This is my Quality is Dead hypothesis: a pleasing level of quality for end users has become too hard to achieve while demand for it has simultaneously evaporated and penalties for not achieving it are weak. The entropy caused by mindboggling change and innovation in computing has reached a point where it is extremely expensive to use traditional development and testing methods to create reasonably good products and get a reasonable return on investment. Meanwhile, user expectations of quality have been beaten out of them. When I say quality is dead, I don’t mean that it’s dying, or that it’s under threat. What I mean is that we have collectively– and rationally– ceased to expect that software normally works well, even under normal conditions. Furthermore, there is very little any one user can do about it.
If you look at engineering or maths, we've been doing that for thousands of years, so we now know how to build a building and make it solid. With code, we've been doing computer science for 70-75 years, so we are still scratching the surface - we don't have a real theory or like physics, where they have a good foundation. We have the Turing machine that doesn't really reflect distributed computation. The lambda calculus captures certain parts, then there is a lot of process algebra, but it's not yet clear that we really have understood everything, which I think is fantastic, because that means there is opportunity to discover new things.
Much of what is wrong about our field is that many of the ideas that happened before 1975 are still the current paradigm. He [Alan Kay] has a strong feeling that our field has been mired for some time, but because of Moore’s law, there are plenty of things to work on. The commercialization of personal computing was a tremendous distraction to our field and we haven’t, and may not, recover from it.
One of Alan’s undergraduate degrees is in molecular biology. He can’t understand it anymore despite having tried to review new developments every few years. That’s not true in computer science. The basics are still mostly the same. If you go to most campuses, there is a single computer science department and the first course in computer science is almost indistinguishable from the first course in 1960. They’re about data structures and algorithms despite the fact that almost nothing exciting about computing today has to do with data structures and algorithms.
Alan Kay (paraphrased by Phil Windley)
[Actually, check the comments for Alan's clarification].
17 comments:
Well, of course I still do understand molecular biology (this is a typical web problem of people not understanding something but still being willing to paraphrase as though the person actually said what they didn't say!).
What I did say was that molecular biology has now advanced so much that it is impossible to for a part timer to really survey the field every few years without missing a lot (and this is apparently also true now for people in the field). But everyone understands it nonetheless. In many ways there is quite a lot more coherence of style in MB because the pathways that evolution took were pretty much an embellishment and expansion of one particular style of "how life learned how to live".
Computing has many styles -- some more powerful than others -- and many fads so it is much more confused than MB.
Best wishes,
Alan Kay
Thanks for your clarification, Alan. I'm sorry Phil's annotations misrepresented your intent, but, on the other hand, had he not put his notes on the web, however unreliable, your remarks would be restricted to the people at that room at that time.
Hi Rafael,
I posted a counter point - and a pointer to someone who is trying to help solve the problem you're talking about here http://robertlally.com/?p=99.
Thanks,
Rob Lally.
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