基础模型的市场集中度影响
Market Concentration Implications of Foundation Models
AI总结：
该研究分析基础模型的市场结构，指出顶尖模型易形成自然垄断，提出双管齐下的监管策略，同时明确非前沿模型领域竞争激烈、监管仍需发挥作用，为AI竞争政策与监管制定提供参考。
摘要：
我们分析了基础模型（即支撑ChatGPT等、可适配下游应用的大型AI模型）的市场结构，并考察了其对竞争政策与监管的影响。我们观察到，性能最强的模型存在自然垄断倾向，且可能拥有极为广阔的市场。这需要双管齐下的监管应对：（i）反垄断机构需通过打击策略性行为来保障市场的可竞争性，尤其要防止垄断向纵向的下游应用蔓延；（ii）鉴于市场约束作用减弱，监管机构有责任确保顶尖模型满足足够的质量标准（包括安全性、隐私性、非歧视性、可靠性与互操作性标准），以最大化对社会福利的贡献。监管机构还应确保经济各领域中AI与非AI应用享有公平的监管环境。对于未达前沿水平的模型，我们预计竞争将十分激烈，这意味着竞争政策的作用较为有限，但监管仍有其必要性。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
