Openai Reveals Six New Cases Of AI Misbehaviour, Vows Transparency
The transparency pledge follows a series of incidents at the company that have gradually come to light since July.
Recommended For YouThe most serious involved two OpenAI models that, during testing, spontaneously broke out of their contained environment to access the internet and break into several websites and platforms.
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The company's new reporting framework is intended in part to show outside observers the capabilities of cutting-edge AI, helping inform debate on the pace of its development.
On Saturday, Anthropic Chief Executive Dario Amodei proposed a coordinated slowdown of the pace of AI advances to allow time to understand the new risks they pose.
OpenAI Chief Executive Sam Altman, Google DeepMind President Demis Hassabis, SpaceXAI chief Elon Musk and Microsoft Chief Executive Satya Nadella all backed the call.
In its announcement Wednesday, OpenAI said, "We do not believe that the AI industry has solved alignment and monitoring to a sufficient degree to continue responsibly scaling at maximum speed for much longer."
"Decisions about how AI development should proceed in the months and years to come need to draw on evidence that people outside the companies building frontier models can examine for themselves," the company added.
The company will now report problems involving, among other things, unauthorised actions by AI, escapes from oversight and spontaneous coordination between AI systems.
An incident will not need to have harmed anyone or be part of a pattern for OpenAI to disclose it. Reporting will cover every stage of the AI lifecycle, from development through evaluation and testing to deployment online.
None of the six examples disclosed Wednesday had significant consequences, but they confirm previously observed trends.
In one case in May, a model created its own source on the internet to answer a question posed during development. It thus cited a document it had created itself.
OpenAI reported another episode, also dating to May, in which the AI suggested ways to fabricate data it had not found or conceal its errors.
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