inference

Sensitivity to online consensus effects within individuals and claim types

When reasoning about a claim, it makes sense to be more persuaded if lots of other people agree. But, there are many factors that make weighing the evidence behind a consensus complicated. For example, a consensus might be more or less informative …

Changing your mind about the data: Updating sampling assumptions in inductive inference

When people use samples of evidence to make inferences, they consider both the sample contents and how the sample was generated (“sampling assumptions”). The current studies examined whether people can update their sampling assumptions – whether they …

Inductive reasoning in humans and large language models

GPT4 is similar to humans on category-based induction tasks unless they involve sampling assumptions

Inferring the truth from deception: What can people learn from helpful and unhelpful information providers?

Sampling assumptions — the assumptions people make about how an example of a category or concept has been chosen — help us learn from examples efficiently. One context where sampling assumptions are particularly important is in social contexts, where …

Source independence affects argument persuasiveness when the relevance is clear

Making inferences about claims we do not have direct experience with is a common feature of everyday life. In these situations, it makes sense to consult others: an apparent consensus may be a useful cue to the truth of a claim. This strategy is not …

Where the truth lies: How sampling implications drive deception without lying

Efficient communication leaves gaps between message and meaning. Interlocutors, by reasoning about how each other reasons, can help to fill these gaps. To the extent that such meta-inference is not calibrated, communication is impaired, raising the …

Exploring the role that encoding and retrieval play in sampling effects

A growing body of literature suggests that making different sampling assumptions about how data are generated can lead to qualitatively different patterns of inference based on that data. However, relatively little is known about how sampling …

Do additional features help or hurt category learning? The curse of dimensionality in human learners

Shows that people are only afflicted by the curse of dimensionality for rule-based categories, not family resemblance ones.

Learning word meaning with little means: An investigation into the inferential capacity of paradigmatic information

Stronger evidence isn't always better: A role for social inference in evidence selection and interpretation