AI companies promised to self-regulate one year ago. What’s changed?
RESULT: Good. This is an encouraging result overall. While watermarking remains experimental and is still unreliable, it’s still good to see research around it and a commitment to the C2PA standard. It’s better than nothing, especially during a busy election year.
Commitment 6
The companies commit to publicly reporting their AI systems’ capabilities, limitations, and areas of appropriate and inappropriate use. This report will cover both security risks and societal risks, such as the effects on fairness and bias.
The White House’s commitments leave a lot of room for interpretation. For example, companies can technically meet this public reporting commitment with widely varying levels of transparency, as long as they do something in that general direction.
The most common solutions tech companies offered here were so-called model cards. Each company calls them by a slightly different name, but in essence they act as a kind of product description for AI models. They can address anything from the model’s capabilities and limitations (including how it measures up against benchmarks on fairness and explainability) to veracity, robustness, governance, privacy, and security. Anthropic said it also tests models for potential safety issues that may arise later.
Microsoft has published an annual Responsible AI Transparency Report, which provides insight into how the company builds applications that use generative AI, make decisions, and oversees the deployment of those applications. The company also says it gives clear notice on where and how AI is used within its products.
RESULT: More work is needed. One area of improvement for AI companies would be to increase transparency on their governance structures and on the financial relationships between companies, Hickok says. She would also have liked to see companies be more public about data provenance, model training processes, safety incidents, and energy use.
Commitment 7
The companies commit to prioritizing research on the societal risks that AI systems can pose, including on avoiding harmful bias and discrimination, and protecting privacy. The track record of AI shows the insidiousness and prevalence of these dangers, and the companies commit to rolling out AI that mitigates them.
Tech companies have been busy on the safety research front, and they have embedded their findings into products. Amazon has built guardrails for Amazon Bedrock that can detect hallucinations and can apply safety, privacy, and truthfulness protections. Anthropic says it employs a team of researchers dedicated to researching societal risks and privacy. In the past year, the company has pushed out research on deception, jailbreaking, strategies to mitigate discrimination, and emergent capabilities such as models’ ability to tamper with their own code or engage in persuasion. And OpenAI says it has trained its models to avoid producing hateful content and refuse to generate output on hateful or extremist content. It trained its GPT-4V to refuse many requests that require drawing from stereotypes to answer. Google DeepMind has also released research to evaluate dangerous capabilities, and the company has done a study on misuses of generative AI.
