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. 1-2025

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

Measuring AI-Driven Risk with Stock Prices – Susana Campos-Martins (Global Priorities Institute, University of Oxford)

We propose an empirical approach to identify and measure AI-driven shocks based on the co-movements of relevant financial asset prices. For that purpose, we first calculate the common volatility of the share prices of major US AI-relevant companies. Then we isolate the events that shake this industry only from those that shake all sectors of economic activity at the same time. For the sample analysed, AI shocks are identified when there are announcements about (mergers and) acquisitions in the AI industry, launching of…

Estimating long-term treatment effects without long-term outcome data – David Rhys Bernard (Paris School of Economics)

Estimating long-term impacts of actions is important in many areas but the key difficulty is that long-term outcomes are only observed with a long delay. One alternative approach is to measure the effect on an intermediate outcome or a statistical surrogate and then use this to estimate the long-term effect. …

Critical-set views, biographical identity, and the long term – Elliott Thornley (Global Priorities Institute, University of Oxford)

Critical-set views avoid the Repugnant Conclusion by subtracting some constant from the welfare score of each life in a population. These views are thus sensitive to facts about biographical identity: identity between lives. In this paper, I argue that questions of biographical identity give us reason to reject critical-set views and embrace the total view. I end with a practical implication. If we shift our credences towards the total view, we should also shift our efforts towards ensuring that humanity survives for the long term.