- Agenda and Results of Shonan "Future of Work" Workshop -
“Human-in-the-loop” is a term to denote approaches that combine the power of humans and machines to solve problems. In the future, all of our works will be a part of human-in-the-loop systems and performed by a hybrid workforce comprising humans and machines. Two key fuels there are bigdata and AI; bigdata allows us to find better divisions of labor among workers, and AI agents will play many roles in the systems, such as workers, knowledge extractors and coordinators. Today, human-in-the-loop has been not only a hot research topic but also proven to be effective in many real-world applications, such as production design, citizen science, online job markets, and natural disaster response.
However, there is still work to be done to adapt methodologies and transfer research results across disciplines and to real-world applications. One of the reasons is that researchers tend to work in silos and focus on a specific aspect of the human-in-the-loop systems. The universally accepted human-in-the-loop system architecture is yet to be agreed upon. It usually contains languages, data management systems, data processing systems, and worker-resource managers. We stress that applications are a major component of the human-in-the-loop system architecture, since otherwise the system would not match real-world applications thereby hindering usability.
We note that we should focus more on worker’s perspectives in our future of work. Most of the current “human-in-the-loop” researches have focused on the requesters’ perspectives such as the cost and time for solving their problems. We believe that the human-in-the-loop systems should be redefined as the “Future of Work” systems, that must deal with human factors for addressing ELSI (Ethical, Legal, Social Issues), such as fairness and transparency.
An important outstanding question in our future of work is how AI will influence future workforces – a common fear is that the machines will fully replace the need of human workers. Instead, we believe that a hybrid workforce will be the future of work comprising of a diverse group of AI-powered machines and humans working together and achieving superior results compared to what either group could accomplish working alone. Given the current state of progress of human-in-the-loop research, we believe that the time is ripe to embark on a fundamental approach to connect research results to real-world problems in human-in-the-loop Big Data and AI for our better future of work.
The main purpose of this NII Shonan meeting is to bring together researchers from the multidisciplinary fields of human-in-the-loop Big Data and AI as well as practitioners, to connect the latest research findings to real-world questions and examine its impact to future of work. The outputs are a series of reports and vision papers that show the state of the art of this area, and a coherent guideline in the future of work system research, including the reference architecture and research questions. We also establish a community formed by core members to develop (possible) future standards and platforms.
Crowdsourcing, human-in-the-loop big data lifecycles, human-AI-collaboration in work, human-AI-interface in human-in-the-loop work, AI for supporting humans in work, security and privacy in human-AI-collaboration, human factors, ELSI (ethical, legal and social is-sues) of human-in-the-loop systems.