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AI Systems in Text-Based Online Counselling: Ethical Considerations Across Three Implementation Approaches

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arxiv 2601.08878 v2 pith:IDAQHEIF submitted 2026-01-12 cs.CY

AI Systems in Text-Based Online Counselling: Ethical Considerations Across Three Implementation Approaches

classification cs.CY
keywords counsellingacrossapproachesethicalimplementationwhilstdistincthealth
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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Text-based online counselling scales across geographical and stigma barriers, yet faces practitioner shortages, lacks non-verbal cues and suffers inconsistent quality assurance. Whilst artificial intelligence offers promising solutions, its use in mental health counselling raises distinct ethical challenges. This paper analyses three AI implementation approaches - autonomous counsellor bots, AI training simulators and counsellor-facing augmentation tools. Drawing on professional codes, regulatory frameworks and scholarly literature, we identify four ethical principles - privacy, fairness, autonomy and accountability - and demonstrate their distinct manifestations across implementation approaches. Textual constraints may enable AI integration whilst requiring attention to implementation-specific hazards. This conceptual paper sensitises developers, researchers and practitioners to navigate AI-enhanced counselling ethics whilst preserving human values central to mental health support.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Transition-Matrix Regularization for Next Dialogue Act Prediction in Counselling Conversations

    cs.CL 2026-04 unverdicted novelty 7.0

    KL regularization aligning model predictions with empirical transition patterns improves macro-F1 by 9-42% in next dialogue act prediction on German counselling data and transfers to other datasets.

  2. A Computational Ethical Framework for Financial Digital Phenotyping for Mental Health

    cs.LO 2026-07 conditional novelty 5.0

    Ethical rules for financial digital phenotyping can be written as deontic temporal constraints whose violations Z3 proves unsatisfiable inside the formal model.