Proposal Topics: Proposals should demonstrate the potential to meaningfully advance our understanding of a range of research questions related to one or more of the following topics:  

1. Skills: Understanding (or shaping) complementarity and substitutability of AI with human expertise
2. Organizations: Analyzing (or shaping) job design, task allocation, offshoring
3. Education: Designing, implementing, and evaluating tools
4. Incentive design: Analyzing (or shaping) design, adoption, usage

We seek proposals that propose and evaluate applications of AI that improve the quality of work, facilitate skills acquisition, and support economic opportunity, with a particular but not exclusive focus on non-college workers. For more information about the objectives of our initiative, see https://shapingwork-mit-edu.ezproxyberklee.flo.org/. We welcome proposals that address these underlying questions even if they may not fit perfectly into these four topic areas. 

Methodological and analytical approaches:

Submissions should be grounded in rigorous theoretical foundations and exhibit a strong empirical strategy. In particular, proposals are expected to:

Employ theory-informed impact evaluation:

• Use a clear theoretical framework that informs the identification and estimation strategy. (A formal model is welcome but not required.)
• Use robust causal inference methods. RCTs and other design-based approaches are admissible.
  

Consider General Equilibrium Effects:

• While general equilibrium and spillover effects need not be a central part of the analysis, proposals should consider whether they are relevant and account for them accordingly:
  • Account for spillovers and general equilibrium interactions, such as how AI-driven changes in one segment of the labor market might indirectly affect workers and firms in other segments.
  • Where applicable, explore dynamic interactions between different market actors and sectors, ensuring that broader systemic effects are not overlooked.
    

Processes and Work Methods:

Once applicants have submitted their expression of interest by March 31st, we will review them and provide feedback to top selected applicants both by email and on Zoom. Feedback will aim to strengthen the proposal’s impact and feasibility, to increase the chances that applicants get funded.

Additional information: Full details, including FAQs, are available on the Schmidt Sciences website. All applications should be submitted via Schmidt Sciences here.