4.结论
如果阿西莫夫的机器人学三定律能够避免或解决机器智能方面的所有伦理困境,他的文学生涯恐怕就不会那么长久。事实上,在引入三定律的故事(Asimov,1942)中,一个机器人就因为第二定律和第三定律之间的冲突陷入了瘫痪;最终只有在人类让自身陷入险境继而触发第一定律之后,问题才得以解决。(*这个机器人起初试图遵守一项措辞含糊的指令,而执行该指令势必导致其自身毁灭,结果它陷入了一种“平衡状态”(文中引用了吉尔伯特与沙利文的表述,但没有解释缘由),直到需要拯救人类生命的时刻来临,它才摆脱了这一状态。)
当机器人被迫在两害相权取其轻的情况下做抉择时,一条“不得伤害人类”的笼统规则显然是不够的。后来阿西莫夫自己又添加了一条“第零定律”,该定律规定机器人的最高职责是维护全人类的利益。在他的最后一部小说(1986年出版)里,一个机器人被问及如何判断什么是对全人类有害的。机器人答道:“确实,先生。从理论上讲,第零定律是我们问题的答案。但在实践中,我们永远无法做出决定。”
人们常常夸大对应对人工智能的新规则的需求。例如瑞安·阿博特(Ryan Abbott,2020,pp.2-4)认为,监管变革的指导原则应该是人工智能法律中立,这意味着法律绝不应区别对待人类行为和人工智能行为。尽管这一原则看似简单直接,但其全部影响很快就被放弃了:人们并不追求人工智能系统具备人格,也不把人工智能的标准(即阿博特书中所称的“理性机器人”)应用于人类行为。实际上,阿博特的论文归根结底是对人工智能活动的不同领域进行个案分析,以确定特定领域是否需要做出改变。
这是一种相当明智的方法,但还需要一些普遍适用的新规则,主要是为了确保能够实现本文开头提及的前两项原则:人类控制和透明度。人类控制要求对可开发的人工智能系统类型施加限制。预防原则为思考这些风险提供了一种思路,不过,在致命性自动化武器这类道德清晰的案例中,显然可以做出最明确的决策。公共部门需要更细致的限制措施,在这个领域,限制公职人员将决策外包给人工智能系统的权限比约束人工智能系统的行为更重要。至于透明度问题,政府官员的可问责还要求限制不透明程序的使用。除此之外,影响评估(impact assessment)、审计和设立人工智能监察员等措施可以减轻部分危害,有助于确保其他问题可追溯并归责于可被问责的法人(legal person)。
随着人工智能日益复杂和普及,以及与人工智能系统相关的危害变得越发常见,对人工智能施加限制的需求将会增加。本文试图将讨论从抽象思考哪些规则可以约束或控制人工智能的行为转向更实际的挑战,即监管机构为何、何时以及如何选择从伦理层面转向法律层面的监管。这些法律的具体性质会因司法辖区的不同而有所差异。唯一可以肯定的是,相关法律的数量很可能不止三条。■
(颜超凡译)
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