This is the clearest explanation I’ve seen Alan Kay give for what the ARPA community’s conception of computer science was. His answer on Quora was particularly directed at someone who was considering entering a CS major. Rather than summarize what he said, I’m just going to let him speak for himself. I’d rather preserve this if anything happens to Quora down the road. There is a lot of gold here.
If you are just looking to get a job in computing, don’t bother to read further.
First, there are several things to get clear with regard to any field.
- What is the best conception of what the field is about?
- What is the best above threshold knowledge to date?
- How incomplete is the field; how much will it need to change?
When I’ve personally asked most people for a definition of “Computer Science” I’ve gotten back an engineering definition, not one of a science. Part of what is wrong with “CS” these days is both a confusion about what it is, and that the current notion is a weak idea.
The good news is that there is some above threshold knowledge. The sobering news is that it is hard to find in any undergrad curriculum. So it must be ferreted out these days.
Finally, most of the field is yet to be invented — or even discovered. So the strategies for becoming a Computer Scientist have to include learning how to invent, learning how to change, learning how to criticize, learning how to convince.
Most people in the liberal arts would not confuse learning a language like English and learning to read and write well in it, with the main contents of the liberal arts — which, in a nutshell, are ideas. The liberal arts spans many fields, including mathematics, science, philosophy, history, literature, etc. and we want to be fluent about reading and writing and understanding these ideas.
So programming is a good thing to learn, but it is most certainly not at the center of the field of computer science! When the first ever Turing Award winner says something, we should pay attention, and Al Perlis — who was one of if not the definer of the term said: “Computer Science is the Science of Processes”, and he meant all processes, not just those that run on digital computers. Most of the processes in the world to study are more complex than most of the ones we’ve been able to build on computers, so just looking at computers is looking at the least stuff you can look at.
Another way to figure out what you should be doing, is to realize that CS is also a “blank canvas” to “something” kind of field — it produces artifacts that can be studied scientifically, just as the building of bridges has led to “bridge science”. Gravitational and weather forces keep bridge designers honest, but analogous forces are extremely weak in computing, and this allows people who don’t know much to get away with murder (rather like the fashion field, where dumb designs can even become fads, and failures are not fatal). Getting into a “learned science of designs that happen to be dumb” is not the best path!
We (my research community) found that having an undergraduate degree in something really difficult and developed helped a lot (a) as a bullshit detector for BS in computing (of which there is a lot), (b) as a guide to what a real “Computer Science” field should be and could be like, and (c) to provide a lot of skills on the one hand and heuristic lore on the other for how to make real progress. Having a parallel interest in the arts, especially theater, provides considerable additional perspective on what UI design is really about, and also in the large, what computing should be about.
So I always advise young people -not- to major in computing as an undergraduate (there’s not enough “there there”) but instead to actually learn as much about the world and how humans work as possible. In grad school you are supposed to advance the state of the art (or at least this used to be the case), so you are in a better position with regard to an unformed field.
Meanwhile, since CS is about systems, you need to start learning about systems, and not to restrict yourself just those on computers. Take a look at biology, cities, economics, etc just to get started.
Finally, at some age you need to take responsibility for your own education. This should happen in high school or earlier (but is rare). However, you should not try to get through college via some degree factory’s notion of “certification” without having formed a personal basis for criticizing and choosing. Find out what real education is, and start working your way through it.
When I’ve looked over other material written by Kay, and what has been written about his work, I’ve seen him talk about a “literate” computing science. This ties into his long-held view that computing is a new medium, and that the purpose of a medium is to allow discussion of ideas. I’ve had a bit of a notion of what he’s meant by this for a while, but the above made it very clear in my mind that a powerful purpose of the medium is to discuss systems, and the nature of them, through the fashioning of computing models that incorporate developed notions of one or more specific kinds of systems. The same applies to the fashioning of simulations. In fact, simulations are used for the design of said computer systems, and their operating systems and programming languages, before they’re manufactured. That’s been the case for decades. This regime can include the study of computer systems, but it must not be restricted to them. This is where CS currently falls flat. What this requires, though, is some content about systems, and Kay points in some directions for where to look for it.
Computing is a means for us to produce system models, and to represent them, and thereby to develop notions of what systems are, and how they work, or don’t work. This includes regarding human beings as systems. When considering how people will interact with computers, the same perspective can apply, looking at it as how two systems will interact. I’m sure this sounds dehumanizing, but from what I’ve read of how the researchers at Xerox PARC approached developing Smalltalk and the graphical user interface as a learning environment, this is how they looked at it, though they talked about getting two “participants” (the human and the computer) to interact/communicate well with each other (See discussion of “Figure 1” in “Design Principles Behind Smalltalk”). It involved scientific knowledge of people and of computer system design. It seems this is how they achieved what they did.
— Mark Miller, https://tekkie.wordpress.com