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

arXiv: https://arxiv.org/abs/2210.13526 · HTML: https://mlsanity.com/paper/2210.13526/

## 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 (most cited first, 12 of 12)

- [Generative Adversarial Networks](https://mlsanity.com/paper/2203.00667/) (2022)
- [Auto-Encoding Variational Bayes](https://mlsanity.com/paper/1312.6114/) (2013)
- [Building machines that adapt and compute like brains](https://mlsanity.com/paper/1711.04203/) (2017)
- [Cognitive computational neuroscience](https://mlsanity.com/paper/1807.11819/) (2018)
- [Deep Reinforcement Learning and its Neuroscientific Implications](https://mlsanity.com/paper/2007.03750/) (2020)
- [Deep Annotation of Therapeutic Working Alliance in Psychotherapy](https://mlsanity.com/paper/2204.05522/) (2022)
- [A Story of Two Streams: Reinforcement Learning Models from Human Behavior and Neuropsychiatry](https://mlsanity.com/paper/1906.11286/) (2019)
- [Neural Topic Modeling of Psychotherapy Sessions](https://mlsanity.com/paper/2204.10189/) (2022)
- [Unified Models of Human Behavioral Agents in Bandits, Contextual Bandits and RL](https://mlsanity.com/paper/2005.04544/) (2020)
- [Predicting human decision making in psychological tasks with recurrent neural networks](https://mlsanity.com/paper/2010.11413/) (2020)
- [Split Q Learning: Reinforcement Learning with Two-Stream Rewards](https://mlsanity.com/paper/1906.12350/) (2019)
- [SupervisorBot: NLP-Annotated Real-Time Recommendations of Psychotherapy Treatment Strategies with Deep Reinforcement Learning](https://mlsanity.com/paper/2208.13077/) (2022)

## Built on by (most cited first, 4 of 4)

- [Towards Healthy AI: Large Language Models Need Therapists Too](https://mlsanity.com/paper/2304.00416/) (2023)
- [COMPASS: Computational Mapping of Patient-Therapist Alliance Strategies with Language Modeling](https://mlsanity.com/paper/2402.14701/) (2024)
- [Psychotherapy AI Companion with Reinforcement Learning Recommendations and Interpretable Policy Dynamics](https://mlsanity.com/paper/2303.09601/) (2023)
- [Utterance Classification with Logical Neural Network: Explainable AI for Mental Disorder Diagnosis](https://mlsanity.com/paper/2306.03902/) (2023)

## 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.