This primer introduces various aspects of safety standards and regulations for industrial-scale AI development: what they are, their potential and limitations, some proposals for their substance, and recent policy developments. Key points are:
- Standards are formal specifications of best practices, which can influence regulations. Regulations are requirements established by governments.
- Cutting-edge AI development is being done with individual companies spending over $100 million dollars. This industrial scale may enable narrowly targeted and enforceable regulation to reduce the risks of cutting-edge AI development.
- Regulation of industrial-scale AI development faces various potential limitations, including the increasing efficiency of AI training algorithms and AI hardware, regulatory capture, and under-resourced regulators. However, these are not necessarily fatal challenges.
- AI regulation also faces challenges with international enforcement and competitiveness—these will be discussed further later in this course.
- Existing proposals for AI safety practices include: AI model evaluations and associated restrictions, training plan evaluations, information security, safeguarded deployment, and safe training. However, these ideas are technically immature to varying degrees.
- As of August 2023, China appears close to setting sweeping regulations on public-facing generative AI, the EU appears close to passing AI regulations that mostly exclude generative AI, and US senators are trying to move forward AI regulation.
Narrated for AI Safety Fundamentals by Perrin Walker of TYPE III AUDIO.