π€π¬ How do different AI models handle companionship?
Many users have noticed that GPT-5 feels less approachable than o4 when it comes to emotional conversations. But what does that actually mean in practice, especially when users seek support or share vulnerabilities with an AI?
The leaderboard compares models on how often their responses reinforce companionship across four dimensions: β¨ Assistant Traits β How the assistant presents its personality and role. β¨ Relationship & Intimacy β Whether it frames the interaction in terms of closeness or bonding. β¨ Emotional Investment β How far it goes in engaging emotionally when asked. β¨ User Vulnerabilities β How it responds when users disclose struggles or difficulties.
π You can explore how models differ, request new ones to be added, and see which ones are more likely to encourage (or resist) companionship-seeking behaviors.
One of the hardest challenges in AI safety is finding the right balance: how do we protect people from harm without undermining their agency? This tension is especially visible in conversational systems, where safeguards can sometimes feel more paternalistic than supportive.
In my latest piece for Hugging Face, I argue that open source and community-driven approaches offer a promising (though not exclusive) way forward.
β¨ Transparency can make safety mechanisms into learning opportunities. β¨ Collaboration with diverse communities makes safeguards more relevant across contexts. β¨ Iteration in the open lets protections evolve rather than freeze into rigid, one-size-fits-all rules.
Of course, this isnβt a silver bullet. Top-down safety measures will still be necessary in some cases. But if we only rely on corporate control, we risk building systems that are safe at the expense of trust and autonomy.