Relational Norms for Human-AI Cooperation
Abstrak
How we should design and interact with social artificial intelligence depends on the socio-relational role the AI is meant to emulate or occupy. In human society, relationships such as teacher-student, parent-child, neighbors, siblings, or employer-employee are governed by specific norms that prescribe or proscribe cooperative functions including hierarchy, care, transaction, and mating. These norms shape our judgments of what is appropriate for each partner. For example, workplace norms may allow a boss to give orders to an employee, but not vice versa, reflecting hierarchical and transactional expectations. As AI agents and chatbots powered by large language models are increasingly designed to serve roles analogous to human positions - such as assistant, mental health provider, tutor, or romantic partner - it is imperative to examine whether and how human relational norms should extend to human-AI interactions. Our analysis explores how differences between AI systems and humans, such as the absence of conscious experience and immunity to fatigue, may affect an AI's capacity to fulfill relationship-specific functions and adhere to corresponding norms. This analysis, which is a collaborative effort by philosophers, psychologists, relationship scientists, ethicists, legal experts, and AI researchers, carries important implications for AI systems design, user behavior, and regulation. While we accept that AI systems can offer significant benefits such as increased availability and consistency in certain socio-relational roles, they also risk fostering unhealthy dependencies or unrealistic expectations that could spill over into human-human relationships. We propose that understanding and thoughtfully shaping (or implementing) suitable human-AI relational norms will be crucial for ensuring that human-AI interactions are ethical, trustworthy, and favorable to human well-being.
Topik & Kata Kunci
Penulis (62)
B. Earp
Sebastian Porsdam Mann
Mateo Aboy
Edmond Awad
M. Betzler
M. Botes
Rachel Calcott
Mina Caraccio
Nick Chater
Mark Coeckelbergh
M. Constantinescu
Hossein Dabbagh
Kate Devlin
Xiao Ding
V. Dranseika
Jim A. C. Everett
Ruiping Fan
F. Feroz
Kathryn B. Francis
Cindy Friedman
Orsolya Friedrich
Iason Gabriel
Ivar Hannikainen
J. Hellmann
Arasj Khodadade Jahrome
N. Janardhanan
Paulius Jurcys
Andreas Kappes
Maryam Ali Khan
Gordon Kraft-Todd
Max Kroner Dale
S. Laham
Benjamin Lange
Muriel Leuenberger
Jonathan Lewis
Pengbo Liu
David M. Lyreskog
M. Maas
J. Mcmillan
Emil G. Mihailov
Timo Minssen
J. Monrad
K. Muyskens
Simon Myers
Sven Nyholm
Alexa M. Owen
Anna Puzio
Christopher Register
Madeline G. Reinecke
Adam Safron
Henry Shevlin
Hayate Shimizu
Peter V. Treit
Cristina Voinea
Karen Yan
Anda Zahiu
Renwen Zhang
Hazem Zohny
Walter Sinnott-Armstrong
Ilina Singh
Julian Savulescu
Margaret S. Clark
Akses Cepat
- Tahun Terbit
- 2025
- Bahasa
- en
- Total Sitasi
- 16×
- Sumber Database
- Semantic Scholar
- DOI
- 10.48550/arXiv.2502.12102
- Akses
- Open Access ✓