One of the most difficult things about studying history is recreating the social, intellectual, technological, and physical environment of your subject. Mostly this entails putting your own assumptions aside, which means understanding the assumptions that you make about life. This is not always easy. Some assumptions we make about life are so ingrained that we cease to notice them anymore, let alone recognize their absence in the past. Two of my favorite examples of this are access to medical care and access to communications infrastructure. People in 1800, even if they lived in a relatively affluent area, had atrocious medical care by our standards, which translated into much lower life expectancies. A letter – which was the dominant mode of long-distance communication – took anywhere from two weeks to several months to cross any significant distance (like the Atlantic Ocean). We take access to decent medical care for granted, as we do communications infrastructures like telephones (and, of course, the internet).
The reason I bring all of this up in a post about an article from the mid-20th century U.S. is relatively simple: I found it hard to understand exactly what computers of Licklider’s time actually looked like and how they functioned. One has the “room-size” computer in mind, the types that were programmed by punch card and were actually susceptible to physical insects (bugs) clogging up vacuum tubes in their inner workings. But beyond this stereotyped understanding of computing, it is very, very difficult to break out of our current understanding of what computers are and how we use them. I’m typing this on a machine that fits in my lap, and yet has many, many, many times the processing power that the room-size computers of Licklider’s day had. I have instant access to a large portion of the world’s information and can use this machine in an almost infinite variety of ways, all without needing to know a single line of computer code. With some coding skills, this number does rise very close to infinity. I can create amazing representations of complex data structures through free programs like R and Gapminder, and do all of this with data sets freely available from governmental and non-governmental agencies across the globe. Not all of these assumptions about what a computer can do immediately recede when I try to put myself in the mind-space of Licklider, like the idea that I would need to articulate exactly what I wanted to compute before I did it, sit down with a programmer to figure out how to compute it, and then wait for the processing time on the machine itself to become available. When we consider how frankly archaic this sounds to us in 2014, I think we start to get a better sense of how far we’ve come. Consider this quote from him about computer storage:
The first thing to face is that we shall not store all the technical and scientific papers in computer memory. We may store the parts that can be summarized most succinctly-the quantitative parts and the reference citations-but not the whole. Books are among the most beautifully engineered, and human-engineered, components in existence, and they will continue to be functionally important within the context of man-computer symbiosis.
We have the capacity to store all of the world’s information in computer memory. What I’m trying to say is that at least in some senses I think we have achieved Licklider’s vision, or at least are approaching it in meaningful ways. Consider his statement about the work that he is actually doing:
The main suggestion conveyed by the findings just described is that the operations that fill most of the time allegedly devoted to technical thinking are operations that can be performed more effectively by machines than by men. Severe problems are posed by the fact that these operations have to be performed upon diverse variables and in unforeseen and continually changing sequences. If those problems can be solved in such a way as to create a symbiotic relation between a man and a fast information-retrieval and data-processing machine, however, it seems evident that the cooperative interaction would greatly improve the thinking process.
We process weather models, simulations of space shuttle reentry, social network analysis, and any number of things with rapidly changing variables today. We use our computers to help us think through problems, to rapid-prototype, if you will, and get to solutions far faster and with much less effort than in Licklider’s day. Perhaps even more to his point, advances in natural language processing, semantic linking, and machine learning are beginning to let computers “think” more like human beings and reckon with new information by themselves, rather than through the mediation of a human being. Considered from this angle, we live in exciting times indeed.