Cognitive Design

Check out Donald Norman’s latest book, The Design of Future Things.  His basic thesis is that in the future the things we design will be smart (emotionally and intellectually) permitting a more natural form of interactions (one similar to a horse and rider) and even achieving a level of human-machine symbiosis. It is people and their artifacts working together – with machines augmenting the capabilities of humans that make up the design of future things. Homes, cars, workspaces, airports, robots and other artifacts will be designed to work with us at three levels including the visceral (automatic and unconscious responses), behavioral and reflective (conscious self awareness).

 He offers six rules for designers of these smart machines of the future: 

1. Provide rich, complex and natural signals

2. Be predictable

3. Provide good conceptual models

4. Make outputs understandable

5. Provide continual awareness without annoyance

6. Exploit natural mappings.

 Being predictable and running on a good conceptual model means I can understand (to a degree) the artifact’s workings, know how it will behave and also come to trust it especially since its outputs are understandable. Rich and natural signals that support my continued awareness of (and feedback about) its operation without annoyance makes it is an active part of my environment. These are many of the same things that make my interactions with other people work.  

 All of these rules effectively lower the cognitive load associated with the artifact without sacrificing functionality. There is a higher degree of integration between the functional states of the artifact and the mental states of the people using the artifact. Indeed, in the case of a symbiotic relationship they are fused together in a dynamic feedback loop.  This represent the fifth level of cognitive fit (1= agitate, 2 = tolerate, 3= resonate, 4 = accelerate and 5 = integrate) that we have discussed elsewhere in this blog.  

 One example Professor Norman gives is that of a Cobot being developed at the Laboratory for Intelligent Mechanical Systems at Northwestern. In this example, humans can move heavy payloads (e.g. automobile engines) in complex environment smoothly and easily by sharing control and intelligence with a robot.  The robot provides not just mechanical muscle but also brains by providing natural resistance to suggested motions that are not consistent with the task or could be unsafe.  All of this takes place NOT via a controller to manipulate a robot arm but by directly interacting with the artifact (e.g. by wrapping a chain around the automobile engine to lift it). This is consistent with rule #6 – exploit natural mappings.

 In a provocative afterwards, Professor Norman describes an imaginary interview he had with an intelligent machine about a set of design rules they (intelligent machines) developed to improve their interactions with people.  We will review those rules and their implications for cognitive design in a future post.