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Artificial intelligence in the psychologist's toolkit: Psypilot as a case study.

Pablo Roca1,2, Rosaria Maria Zangri2,3, Guillermo Rodriguez-Fernandez2

  • 1Precision Mind Lab (Premind), Faculty of Health Sciences, Universidad Villanueva, Madrid, Spain.

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Summary

Artificial intelligence (AI) offers two paths for psychology: automated therapists or AI copilots. This research explores AI copilots, like Psypilot, to augment clinical judgment and support precision mental health.

Keywords:
AIartificial intelligenceclinical decision supportlarge language modelsmeasurement-based careprecision mental health

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Area of Science:

  • Psychology and Artificial Intelligence
  • Clinical Psychology
  • Health Informatics

Background:

  • Artificial intelligence (AI) is transforming psychological practice, presenting a choice between automated care and augmented professional judgment.
  • Contemporary AI, including Machine Learning and Large Language Models, impacts core psychological tasks like assessment, formulation, and intervention.
  • The integration of AI necessitates careful consideration of clinical quality, scalability, and innovation.

Purpose of the Study:

  • To analyze how current AI technologies map onto psychologists' core tasks.
  • To present Psypilot as a case study for the AI copilot paradigm in Precision Mental Health.
  • To examine risks and governance challenges associated with AI in clinical settings and provide recommendations.

Main Methods:

  • Synthesis of contemporary AI capabilities (Machine Learning, LLMs) in relation to psychological practice.
  • Case study presentation of Psypilot, an AI-powered clinical assistance platform.
  • Critical examination of risks (automation bias, data fairness, privacy, transparency, accountability) and development of design/training recommendations.

Main Results:

  • AI can be framed as workflow-embedded decision support, augmenting rather than replacing psychologists.
  • Psypilot exemplifies the copilot model, supporting Precision Mental Health.
  • Identified key risks and proposed practical recommendations for responsible AI implementation and training.

Conclusions:

  • AI copilots offer a responsible innovation pathway, preserving the relational and ethical core of psychological work.
  • Psychologists require new competencies to effectively utilize AI decision support tools.
  • Framing AI as decision support, not autonomous care, is crucial for navigating the AI-driven professional landscape.