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The writer is professor of law at Penn State
本文作者是宾夕法尼亚州立大学法学教授
We don’t know the future, nor how artificial intelligence will affect it. Some believe AI will lead to explosive economic growth, others are convinced it will immiserate all but a select few, while some aver that its economic impact will be marginal.
我们既无法预知未来，也无法预知人工智能(AI)将如何影响它。有人认为AI会带来爆炸性的经济增长，也有人坚信它会让除精选出来的少数人之外的所有人陷入贫困，还有人断言其经济影响将微乎其微。
So how do legislators do their job under such uncertainty? Currently they don’t. They have abrogated their responsibilities to promote the health, safety and welfare of voters through inaction, adopting a wait-and-see approach. If they delay too long, the new technology could have already harmed society and generated new billionaires ready to capture future regulatory processes. Yet regulating too early also has risks, inadvertently hampering innovation.
那么，立法者如何在这种不确定性下履职？目前他们没有行动。他们通过不作为、采取观望态度，放弃了他们促进选民健康、安全与福祉的职责。如果拖延得太久，这一新技术可能会已经对社会造成伤害，并催生出若干准备主导未来监管流程的新亿万富豪。然而，过早进行监管也存在风险，可能不经意地抑制创新。
There is a better way to proceed that allows us to respond proactively to uncertainty. We need adaptive AI laws that detail how to react to each possible future harm or benefit but that don’t kick in until we see how AI is transforming society. Such adaptive AI laws would be passed now and take effect automatically when benchmarks are met to hedge social risks and distribute benefits.
有一种更好的推进方式，能让我们主动地应对不确定性。我们需要具有适应性的AI法律，详细规定如何应对每一种可能的未来危害或收益，但要等到我们看清楚AI如何改变社会时生效。这类适应性AI法律应当现在通过，并在满足既定基准时自动生效，以对冲社会风险并分配福利。
Adaptive AI laws could take many forms and borrow tools from elsewhere, such as the decision trees used in machine learning. For example, politicians can currently pass one set of laws that take effect if job losses mount, triggering policies like supplemental unemployment benefits and increased taxes on the rich. Another set of acts could be triggered with job growth, such as improved sick leave and fewer corporate subsidies. Benefits and taxes could rise using sliding scales tied to job losses or income inequality. Some responses, such as instituting a universal wage, could activate under numerous scenarios if economic inequality got too bad or if economic growth exploded.
适应性AI法律可以采取多种形式，并借鉴其他领域的工具，例如机器学习中使用的决策树。比如，政界人士可以现在通过一套法律，并在失业加剧时生效，从而触发增补失业救济、对富人加税等政策。另一套法律则可在就业增长时生效，例如增加病假、减少对企业的补贴。福利与税收还可以依据失业水平或收入不平等程度按比例增减。一些应对措施——如实行全民基本收入——则可在多种情形下启动，例如当经济不平等恶化到一定程度或当经济爆发式增长时。
Such adaptive AI legislation could be applied to a range of other fields. It was initially unknown how harmful social media would be for children. If it emerges that AI has similarly negative effects, adaptive laws could restrict children’s access to it. If AI instead advances mental health goals, more public resources could be allocated.
这种适应性AI立法可以应用于其他诸多领域。社交媒体对儿童的危害起初并不为人所知。若事实表明AI也有类似的负面影响，适应性法律可以限制儿童接触AI。相反，如果AI有助于促进心理健康目标，则应该投入更多公共资源。
It’s easy to assume that AI will enhance our learning and expertise, yet a recent study showed that oncologists were 20 per cent worse at detecting precancerous growths on their own after having relied on AI as a detection aid. Adaptive AI regulation could grapple with the uncertain effects of AI on education across disciplines and ages.
我们很容易认为AI会提升我们的学习和专业能力，但一项最新研究显示，在依赖AI作为检测辅助后，肿瘤科医生发现癌前病灶的表现反而下降了20%。适应性AI监管可以应对AI对不同学科和不同年龄阶段教育的不确定影响。
Many benchmarks for triggering the activation of an adaptive law could draw from reliable governmental data, such as on income distributions, educational attainment and lifespans. Triggering measurements for other topics, such as mental health, would be more complex to gauge and would benefit from bipartisan legislative guidance and monitoring from designated agencies. If partisan disagreement surfaces about whether a triggering event has occurred, courts can fulfil their established role as legal interpreters.
许多用于触发适应性法律生效的基准可以借鉴可靠的政府数据，例如收入分配、受教育程度和预期寿命等。判断针对其他议题（如心理健康）的触发标准将更复杂，更需要两党立法指引以及指定机构的监督。如果在某一触发事件是否已经发生上出现党派分歧，法院可以履行其作为法律解释者的已确定角色。
Adaptive AI laws would provide three main benefits. First, they would empower lawmakers to act now to avoid future problems, to be proactive instead of reactive. This would occur without sacrificing flexibility, because legislators could always change the adaptive regulation in response to technological developments or social change. Second, the structure of adaptive regulation would encourage lawmakers to think more deeply about the different possible paths that AI could take, which one hopes would lead to better policies. Third, adaptive AI regulations would provide a more stable regulatory framework for AI labs, creating legal clarity by informing labs how laws will automatically change depending on their actions.
适应性AI法律将带来三方面益处。首先，它能让立法者现在就采取行动以避免未来问题，变被动为主动。这不会牺牲灵活性，因为立法者可随技术进步或社会变化随时调整这类适应性监管。其次，适应性监管架构会促使立法者更深入思考AI可能走的不同路径，从而有望制定出更优的政策。第三，适应性AI监管将为AI实验室提供更稳定的监管框架，通过明确法律将如何随其实践自动调整，提升法律明确性。
This wouldn’t be the first time that legislatures adopted laws that only activate under certain scenarios. For example, states have passed trigger laws contingent on developments related to abortion, Medicaid and rent control.
这将不是立法机关第一次通过只在特定情形下生效的法律。例如，一些州已通过“触发法”，其生效取决于与堕胎、医疗补助计划和租金管制相关的进展。
AI labs have already committed to voluntary if-then commitments, pledging to enhance safety measures once AI models have a particular capability. Yet these commitments are nonbinding, not universal and only touch on safety considerations, not how AI will affect society more broadly.
多家AI实验室已作出自愿的如果则承诺：一旦其模型具备特定能力，就将加强安全措施。然而，这些承诺不具约束力、并非普遍适用，而且只涉及安全层面，而未考虑AI更广泛的社会影响。
We can reasonably imagine the different effects AI might have on society, but we can’t predict which path it will take. Adaptive AI laws would allow us to think through how to regulate the technology now without delaying until it’s too late or hurting innovation through having the regulations kick in immediately. To manage the potential AI revolution, law needs one of its own.
我们可以合理想象AI可能对社会产生的不同影响，但我们无法预测它推进的路径。适应性AI法律能让我们现在就系统思考如何监管这项技术，而不是等到为时已晚，或因监管立刻生效而扼杀创新。要应对潜在的AI革命，法律也需要一场自己的革命。