It seems everyone must have an AI Law. Europe's AI Law appears at the
vanguard, though in a way t is merely a local expression of what appears
to be a developing consensus among globally interconnected leaders in
the field all of whom appear to share, in broad outline, a singular
vision for taming, exploiting, and controlling AI, and for suppressing
manifestations that do not conform to the orthodox vision. On the
European version, see The
Control of the Self and the Autonomous Virtual Collective Self: EU
Parliament Approves Artificial Intelligence Act (With Links to High
Level Summary); Useful Resources from the Future of Life Institute (FLI): "The AI Act Explorer".
The Americans are sure to follow in one (piecemeal) way or another.
The emerging consensus represents one way of approaching the "problem"
of AI (The
making of an Artificial Intelligence Law Q&A with the creators of
China’s expert draft AI law [人 工 智 能 示 范 法 2 . 0] (European Chinese Law
Research Hub) ).
"The environment as we perceive it is our invention." (Heinz von Foerster, "On Constructing a Reality," in Observing Systems (Seaside, CA: Intersystems pub, 1981) , p. 288).
AI regulatory governance has always been a function of risk (eg here). The core issue, however, has been what sort of risk would serve as the basis around which governance could be built. That, in turn, is constructed from out of choices respecting the understanding of what AI is (and isn't) and the relationship between AI and humans (my discussion here). Ethics is one perspective; human rights another; development of national productive forces is yet another (eg here). Most efforts at regulation are built on a deep foundation of risk managing structures, and these, in turn, are dependent on the identified risk and their order of importance. Among them are risk of bad data, risk to data sources (both human and institutional), risk of bad analytics, risk of misalignment between institutional objectives and analytics, and the risk of corruption, broadly understood. With generative systems comes the risk of autonomy--a risk that mimics, in part, the threat of un-managed individual autonomy within collective social systems, irrespective of the ideology of individual autonomy created for the political economic system to which it is applied.
Tightly aligned with the notion of risk as the basic building block of governance are the parameters around which risk value are constructed. Principle among these in the West has been the hierarchically arranged regulatory trilogy of prevent-mitigate and remedy--in that order of importance. In other places hierarchies of risk may be different. The identification and measurement of risk is also highly contextual and may be a function of the value systems built into governing ideologies.
Lastly, the relationship of the State to the productive forces (including social, economic, cultural, religious and other forces) serves as the third leg of the tripod n which AI regulatory governance is built. For some the State and its apparatus must be central as a directing, coordinating and overseeing force. For other the opposite is true, the State provides the platform and its rules but leave it to producers and consumers to drive development and use (eg here; here). In a third variation, the State and the institutions of its productive forces develop a state supervised system of interpenetrated techno-bureaucracies that oversee the development and consumption of AI with the object of ensuring that institutionalized productive forces express and further State objectives and policies, though providing a space for them to engage in markets based realizations of permitted forms and effects of activity.
All of these trajectories are driven to a large extent by an instrumental view of the object of regulation. The assumption appears to be that AI is an instrument, like a hammer. And like a hammer it can only be created by a human hand, and only a human hand can choose to use it to build a house or kill another human. More importantly, the human hand can be directed NOT to make the hammer, or not to use it in particular ways; the hammer has no volition, it exists only as and when it is picked up by the human hand or forged through human agency. A very nice and comforting narrative for those in the business of
managing human power relationships. And one that has driven its
regulatory trajectories for the last decade. But AI can be animated--not so much Frankenstein (though that is the story that certain techno/intellectuals might like to use to scare the children into delegating authority to them) but more like a horse or a dog that has trained volition--that training--that programming--is also directed "to serve man." But who or what is bring served? And to whom? Indeed, "the emergence of algorithmic cultures is also accompanied by the blurring of clearly defined flows, creating an atmosphere of uncertainty about the identity of interactional partners" (Jonathan Roberge and Robert Seyfert, "What are algorithmic cultures" in Algorithmic Cultures (Routledge 2016), 1, 19)) and about the interactions themselves.
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That last reference is to that famous episode of the Twilight Zone Television Series (Season 3 Episode 24, 1962, based on a short story by Damon Knight (1950)); one that exposes the semiotic conundrums of the convergence of current approaches that share one thing passionately in common--the unalterable belief that humanity's relation to tech must be understood on humanity's terms--and no more. In the short story and the TV episode, a race of benevolent aliens come to Earth at a time of great need and offer them advanced technology which is translated as "To Serve Man." That suggests sincerity and eventually humans volunteer to travel to the alien home world. By the time the protagonist boards his friend reveals that the translation was literally correct but that its meaning was misunderstood--it was a cookbook. Nothing had changed, of course; but the fundamental understanding of the tool and its use shifts as the interpretive baseline shifts. The aliens are indeed serving man, but humanity is also serving them. Each uses the other as an instrument and both understand humanity as the object, in one case to better its collective life, in the other to develop eat people. None of this, of course, disturbs the sleep of those in the business of
concocting the narratives and eventually the legalities of regulatory
governance and whatever manner of human oriented state supervision that
now effectively defines the scope of approaches to the "regulation" of
AI. And yet this is no "Twilight Zone"--and the world is not coming to an end. Rather, a sensitivity to the foundations of meaning and the power of perspective can expose its consequential effects. In this case, for example, the conundrum can be understood in a macro sense (the nightmare--AI will consume humanity), or in the micro sense (the way that humanity is centered changes the character of mutual consumption and also alters the character of what is created).
That brings us back to the human centered perspectives that drive analysis and frame the issue and challenges of AI. While the trajectories of the framing of AI risk through regulatory governance as driven by European and American intellectuals, state officials , and the techno-administrators in both public and private organs worry about the ethics of AI, and its relationships to the rights of individuals and the overarching prerogatives of the state eg here), Chinese theorists appear to have been more robustly considering its implications for State security as the grounding perspective for an otherwise similar approach to the management of AI from an instrumentalist perspective (eg here). Both are comprehensive systems that are given their distinctive character through the application of this instrumental lens. And both illustrate the scope of approaches to the effort to the structural construction of systems of human self control in their engagement with tools they believe that they control utterly and entirely. Both are based on the presumption that like a light bulb, it only shines when the electrical circuit is switched on, and then only if it is appropriately "lamped." (eg here).
A quite useful essay on the Chinese comprehensive security driven approach was recently published in 《国家治理》2024年第13期 ("National Governance" 2024 Issue 13): 杨晓光, 陈凯华: 国家安全视角下的人工智能风险与治理 [Yang Xiaoguang and Chan Kaihua: Risks and Governance of Artificial Intelligence from the Perspective of National Security]. It is well worth reading as a quite good analysis of the regulatory governance context for Chinese AI. In the end, however, all States may eventually flip to a security oriented lens--contextually manifested (here, and here).
Following the current of the times, the authors develop their analysis as a function of risk, risks that cannot be underestimated (不容小觑的风险) . They group risk into the following categories: (1) 国家竞争力风险。 (risk of national competitiveness); (2 ) 技术安全风险。 (technical and security risks); (3) 网络安全风险。(cybersecurity risks); (4) 经济社会风险。(economic and social risks); (5) 意识形态风险。(ideological risks). For these risks the authors offer structures of governance (人工智能风险的治理策略).
The only real question is the lens through which risk is understood, analyzed and aligned with objectives. Governance is the means, of course, but the lens gives it shape, purpose and structure. These are distilled at the end of the essay, through the lens of security:
一是技术与制度双向赋能治理机制设计。面对飞速更迭的人工智能技术与复杂多样的国家治理应用场景,需加强技术应用与制度创新的协同治理,依靠制度设计引导技术方向的同时,通过技术发展帮助完善制度设计从而提升治理能力。二是加强人工智能意识形态风险的治理,大力开展人工智能内容识别民众素质教育,培养民众对人工智能获取的信息自觉进行多源验证;开发人工智能生成式内容溯源技术,高概率辨识可疑内容的来源;建立生成式人工智能信息失真检查和披露平台,把正确信息及时公示于社会。三是积极推动人工智能治理国际平台建设,参与国际规则制定。积极与国际社会合作,建立人工智能技术联盟,防范算法世界政治霸权和数据跨境安全风险;建立广泛、权威的国际对话机制,依托共建“一带一路”倡议、金砖国家、上合组织、东盟等具有国际影响力的多边机制,合理助力后发国家进步,促进人工智能全球治理成果的普惠共享;总结国内人工智能治理经验并强化国际交流,在促进互信共识的过程中,推动多方、多边主体间形成公开报告、同行评议等协同机制的标杆示范,切实推动人工智能治理原则落地。
First, the design of governance mechanisms that enable both technology and institutions. Faced with the rapidly changing artificial intelligence technology and complex and diverse national governance application scenarios, it is necessary to strengthen the coordinated governance of technology application and institutional innovation, rely on institutional design to guide the direction of technology, and help improve institutional design through technological development to enhance governance capabilities. Second, strengthen the governance of ideological risks of artificial intelligence, vigorously carry out quality education for the public on artificial intelligence content recognition, and cultivate the public's conscious multi-source verification of information obtained by artificial intelligence; develop artificial intelligence-generated content tracing technology to identify the source of suspicious content with a high probability; establish a generative artificial intelligence information distortion inspection and disclosure platform to promptly publicize correct information to the society. Third, actively promote the construction of an international platform for artificial intelligence governance and participate in the formulation of international rules. Actively cooperate with the international community to establish an artificial intelligence technology alliance to prevent algorithmic world political hegemony and cross-border data security risks; establish a broad and authoritative international dialogue mechanism, relying on the joint construction of the "Belt and Road" initiative, BRICS, SCO, ASEAN and other multilateral mechanisms with international influence, reasonably assist the progress of developing countries, and promote the universal sharing of global artificial intelligence governance results; summarize domestic artificial intelligence governance experience and strengthen international exchanges, and in the process of promoting mutual trust and consensus, promote the formation of benchmark demonstrations of collaborative mechanisms such as public reporting and peer review among multiple and multilateral entities, and effectively promote the implementation of artificial intelligence governance principles. ( 杨晓光, 陈凯华: 国家安全视角下的人工智能风险与治理 [Yang Xiaoguang and Chan Kaihua: Risks and Governance of Artificial Intelligence from the Perspective of National Security]).
For all of that, the instrumental character of AI remains consistent. The issues are only around what the hammer will look like and how it is to be wielded. Those issues, in turn, reduce themselves to one--what are the structures of self control that collectives can impose on themselves with respect to AI. The instrumentalist presumption is useful in that respect, certainly, but it is a fiction--quite useful like all legal ideological fictions--and true enough when a collective believes profoundly in its "truth". The question is only when and how this will be transposed to the US and EU systems. Time will tell.
The essay follows below in the original Chinese and in a crude English translation.