Weaponizing cognitive bias in autonomous systems: a framework for black-box inference attacks Article Swipe
Shiyong Chu
,
Yuwei Chen
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3389/frai.2025.1623573
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3389/frai.2025.1623573
Autonomous systems operating in high-dimensional environments increasingly rely on prioritization heuristics to allocate attention and assess risk, yet these mechanisms can introduce cognitive biases such as salience, spatial framing, and temporal familiarity that influence decision-making without altering the input or accessing internal states. This study presents Priority Inversion via Operational Reasoning (PRIOR), a black-box, non-perturbative diagnostic framework that employs structurally biased but semantically neutral scenario cues to probe inference-level vulnerabilities without modifying pixel-level, statistical, or surface semantic properties. Given the limited accessibility of embodied vision-based systems, we evaluate PRIOR using large language models (LLMs) as abstract reasoning proxies to simulate cognitive prioritization in constrained textual surveillance scenarios inspired by Unmanned Aerial Vehicle (UAV) operations. Controlled experiments demonstrate that minimal structural cues can consistently induce priority inversions across multiple models, and joint analysis of model justifications and confidence estimates reveals systematic distortions in inferred threat relevance even when inputs are symmetrical. These findings expose the fragility of inference-level reasoning in black-box systems and motivate the development of evaluation strategies that extend beyond output correctness to interrogate internal prioritization logic, with implications for dynamic, embodied, and visually grounded agents in real-world deployments.
Related Topics
Concepts
Computer science
Inference
Embodied cognition
Leverage (statistics)
Debiasing
Artificial intelligence
Heuristics
Cognition
Cognitive map
Black box
Machine learning
Cognitive bias
Salience (neuroscience)
Bayesian inference
Correctness
Commonsense reasoning
Bayesian probability
Cognitive science
Programming language
Operating system
Neuroscience
Psychology
Biology
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3389/frai.2025.1623573
- https://www.frontiersin.org/journals/artificial-intelligence/articles/10.3389/frai.2025.1623573/pdf
- OA Status
- gold
- References
- 51
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4413362827
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4413362827Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3389/frai.2025.1623573Digital Object Identifier
- Title
-
Weaponizing cognitive bias in autonomous systems: a framework for black-box inference attacksWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2025Year of publication
- Publication date
-
2025-08-20Full publication date if available
- Authors
-
Shiyong Chu, Yuwei ChenList of authors in order
- Landing page
-
https://doi.org/10.3389/frai.2025.1623573Publisher landing page
- PDF URL
-
https://www.frontiersin.org/journals/artificial-intelligence/articles/10.3389/frai.2025.1623573/pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.frontiersin.org/journals/artificial-intelligence/articles/10.3389/frai.2025.1623573/pdfDirect OA link when available
- Concepts
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Computer science, Inference, Embodied cognition, Leverage (statistics), Debiasing, Artificial intelligence, Heuristics, Cognition, Cognitive map, Black box, Machine learning, Cognitive bias, Salience (neuroscience), Bayesian inference, Correctness, Commonsense reasoning, Bayesian probability, Cognitive science, Programming language, Operating system, Neuroscience, Psychology, BiologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- References (count)
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51Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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