Artificial Intelligence and Human-Robot Teaming: Challenges and Design Considerations

Artificial Intelligence and Human-Robot Teaming: Challenges and Design Considerations

Xuefei (Nancy) Deng
DOI: 10.4018/978-1-7998-2355-1.ch005
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Abstract

Artificial Intelligence or AI is the theory and development of computer systems that can think and act humanly and rationally. AI is gradually transforming our work and life. Along with the increasing presence of robots in our lives arises the fear that AI may take away human jobs. Debates or worries notwithstanding, AI and robots are increasingly brought into the teams of human workers, but our understanding of this emerging human-robot teaming phenomenon remains limited. This chapter presents a brief overview of AI and discusses the relationship between AI and knowledge management. Moreover, it focuses on understanding key issues arising in the collaboration between human and intelligent agents (i.e. robots) in the team setting, and coping strategies and design considerations. This chapter also discusses the value sensitive design framework as a useful tool for incorporating the values of agent transparency and team trust into the design of human-robotic systems. The chapter concludes with the new perspective of augmented intelligence and promising avenues for future research.
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Introduction

Artificial Intelligence or AI is the theory and development of computer systems that can think and act humanly and rationally (Russell et al., 2003). AI is gradually transforming our work and life. In businesses, AI has enhanced companies’ interactions with their customers and affected the delivery of products and services. For example, intelligent agents such as Siri, Alexa, or Google Assistant have become a reliable source for mobile device users to locate information and purchase goods. In healthcare, AI assists radiologists with image interpretation by bringing the relevant information out of the electronic medical record and presenting it to them in a meaningful way to better inform their clinical judgment. Moreover, robots have been found to help or support humans in carrying daily, routine activities, from mopping floors to serving as an information guide. Widely used in a variety of settings, those robots play a supporting role in our daily activities, and examples of such robot assistants include rehabilitation robots, wheelchair robots and walking robots, companion robots, and educational robots that are found in hospitals, homes and schools.

According to the Oxford English Dictionary, a robot is “a machine capable of carrying out a complex series of actions automatically”. Along with the increasing presence of robots in our lives arises the fear that AI and robots may take away human workers’ jobs. Heated discussions have been reported on news media, which cover topics from the possibility of robot replacing human workers to the types of jobs (such as the job with high degree of automation) that are at risk of being replaced (e.g., Lepore, 2019; O’Brien, 2019). In contrast to the fear, a more positive view has been expressed, that is, robots can assist, not replace, human workers, as shown in the teamwork by human and robots. For example, a Forbes article explains why human workers should not worry about losing their jobs to robots (Arnold, 2018). One key point is that technology won’t place the need for creative thinking, problem-solving, leadership, teamwork and initiative and humans can leverage technology to provide a better world for all of us.

Debates or worries notwithstanding, there is evidence that robots are increasing brought into the teams of human workers to work together and accomplish common goals. As highlighted in the Forbes article, humans and technology must work together, with humans in control and the technology providing what it is programmed to provide (Arnold, 2018). For instance, in search and rescue operations, human supervises robots such that human gives robot instructions to conduct search and remove heavy objects to rescue those in danger. Similarly, in military and police operations, humans act as commanders, and direct robots to complete tasks such as information acquisition and bomb demolition. Such human-robot teaming has been deployed in dangerous missions such as detonating a bomb to save lives. In this case, the bomb disposal robots are described as tracked, human-controlled robots, with an ‘arm’ that can manipulate suspect devices (Allison, 2016).

As the practice of human-agent teaming increases, our understanding of this emerging, complex phenomenon remains limited. Therefore, this article intends to present a brief overview of AI studies on the collaboration of human and intelligent agents (i.e. robots) in the team setting. The focus is on understanding not just key issues arising in the teamwork of human and robots, but also coping strategies and design considerations. The relationship between AI and knowledge management is also discussed. AI and human-robot interaction are fields with a wealth of research. This chapter does not intend to provide a comprehensive review of the literature, nor does it intend to discuss the major aspects of the research stream ranging from technical architecture of AI to the performance of the human-robot teams. Rather, the main objective of this chapter is to provide a glimpse into AI and robots, knowledge management, and the collaboration in human-robot teaming.

Key Terms in this Chapter

Augmented Intelligence: It is a new perspective to look at the artificial intelligence, social computing, machine learning, big data, data mining, and related areas. It emphasizes that the core of this scientific inquiry is humanity, not machines; its ultimate goal is to augment human, not to replace human.

Robot: A robot is an autonomous, intelligent agent such that a robot makes decisions and solves problems on its own.

Knowledge Management Systems (KMS): It refers to a class of information systems that is developed and deployed to facilitate the storage, sharing, and application of knowledge to support organizational activities and objectives.

Intelligent Agent: An intelligent agent embeds artificial intelligence, such an agent is expected to possess the following characteristics: autonomy, observation of the environment (through some forms of sensors), action upon an environment (through some forms of actuators), and direction of its activity toward achieving certain goals.

Haptic Turing Test: The Turing test was proposed by A. Turning (1950) AU8: The in-text citation "Turning (1950)" is not in the reference list. Please correct the citation, add the reference to the list, or delete the citation. for verbal communication between a human and a non-human agent. A non-human agent “passes” the test if it is able to simulate a human sufficiently well to deceive a human interlocutor.

Human-Robot Teaming: Also called “human-robot teaming,” it refers to the collaboration between human and robot to achieve a common goal in a team setting. During such a teamwork arrangement, both human and robot have interdependent roles but work together to accomplish a task that requires interactions between human and robotic team members.

Knowledge Management (KM): It is defined as the process of selectively applying knowledge from previous experiences of decision making to current and future decision-making activities with the express purpose of improving the organization’s effectiveness.

Artificial Intelligence (AI): It refers to the theory and development of computer systems that can think and act humanly and rationally. AI can be viewed from multiple aspects, including technical, economic, social and ethical aspects.

Value Sensitive Design (VSD): It is a value-oriented design methodology first developed by Friedman and colleagues and commonly adopted by the research community of human–computer interaction. The VSD framework seeks to understand how human values (e.g., welfare, accountability, autonomy, freedom from bias) can be accounted for in the design of computer technologies.

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