---
title: "A Privacy-Preserving Intelligent Assistant for Clinical Psychology Practice"
authors:
  - "Aaron Pico"
  - "Joaquin Taverner"
  - "Emilio Vivancos"
  - "Ana Garcia-Fornes"
  - "Vicent Botti"
doi: "10.24963/ijcai.2026/985"
url: "https://ijcai.org/proceedings/2026/985"
pdf: "https://ijcai.org/proceedings/2026/0985.pdf"
venue: "Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence"
year: 2026
pages: "8483-8486"
track: "Demo Track"
keywords:
  - "AI: Humans and AI"
  - "AI: Multidisciplinary Topics and Applications"
  - "AI: AI Ethics, Trust, Fairnes"
  - "AI: Natural Language Processing"
---

# A Privacy-Preserving Intelligent Assistant for Clinical Psychology Practice

Aaron Pico, Joaquin Taverner, Emilio Vivancos, Ana Garcia-Fornes, Vicent Botti

*Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence*, pages 8483-8486. DOI: [10.24963/ijcai.2026/985](https://doi.org/10.24963/ijcai.2026/985)

## Abstract

This paper describes a fully local, privacy-preserving intelligent system designed to assist in clinical psychology practice. The system automatically transcribes therapy sessions performing speaker attribution. Beyond transcription, the tool enhances clinical reasoning by detecting cognitive distortions and emotional patterns utilizing specialized deep learning classifiers and Large Language Models (LLMs). By guiding an LLM locally through a multi-step analysis process, the assistant synthesizes the enriched data and generates a series of analysis reports and clinical documentation of the session. As a result, the assistant reduces the administrative burden on professionals while preserving privacy with an edge computing approach in which the data never leaves the therapist's device. Finally, the assistant uses human-in-the-loop validation so that the professional always remains in control, ensuring clinical accuracy and trust.