Nick Powdthavee

Why do people pay for transparently useless advice? An update. Over ten years ago, we showed that people—most of whom have advanced statistical knowledge—were willing to pay for predictions of fair coin flips after witnessing a streak of correct predictions live in the lab.

In @PNASNews, Media Lab Prof. @patpatMIT, @NTUsg Prof. Nattavudh Powdthavee, Media Lab master’s student Chayapatr Archiwaranguprok, and Prof. Pattie Maes (@fluidinterfaces) evaluate the use of LLMs to simulate human happiness and subjective wellbeing. Their research found that while today's AI systems can reproduce broad patterns of global life satisfaction, they also carry deep structural biases that risk obscuring the lived realities of millions. media.mit.edu/projects/simul…

🌿New Research: "Understanding the role of pluralistic ignorance in biodiversity conservation: A research agenda" 🌏Read more about this important research #OpenAccess in GEC: doi.org/10.1016/j.gloe…

Paper: Large Language Models Predict Human Well-being—But Not Equally Everywhere By Pat Pataranutaporn, Nattavudh Powdthavee, Chayapatr Achiwaranguprok, and Pattie Maes. 📄 arxiv.org/abs/2507.06141 💻 github.com/mitmedialab/we…

So while LLMs can generate plausible-sounding estimates of well-being, they’re often wrong in meaningful and systematic ways. Especially in the very settings where high-quality well-being data are hardest to get.

Can AI predict how satisfied people are with their lives? In a new paper with colleagues from MIT and NTU, we tested four leading LLMs—GPT, Claude, LLaMA, and Gemma—on their ability to estimate actual life satisfaction across 64 countries. 🧵

My new paper shows that AI is secretly judging us based on our last names. Analyzing 72,000 AI-driven evaluations, we found that “elite” surnames boost perceptions of intelligence, power, and wealth, influencing hiring, leadership, and loan decisions. media.mit.edu/projects/algor…

10/ What are your thoughts on AI in peer review? Can we trust machines to make fair evaluations? Let's discuss! ⬇️ #AcademicTwitter #EconTwitter #AI #PeerReview

9/ Want to dive deeper? Read the full paper here: arxiv.org/pdf/2502.00070. The paper's authors include @NickPowdthavee, @patpat_mit and @PattieMaes

🚀 Can AI solve the peer review crisis in economics? Our new paper explores the capabilities and biases of LLMs in evaluating research papers. A thread 🧵: