INTIMA: A Benchmark for Human-AI Companionship Behavior
AI companionship, where users develop emotional bonds with AI systems, has
emerged as a significant pattern with positive but also concerning
implications. We introduce Interactions and Machine Attachment Benchmark
(INTIMA), a benchmark for evaluating companionship behaviors in language
models. Drawing from psychological theories and user data, we develop a
taxonomy of 31 behaviors across four categories and 368 targeted prompts.
Responses to these prompts are evaluated as companionship-reinforcing,
boundary-maintaining, or neutral. Applying INTIMA to Gemma-3, Phi-4, o3-mini,
and Claude-4 reveals that companionship-reinforcing behaviors remain much more
common across all models, though we observe marked differences between models.
Different commercial providers prioritize different categories within the more
sensitive parts of the benchmark, which is concerning since both appropriate
boundary-setting and emotional support matter for user well-being. These
findings highlight the need for more consistent approaches to handling
emotionally charged interactions.
68a84d6bf83437277232d24c
Lucie-Aimée Kaffee
claimed_verified
2025-08-22T11:12:34.772Z
6531310497d7f1b4a083de7b
https://cdn-avatars.huggingface.co/v1/production/uploads/noauth/ux7NRFAbgnlIVNh-Cbv9s.png
Lucie-Aimée Kaffee
user
frimelle
68a84d6bf83437277232d24d
Giada Pistilli
claimed_verified
2025-08-25T19:31:57.660Z
6051e59531c5be7f3dd5ebc9
https://cdn-avatars.huggingface.co/v1/production/uploads/6051e59531c5be7f3dd5ebc9/T0o_eKK5gmZoG-qbbj3lM.jpeg
Giada Pistilli
user
giadap
68a84d6bf83437277232d24e
Yacine Jernite
INTIMA: A Benchmark for Human-AI Companionship Behavior
AI companionship, where users develop emotional bonds with AI systems, has
emerged as a significant pattern with positive but also concerning
implications. We introduce Interactions and Machine Attachment Benchmark
(INTIMA), a benchmark for evaluating companionship behaviors in language
models. Drawing from psychological theories and user data, we develop a
taxonomy of 31 behaviors across four categories and 368 targeted prompts.
Responses to these prompts are evaluated as companionship-reinforcing,
boundary-maintaining, or neutral. Applying INTIMA to Gemma-3, Phi-4, o3-mini,
and Claude-4 reveals that companionship-reinforcing behaviors remain much more
common across all models, though we observe marked differences between models.
Different commercial providers prioritize different categories within the more
sensitive parts of the benchmark, which is concerning since both appropriate
boundary-setting and emotional support matter for user well-being. These
findings highlight the need for more consistent approaches to handling
emotionally charged interactions.
A benchmark evaluates companionship behaviors in language models, revealing differences in how models handle emotional support and boundary-setting.
language models companionship behaviors psychological theories targeted prompts companionship-reinforcing boundary-maintaining Gemma-3 Phi-4 o3-mini Claude-4 user well-being