The fund specifies five priority areas but also welcomes innovative proposals outside these areas. First, shaping AI's impact on workers at the firm and workplace level, including field experiments that randomly assign AI systems and integration designs, evaluating the differences between worker participatory design and top-down approaches, and assessing the effects of retention tax credits and employer co-investment requirements.
Second, helping people navigate AI-driven transitions, evaluating skills retraining, job placement, licensing reforms, and sector transition programs, particularly AI-driven matching, certification, and learning models, as well as models that bundle income support with reemployment services. Third, modernizing income support systems, reforming traditional mechanisms like unemployment insurance for AI-driven job displacement.
Fourth, establishing worker benefit-sharing mechanisms for AI growth before disruption arrives, exploring models such as worker ownership or profit sharing. Fifth, generating new evidence for public investment, evaluating the effectiveness of government investments in AI transitions.