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AI Answers Fast, But Can We Ask Better Questions?

Summary

  • Societies need question-literacy more than answer-literacy in the AI age.
  • Investing in question formulation is vital for discovery and democracy.
  • Participatory models are needed to avoid 'question inequities' in science.
AI Answers Fast, But Can We Ask Better Questions?

In the era of artificial intelligence, the ability to ask meaningful questions is becoming more crucial than finding answers. While significant investment has been made in data science and STEM education, the vital skill of formulating impactful questions has been largely overlooked.

This capacity for asking good questions is not merely a prerequisite for knowledge creation but a fundamental civic and democratic competence. Efforts like Harvard's "Genuinely Hard Problems" initiative are commendable, yet they risk perpetuating "question inequities" if the agenda is set by a narrow group.

A more inclusive approach to question formation is essential, involving policymakers, practitioners, and communities. Initiatives like The GovLab's "100 Questions Initiative" demonstrate the power of engaging diverse networks to identify pressing societal questions, ensuring science addresses both intellectual challenges and real-world consequences.

Disclaimer: This story has been auto-aggregated and auto-summarised by a computer program. This story has not been edited or created by the Feedzop team.
Question-literacy refers to the ability to formulate meaningful, ambitious, and socially relevant questions, a skill becoming more critical as AI readily provides answers.
It's important for encouraging scientific inquiry into challenging problems, but the article argues for a broader approach to avoid limiting which questions are considered valuable.
By adopting more participatory models for question formation that include diverse voices from policymakers, practitioners, and communities, not just elite academic institutions.

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