Outcomes

Abstract

The main purpose of this chapter is to unpack the mechanics within generative AI that lead to the introduction of hate and targeting of hate towards specific groups or people. The main thesis is that AI is a protraction and implication of human behavior and human behavior alone. AI, at its best, democratizes access to expertise and removes barriers of inherited affluence. At its worst, however, it reinforces and amplifies extreme positions (“reductive AI”) while inhibiting dialogue and, therefore, learning. To mitigate this, we propose three measures: (1) triangulation of generated content via k-class validation, (2) an evaluation process that pursues falsification following Popperian falsification principles, and (3) deep investment in training and education.

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