FW-HTF-P/Collaborative Research: Exploring Tools to Help Workers and Organizations Adapt to AI-enabled Robots

FW-HTF-P/协作研究：探索帮助工人和组织适应人工智能机器人的工具

• 批准号: 1928472
• 负责人: Erik Brynjolfsson
• 金额: $ 7.72万
• 依托单位: Massachusetts Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-10-01 至 2021-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1928472&HistoricalAwards=false
• 关键词: FW; HTF; Collaborative; Research; Exploring

This project will promote exploration of scalable tools to aid workers and organizations adapt to artificially-intelligent robots. In a sharp departure from current robotic systems that have to be programmed for a single manipulation task in a very tightly constrained set of conditions, venture-funded firms are designing and beginning to test qualitatively new robotic technologies that promise to flexibly automate entire classes of embodied tasks in widely divergent conditions. In this likely future, robots will adapt as readily to new repetitive manual tasks as a modern microprocessor adapts to new computational tasks. Such "learning" robots would clearly have profound implications for workers and organizations, but previous research on automation offers only limited guidance on how they will adapt. The researchers have recently begun a nationwide, four-year field study that will identify edge cases in which organizations and low-skill workers achieve unlikely yet systematic success, given the introduction of this disruptive technology. This will allow deriving design constraints for potential solutions from grounded theory, centering on the hard-won, demonstrably successful innovations of a suitably-diverse pool of informants. While existing research stands to unveil the mechanisms behind rare, in vivo learning successes to the world, this FW-HTF-P (Future of Work at the Human-Technology Frontier - Planning) award will assemble a world-class team of researchers who are committed to trying to expand and capitalize upon these mechanisms via new tools. This research has high-impact potential for organizations, lower-skilled workers and policy makers on how to expand and enrich work involving increasingly intelligent systems in the 21st century.With AI in robotics as the technology, humans collaborating with robots as the workers, and organizations employing both the robots and the workers as the context of work, the team of researchers will specifically contact and convene a group of top experts in diverse technical domains including social media, massive open online courseware, crowdsourced knowledge repositories, peer assessment and coaching, user experience design and platforms for on-demand labor, crowdsourcing and innovation challenge execution. Beyond these technical disciplines, the researchers will invite policymakers and technologists, as the pathways to local success will likely be deeply intertwined with legal and commercialization processes. The researchers will begin by sharing very preliminary findings, research questions and objectives from the current study with a select group of such researchers who may have interest in a potential collaboration. The researchers will then extend formal invitations to a workshop to no more than ten potential collaborators. This workshop will be one day in length and will be described as an opportunity to explore and decide upon potential collaborative opportunities related to helping workers and organizations adapt more productively to general-purpose robots. The researchers will explore potentially new organizational theories that take perspectives such as: (a) accounting for success as a learning problem in which robots, workers and organizations learn from each other; (b) the character of learning infrastructures evident in various practices for adapting to learning machines acting as co-workers; (c) how the organization of such learning practices impacts skill changes, role transformations, as well as workers and organizations. The researchers will then solicit participants' input and commitment for tools to scale the successes inherent in the findings and select the tool likely to have the greatest benefit for the most Americans. The researchers will then jointly craft an FW-HTF-R (Future of Work at the Human-Technology Frontier - Research) proposal with interested collaborators that reflects a rigorous test of this tool in real-world settings. The ultimate goal of this project is to develop the necessary research personnel, research infrastructure, and foundational work to expand the opportunities for studying future technology, future workers, and future work at the level of a FW-HTF full research proposal.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该项目将促进可扩展工具的探索，以帮助工人和组织适应人工智能机器人。与目前的机器人系统截然不同的是，目前的机器人系统必须在非常严格的一组条件下为单一的操作任务进行编程，风险投资公司正在设计并开始测试质量上的新机器人技术，这些技术承诺在非常不同的条件下灵活地自动完成整个类别的具体任务。在这个可能的未来，机器人将像现代微处理器适应新的计算任务一样容易地适应新的重复性手工任务。这种“学习”机器人显然将对工人和组织产生深远的影响，但之前关于自动化的研究只提供了有限的指导，说明它们将如何适应。研究人员最近开始了一项为期四年的全国性实地研究，将确定一些边缘案例，在这些案例中，考虑到这种颠覆性技术的引入，组织和低技能员工取得了不太可能但系统性的成功。这将允许根据扎根的理论，以适当多样化的线人池来之不易、明显成功的创新为中心，推导出潜在解决方案的设计约束。虽然现有的研究将向世界揭示罕见的活体学习成功背后的机制，但FW-HTF-P(人类-技术前沿-规划的未来工作)奖将汇集一支世界级的研究团队，他们致力于通过新工具扩展和利用这些机制。这项研究对组织、低技能工人和政策制定者如何在21世纪扩大和丰富涉及越来越智能的系统的工作具有很高的影响潜力。以机器人技术中的人工智能为技术，以人类与机器人合作的人为工人，以雇用机器人和工人的组织为工作背景，研究团队将具体联系和召集一批不同技术领域的顶尖专家，包括社交媒体、海量开放在线课件、众包知识库、同行评估和指导、用户体验设计和按需劳动力、众包和创新挑战执行平台。除了这些技术学科之外，研究人员还将邀请政策制定者和技术专家，因为当地成功的道路可能会与法律和商业化过程深度交织在一起。研究人员将首先与可能对潜在合作感兴趣的一组这样的研究人员分享当前研究的非常初步的发现、研究问题和目标。然后，研究人员将向不超过10名潜在的合作者发出正式的研讨会邀请。该研讨会为期一天，将被描述为探索和决定与帮助工人和组织更有效地适应通用机器人有关的潜在合作机会的机会。研究人员将探索潜在的新组织理论，其视角如下：(A)将成功视为机器人、工人和组织相互学习的学习问题；(B)在适应作为同事的学习机器的各种实践中明显体现的学习基础设施的特征；(C)这种学习实践的组织如何影响技能变化、角色转换以及工人和组织。然后，研究人员将征求参与者对工具的投入和承诺，以衡量研究结果所固有的成功，并选择可能对大多数美国人具有最大好处的工具。然后，研究人员将与感兴趣的合作者共同起草一份FW-HTF-R(人类-技术前沿-研究的未来工作)提案，反映出该工具在现实世界中的严格测试。该项目的最终目标是发展必要的研究人员、研究基础设施和基础工作，以在FW-HTF全面研究计划的层面上扩大研究未来技术、未来工人和未来工作的机会。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。