The growth of sophistication in machine capabilities must go hand in hand with growth of sophistication in human–machine interaction capabilities. To continue advancement as we build today’s intelligent machines, designers need formative tools for creating sociotechnical systems. In this article, we will briefly assess the appropriateness of “levels of automation” as a tool for designing human–machine systems. Additionally, we present coactive design and interdependence analysis as a viable alternative tool moving forward into more advanced and sophisticated human–machine systems.
EndsleyM. R.KirisE. O. (1995). The out-of-the-loop performance problem and level of control in automation. Human Factors, 37, 381–394. http://doi.org/10.1518/001872095779064555
8.
FeighK. M.PritchettA. R. (2014). Requirements for effective function allocation: A critical review. Journal of Cognitive Engineering and Decision Making, 8, 23–32. http://doi.org/10.1177/1555343413490945
9.
FongT. W. (2001). Collaborative control: A robot-centric model for vehicle teleoperation. Pittsburgh, PA: Robotics Institute, Carnegie Mellon University.
10.
GaoJ. G. J.LeeJ. (2006). Extending the decision field theory to model operators’ reliance on automation in supervisory control situations. IEEE Transactions on Systems, Man, and Cybernetics–Part A: Systems and Humans, 36, 943–959. http://doi.org/10.1109/TSMCA.2005.855783
11.
JohnsonM.BradshawJ. M.FeltovichP. J.HoffmanR. R.JonkerC. M.van RiemsdijkM. B.SierhuisM. (2011). Beyond cooperative robotics: The central role of interdependence in coactive design. IEEE Intelligent Systems, 26, 81–88. http://doi.ieeecomputersociety.org/10.1109/MIS.2011.47
12.
JohnsonM.BradshawJ.FeltovichP.JonkerC.van RiemsdijkB.SierhuisM. (2011). The fundamental principle of coactive design: Interdependence must shape autonomy. In De VosM.FornaraN.PittJ.VourosG. (Eds.), Coordination, organizations, institutions, and norms in agent systems VI (Vol. 6541, pp. 172–191). Berlin, Germany: Springer. http://doi.org/10.1007/978-3-642-21268-0_10
13.
JohnsonM.BradshawJ. M.FeltovichP. J.JonkerC. M.van RiemsdijkB. M.SierhuisM. (2014). Coactive design: Designing support for interdependence in joint activity. Journal of Human–Robot Interaction, 3, 43–69.
14.
JohnsonM.ShrewsburyB.BertrandS.CalvertD.WuT.DuranD.. . . PrattJ. (2017). Team IHMC’s lessons learned from the DARPA Robotics Challenge: Finding data in the rubble. Journal of Field Robotics, 34, 241–261. http://doi.org/10.1002/rob.21674
15.
KaberD. B.OnalE.EndsleyM. R. (2000). Design of automation for telerobots and the effect on performance, operator situation awareness, and subjective workload. Human Factors and Ergonomics in Manufacturing, 10, 409–430. http://doi.org/10.1002/1520-6564(200023)10:4<409::AID-HFM4>3.3.CO;2-M
16.
KirlikA.MillerR. A.JagacinskiR. J. (1993). Supervisory control in a dynamic and uncertain environment II: A process model of skilled human environment interaction. IEEE Transactions on Systems, Man, and Cybernetics, 23, 929–952. http://doi.org/10.1109/21.247880
17.
KleinG.FeltovichP. J.BradshawJ. M.WoodsD. D. (2005). Common ground and coordination in joint activity. In RouseW. B.BoffK. R. (Eds.), Organizational simulation (pp. 139–184). New York: Wiley.
18.
KleinG.WoodsD. D.BradshawJ. M.HoffmanR. R.FeltovichP. J. (2004). Ten challenges for making automation a “team player” in joint human–agent activity. IEEE Intelligent Systems, 19, 91–95. http://dx.doi.org/10.1109/MIS.2004.74
19.
ParasuramanR.SheridanT.WickensC. (2000). A model for types and levels of human interaction with automation. IEEE Transactions on Systems, Man and Cybernetics–Part A, 30, 286–297. http://dx.doi.org/10.1109/3468.844354
20.
RoviraE.McGarryK.ParasuramanR. (2007). Effects of imperfect automation on decision making in a simulated command and control task. Human Factors, 49, 76–87. http://doi.org/10.1518/001872007779598082
21.
SheridanT. B. (1992). Telerobotics, automation, and human supervisory control. Cambridge, MA: MIT Press.
22.
SheridanT. B.VerplankW. (1978). Human and computer control of undersea teleoperators. Cambridge, MA: Man-Machine Systems Laboratory, Department of Mechanical Engineering, MIT.
