Evidence map›Paper›PMID 41640575›Full record

ArticlePhilosophy & technology2025

Privacy and Human-AI Relationships.

Christopher Register, Maryam Ali Khan, Alberto Giubilini, Brian David Earp, Julian Savulescu

Abstract read
In one paragraph

Article in Philosophy & technology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Christopher RegisterUehiro Oxford Institute, University of Oxford, Suite 1 Littlegate House, St Ebbe's Street, Oxford OX1 1PT, England.ORCID 0000-0002-5957-6376
Maryam Ali KhanUehiro Oxford Institute, University of Oxford, Suite 1 Littlegate House, St Ebbe's Street, Oxford OX1 1PT, England.ORCID https://orcid.org/0000-0001-5996-0610
Alberto GiubiliniUehiro Oxford Institute, University of Oxford, Suite 1 Littlegate House, St Ebbe's Street, Oxford OX1 1PT, England.ORCID https://orcid.org/0000-0001-5163-3017
Brian David EarpUehiro Oxford Institute, University of Oxford, Suite 1 Littlegate House, St Ebbe's Street, Oxford OX1 1PT, England.ORCID https://orcid.org/0000-0001-9691-2888
Julian SavulescuUehiro Oxford Institute, University of Oxford, Suite 1 Littlegate House, St Ebbe's Street, Oxford OX1 1PT, England.ORCID https://orcid.org/0000-0003-1691-6403

Funding

Wellcome Trust 203132
6 · The paper itself

Abstract

Artificial intelligence (AI) agents such as chatbots and personal AI assistants are increasingly popular. These technologies raise new privacy concerns beyond those posed by other AI systems or information technologies. For example, anthropomorphic features of AI chatbots may invite users to disclose more information with these systems than they would otherwise, especially when users interact with chatbots in relationship-like ways. In this paper, we aim to develop a framework for assessing the distinctive privacy ramifications of AI agents, especially as humans begin to interact with them in relationship-like ways. In particular, we draw from prominent theories of privacy and results from human relational psychology to better understand how AI agents may affect human behavior and the flow of personal information. We then assess how these effects could bear on eight distinct values of privacy, such as autonomy, the value of forming and maintaining relationships, security from harm, and more.

Indexed as

Artificial intelligenceHuman-AI relationshipsPrivacyRelational moral psychology

Identifiers

PMID41640575
PMCPMC7618715

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.