Just after Labor Day, American University Professor and Harvard Griffin GSAS alumnus, Allan Lichtman predicted a victory for Democratic candidate Kamala Harris in the 2024 presidential election. It was a source of some encouragement for Harris's supporters, given that Lichtman had correctly predicted the winner of 9 of the last 10 elections based on his historical analysis of campaign trends since 1860.

Despite his track record, Lichtman has been scorned by election forecasters like Nate Silver, who build probabilistic models based on weighted averages from scores of national and state-level polls. But are these quantitative models really any more reliable than ones that leverage historical fundamentals, like Lichtman's, or, for that matter, a random guess?

The Stanford University political scientist Justin Grimmer, PhD ’10, and his colleagues, Dean Knox of the University of Pennsylvania and Sean Westwood of Dartmouth, published research last August evaluating US presidential election forecasts like Silver's. Their verdict? Scientists and voters are decades to millennia away from assessing whether probabilistic forecasting provides reliable insights into election outcomes. In the meantime, they see growing evidence of harm in the centrality of these forecasts and the horse race campaign coverage they facilitate.

This month on Colloquy: Justin Grimmer on the reliability of probabilistic election forecasts.

Fail fast, fail frequently, and learn from it. That's the mantra adopted by many Silicon Valley firms in recent years. Fine. But would you tell that to your emergency room doctor for someone who's managing your retirement funds or the pilot of your next flight?

Harvard Business School Professor Amy Edmondson says that the key to squaring this circle is failure-proofing critical areas where best practices are well-known while encouraging experimentation in new fields where useful and productive knowledge can be gathered. That means building a sense of psychological safety among colleagues and coworkers that fosters trust, open communication, and new ideas.

Per- and polyfluoroalkyl substances (PFAS) are persistent, they’re everywhere, and they're probably bad for you. PFAS are probably bad for you. Some of the detrimental health effects associated with the chemical compounds include liver disease, decreased fertility and hypertension in pregnant women, immune and developmental effects in children including decreased antibody response to vaccines, and certain organ cancers. In this talk, delivered in April 2024 at the annual Harvard Horizons Symposium, scientist Heidi Pickard, PhD '24, uncovers the prevalence of PFAS, as well as their impact on the environment and health.