The author of this piece seems to miss an extremely important piece of khun's philosophy: 'normal science'. Normal science is the practice of the everday scientist working in their paradigm, that is working on known problems, with known methods, make progress - i.e. breeding fruit flies, observing planets. As for the revolution, you need reasons that cause the fundamental shift - problems/inconsistencies that resist current methods.
Computer Science and Software Development fall into a unique area in which there are so many problems we are often working without paradigms and often adopt pragmatic approaches, and quickly discover whole new "domains". Social, mobile, REST/CRUD, media - are all revolutions, but not just in technology but in society, they're fundamentally changing how individuals interact in society.
Now this isn't to say that pure research isn't needed, but I don't think it's supported through this appeal to khun. With so much low hanging fruit it's hard to properly allocate resources. Is developing Ruby on Rails and increasing the productivity of a large swath of programmers more important than a more efficient garbage collector or better NLP system? Both types of R&D are crucial and to write off mobile mobile apps as not being research is short sighted; if an app gains traction like facebook or google it will most likely radically change our current behavior in an as yet unforeseen way.
I'm glad he's reading up on the philosophy of science, it's critical imho to better understand how ideas and technology progress.
The following quote is also relevant (from the 1969 postcript to the book)
"A number of those who have taken pleasure from it have done so less because it illuminates science than because they read its main theses as applicable to many other fields as well. I see what they mean and would not like to discourage their attempts to extend the position, but their reaction has nevertheless puzzled me. To the extent that the book portrays scientific development as a succession of tradition-bounds periods punctuated by non-cumulative breaks, its theses are undoubtedly of wide applicability. But they should be, for they are borrowed from other fields. Historians of literature, of music, of the arts, of political development, and of many other human activities have long described their subjects in the same way. Periodization in terms of revolutionary breaks in style, taste, and institutional structure have been among their standard tools. If I have been original with respect to concepts like these, it has mainly been by applying them to the sciences, fields which had been widely though to develop in a different way."
Social, Mobile, REST/CRUD, etc. are revolutions, but they are not 'Kuhnian revolutions.' They are innovative technologies that enable progress. Just as cubism, pointillism, impressionism are revolutions in painting. The difference is, that in a scientific revolution, a new idea completely supplants its predecessors. An example in Computer Science would be the 'information revolution' in the late 1940s, in which Shannon's theory of information supplanted that of Hartley and Nyquist. While leaps and bounds in things like development of scripting languages are revolutionary, they are revolutionary in a manner different from Kuhn's description.
A "Kuhnian revolutions" doesn't need to be a wholesale replacement of assumptions underlying an entire field of inquiry. Sure, most of the examples he used in his original book were drawn from such large-scale paradigm shifts. But especially in his later writing, Kuhn seems to focus more on what we might call "micro-revolutions": paradigm shifts that affect only a small part of the relevant science or technology, but which work in much the same way as large-scale scientific revolutions. Of course this isn't the only interpretation out there, and philosophers of science can disagree among themselves all day long. But much of the Sociology of Scientific Knowledge research that took place after Kuhn's book followed this broader interpretation, and studied small-scale changes in very narrow sub-fields of science as well as larger ones.
In other words, Kuhnian revolutions aren't as rare and far between as his original book might seem to suggest.
New concepts in IT might not "completely supplant" their predecessors, but their rise to prominence can certainly be called revolutions in the area(s) that are irreversibly changed by them. For example, very few people nowadays think that APIs on the Internet should be anything other than RESTful. Previous paradigms for remote computing protocols have been almost completely supplanted in this area. Likewise, table-based HTML layouts have been completely supplanted by CSS in the last 10 years. The change, of course, was motivated by the previous paradigm's inadequacy in addressing the needs of the evolving Web. There are lots of examples like this, even trivial ones, that can nevertheless be called miniature Kuhnian revolutions.
First time I've ever heard of Khun so Im far from qualified but I think what the author is getting at is the copycat nature of the startup ecosystem. Especially lately, there seems to be a focus by many entrepreneurs and investors to replicate previous successes as fast and as cheaply as possible by following a template. This paradigm discourages people from pushing on the doors that look big, heavy and risky but these are the doors when unlocked that typically lead to explosions in innovation and become the next drivers of the economy.
The problem is that those heavy doors are usually expensive to push on and with the falterings of our government and higher education systems there are less entities that seem to be focusing on the hard, immediately unprofitable stuff. For example, think of all the innovations that have come out of NASA and now that seems to be slowly becoming dismembered.
Its really hard to actually know but I feel like social, mobile, media, web 2.0, etc. are nice iterations within the computing world with a lot of growth but aren't really game changing innovations. I think what you are saying is that through these iterations the next big thing will appear. I can see this as a trajectory as well - lets just hope Groupon and Zynga don't end up being the biggest advances of this decade.
First, I was arguing that the "copycatting" could be considered "normal science", where we have scientists finding a technique that works and trying to learn as much as they can, for example breeding fruit flies. I quote copycatting before because each entrepreneur has different ideas about 1. the problem 2. the market 3. the technical approach, etc and could perhaps be seen as an experiment. As we learn more about those 3 areas above things progress until the next new big wave of innovation comes through. For example, you could consider the web 1 to web2.0 as a "scientific revolution", there was a radical change in what was expected, the problems being solved, and the techniques to do it.
As for NASA, it's been crippled by bureaucracy and politics; and one could question if they ever had the systems engineering experience that tout as the majority of their Appolo and other groundbreaking systems were contracted out and had simple interfaces. The space shuttle was a giant boondoggle that hampered space research. Nasa will continue to innovate through the JPL and unmanned exploration - where science is done.
As for pure research, google now provides world class machine translation for free and continues to do research in that field at a scale that would be difficult for an academic lab to achieve.
Mobile is a game changer in the 3rd world - it allows poor farmers to understand market prices and integrate with the rest of the world. Social seems like it has/is radically altering society - it'll be interesting to see how it plays out.
Lastly, I agree we need pure research and I support it, I personally prefer applied, but I think that we've barely scratched the surface of how computers/internet can improve the world (with our current technical and scientific understanding). And we're opening up whole new avenues of study - complexity science, computational social science, web science, etc.
I think we can view paradigm shifts in science as a gradual accumulation of evidence (data), leading to more sophisticated and complex models until someone sees a new way of thinking about it that explains the evidence more simply. The evidence accumulated before the shift is essential.
In programming, we're not seeking theories, but solutions to problems, so I think the analogy is that as we try to solve problems, we learn more about them (collect data), creating increasingly elaborate solutions, until eventually someone realizes there's a better approach. Again, the accumulated knowledge about the problem is essential for the breakthrough.
In science, reality is constant and it's only our knowledge and theories that change. But in programming, the actual problems also change as we enter new domains with new problems and criteria.
Computer Science and Software Development fall into a unique area in which there are so many problems we are often working without paradigms and often adopt pragmatic approaches, and quickly discover whole new "domains". Social, mobile, REST/CRUD, media - are all revolutions, but not just in technology but in society, they're fundamentally changing how individuals interact in society.
Now this isn't to say that pure research isn't needed, but I don't think it's supported through this appeal to khun. With so much low hanging fruit it's hard to properly allocate resources. Is developing Ruby on Rails and increasing the productivity of a large swath of programmers more important than a more efficient garbage collector or better NLP system? Both types of R&D are crucial and to write off mobile mobile apps as not being research is short sighted; if an app gains traction like facebook or google it will most likely radically change our current behavior in an as yet unforeseen way.
I'm glad he's reading up on the philosophy of science, it's critical imho to better understand how ideas and technology progress.