“AI in Practice: Education, Healthcare, Jobs, Governance and Public Services”

ARTICLE 10

“AI in Practice: Education, Healthcare, Jobs, Governance and Public Services”

I. OVERARCHING THEME: AI AS INFRASTRUCTURE, NOT JUST TECHNOLOGY

1) AI is moving from tool to foundational infrastructure

• AI is no longer treated as an experimental gadget.
• It is increasingly embedded in:
• • classrooms,
  • hospitals,
  • employment systems,
  • administrative workflows,
  • verification and public data systems.
• The real question is no longer:
• • “Will AI come?”
  • but “How will we design AI systems, and who benefits?”

2) The central policy dilemma

• AI can:
• • widen inequality if concentrated among elites,
  • or broaden opportunity if made accessible and accountable.
• The transformation is not automatic; it is shaped by:
• • design,
  • regulation,
  • literacy,
  • institutional safeguards.

II. PART A — AI IN EDUCATION

3) AI as accelerator — but also amplifier of existing weaknesses

• AI can:
• • personalise learning,
  • diagnose gaps,
  • provide instant feedback.
• However, if blindly adopted, it may:
• • reinforce exam obsession,
  • deepen coaching culture,
  • magnify inequality,
  • reduce foundational learning to automation.
• Therefore, design principles must precede tool adoption.

4) Teacher-plus-AI model (augmentation, not replacement)