Work in Progress

  1. Changing Narratives: AI-Assisted Reframing for NEET Youth
    Pilot stage

Working Papers

  1. Bennet Feld and Nicolas Roever
    PDF Presentations: NBER Spring Meeting on AI in Healthcare (May 2026)
    Abstract

    A large share of those affected by mental illnesses go untreated. Psychotherapy, a first-line treatment, works through a collaboration between patient and therapist, and that relationship is why many stay away: therapy is expensive, and to be helped, one must disclose to another person and risk being judged. In a randomized controlled trial with 400 US adults with moderate-to-severe anxiety and depression, none in therapy and most of them lonely, we replace the human side of the collaboration with a voice-based AI delivering CBT. For this population, the treatment appears to survive the removal of the therapist: participants take up the AI-delivered care and their demand shifts away from the human provider, not away from care or social support. Assignment lowers anxiety and depression by roughly 0.8 standard deviations at four weeks, within the range reported for human-delivered CBT, moves the mechanisms CBT targets, and forms a working alliance matching published norms for human therapists. Demand for human therapy falls on a stated measure and, by 18 percentage points, in a behavioral choice, while demand for medication and reliance on friends and family are unchanged; among participants who prefer the AI, the stated appeal is the absence of another person's judgment. Treated participants also report more social contact, not less, and lower loneliness, with the contact gains concentrated among the loneliest. By removing the person, automation may expand access to relational services, lowering both their price and the social cost of seeking them.


  2. Nicolas Röver, Lukas Wolf, Valerie Forman-Hoffman, Patricia Areán, and Bennet Feld
    PDF R&R at npj Digital Medicine

  3. PDF Coverage: VoxEU Presentations: Urban Economics Association European Meeting (Apr 2025), KU Leuven (Jun 2025)
    Abstract

    This paper leverages generative AI to build a network structure over 5,000 product nodes, where directed edges represent input-output relationships in production. We layout a two-step 'build-prune' approach using an ensemble of prompt-tuned generative AI classifications. The 'build' step provides an initial distribution of edge-predictions, the 'prune' step then re-evaluates all edges. With our AI-generated Production Network (AIPNET) in toe, we document a host of shifts in the network position of products and countries during the 21st century. Finally, we study production network spillovers using the natural experiment presented by the 2017 blockade of Qatar. We find strong evidence of such spill-overs, suggestive of on-shoring of critical production. This descriptive and causal evidence demonstrates some of the many research possibilities opened up by our granular measurement of product linkages, including studies of on-shoring, industrial policy, and other recent shifts in global trade.


Bennet Feld. Powered by Jekyll and the Minimal Light theme, though I changed quite a lot of it.