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AI tutors should not approximate human tutors

aipolicyperspectives.com · 2,024 words · saved by 1 readers

Today’s post comes from Daniel Gillick, a research scientist at Google DeepMind, who works on making Gemini more useful for teaching and learning. Daniel explores five pedagogical principles that the team is using in their work, the degree to which today’s AI systems can embody them, and what that means for how we should think about AI tutors. As with all the pieces you read here, it’s written in a personal capacity. Artificial Intelligence will no doubt reshape many of society’s institutions and industries, but this shift has come quickly to education. Sharply increasing student use across all grade levels, a crisis in assessment, skepticism of the benefits, and concerns over data privacy and safety have created turmoil across the sector. Still, a longer-term view provides cause for optimism, as AI has the potential to streamline the logistics of teaching and enable more effective learning. The most mainstream hope for AI in education is the possibility of a personalised tutor for eve

Essays AI tutors should not approximate human tutors 5 principles of learning science AI Policy Perspectives Nov 10, 2025 28 5 10 Share Today’s post comes from Daniel Gillick, a research scientist at Google DeepMind, who works on making Gemini more useful for teaching and learning . Daniel explores five pedagogical principles that the team is using in their work, the degree to which today’s AI systems can embody them, and what that means for how we should think about AI tutors. Artificial Intelligence will reshape many of society’s institutions and industries, but this shift has come quickly t

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