Causal Persuasion
Anastasia Burkovskaya, Egor Starkov
TLDR
This paper proposes a model of causal persuasion, showing it's easier to establish a causal link than to debunk one.
Key contributions
- Introduces a formal model of causal persuasion between a sender and a receiver.
- Characterizes conditions for successful causal persuasion and debunking pre-existing beliefs.
- Reveals a fundamental asymmetry: establishing causality is easier than ruling it out.
- Shows establishing a causal link needs few variables, while dispelling one requires disclosing all common causes.
Why it matters
This paper reveals a critical asymmetry in how we understand and communicate causality. It provides insights into effective communication strategies for establishing or refuting causal claims, which is vital for scientific discourse and public policy.
Original Abstract
We propose a model of causal persuasion, in which a sender selectively discloses a set of variables together with their true joint distribution and proposes a subjective causal model that binds them. A receiver is persuaded by this model only if the data conclusively identifies the causal link of interest. We characterize when such persuasion succeeds or fails, and how easily it can be achieved. We further show that if the receiver holds a pre-existing subjective model, debunking it is similar to persuading a receiver without one. To establish a true causal link, the sender often needs to disclose only one or two well-chosen variables. But to dispel a perceived link -- to persuade the receiver there is no causal relationship -- every common cause must be disclosed. Our results highlight a fundamental asymmetry in causal persuasion: Establishing causality is often much easier than ruling it out.
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