According to Ethan Mollick on X, Wharton-affiliated researchers including Hamsa Bastani found that giving high school students unrestricted ChatGPT access improved practice accuracy but led to worse exam performance without AI, while AI prompted to act as a tutor improved learning in controlled settings (as reported by Bastani et al., SSRN working paper and PNAS preprint references). According to Anand Sanwal citing the study, students using basic ChatGPT scored 17% lower on no-AI exams than those practicing without technology, indicating overreliance on answer-giving rather than reasoning. According to the SSRN paper by Bastani et al., a separate randomized controlled trial showed that structured tutor prompts increased learning outcomes, suggesting that guardrailed, step-by-step tutoring mitigates shortcutting. As reported by the authors, business opportunities include AI tutoring systems with scaffolded prompts, process feedback, and exam-transfer alignment for K–12 math, as well as district-level deployments focusing on formative assessment and metacognitive coaching.

According to @ylecun, recent studies and data from the American Economic Association and PNAS highlight that AI-driven data analysis is increasingly used to examine crime rates among immigrants and citizens. These AI-powered approaches enable researchers and policymakers to process large-scale datasets, uncovering trends such as lower crime rates among immigrants compared to citizens, as reported by the American Economic Association and corroborated by the House of Representatives and PNAS studies. This trend demonstrates the growing role of machine learning and advanced analytics in public policy and social science, opening new business opportunities for AI solution providers in government data analysis.