Keeping Healthcare AI Safe and Effective

Keeping Healthcare AI Safe and Effective

Hardly a day passes without a new study comparing the performance of artificial intelligence to human expertise, often with the computer having the edge. Doomsayers fear the loss of human expertise altogether, eliminating not only livelihoods but the evolving knowledge necessary to judge and improve the AI systems themselves.Don’t worry, say the doom doubters. AI isn’t really thinking — powerful chatbots are just trained to represent relationships between words and phrases. They create humanlike responses to your queries by guessing the next word based on the query itself and the answer it progressively builds. Therefore, say the doubters, human thinkers will always be essential in critical arenas like healthcare.While the principles underlying large language models may be simple, human thought is also simple when reduced to its biological mechanics. Trained on a significant slice of accumulated human knowledge, chatbots like GPT-4 exhibit — or convincingly simulate — humanlike reasoning abilities and vast contextual awareness.

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AI does not genuinely perform as an expert — it just recognizes patterns at an expert’s level. Humans can identify the image regions on which the AI bases its judgment but not the basis for the decision — at least not yet. Efforts to develop “explainable” AI have foundered on the increasing complexity of AI models. Knowing nothing about the world or its narrow specialty within it, AI isn’t smart about what it’s looking at. It’s too dumb (in both senses) to provide the basis for its decisions.As a result, our trust in AI derives almost entirely from its record of success. Once that record reaches a high enough level, the temptation to unthinkingly rely on its judgment may be irresistible. This mindless trust in machine competence can lead to the erosion of expertise on the part of humans (“deskilling”) and overreliance on AI support (“automation complacency”).


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