Background

This post first originated from an application question and is not yet finished. At the moment it simply introduces Safety Cases as I personally see them but does not go into depth about their benefits or drawbacks.

Review of the Safety Cases Agenda for Mitigating AI Risk

After reading Safety cases for frontier AI, my preliminary belief is that safety cases are a powerful tool for incentivizing AI labs to innovate and self-reflect on safety practices, but which still suffer from certain misaligned incentives. Safety cases may be a powerful alternative (but not perfect substitute) for rule-based legislation, especially given the 2025 political climate in which governments (particularly the United States) have little appetite for strong regulation.

To summarize the approach, safety cases, in general, are a soft-regulatory mechanism1 where the company producing the product under scrutiny — either by their own volition or by law — produce a structured argument, supported by evidence, for why their product is safe in a given environment and set of circumstances. Their safety case is typically public or semi-public and is reviewed by the company’s leadership, third-party auditors, and government regulators. While the safety case itself doesn’t mandate the company do anything other than produce the report, failure to comply in good-faith with the actual goal of “being safe” can still lead to real consequences. Some that come to mind include:

  1. The loss of trust between developers, users, and governments
  2. Potential litigation if the company was shown to be negligent in their safety plans with the safety case used as evidence.
  3. The threat of hard regulation
  4. Taking a hit on Public Relations

This approach has some considerable upsides, one of which being that it can align the incentives within AI labs to put at least a bare minimum effort into making sure that their product is safe while also forcing labs to seriously consider the potentially devastating implications of advancing AI. Even as AI progress rapidly advances beyond the paste of legislation, safety cases robustly main good incentives for the companies to remain safe as opposed to rule based legislation which is mainly about thoughtlessly crossing off items that could leave them liable. One understated aspect of this is that it treats the auditors, regulators, and companies as allies in making sure the product is safe rather than adversaries.

However, this approach also relies heavily on the company’s good-faith attendance to the safety cases and can easily lead to gamifying their plan as to obscure the dangers to policy makers. It also does not provide any kind of external feedback loop from the external world to the company on short periods of time.

Footnotes

  1. This mechanism was developed in the past few decades and which have become popular in industries like nuclear power and aviation among others.