The Ethical Introduction of AI in Clinical Practice: Is There Such a Thing?
summary
Panel argues that AI is already outperforming clinicians in some diagnostics but adoption stalls on trust, bias and data ownership: only ~19% of trial participants are women, 92% of trials run in US/EU, and 23andMe lacks 430 million Arab genomes. Companies launch anonymized clinical datasets and a medical-record product yesterday, regulators push risk-tiered rules, and solutions under trial include self-sovereign data, federated learning, and a patient-facing wallet like mage.health to enable decentralized, privacy-preserving precision medicine.
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chapters (7)
- 0:00Ethical AI in healthcare
- 2:36Trust in AI medical systems
- 7:35Legal responsibility for AI errors
- 11:27Real-world AI in clinics
- 15:59Bias in AI training data
- 19:28Decentralized health data
- 22:13Future AI regulations
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