标题： 基础模型的市场集中度影响 显示英文标题

标题： Market Concentration Implications of Foundation Models

摘要： 我们分析基础模型市场的结构，即诸如推动ChatGPT运行并可适应下游用途的大型人工智能模型，并研究其对竞争政策和监管的影响。 我们观察到，最强大的模型可能会倾向于自然垄断，并可能拥有巨大的市场。 这需要采取双管齐下的监管措施：(i) 反垄断机构需要通过解决战略行为来确保市场的可竞争性，特别是确保垄断不会垂直扩展到下游用途，以及 (ii) 鉴于市场纪律的潜力减弱，监管机构有责任确保最强大的模型达到足够的质量标准（包括安全、隐私、非歧视、可靠性和互操作性标准），以最大程度地促进社会福利。 监管机构还应确保经济所有部门中人工智能和非人工智能应用之间的监管环境公平。 对于处于前沿之后的模型，我们预计竞争将非常激烈，这意味着竞争政策的作用较为有限，尽管监管仍有一定作用。 显示英文摘要

摘要： We analyze the structure of the market for foundation models, i.e., large AI models such as those that power ChatGPT and that are adaptable to downstream uses, and we examine the implications for competition policy and regulation. We observe that the most capable models will have a tendency towards natural monopoly and may have potentially vast markets. This calls for a two-pronged regulatory response: (i) Antitrust authorities need to ensure the contestability of the market by tackling strategic behavior, in particular by ensuring that monopolies do not propagate vertically to downstream uses, and (ii) given the diminished potential for market discipline, there is a role for regulators to ensure that the most capable models meet sufficient quality standards (including safety, privacy, non-discrimination, reliability and interoperability standards) to maximally contribute to social welfare. Regulators should also ensure a level regulatory playing field between AI and non-AI applications in all sectors of the economy. For models that are behind the frontier, we expect competition to be quite intense, implying a more limited role for competition policy, although a role for regulation remains.