The blind prompt: a limitation preceding the artificial intelligence response in relationship advice

Authors

DOI:

https://doi.org/10.25118/2763-9037.2026.v16.1685

Keywords:

AI, artificial inteligence, psychoterapy, interpersonal relationships, decision-making, mental health

Abstract

Introduction: People experiencing relationship distress increasingly turn to generative artificial intelligence to interpret conflicts, draft messages and decide whether to separate. Current debate emphasises inaccurate responses, excessive validation and the entry of a “third voice” into relationships, but pays less attention to a limitation that precedes the answer: users can include in a prompt only what is available to their own understanding at that moment. Objective: To propose the blind prompt as a theoretical-clinical formulation and discuss its usefulness in psychiatry and psychotherapy. Method: A theoretical-clinical essay illustrated by an entirely fictional vignette not derived from an identifiable patient. Result: The blind prompt describes questions structured by clinically relevant omissions that users do not recognise, cannot mentalise or cannot formulate under intense affective activation. Four heuristic types of blind spot are proposed: unformulated, contradictory, relational and state-dependent. Even when coherent with the problem presented, the artificial intelligence response may reinforce premature decisional closure, unilateral attributions or the reduction of a dyadic conflict to individual traits. Clinicians are encouraged to examine the function, frame, absences and subsequent effects of the consultation. Conclusion: The clinical limitation may arise before the answer. The prompt should be treated as clinical material and as a provisional map of what the patient can and cannot yet think.

Downloads

Download data is not yet available.

Metrics

Metrics Loading ...

Author Biography

Harmony Trade Center, MT Psiquiatria, Harmony Trade Center, Maceió, AL, Brasil

http://lattes.cnpq.br/8381023808070684

Médico psiquiatra e psicoterapeuta (CRM-AL 4701, RQE 2429), com atuação clínica em MT Psiquiatria, Harmony Trade Center, Maceió, AL, Brasil. Já publicou na Revista Debates em Psiquiatria o relato de caso "Síndrome de Capgras secundária a traumatismo crânioencefálico frontal em paciente com transtorno afetivo bipolar tipo II" e o artigo de atualização "Neurobiologia do insight terapêutico: um modelo integrado de reconsolidação, erro de predição e processamento emocional implícito". Recebeu convite para apresentar o trabalho sobre síndrome de Capgras em congresso em Paris, França. Encontra-se atualmente em fase final do processo de reconhecimento de grau, Mestrado (revalidação de diploma) junto à Faculdade de Medicina da Universidade do Porto (FMUP), Portugal.

References

1. Haber Y, Levkovich I, Hadar-Shoval D, Elyoseph Z. The artificial third: a broad view of the effects of introducing generative artificial intelligence on psychotherapy. JMIR Ment Health. 2024;11:e54781. https://doi.org/10.2196/54781 PMid:38787297 PMCid:PMC11137430

2. Levkovich I, Alon L. Generative AI as a third voice in human couple relationships: a systematic review. Comput Hum Behav Rep. 2026;23:101255. https://doi.org/10.1016/j.chbr.2026.101255

3. Rousmaniere T, Goldberg SB, Torous J. Large language models as mental health providers. Lancet Psychiatry. 2026;13(1):7-9. https://doi.org/10.1016/S2215-0366(25)00269-X PMid:40939602 PMCid:PMC12462653

4. Moore J, Grabb D, Agnew W, Klyman K, Chancellor S, Ong DC, Haber N. Expressing stigma and inappropriate responses prevents LLMs from safely replacing mental health providers. In: Proceedings of the 2025 ACM Conference on Fairness, Accountability, and Transparency [Internet]. New York: Association for Computing Machinery; 2025. p. 599-627. https://doi.org/10.1145/3715275.3732039

5. Cheng M, Lee C, Khadpe P, Yu S, Han D, Jurafsky D. Sycophantic AI decreases prosocial intentions and promotes dependence. Science. 2026;391:eaec8352. https://doi.org/10.1126/science.aec8352 PMid:41886588

6. Lemma A. At the meniscus of self-understanding: rethinking the examined life in technogenetic times. Int J Psychoanal. 2025;106(6):1089-1107. https://doi.org/10.1080/00207578.2025.2577114 PMid:41627093

7. Stern DB. Unformulated experience: from dissociation to imagination in psychoanalysis. Hillsdale: Analytic Press; 1997.

8. Bion WR. Learning from experience. London: Heinemann; 1962.

9. Bateman AW, Fonagy P. Mentalization-based treatment for personality disorders: a practical guide. Oxford: Oxford University Press; 2016. https://doi.org/10.1093/med:psych/9780199680375.001.0001

10. Morgan M. A couple state of mind: psychoanalysis of couples and the Tavistock Relationships model. Abingdon: Routledge; 2019. https://doi.org/10.4324/9780429451102

11. Nickerson RS. Confirmation bias: a ubiquitous phenomenon in many guises. Rev Gen Psychol. 1998;2(2):175-220. https://doi.org/10.1037/1089-2680.2.2.175

Published

2026-10-14

How to Cite

1.
Duarte MT. The blind prompt: a limitation preceding the artificial intelligence response in relationship advice. Debates Psiquiatr. [Internet]. 2026 Oct. 14 [cited 2026 Oct. 16];16:1-10, e1685. Available from: https://revistardp.org.br/revista/article/view/1685

Issue

Section

Brief Communication

Plaudit