Don't outsource your critical thinking: human-centred design in the age of AI (hyprinnovation.io)

HYPR’s piece warns against “outsourcing” critical thinking to AI and argues for a human-centred design approach that blends Design Thinking, behavioural science and AI capabilities. It highlights the “double bias problem”: ML systems inherit biases from human-generated training data while users bring their own cognitive shortcuts and a tendency to overtrust confident-sounding AI outputs. That combination can amplify errors and create dangerous blind spots unless organisations retain human oversight, critical evaluation and ethical stewardship. Practically, the authors recommend tactics like persona-based prompting (asking models to adopt risk, legal or domain perspectives to surface overlooked issues), treating AI as a rapid ideation and routine-processing engine while reserving evaluation, synthesis and judgement for humans, and using a design–AI–brain science triangle to contextualise solutions. They also flag organisational and educational shifts—encouraging hands-on experimentation to reduce resistance, rethinking entry-level training as AI handles routine tasks, and attending to ethical risks (job displacement, cognitive offloading, early MIT findings on reduced cognitive ability). For AI/ML practitioners, the takeaway is clear: invest in prompt engineering, human-in-the-loop workflows, bias audits and behavioural-informed UX to ensure models augment rather than erode human decision-making.