# Comparative Analysis of Inference Under Uncertainty

> **NSF 01002627DB NSF RESEARCH & RELATED ACTIVIT** · University of California-Los Angeles (CA) · $594,592

## Abstract

When people make decisions under uncertainty or with incomplete information, people may rely on mental “fill‑ins” that are part of everyday intelligence but can sometimes lead to errors, like jumping to the wrong conclusion. This project asks why those “quick but wrong” choices happen and whether they arise from the same basic rules of intelligent behavior in humans and comparative animal models. Examining these processes in species that lack language is important for being able to understand the origins of reasoning and the principles that are independent of language abilities. Investigating how different species fill in missing information has potential for determining core principles of learning and reasoning under conditions of uncertainty. This understanding is important for fundamental brain science and relevant for artificial-intelligence (AI) engineers in building tools that guide smarter, safer decisions. The project also provides hands‑on research and data‑science training for high‑school, undergraduate, and graduate students, helping to prepare the next generation of scientists and AI‑literate STEM professionals.

The research focuses on a phenomenon called the positive contingency bias, which is a kind of error made when making probabilistic inferences. The project focuses on a tendency to assume that a hidden part of a familiar scene is still present, even when that guess can be wrong. The team plans to develop matched computer‑based and conditioning tasks for 

## Key facts

- **NSF award ID:** 2523638
- **Awardee organization:** University of California-Los Angeles (CA)
- **SAM.gov UEI:** RN64EPNH8JC6
- **PI:** Aaron Blaisdell
- **Primary program:** 01002627DB NSF RESEARCH & RELATED ACTIVIT
- **All programs:** Science of Learning, Artificial Intelligence (AI), DECISION RISK & MANAGEMENT SCI
- **Estimated total:** $594,592
- **Funds obligated:** $594,592
- **Transaction type:** Standard Grant
- **Period:** 07/01/2026 → 06/30/2029

## Primary source

NSF Award Search: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2523638

## Citation

> US National Science Foundation, Award 2523638, Comparative Analysis of Inference Under Uncertainty. Retrieved via AI Analytics 2026-06-08 from https://api.ai-analytics.org/grant/nsf/2523638. Licensed CC0.

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