This weeks lecture was given by Peter McCaughey who opened and led a loose discussion touching on many topics to do with creativity, the future, the social implications design can have and the way it could be used to form policies.
He gave a useful piece of advice for evaluating an idea, he suggested putting it the past tense, put it in context, give it a story and ask how it went wrong. His advice reminds me of Ross Lovegrove who’s ideals are formed by what he thinks is utopian or dystopian, I feel this is also a useful method for arguing whether something should or shouldn’t exist.
During the discussion we talked about futurology, how machines are increasingly taking over human tasks to the extent we are working ourselves out of a job. I feel however that a “post-work” society might not be so bad, it would leave more time for us to do what we want (for those who are not so fortunate to enjoy what they do). I also think that if we design responsibly, instead of replacing jobs, we can create tools to enhance our capabilities as opposed to replacing us.
Don Norman gives a number of good examples in this essay, he says:
“The development of calculators (from arithmetic through calculus) and computer systems did not eliminate the need for people with mathematical training. What it did do was eliminate the kinds of clerical errors even great mathematicians make. The machines and programs do the math; the mathematician concentrates on figuring out what problems should be solved. The human mind is far more powerful when coupled with the smart tool. The combination is far superior to either one alone.”
He goes on to talk about how those who are developing certain technologies often have the tendency and desire (perhaps subconsciously) to automate tasks to the extend that human factors are ignored. He argues that people are often only used for tasks that can’t be automated, resulting in an undesirable relationship with machines where people have to monitor the machines and take over when necessary. So people are left to work on the machines terms, in effect we are working to enhance the machine instead of the machine working to enhance us. Take self driving cars for example, they require the driver to pay close attention and constantly monitor what is going on in case he/she needs to take over. This is something that the human brain is not good at, we have a short attention span and cannot pay close, unwavering attention to something. Instead, we “excel at tasks requiring the exercise of creativity, a response to unexpected situations, or general attentiveness to the entire surrounding environment” where as “machines process information very quickly, never get bored, and reliably do the things they are designed to do.” in Norman’s words.
He uses Autodesk’s research project Dreamcatcher as an example of how automation through technology can be used as a tool to enhance human capabilities with a collaborative system. Currently we use computer aided design as tools for computing finite element models of mechanical, thermal or electronic systems but we still have to have designed whatever it is we are modelling. If this is a bottom up approach, Dreamcatcher uses a top down approach called “Generative Design”. Instead of the designer doing the “low-level drawing… they specify the high-level parameters--goals and constraints--and the tool would generate potential solutions. Then, as solutions are generated, the designer would assess them, encouraging some directions and discouraging others. If the suggested solutions did not satisfy the designer, the system could be given modified goals and constraints, or perhaps more restrictions, to force the solutions into a desirable set of alternatives.” The result is a collaborative relationship between human and machine.