{
  "annotation_id": "2ff98b35-ac35-40f8-a4e1-da2e019c4767",
  "date_created": "2026-02-17T05:53:20.172000Z",
  "date_modified": "2026-02-17T05:53:20.172000Z",
  "file_hash": "70b32f34b1c625381252761c9b196d7b525e3a7386b5bbc48eb9fa20bffd97c7",
  "private": false,
  "record": {
    "abstract": "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.",
    "arxiv_id": "2601.08878",
    "authors": [
      "Philipp Steigerwald",
      "Jennifer Burghardt",
      "Eric Rudolph",
      "Jens Albrecht"
    ],
    "categories": [
      "cs.CY"
    ],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "title": "AI Systems in Text-Based Online Counselling: Ethical Considerations Across Three Implementation Approaches",
    "url": "https://arxiv.org/abs/2601.08878",
    "version": "v1"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "0ffc4e2e-0c68-4ce6-8230-fe8aab478ce6",
    "id": "arXiv Dataset",
    "type": "Model",
    "variant": "snapshot-2026-01-17",
    "version": "0.1.0"
  },
  "user_id": 1000002
}