The Design of Future Things by Don Norman

continuum between “tight-rein” and “loose-rein” control still applies. Note how the degree of animal autonomy or of human control is communicated by exploiting the implicit communication made possible through the affordances of the reins. Combining implicit communication with affordances is a powerful, very natural concept. This aspect of working with a horse is the critical component that can be borrowed in the design of machine+human systems—in designing the system so that the amount of independence and interaction can vary in a natural manner, capitalizing upon the affordances of the controller and the communicative capabilities it provides.

    F IGURE 3.2
    Loose-rein guidance of a horse and carriage. With an intelligent horse providing the power and guidance, the driver can relax and not even pay much attention to the driving. This is loose-rein control, where the horse has taken over.
    Photograph by the author in Brugge, Belgium.
    When I drove the automobile simulator at Braunschweig, the difference between “loose-” and “tight-rein” control was apparent. Under tight-rein conditions, I did most of the work, determining the force on the accelerator, brake, and steering wheel, but the car nudged me, this way or that, trying to keep me on a steady course within the highway’s lane boundaries. If I got too close to the car ahead of me, the steering wheel pushed back, indicating that I should back off. Similarly, if I lagged behind too much, the steering wheel moved forward, urging me to speed up a bit. Under loose-rein conditions, the car was more aggressive in its actions, so much so that I hardly had to do anything at all. I had the impression that I could close my eyes and simply let the car guide me through the driving. Unfortunately, during the limited time available for my visit, I wasn’t able to try everything I now realize I should have. The one thing missing from the demonstration was a way for the driver to select how much control to give to the system. This transition in amount of control is important, for when an emergency arises, it may be necessary to transfer the control very rapidly, without distracting from the attention required to deal with the situation.
    The horse+rider conceptualization provides a powerful metaphor for the development of machine+human interfaces, but the metaphor alone is not enough. We need to learn more about these interfaces, and it is reassuring to see that research has already begun, with scientists studying how a person’s intentions might best be communicated to the system, and vice versa.
    One way for the system to communicate its goals and intentions to a person is through an explicit presentation of the strategythat is being followed. One research group, Christopher Miller and his colleagues, proposes that systems share a “playbook” with everyone involved. The group describes their work as “based on a shared model of the tasks in the domain. This model provides a means of human-automation communication about plans, goals, methods and resource usage—a process akin to referencing plays in a sports team’s playbook. The Playbook enables human operators to interact with subordinate systems with the same flexibility as with well-trained human subordinates, thus allowing for adaptive automation.” The idea is that the person can convey intentions by selecting a particular playbook for the automatic systems to follow, or if the automation is in control, it shows the playbook it has selected. These researchers are concerned with the control of airplanes, so the playbook might specify how it will control take off and the achievement of cruising altitude. Whenever the machine is working autonomously, controlling what is happening, it always displays the play that it is following, letting the human understand how the immediate actions fit into the overall scheme and change the choice of plays if necessary.