Do striking biases in mass inference reflect a flawed mental model of physics?

Invariant representations in abstract concept grounding - the physical world in grounded cognition

Grounded cognition states that mental representations of concepts consist of experiential aspects. For example, the concept "cup" consists of the sensorimotor experiences from interactions with cups. Typical modalities in which concepts are grounded are: The sensorimotor system (including interoception), emotion, action, language, and social aspects. Here, we argue that this list should be expanded to include physical invariants (unchanging features of physical motion; e.g., gravity, momentum, friction). Research on physical reasoning consistently demonstrates that physical invariants are represented as fundamentally as other grounding substrates, and therefore should qualify. We assess several theories of concept representation (simulation, conceptual metaphor, conceptual spaces, predictive processing) and their positions on physical invariants. We find that the classic grounded cognition theories, simulation and conceptual metaphor theory, have not considered physical invariants, while conceptual spaces and predictive processing have. We conclude that physical invariants should be included into grounded cognition theories, and that the core mechanisms of simulation and conceptual metaphor theory are well suited to do this. Furthermore, conceptual spaces and predictive processing are very promising and should also be integrated with grounded cognition in the future.

A dedicated mental resource for intuitive physics

Countless decisions and actions in daily life draw on a mental model of the physical structure and dynamics of the world - from stepping carefully around a patch of slippery pavement to stacking delicate produce in a shopping basket. People can make fast and accurate inferences about how physical interactions will unfold, but it remains unclear whether we do so by applying a general set of physical principles across scenarios, or instead by reasoning about the physics of individual scenarios in an ad-hoc fashion. Here, we hypothesized that humans possess a dedicated and flexible mental resource for physical inference, and we tested for such a resource using a battery of fine-tuned tasks to capture individual differences in performance. Despite varying scene contents across tasks, we found that performance was highly correlated among them and well-explained by a unitary intuitive physics resource, distinct from other facets of cognition such as spatial reasoning and working memory.