Numbers Tell, Words Sell
Michael Thaler (University College London), Mattie Toma (University of Warwick) and Victor Yaneng Wang (Massachusetts Institute of Technology)
GPI Working Paper No. 31-2025
When communicating numeric estimates with policymakers, journalists, or the general public, experts must choose between using numbers or natural language. We run two experiments to study whether experts strategically use language to communicate numeric estimates in order to persuade receivers. In Study 1, senders communicate probabilities of abstract events to receivers on Prolific, and in Study 2 academic researchers communicate the effect sizes in research papers to government policymakers. When experts face incentives to directionally persuade instead of incentives to accurately inform receivers, they are 25-29 percentage points more likely to communicate using language rather than numbers. Experts with incentives to persuade are more likely to slant language messages than numeric messages in the direction of their incentives, and this effect is driven by those who prefer to use language. Our findings suggest that experts are strategically leveraging the imprecision of language to excuse themselves for slanting more. Receivers are persuaded by experts with directional incentives, particularly when language is used.
Other working papers
Should longtermists recommend hastening extinction rather than delaying it? – Richard Pettigrew (University of Bristol)
Longtermism is the view that the most urgent global priorities, and those to which we should devote the largest portion of our current resources, are those that focus on ensuring a long future for humanity, and perhaps sentient or intelligent life more generally, and improving the quality of those lives in that long future. The central argument for this conclusion is that, given a fixed amount of are source that we are able to devote to global priorities, the longtermist’s favoured interventions have…
Tough enough? Robust satisficing as a decision norm for long-term policy analysis – Andreas Mogensen and David Thorstad (Global Priorities Institute, Oxford University)
This paper aims to open a dialogue between philosophers working in decision theory and operations researchers and engineers whose research addresses the topic of decision making under deep uncertainty. Specifically, we assess the recommendation to follow a norm of robust satisficing when making decisions under deep uncertainty in the context of decision analyses that rely on the tools of Robust Decision Making developed by Robert Lempert and colleagues at RAND …
Prediction: The long and the short of it – Antony Millner (University of California, Santa Barbara) and Daniel Heyen (ETH Zurich)
Commentators often lament forecasters’ inability to provide precise predictions of the long-run behaviour of complex economic and physical systems. Yet their concerns often conflate the presence of substantial long-run uncertainty with the need for long-run predictability; short-run predictions can partially substitute for long-run predictions if decision-makers can adjust their activities over time. …