mlsanityData to 14 Oct 2026

Computational Inference in Cognitive Science: Operational, Societal and Ethical Considerations

arXiv 2210.13526 ↗First posted 24 Oct 2022q-bio.NC cs.AI cs.CLcited by 4

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Abstract (arXiv)

Emerging research frontiers and computational advances have gradually transformed cognitive science into a multidisciplinary and data-driven field. As a result, there is a proliferation of cognitive theories investigated and interpreted from different academic lens and in different levels of abstraction. We formulate this applied aspect of this challenge as the computational cognitive inference, and describe the major routes of computational approaches. To balance the potential optimism alongside the speed and scale of the data-driven era of cognitive science, we propose to inspect this trend in more empirical terms by identifying the operational challenges, societal impacts and ethical guidelines in conducting research and interpreting results from the computational inference in cognitive science.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 12 of its 48 references that are in the map. First posted on arXiv 24 Oct 2022.

Builds on

12 of 48 references.

References · 12

  1. 2022Generative Adversarial Networkscited by 5,627
  2. 2013Auto-Encoding Variational Bayescited by 4,053
  3. 2017Building machines that adapt and compute like brainscited by 99
  4. 2018Cognitive computational neurosciencecited by 43
  5. 2020Deep Reinforcement Learning and its Neuroscientific Implicationscited by 33
  6. 2022Deep Annotation of Therapeutic Working Alliance in Psychotherapycited by 14
  7. 2019A Story of Two Streams: Reinforcement Learning Models from Human Behavior and Neuropsychiatrycited by 13
  8. 2022Neural Topic Modeling of Psychotherapy Sessionscited by 13
  9. 2020Unified Models of Human Behavioral Agents in Bandits, Contextual Bandits and RLcited by 11
  10. 2020Predicting human decision making in psychological tasks with recurrent neural networkscited by 11
  11. 2019Split Q Learning: Reinforcement Learning with Two-Stream Rewardscited by 8
  12. 2022SupervisorBot: NLP-Annotated Real-Time Recommendations of Psychotherapy Treatment Strategies with Deep Reinforcement Learningcited by 8

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Cited by year

Citing papers per year: 2023: 3; 2024: 1.

4 papers.

  1. 2023Towards Healthy AI: Large Language Models Need Therapists Toocited by 13
  2. 2024COMPASS: Computational Mapping of Patient-Therapist Alliance Strategies with Language Modelingcited by 8
  3. 2023Psychotherapy AI Companion with Reinforcement Learning Recommendations and Interpretable Policy Dynamicscited by 6
  4. 2023Utterance Classification with Logical Neural Network: Explainable AI for Mental Disorder Diagnosiscited by 4