Projects per year
Abstract / Description of output
The outcome of any scientific experiment or intervention will naturally unfold over time. How then should individuals make causal inferences from measurements over time? Across three experiments, we had participants observe experimental and control groups over several days post-treatment in a fictional biological research setting. We identify competing perspectives in the literature: Contingency-driven accounts predict no effect of outcome timing while the contiguity principle suggests people will view a treatment as more harmful to the extent that bad treatment outcomes occur earlier rather than later. In contrast, inference to the functional form of a treatment effect can license extrapolation beyond the measurements and lead to different causal inferences. We find participants’ causal strength and direction judgments in temporal settings vary with minimal manipulations of instruction framing. When it is implied that the observations are made over a pre-planned number of days, causal judgments depend strongly on contiguity. When it is implied that the observation may be ongoing, participants extrapolate current trends into the future and adapt their causal judgments accordingly. When data are revealed sequentially, participants rely on extrapolation regardless of instruction framing. Our results demonstrate human flexibility in interpreting temporal evidence for causal reasoning and emphasize human tendency to generalize from evidence in ways that are acutely sensitive to task framing.
Original language | English |
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Pages (from-to) | 864-872 |
Number of pages | 10 |
Journal | Journal of Experimental Psychology: General |
Volume | 153 |
Issue number | 3 |
Early online date | 18 Jan 2024 |
DOIs | |
Publication status | Published - 1 Mar 2024 |
Keywords / Materials (for Non-textual outputs)
- causality
- causal learning
- time
- generalization
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Dive into the research topics of 'Evidence from the future'. Together they form a unique fingerprint.Projects
- 1 Finished
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Computational constructivism: Exploring the algorithmic basis of discovery
1/04/21 → 31/03/24
Project: Research