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算法与未来工作。

Algorithms and the future of work.

机构信息

Office of the Director, National Institute for Occupational Safety and Health, Washington, District of Columbia, USA.

出版信息

Am J Ind Med. 2022 Dec;65(12):943-952. doi: 10.1002/ajim.23429. Epub 2022 Sep 20.

Abstract

An algorithm refers to a series of stepwise instructions used by a machine to perform a mathematical operation. In 1955, the term artificial intelligence (AI) was coined to indicate that a machine could be programmed to duplicate human intelligence. Even though that goal has not yet been reached, the use of sophisticated machine learning algorithms has moved us closer to that goal. While algorithm-enabled systems and devices will bring many benefits to occupational safety and health, this Commentary focuses on new sources of worker risk that algorithms present in the use of worker management systems, advanced sensor technologies, and robotic devices. A new "digital Taylorism" may erode worker autonomy, and lead to work intensification and psychosocial stress. The presence of large amounts of information on workers within algorithmic-enabled systems presents security and privacy risks. Reliance on indiscriminate data mining may reproduce forms of discrimination and lead to inequalities in hiring, retention, and termination. Workers interfacing with robots may face work intensification and job displacement, while injury in the course of employment by a robotic device is also possible. Algorithm governance strategies are discussed such as risk management practices, national and international laws and regulations, and emerging legal accountability proposals. Determining if an algorithm is safe for workplace use is rapidly becoming a challenge for manufacturers, programmers, employers, workers, and occupational safety and health practitioners. To achieve the benefits that algorithm-enabled systems and devices promise in the future of work, now is the time to study how to effectively manage their risks.

摘要

算法是机器执行数学运算时使用的一系列逐步指令。1955 年,“人工智能”(AI)一词被创造出来,以表明机器可以被编程来复制人类的智能。尽管这一目标尚未实现,但复杂的机器学习算法的使用使我们更接近这一目标。虽然算法支持的系统和设备将为职业安全和健康带来许多好处,但本评论重点关注算法在工人管理系统、先进传感器技术和机器人设备中的使用所带来的新的工人风险源。新的“数字泰勒主义”可能会侵蚀工人的自主权,并导致工作强度增加和心理社会压力。算法支持的系统中存在大量关于工人的信息,这带来了安全和隐私风险。对无差别的数据挖掘的依赖可能会再现歧视形式,并导致雇佣、留用和解雇方面的不平等。与机器人交互的工人可能面临工作强度增加和工作岗位流失的风险,而在使用机器人设备过程中受伤也是有可能的。本文讨论了算法治理策略,如风险管理实践、国家和国际法律法规以及新兴的法律责任建议。确定算法是否适合在工作场所使用,这对制造商、程序员、雇主、工人和职业安全与健康从业者来说,正迅速成为一个挑战。为了实现算法支持的系统和设备在未来工作中所承诺的好处,现在是时候研究如何有效地管理其风险了。

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