The Guardian · 23 Oct, 07:01 · Artificial Intelligence briefing

Can AI really predict cancer survival better than a doctor? I have my doubts | Devi Sridhar

Professor Devi Sridhar questions recent claims that artificial intelligence outperforms clinical doctors in predicting cancer survival rates.

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Professor Devi Sridhar questions recent claims that artificial intelligence outperforms clinical doctors in predicting cancer survival rates. The article highlights significant methodological flaws in the studies, noting that AI models often rely on historical data containing systemic biases and incomplete patient records. Sridhar argues that these algorithms may perpetuate existing healthcare inequalities rather than eliminate them. For professionals, this underscores the critical distinction between algorithmic output and clinical reality, emphasising that technology lacks the contextual nuance required for complex medical decision-making.

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This debate signals that technical proficiency in AI is no longer sufficient; you must cultivate critical evaluation skills. Professionals in healthcare, data science, and policy must understand the ethical implications of algorithmic bias. If you work in these sectors, prioritise learning how to audit AI systems for fairness and transparency. Do not assume automation guarantees accuracy. Instead, focus on developing hybrid expertise that combines data literacy with domain-specific clinical or operational knowledge. This positions you to bridge the gap between technologists and practitioners. Start by exploring courses on AI ethics and data governance. Your value lies in your ability to question machine outputs and ensure they align with human-centric outcomes, rather than blindly trusting predictive models.

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