ESCAPING AI PRODUCTIVITY TRAPS: A LEADERSHIP PLAYBOOK FOR ARTIFICIAL INTEGRITY

Leader to Leader Pub Date : 2026-03-01 Epub Date: 2026-02-11 DOI:10.1002/ltl.70030
Hamilton Mann
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Abstract

The author is Group Vice President at Thales, a lecturer at INSEAD and HEC Paris, originator of the concept of “Artificial Integrity,” and an AI researcher. He ebelieves that “five traps neutralize AI's productivity promise.” These traps, in his words, are Trap 1: The sum-of-tasks fallacy. Trap 2: AI-mediated Pseudo Work. Trap 3: Local wins and systematic bottlenecks. Trap 4: Bolt-on adoption breaks. Trap 5: Ignoring intangible inputs. He further writes that “the focus should shift from the narrow task a system performs at a particular place and time within specific teams to enhancing the organization's human capital while safeguarding its integrity.” He weaves in his concept of Artificial Integrity, observing that “for AI-enabled work, Artificial Integrity means AI systems that (1) states purpose, context, and limits for each use, (2) protects human capacities and values where they drive outcomes, (3) measures system flow and decision quality, not activity volume; and (4) aligns incentives and governance so speed compounds into value without eroding the social fabric.” He concludes that “as a north star for envisioning AI systems’ capabilities, Artificial Integrity is what keeps efficiency focused on meaningful outcomes, not on volume or speed for their own sake.”

逃离人工智能生产力陷阱:人工诚信的领导力剧本
作者是泰雷兹集团副总裁、欧洲工商管理学院(INSEAD)和巴黎高等商学院(HEC)讲师、“人工完整性”(Artificial Integrity)概念的创始人、人工智能(AI)研究员。他认为,“五大陷阱抵消了人工智能的生产力承诺。”用他的话来说,这些陷阱就是陷阱1:任务总和谬论。陷阱2:ai介导的伪工作。陷阱3:局部胜利和系统瓶颈。陷阱4:栓接式收养中断。陷阱5:忽视无形的投入。他进一步写道:“重点应该从系统在特定地点和时间在特定团队中执行的狭隘任务转移到在维护组织完整性的同时增强组织的人力资本。”他将人工完整性的概念融入其中,观察到“对于支持人工智能的工作,人工完整性意味着人工智能系统(1)阐明每次使用的目的、背景和限制,(2)在驱动结果的地方保护人类的能力和价值,(3)衡量系统流程和决策质量,而不是活动量;(4)将激励和治理结合起来,在不侵蚀社会结构的情况下加速化合物的价值。”他总结道:“作为设想人工智能系统能力的北极星,人工完整性使效率集中在有意义的结果上,而不是为了数量或速度。”
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