I read Adam Greenfield’s Everyware in August of this year, but haven’t written anything about it yet. I like the book, a lot. It led me to think again about a number of issues that I kind of put to the side over the last two decades as I’ve made a living as a knowledge worker, i.e. methods analyst, technical writer, multimedia developer, Professor of Communication, web designer, human capital manager, e-Learning researcher, learning architect, customer experience designer. However, Adam’s book made an impression on me initially, more because of things that I experienced in the late 1980s and early 1990s than for its relevance today, though it is extremely relevant to today’s challenges in relating human experience to the ubiquitous nature of computing technology.
As a graduate student in sociology at Washington University in St. Louis, working full time in the telecommunications industry during the 1980s and finishing a long and tortuous dissertation odyssey, I was fortunate to develop a research relationship with a professor in sociology at Washington University named Deirdre Boden. Dede was fresh out of a post-doc at Stanford, after finishing a Ph.D. at UC-Santa Barbara, specializing in the use of conversation analysis in researching the organization of business meetings. During her time at Stanford in the early 1980s, she developed a relationship with an anthropologist named Lucy Suchman who worked at Xerox PARC. I was struggling at the time to develop a dissertation topic, but had been interested in artificial intelligence since reading Hubert Dreyfus’ What Computers Can’t Do. Expert systems were given a great deal of credibility in the mid-1980s, but after reading Dreyfus I suspected there were challenges in the way of their success that weren’t merely technological in nature. At the time, search techniques were attempting to solve the problem of depth-first versus breadth-first search through knowledge bases, and many people advocating the usefulness of expert systems just thought it was a matter of crunch power.
In 1986, Dede offered to lend me a copy of a research monograph that Suchman had just written called Plans and Situated Action, later to become a founding work in the field of Computer Supported Collaborative Work (CSCW). Once I read that research monograph, I knew how to put together my interpretation of Dreyfus with a research problem that could be studied in a corporate setting. From that serendipitous combination of relationships, I did a dissertation on knowledge acquisition in expert systems development using the conversation analysis approach offered in Suchman’s research monograph, and the many phenomenologists and ethnomethodologists I was familiar with, focusing specifically on the way participants to knowledge acquisition design used stories to negotiate a definition of whatever bit of knowledge was under dispute. The dissertation was called Designing Knowledge. It was completed in 1992 using Bitnet for collaboration as Dede left Washington University in 1991 to become the Jean Monnet Fellow at the European University Institute in Florence, Italy in 1991-1992.
While reading Greenfield’s Everyware, I was reminded of the many promises that artificial intelligence made for expert systems in the 1980s as he describes how the designers of context-aware, ubiquitous computing think they can make it work. Interestingly, both Greenfield’s Everyware and Peter Moreville’s Ambient Findability, after some quibbling, defer to the aspirations of advocates for machine learning, as if the claims of artificial intelligence for having machines act in a sociable manner are credible after all the fiascos and shortfalls of the past 30 years. Most people do not want to take the time to teach a machine how to act on their behalf in the most basic of settings and, in the best of outcomes that is what machine learning requires.
Copyright © 2006 by Larry R. Irons
Share this post…