3

Uncalibrated models can improve human-AI collaboration

In many practical applications of AI, an AI model is used as a decision aid for human users. The AI provides advice that a human (sometimes) incorporates into their decision-making process. The AI advice is often presented with some measure of …

Who went fishing? Inferences from social evaluations

Humans have a remarkable ability to go beyond the observable. From seeing the current state of our shared kitchen, we can infer what happened and who did it. Prior work has shown how the physical state of the world licenses inferences about the …

The language of causation

People use varied language to express their causal understanding of the world. But how does that language map onto people’s underlying representations, and how do people choose between competing ways to best describe what happened? In this paper we …

Whom will Granny thank? Thinking about what could have been informs children's inferences about relative helpfulness

To evaluate others' actions, we consider action outcomes (e.g., positive or negative) and the actors' underlying intentions (e.g., intentional or accidental). However, we often encounter situ- ations where neither actual outcomes nor intentions …

Explaining intuitive difficulty judgments by modeling physical effort and risk

How do we estimate the difficulty of performing a new task, a task we've never tried before such as making a sculpture, a birthday cake, or building a tower with LEGO blocks? Estimating difficulty helps us appreciate others' accomplishments, and …

Tiptoeing around it: Inference from absence in potentially offensive speech

Language that describes people in a concise manner may conflict with social norms (e.g., referring to people by their race), presenting a conflict between transferring information efficiently and avoiding offensive language. When a speaker is …

What happened? Reconstructing the past from vision and sound

We introduce a novel experimental paradigm for studying multi-modal integration in causal inference. Our experiments feature a physically realistic Plinko machine in which a ball is dropped through one of three holes and comes to rest at the bottom …

Causal learning from interventions and dynamics in continuous time

Event timing and interventions are important and intertwined cues to causal structure, yet they have typically been studied separately. We bring them together for the first time in an experiment where participants learn causal structure by performing …

Faulty towers: A hypothetical simulation model of physical support

In this paper we introduce the hypothetical simulation model (HSM) of physical support. The HSM predicts that people judge physical support by mentally simulating what would happen if the object of interest were removed. Two experiments test the …

Marbles in inaction: Counterfactual simulation and causation by omission

Consider the following causal explanation: The ball went through the goal because the defender didn’t block it. There are at least two problems with citing omissions as causal explanations. First, how do we choose the relevant candidate omission …