James is polite and punctual (and useless): A Bayesian formalisation of faint praise

A Pragmatic Account of the Weak Evidence Effect

Language is not only used for neutral information; we often seek to persuade by arguing in favor of a particular view. Persuasion raises a number of challenges for classical accounts of belief updating, as information cannot be taken at face value. How should listeners account for a speaker’s “hidden agenda” when incorporating new information? Here, we extend recent probabilistic models of recursive social reasoning to allow for persuasive goals and show that our model provides a pragmatic account for why weakly favorable arguments may backfire, a phenomenon known as the weak evidence effect. Critically, this model predicts a systematic relationship between belief updates and expectations about the information source: weak evidence should only backfire when speakers are expected to act under persuasive goals and prefer the strongest evidence. We introduce a simple experimental paradigm called the Stick Contest to measure the extent to which the weak evidence effect depends on speaker expectations, and show that a pragmatic listener model accounts for the empirical data better than alternative models. Our findings suggest further avenues for rational models of social reasoning to illuminate classical decision-making phenomena.

Developmental Trajectories in the Understanding of Everyday Uncertainty Terms

Dealing with uncertainty and different degrees of frequency and probability is critical in many everyday activities. However, relevant information does not always come in the form of numerical estimates or direct experiences, but is instead obtained through qualitative, rather vague verbal terms (e.g., "the virus often causes coughing" or "the train is likely to be delayed"). Investigating how people interpret and utilize different natural language expressions of frequency and probability is therefore crucial to understand reasoning and behavior in real-world situations. While there is considerable work exploring how adults understand everyday uncertainty phrases, very little is known about how children interpret them and how their understanding develops with age. We take a developmental and computational perspective to address this issue and examine how 4- to 14-year-old children and adults interpret different terms. Each participant provided numerical estimates for 14 expressions, comprising both frequency and probability phrases. In total we obtained 2856 quantitative judgments, including 2240 judgments from children. Our findings demonstrate that adult-like intuitions about the interpretation of everyday uncertainty terms emerge fairly early in development, with the quantitative estimates of children converging to those of adults from around 9 years on. We also demonstrate how the vagueness of verbal terms can be represented through probability distributions, which provides additional leverage for tracking developmental shifts through cognitive modeling techniques. Taken together, our findings provide key insights into the developmental trajectories underlying the understanding of everyday uncertainty terms, and open up novel methodological pathways to formally model the vagueness of probability and frequency phrases, which are abundant in our everyday life and activities.

Argument Quality in Real World Argumentation

The idea of resolving dispute through the exchange of arguments and reasons has been central to society for millennia. We exchange arguments as a way of getting at the truth in contexts as diverse as science, the court room, and our everyday lives. In democracies, political decisions should be negotiated through argument, not deception, or even worse, brute force. If argument is to lead to the truth or to good decisions, then some arguments must be better than others and 'argument strength' must have some meaningful connection with truth. Can argument strength be measured in a way that tracks an objective relationship with truth and not just mere persuasiveness? This article describes recent developments in providing such measures.

Beware of vested interests: Epistemic vigilance improves reasoning about scientific evidence (for some people)

In public disputes, stakeholders sometimes misrepresent statistics or other types of scientific evidence to support their claims. One of the reasons this is problematic is that citizens often do not have the motivation nor the cognitive skills to accurately judge the meaning of statistics and thus run the risk of being misinformed. This study reports an experiment investigating the conditions under which people become vigilant towards a source’s claim and thus reason more carefully about the supporting evidence. For this, participants were presented with a claim by a vested-interest or a neutral source and with statistical evidence which was cited by the source as being in support of the claim. However, this statistical evidence actually contradicted the source’s claim but was presented as a contingency table, which are typically difficult for people to interpret correctly. When the source was a lobbyist arguing for his company’s product people were better at interpreting the evidence compared to when the same source argued against the product. This was not the case for a different vested-interests source nor for the neutral source. Further, while all sources were rated as less trustworthy when participants realized that the source had misrepresented the evidence, only for the lobbyist source was this seen as a deliberate attempt at deception. Implications for research on epistemic trust, source credibility effects and science communication are discussed.

New Paradigms in the Psychology of Reasoning

The psychology of verbal reasoning initially compared performance with classical logic. In the last 25 years, a new paradigm has arisen, which focuses on knowledge-rich reasoning for communication and persuasion and is typically modeled using Bayesian probability theory rather than logic. This paradigm provides a new perspective on argumentation, explaining the rational persuasiveness of arguments that are logical fallacies. It also helps explain how and why people stray from logic when given deductive reasoning tasks. What appear to be erroneous responses, when compared against logic, often turn out to be rationally justified when seen in the richer rational framework of the new paradigm. Moreover, the same approach extends naturally to inductive reasoning tasks, in which people extrapolate beyond the data they are given and logic does not readily apply. We outline links between social and individual reasoning and set recent developments in the psychology of reasoning in the wider context of Bayesian cognitive science.

The Bi-directional Relationship between Source Characteristics and Message Content

Much of what we believe we know, we know through the testimony of others (Coady, 1992). While there has been long-standing evidence that people are sensitive to the characteristics of the sources of testimony, for example in the context of persuasion, researchers have only recently begun to explore the wider implications of source reliability considerations for the nature of our beliefs. Likewise, much remains to be established concerning what factors influence source reliability. In this paper, we examine, both theoretically and empirically, the implications of using message content as a cue to source reliability. We present a set of experiments examining the relationship between source information and message content in people's responses to simple communications. The results show that people spontaneously revise their beliefs in the reliability of the source on the basis of the expectedness of a source's claim and, conversely, adjust message impact by perceived reliability; hence source reliability and message content have a bi-directional relationship. The implications are discussed for a variety of psychological, philosophical and political issues such as belief polarization and dual-route models of persuasion.