Who is Responsible, the Advisor or the AI? Understanding the Effects of Advisors Disclosing Their AI Use on Their Perceived Responsibility and AI Reliance

Human advisors increasingly have access to AI recommendations and use them to shape the advice they give clients, often without disclosing their AI use to their clients. Disclosure of AI use involves informing individuals when AI is being used on their behalf by another person, such as disclosing to clients that advisors are using AI to formulate their expert advice. Our study aims to investigate whether and how disclosing advisors' use of AI assistance to their clients influences the advisors' perceived responsibility for decisions and degree of AI reliance. Recruiting financial advisors to perform a personal finance advising simulation that manipulated whether clients would know that advisors used an AI system (disclosed vs. not disclosed), we found that financial advisors felt less responsible for their recommendations when they believed their use of AI assistance would be disclosed rather than undisclosed to clients. We also found that advisors' perceived personal responsibility was higher when their reliance on AI was lower. Advisors' perceived self-competence increased their perceived personal responsibility for investment decisions relative to AI, and their trust in AI decreased their perceived responsibility. We conclude by discussing how our findings can inform disclosure schemes for improved human-AI collaboration in advising.

Authors

Institutions

Publication Details

Journal
Proceedings of the ACM on Human-Computer Interaction
Published
2025-10-16
DOI
https://doi.org/10.1145/3757524
Citations
2
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
4.73
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Who is Responsible, the Advisor or the AI? Understanding the Effects of Advisors Disclosing Their AI Use on Their Perceived Responsibility and AI Reliance

Oded Nov, Tamir Mendel, Batia M. Wiesenfeld, Soumik Mandal
2 citations
Proceedings of the ACM on Human-Computer Interaction
Ethics and Social Impacts of AI
4.73
article

Who is Responsible, the Advisor or the AI? Understanding the Effects of Advisors Disclosing Their AI Use on Their Perceived Responsibility and AI Reliance

Oded Nov, Tamir Mendel, Batia M. Wiesenfeld, Soumik Mandal
article en
2 citations

Abstract

Human advisors increasingly have access to AI recommendations and use them to shape the advice they give clients, often without disclosing their AI use to their clients. Disclosure of AI use involves informing individuals when AI is being used on their behalf by another person, such as disclosing to clients that advisors are using AI to formulate their expert advice. Our study aims to investigate whether and how disclosing advisors' use of AI assistance to their clients influences the advisors' perceived responsibility for decisions and degree of AI reliance. Recruiting financial advisors to perform a personal finance advising simulation that manipulated whether clients would know that advisors used an AI system (disclosed vs. not disclosed), we found that financial advisors felt less responsible for their recommendations when they believed their use of AI assistance would be disclosed rather than undisclosed to clients. We also found that advisors' perceived personal responsibility was higher when their reliance on AI was lower. Advisors' perceived self-competence increased their perceived personal responsibility for investment decisions relative to AI, and their trust in AI decreased their perceived responsibility. We conclude by discussing how our findings can inform disclosure schemes for improved human-AI collaboration in advising.

Proceedings of the ACM on Human-Computer InteractionVol. 9(7)
New York University (US)
Openalex Percentile: Top 5%
Ethics and Social Impacts of AI
4.73
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.