Abstract
In medicine, as in many aspects of our lives, we are experiencing the implementation of software tools described as artificial ‘intelligence' (AI) or, more precisely, machine learning (ML). These are systems built on a body of mathematics combining Bayesian probability modeling, rules, and neural networks (NN). This transformational technology is a cause for much optimism and concern. The change enabled by any new technology is naturally followed by a gradual appreciation of the impact, as optimism is gradually tempered by real experiences, often as we revise and refine our opinions in a dialectic manner. It takes time to understand the capabilities of these AI and ML tools before we can feel safe and comfortable working with them in critical tasks. These issues are discussed from various perspectives with implications for the future of how we consider evidence in medical decision-making.
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