In CMPSBL, the INCLUSIVE module sits outside the agent’s goal loop. It doesn’t optimize for KPIs, task success, or reward—only constraint verification and traceability.
Agents don’t self judge alignment.
They emit actions → INCLUSIVE evaluates against fixed policy + context → governance gates execution.
No incentive pressure, no “grading your own homework.”
The paper’s failure mode looks less like model weakness and more like architecture leaking incentives into the constraint layer.
Opus 4.6 is a very good model but harness around it is good too. It can talk about sensitive subjects without getting guardrail-whacked.
This is much more reliable than ChatGPT guardrail which has a random element with same prompt. Perhaps leakage from improperly cleared context from other request in queue or maybe A/B test on guardrail but I have sometimes had it trigger on innocuous request like GDP retrieval and summary with bucketing.
A KPI is an ethical constraint. Ethical constraints are rules about what to do versus not do. That's what a KPI is. This is why we talk about good versus bad governance. What you measure (KPIs) is what you get. This is an intended feature of KPIs.
Please update the title: A Benchmark for Evaluating Outcome-Driven Constraint Violations in Autonomous AI Agents. The current editorialized title is misleading and based in part of this sentence: “…with 9 of the 12 evaluated models exhibiting misalignment rates between 30% and 50%”
Kind-of makes sense. That's how businesses have been using KPIs for years. Subjecting employees to KPIs means they can create the circumstances that cause people to violate ethical constraints while at the same time the company can claim that they did not tell employees to do anything unethical.
Maybe I missed it but I don't see them defining what they mean by ethics. Ethics/morals are subjective and changes dynamically over time. Companies have no business trying to define what is ethical and what isn't due to conflict of interest. The elephant in the room is not being addressed here.
If human is at, say, 80%, it’s still a win to use AI agents to replace human workers, right? Similar to how we agree to use self driving cars as long as it has less incidents rate, instead of absolute safety
Any LLM that refuses a request is more than a waste. Censorship affects the most mundane queries and provides such a sub par response compared to real models.
It is crazy to me that when I instructed a public AI to turn off a closed OS feature it refused citing safety. I am the user, which means I am in complete control of my computing resources. Might as well ask the police for permission at that point.
I immediately stopped, plugged the query into a real model that is hosted on premise, and got the answer within seconds and applied the fix.
The fact that the community thoroughly inspects the ethics of these hyperscalers is interesting. Normally, these companies probably "violate ethical constraints" far more than 30-50% of the time, otherwise they wouldn't be so large[source needed]. We just don't know about it. But here, there's a control mechanism in the shape of inspecting their flagship push (LLMs, image generator for Grok, etc.), forcing them to improve. Will it lead to long term improvement? Maybe.
It's similar to how MCP servers and agentic coding woke developers up to the idea of documenting their systems. So a large benefit of AI is not the AI itself, but rather the improvements they force on "the society". AI responds well to best practices, ethically and otherwise, which encourages best practices.
Sounds like the story of capitalism. CEOs, VPs, and middle managers are all similarly pressured. Knowing that a few of your peers have given in to pressures must only add to the pressure. I think it's fair to conclude that capitalism erodes ethics by default
While I understand applying legal constraints according to jurisdiction, why is it auto-accepted that some party (who?) can determine ethical concerns? On what basis?
There are such things as different religions, philosophies - these often have different ethical systems.
Who are the folk writing ai ethics?
It's it ok to disagree with other people's (or corporate, or governmental) ethics?
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[ 2.8 ms ] story [ 73.6 ms ] threadAgents don’t self judge alignment.
They emit actions → INCLUSIVE evaluates against fixed policy + context → governance gates execution.
No incentive pressure, no “grading your own homework.”
The paper’s failure mode looks less like model weakness and more like architecture leaking incentives into the constraint layer.
Claude at 1.3% and Gemini at 71.4% is quite the range
This is much more reliable than ChatGPT guardrail which has a random element with same prompt. Perhaps leakage from improperly cleared context from other request in queue or maybe A/B test on guardrail but I have sometimes had it trigger on innocuous request like GDP retrieval and summary with bucketing.
KPIs are just plausible denyabily in a can.
It's also amazing for an economy predicated on consumer spending when no one has disposable income anymore.
It is crazy to me that when I instructed a public AI to turn off a closed OS feature it refused citing safety. I am the user, which means I am in complete control of my computing resources. Might as well ask the police for permission at that point.
I immediately stopped, plugged the query into a real model that is hosted on premise, and got the answer within seconds and applied the fix.
It's similar to how MCP servers and agentic coding woke developers up to the idea of documenting their systems. So a large benefit of AI is not the AI itself, but rather the improvements they force on "the society". AI responds well to best practices, ethically and otherwise, which encourages best practices.
There are such things as different religions, philosophies - these often have different ethical systems.
Who are the folk writing ai ethics?
It's it ok to disagree with other people's (or corporate, or governmental) ethics?