Five AI Fails and How We Can Learn from ThemAugust 2021
Topics: Artificial Intelligence, Machine Learning, Innovation, Federal Government Services, Data (General)
These lessons derive from a more holistic view of automated technologies. Such technologies are more than independent widgets; they are part of a complex ecosystem that interacts with and influences human behavior and decision making.
"AI Fails" proposes a shift in perspective: we should measure the success of an AI system by its impact on human beings, rather than prioritizing its mathematical or economic properties (e.g., accuracy, false alarm rate, or efficiency). Such a shift has the potential to empower the development and deployment of amazing as well as responsible AI.