Selection Strategy of Effort Control: Allocation of Function to Manual Operator or Automation System

Selection Strategy of Effort Control: Allocation of Function to Manual Operator or Automation System Akihiro Maehigashi (mhigashi@cog.human.nagoya-u.ac.jp) Kazuhisa Miwa (miwa@is.nagoya-u.ac.jp) Hitoshi Terai (terai@is.nagoya-u.ac.jp) Graduate School of Information Science, Nagoya University, Japan Kazuaki Kojima (koj@aoni.waseda.jp ) Faculty of Human Sciences, Waseda University, Japan Junya Morita (j-morita@jaist.ac.jp) School of Knowledge Science, Japan Advanced Institute of Science and Technology, Japan Abstract In this study, we experimentally investigated the human selec- tion strategy of effort control, the control of function alloca- tion to either the manual operator or the automation system. We conducted two experiments using two types of tracking tasks. As a result, we found that people tended to perform ef- fort control based on manual-based selection, depending more on manual performance than system performance. Also, we confirmed that the tendency to use an automation system was related to the selection strategy. Keywords: Human-automation system interaction; Misuse; Disuse; Effort control. Introduction The development of technologies has rapidly increased in re- cent years. People have more opportunities to work with au- tomation systems as important resources for performing tasks (Hutchins, 1995). Lee and Moray (1994) stated that in the situation where people work with automation systems, they do not play only the role of a manual operator, but also play the role of a supervisory controller who monitors the whole system consisting of human and automation system from the meta viewpoint. A primary role of such a supervisory controller is effort control, the control of function allocation to either the manual operator or the automation system. In previous studies about human use of external resources, it was confirmed that people adaptively control such a function allocation to either internal processing or external processing (processing using external resources), appropriately estimating the costs of a task and using external resources (e.g., Cary & Carlson, 2001; Gray & Fu, 2004; Walsh & Anderson, 2009). On the other hand, in previous studies about human use of automation systems, it has been pointed out that many failures emerged in the ef- fort control, and these failures often caused fatal accidents (Norman, 1990). Parasuraman and Riley (1997) defined these maladaptive effort controls as misuse and disuse. Misuse is overreliance on automation systems, and disuse is underuti- lization of the systems. Many researchers are rigorously in- vestigating human misuse and disuse of automation systems (e.g., Bahner, H¨uper, & Manzey, 2008; Dzindolet, Peterson, Pomranky, Pierce, & Beck, 2003). Lee and Moray (1994) stated that effort control is not per- formed depending only on the performance of an automation system, but also on the performance of human manual oper- ation. In a normative manner, it is ideal to allocate functions based on evaluations of both kinds of performances evenly. However, the balance of the consideration might be dispro- portionate. Our first interest in the current study is to inves- tigate the selection strategy of effort control. In this study, we define system-based selection as effort control depending more on system performance than on manual performance. In contrast, we define manual-based selection as effort con- trol depending more on manual performance than on system performance. We investigate whether people perform effort control based on system- or manual-based selection. Human ability to evaluate manual performance has been investigated in the study area of metacognition. The term metacognition here means people’s ability to monitor their own actions (Metcalfe & Greene, 2007). Metcalfe and Greene (2007) found that people could appropriately judge their manual operation performance (Judgment of perfor- mance: JOP). On the other hand, human evaluation of sys- tem performance has been investigated in the study area of human-computer interaction. Madhavan and Phillips (2010) found that people tend to evaluate system performance as lower than its actual performance. Moreover, many re- searchers are investigating situation awareness. These studies showed that there are two types of monitoring: active mon- itoring (monitoring situations while manually conducting a task) and passive monitoring (monitoring situations while ob- serving an automation system’s operation) (e.g., Metzger & Parasuraman, 2001). Endsley and Kiris (1995) and Metzger and Parasuraman (2001) found that people show higher situ- ation awareness during active monitoring than during passive monitoring. These previous studies lead to an expectation that in co- operative work with an automation system, people are ex- pected to perform effort control depending more on manual performance than on system performance. In other words, we expect that people perform effort control based on manual- based selection. The first research question of the current