The Design of Future Things: Chapter 5

Neural Networks... not how the brain thinks. At all.

The Design of Future Things, Donald A. Norman

Summary:
Chapter 5 is entitled "The Role of Automation", and it talks about automation, augmentation, and autonomy, generally in the context of the home. It also mentions neural networks, explained in the traditional "its like magic that mimics the way a human mind works" method that makes me want to strangle people.

He starts off with an explanation that automation isn't generally as simple as "Let's replace worker x with a machine." In fact, the maintenance of the machine often brings about new jobs to replace the old ones. Towards the end he also talks about how you lose certain advantages which are inherent in the process now- an experienced worker can spot and correct problems that a machine may blindly overlook.

He then  talks about the house of Mike Mozer. Mike is a research scientist specializing in neural networks. He outfitted his house with a wide array of sensors, and a few actuators, and fed them all into a neural net so that he wouldn't have to fiddle with the thermostat, water heater, or lights. Mike also talks a bit about how certain levels of automation are undesirable or unattainable- turning on music when the occupant wants to listen to something is the prime example- there's no simple sensor in the house (other then the stereo power button) that says "I want music," and machine attempts to discern this will tend towards false positives, annoying the inhabitants, and causing the house to undergo a lobotomy. Don goes on / throughout the section to ask "Is this a smart house? It uses neural nets! It's Learning! It's this awesomely complex thing!", where as Mike puts it into a better context of "It's adapting based on my feedback". I like Mike.

The next topic covered is looking at augmentation in home environments rather then automation. Automation is hard, and painfully difficult to get right in the average context. Augmentation, by contrast, is "easy", can be ignored if desired, and it is more approachable as it does not need to read the humans mind in order to be successful. Two examples were in the smart home context- a bulletin board system tied into smart phones, and a cooking helper to help distracted cooks. 

Discussion:

1. Why is this paper interesting or significant?

Most useful element of this chapter is that automation is not"free",it's rarely/never a drop in replacement for a worker.

2. What are the faults of this work?

The neural networks reference. In that context, it feels like he's trying to make the entire thing seem more impressive then it actually is. I can see a conversation between a wide-eyed Norman and a disinterested Mozer as the concepts are explained back and forth.

Another fault comes from the way he's making the argument for augments vs. automated/autonomous. In that context he says "These groups could have done <really complex thing>, but instead they chose to do <simple thing>". I doubt that the researchers could have ever gotten such complex systems to the point of usefulness- if they thought they could, they probably would have spent time on that; but rather they were looking for rapid product development.

3. What is the possible future work extending from this work?

Arguably, looking for points of augmentation rather then of automation or autonomy in our projects.