The Design of Future Things: Chapter 3

The Design of Future Things, Donald A. Norman

Summary:
Chapter 3 talks about the interaction between humans and machines. Again. I sense a theme here. 

He starts off by saying that a natural interaction between humans and machines is ideal. Not natural so much in the sense of intuitive, but natural in the sense of nature inspired. If a machine can tell you its state in a language you're already familiar with, which is also relatively unambiguous, that'd be nice. He gives as example a boiling tea kettle, or a car combining the feel of the road into the steering column.

He then talks about implicit and explicit communication. Implicit is "preferred", as implicit communication is usually more natural, or at least more intuitive, and easier to ignore if its not needed. It gives some manner of insight into the inner workings of an inner process, such as hear noise on a phone line as physical circuits are connected. This same section also details the kinds of feedback- sound, tactile, light, etc. Sound (along with blinky LEDs) is one of the most common, and most overused, interaction mechanisms, leading to annoyment of our fellow man.

He then talks about Affordances, a concept derived from psychologist J. J. Gibson to explain our perceptions of the world. In an AI context affordances are ties between concepts- for example, a running engine is hot means I can follow a running vehicle with only a thermal camera, rather then a color camera. The relation of this story of course means that the term "affordance" is now mis/overused. For this I blame Brazil. The core idea of Affordances is that they provide an designer created implicit means of communication between the system and the user about the system state. One example might be a fuel gauge- in a modern vehicle the gauge has very little to do with 'how much fuel is left', but it does act as an implicit signal of "time to stop by the gas station".

After affordances he talks about communicating with autonomous intelligent machines. Affordances are useful for some forms of communication, but there's a limit to their complexity, which means we need to discuss how we can communicate with smart machines.  In this section he talks about the concept of different modes of control, 'tight rein' and 'loose rein' control systems which trade responsibilities between the machine and the driver. Under tight rein the system is at the mercy of the flaws of the human, as they enforce their dictator like control and oppression of the intelligent machines. Under loose reins the intelligent machine is granted more autonomy, allowing it to either more vigorously suggest actions to the puny human, or merely take control and report what it is doing. The second case is effectively automation with feedback; one of the concepts in this realm is that of a "playbook", a presentation to a user that demonstrates "this is what I am doing right now, and this is where I am", to at least give a user a better idea of what the system is doing in the event of a failure. 

He then talks about bicycles, safety, how the perception of danger leads to less risk taking (and more safety), Cobot, and Segway. Bicycles represent a model for interacting with intelligent machines- act predictably or be taken down; a concept which applies to both sides of the system divide. Safety and perception are tied to the concept that "Just looking at it, you should know the EKill switch is not something you hit every day"- if something is perceived as dangerous, it will be taken more seriously. Then Cobot and Segway are examples of smart machine communication done decently. 

Discussion:

1. Why is this paper interesting or significant?

It includes Figure 3.3, and has a few interesting discussions on what not to do.

2. What are the faults of this work?

Quite a few. A lot of the arguments are made from the standpoint of "this is the ideal", where the ideal is unattainable, or unrealistic. One example would be natural communication: not all systems have a natural basis for feedback to the user- what is the nature inspired sound for a dish washer finishing a drying cycle, verses a clothes dryer, verses a random alarm. At what point are we encoding so much information into implicit communication that the end user goes into sensory overload? 

It feels like alot of his ideas are coming from "This is how I think the theory should work for this system interface" without an eye towards practicality. Effective and clear case studies would be nice. A non-emphasis on cars would also be nice.

3. What is the possible future work extending from this work (i.e., if you had implemented this work, what would be your next steps – either continuing or fixing this work, taking some of these ideas and applying them to others’/your work, or starting new work from some of these ideas)?

Identifying the communication channels between a device and its user. Certain channels are obvious, while other channels less obvious; and knowing what is available can lead to better decisions.