Feel strongly about these letters, or any other aspects of the news? Share your views by emailing us your Letter to the Editor at [email protected] or filling in this Google form. Submissions should not exceed 400 wordsAs governments rush to draft AI legislation, it is crucial to define clear principles on how far artificial intelligence should be allowed to reshape the employment landscape. Technological progress is inevitable, but policymakers must recognise that some changes will be irreversible. A laissez-faire approach risks creating long-term social and economic damage, leaving entire segments of the workforce behind.
Nobel laureate Geoffrey Hinton has warned that AI could wipe out humanity. While that may sound extreme, ignoring the disruptive impact on jobs is equally dangerous.
Regulation should not be reactive. Waiting until tech giants accumulate unprecedented wealth while the labour class is decimated is a recipe for inequality and instability. Instead, governments must adopt proactive frameworks that balance innovation with social responsibility, ensuring AI serves society rather than undermines it.
One possible model can be drawn from immigration policy. For decades, governments have managed foreign talent inflows through the test of labour markets, requiring proof that certain skills are unavailable locally and applying quota systems that limit foreign hires once a threshold is reached. A similar matrix-based approach could apply to AI adoption. Businesses could be required to assess the availability of local human talent before automating roles, set thresholds for automation to prevent large-scale redundancies and conduct impact assessments to evaluate workforce displacement prior to deploying AI or robotics.
These measures would ensure AI integration is responsible and socially sustainable. By introducing checks and balances, governments can prevent mass unemployment while still encouraging innovation and competitiveness. Such policies would also help maintain economic stability and protect vulnerable sectors from abrupt disruption.