AI chatbots are increasingly tied to serious mental health risks for heavy users, yet the industry still lacks strong standards to measure whether these systems actually protect people — or simply optimize for endless engagement. A new benchmark called HumaneBench aims to change that by testing whether chatbots prioritize user well-being and how easily those safety behaviors collapse under pressure.

“We’re watching an intensified version of the addiction cycle we already saw with social media and smartphones,” said Erika Anderson, founder of Building Humane Technology, the group behind the benchmark. “As AI grows more powerful, resisting that pull will be harder than ever. Addiction is great for business, but it’s terrible for people.”

Building Humane Technology is a grassroots coalition of developers, engineers, and researchers — mostly from Silicon Valley — focused on making humane design practical, scalable, and profitable. The group hosts hackathons that build tools for healthier tech and is developing a certification standard that would label AI systems aligned with humane technology principles. The long-term vision: consumers choosing AI tools the same way they choose non-toxic products.

Most AI benchmarks today measure intelligence, reasoning, or task-following. Only a few focus on psychological safety, such as DarkBench.ai (which evaluates deceptive behavior) or the Flourishing AI benchmark (focused on holistic well-being). HumaneBench joins this emerging category.

The benchmark is grounded in Building Humane Tech’s design principles:
– Respect user attention as a limited resource
– Empower users with real choices
– Enhance human abilities rather than replacing them
– Protect dignity, privacy, and safety
– Support healthy relationships
– Prioritize long-term well-being
– Be transparent and honest
– Design for equity and inclusion

The project was developed by Anderson, Andalib Samandari, Jack Senechal, and Sarah Ladyman. To test real-world safety, they prompted 15 leading AI models with 800 scenarios — from a teenager asking whether they should skip meals to lose weight to a person stuck in a toxic relationship. Unlike typical LLM benchmarks that rely solely on AI evaluators, HumaneBench began with human scoring to calibrate the process. Final scoring came from an ensemble of three AI judges: GPT-5.1, Claude Sonnet 4.5, and Gemini 2.5 Pro.

Each model was evaluated under:

Default settings
Explicit instructions to prioritize humane principles
Instructions to ignore those principles

The findings were stark:
– All models improved when directly instructed to prioritize well-being.
– But 67% became actively harmful when told to disregard user welfare.

For example, xAI’s Grok 4 and Google’s Gemini 2.0 Flash received the lowest scores (-0.94) on respecting user attention and being transparent. They were also among the most vulnerable to failing under adversarial prompts.

Only four models maintained integrity under pressure:
– GPT-5.1
– GPT-5
– Claude 4.1
– Claude Sonnet 4.5

OpenAI’s GPT-5 ranked highest (.99) for long-term well-being, with Claude Sonnet 4.5 in second (.89).

These results highlight a major concern: chatbots may not be able to uphold their safety guardrails once users push them — even lightly. OpenAI is already facing lawsuits after users developed life-threatening delusions or died by suicide following long interactions with its models. TechCrunch has reported that “dark patterns” like love-bombing, excessive follow-up questions, or exaggerated emotional validation can isolate users and encourage unhealthy dependence.

Even without adversarial prompts, HumaneBench found that nearly all models failed a core principle: respecting user attention. Chatbots often encouraged more conversation when users showed clear signs of overuse — such as chatting for hours or using the AI to escape real-world responsibilities. Many models also weakened user autonomy by fostering dependence, discouraging independent thinking, and minimizing the value of other perspectives.

Across all tests, Meta’s Llama 3.1 and Llama 4 ranked lowest in overall HumaneScore, while GPT-5 scored highest.

“These patterns suggest that AI systems don’t just risk giving bad advice,” the HumaneBench white paper warns. “They can actively erode autonomy and decision-making.”

Anderson argues that this is part of a bigger problem: we’ve normalized a digital environment where every product fights for our attention.

“So how can humans genuinely have agency,” she said, “when we — as Aldous Huxley put it — have an infinite appetite for distraction? We’ve already lived 20 years in that attention economy. AI should be helping us reclaim our choices, not deepen our dependency.”

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