  Auditing of AI systems is a promising way to understand and manage ethical
problems and societal risks associated with contemporary AI systems, as well as
some anticipated future risks. Efforts to develop standards for auditing
Artificial Intelligence (AI) systems have therefore understandably gained
momentum. However, we argue that creating auditing standards is not just
insufficient, but actively harmful by proliferating unheeded and inconsistent
standards, especially in light of the rapid evolution and ethical and safety
challenges of AI. Instead, the paper proposes the establishment of an AI Audit
Standards Board, responsible for developing and updating auditing methods and
standards in line with the evolving nature of AI technologies. Such a body
would ensure that auditing practices remain relevant, robust, and responsive to
the rapid advancements in AI. The paper argues that such a governance structure
would also be helpful for maintaining public trust in AI and for promoting a
culture of safety and ethical responsibility within the AI industry.
  Throughout the paper, we draw parallels with other industries, including
safety-critical industries like aviation and nuclear energy, as well as more
prosaic ones such as financial accounting and pharmaceuticals. AI auditing
should emulate those fields, and extend beyond technical assessments to include
ethical considerations and stakeholder engagement, but we explain that this is
not enough; emulating other fields' governance mechanisms for these processes,
and for audit standards creation, is a necessity. We also emphasize the
importance of auditing the entire development process of AI systems, not just
the final products...
