1 Independent Writer and Researcher, Technology , Society & Democracy, Toronto, Canada .
2 School of Biotechnology, Amrita Vishwa Vidyapeetham (Amrita University) , Kerala, India .
OMICS. 2018 Jan;22(1):65-76. doi: 10.1089/omi.2017.0194. Epub 2018 Jan 2.
Driverless cars with artificial intelligence (AI) and automated supermarkets run by collaborative robots (cobots) working without human supervision have sparked off new debates: what will be the impacts of extreme automation, turbocharged by the Internet of Things (IoT), AI, and the Industry 4.0, on Big Data and omics implementation science? The IoT builds on (1) broadband wireless internet connectivity, (2) miniaturized sensors embedded in animate and inanimate objects ranging from the house cat to the milk carton in your smart fridge, and (3) AI and cobots making sense of Big Data collected by sensors. Industry 4.0 is a high-tech strategy for manufacturing automation that employs the IoT, thus creating the Smart Factory. Extreme automation until "everything is connected to everything else" poses, however, vulnerabilities that have been little considered to date. First, highly integrated systems are vulnerable to systemic risks such as total network collapse in the event of failure of one of its parts, for example, by hacking or Internet viruses that can fully invade integrated systems. Second, extreme connectivity creates new social and political power structures. If left unchecked, they might lead to authoritarian governance by one person in total control of network power, directly or through her/his connected surrogates. We propose Industry 5.0 that can democratize knowledge coproduction from Big Data, building on the new concept of symmetrical innovation. Industry 5.0 utilizes IoT, but differs from predecessor automation systems by having three-dimensional (3D) symmetry in innovation ecosystem design: (1) a built-in safe exit strategy in case of demise of hyperconnected entrenched digital knowledge networks. Importantly, such safe exists are orthogonal-in that they allow "digital detox" by employing pathways unrelated/unaffected by automated networks, for example, electronic patient records versus material/article trails on vital medical information; (2) equal emphasis on both acceleration and deceleration of innovation if diminishing returns become apparent; and (3) next generation social science and humanities (SSH) research for global governance of emerging technologies: "Post-ELSI Technology Evaluation Research" (PETER). Importantly, PETER considers the technology opportunity costs, ethics, ethics-of-ethics, framings (epistemology), independence, and reflexivity of SSH research in technology policymaking. Industry 5.0 is poised to harness extreme automation and Big Data with safety, innovative technology policy, and responsible implementation science, enabled by 3D symmetry in innovation ecosystem design.
自动驾驶汽车配备人工智能 (AI) 和协作机器人 (cobot) 管理的自动化超市在没有人工监督的情况下运行,引发了新的辩论:物联网 (IoT)、AI 和第四次工业革命所带来的极端自动化会对大数据和组学实施科学产生什么影响?物联网基于 (1) 宽带无线互联网连接、(2) 从家猫到智能冰箱中的牛奶纸盒等有生命和无生命物体中嵌入的微型传感器,以及 (3) AI 和 cobot 对传感器收集的大数据进行解释。工业 4.0 是一种制造自动化的高科技策略,它采用物联网,从而创建智能工厂。然而,到“一切都与其他一切相连”的极端自动化存在迄今为止尚未充分考虑到的漏洞。首先,高度集成的系统容易受到系统性风险的影响,例如,如果其部分部件(例如通过黑客攻击或互联网病毒)发生故障,整个网络可能会完全崩溃。其次,极端连接性创造了新的社会和政治权力结构。如果不加控制,它们可能导致一个人对网络权力的完全控制,直接或通过她/他的连接代理人实施独裁统治。我们提出了工业 5.0,可以从大数据的知识共创中实现民主化,这是基于对称创新的新概念。工业 5.0 利用物联网,但与前几代自动化系统不同,其创新生态系统设计具有三维 (3D) 对称性:(1) 在超连接的固有数字知识网络消亡的情况下,内置安全退出策略。重要的是,这样的安全出口是正交的——它们允许通过与自动化网络无关/不受其影响的途径进行“数字戒毒”,例如,电子病历与重要医疗信息的物质/文章记录;(2) 如果回报递减变得明显,则同等重视创新的加速和减速;(3) 下一代社会科学和人文学科 (SSH) 用于新兴技术的全球治理:“后 ELSI 技术评估研究”(PETER)。重要的是,PETER 考虑了技术机会成本、伦理、伦理伦理、框架(认识论)、SSH 研究在技术决策中的独立性和反思性。工业 5.0 有望利用安全、创新的技术政策和负责任的实施科学来利用极端自动化和大数据,这得益于创新生态系统设计中的三维对称性。