Martin Ford · For the resolution
AI can break the historical pattern
Martin argues that AI competes with the broad cognitive abilities that have helped people find new work after earlier waves of automation. It need not replace every job to cause substantial displacement.
More of Martin’s case
Today’s limits can change
He acknowledges that widespread job losses have not yet appeared. His forecast depends on further advances, including AI that can learn on the job, and on businesses adopting those capabilities.
Prepare before disruption
Martin argues that productivity gains do not guarantee paid work for everyone. He wants policies ready to protect incomes and demand if significant job losses emerge.
Pedro Domingos · Against the resolution
Cheaper intelligence can create more work
Pedro argues that automating parts of a job can make a worker more productive. Human adaptability, relationships and the value people place on human service leave room for work that AI does not replace.
More of Pedro’s case
Lower costs, new demand
He argues that cheaper goods and services leave people money to spend elsewhere, creating demand for new products, industries and occupations. Existing jobs at risk are easier to see than jobs that do not yet exist.
Capability is not adoption
Pedro questions whether AI will become sufficiently adaptable within twenty years. He also emphasizes the organizational, economic and social barriers between a technical advance and widespread job replacement.
