Regulating the AI Casino: Proposals for Macao
The era of the AI Casino is already upon us. Cutting-edge advances in machine learning, AI, and facial recognition technology has enabled casinos to enhance their operations in a myriad of ways. Specifically, the technology was meant to improve security, prevent fraud, blacklist undesirable customers, increase operational efficiency by automating certain gaming procedures, and entice big spenders with targeted marketing such as complimentary meals and drinks, lines of credit, and other perks like free show tickets. AI could also identify and deter gambling addicts. However, there are privacy concerns about the unrestricted harvesting of bioemtric information by casinos without consent. Also, casinos could abuse these capabilities to take advantage of compulsive gamblers. Thus, taking Macao as an example, this article overviews the state of the current law and provides suggestions for regulatory updates based on foreign examples.
Sino-AI: AI Regulations in Sinophone Regions
China's rise as an AI power challenges the narrative in the U.S. and increasingly in Europe that innovation is stifled by regulation, because China has a robust AI regulatory regime that prohibits a wide range of AI applications and activities that imperil public safety. At the same time, most people live in countries that do not realistically aspire to become pioneers in either AI technology or AI regulations. For these countries, the question of whether innovation in AI is hindered by regulation is not as urgent because these countries are unlikely to ever become AI leaders in any case. Moreover, strict regulations of AI services would be difficult to enforce for most countries that lack the regulatory capacity and experience of jurisdictions like China or the EU. Finally, since AI models have become quite popular among the general public, most governments have been reluctant to restrict access to these models for fear of a public backlash. Thus, this paper takes a closer look at three notable "Sinophone" regions and "middle powers" outside of Mainland China, namely Taiwan, Singapore, and Hong Kong, to examine how their approaches to AI regulation have been influenced by their desire to balance innovation with risk mitigation in light of their limitations as "middle powers."
