TITLE: Notes on the Rebooting Computing Summit AUTHOR: Eugene Wallingford DATE: January 17, 2009 3:09 PM DESC: ----- BODY: the Rebooting Computing logo [This is the first of several pieces on my thoughts at the Rebooting Computing summit, held January 12-14 in San Jose, California. Later articles talk about image of CS, thoughts on approach, thoughts on personal stories and, as always, a little of this and that.] This was unusual: a workshop with no laptops out. Some participants broke the rule almost immediately, including some big names, but I decided to follow my leaders. That meant no live note-taking, except on paper, nor any interleaved blogging. I decided to expand this opportunity and take advantage of an Internet-free trip, even back in the hotel! The workshop brought together 225 people or so from all parts of computer science: industry, universities, K-12 education, and government. We had a higher percentage of women than the discipline as a whole, which made sense given our goals, and a large international contingent. Three Turing Award winners joined in: Alan Kay, Vinton Cerf, and Fran Allen, who was an intellectual connection to the compiler course I put on hold for a few days in order to participate myself. There were also a number of other major contributors to computing, people such as Grady Booch, Richard Gabriel, Dan Ingalls, and the most famous of three Eugenes in the room, Gene Spafford. Most came without knowing what in particular we would do for these three days, or how. The draw was the vision: a desire to reinvigorate computing everywhere. a photo of the Computer History Museum's Difference Engine The location was a perfect backdrop, the Computer History Museum. The large printout of a chess program on old green and white computer paper hanging from the rafters near our upper-floor meeting room served as a constant reminder of a day when everything about computers and programming seemed new and exciting, when everything was a challenge to tackle. The working replica of Charles Babbage's Difference Engine on the main floor reminded us that big dreams are good -- and may go unfulfilled in one's lifetime. The Introduction Peter Denning opened with a few remarks on what led him to organize the workshop. He expressed his long-standing dissatisfaction with the idea that computer science == programming. Dijkstra famously proclaimed that he was a programmer, and proud of it, but Denning always knew there was something bigger. What is missing if we think only of programming? Using his personal experience as an example, he claimed that the outliers in the general population who make enter CS have invested many hours in several kinds of activity: math, science, and engineering. Throughout much of the history of computer science, people made magic because they didn't know what they were doing was impossible. This gave rise to the metaphor driving the workshop and his current effort -- to reboot computing, to clean out the cruft. We have non-volatile memory, though, so we can start fresh with wisdom accumulated over the first 60-70 years of the discipline. (Later the next day, Alan Kay pointed out that rebooting leaves same operating system and architecture in place, and that what we need to do is redesign them from the bottom up, too!) A spark ignited inside each of us once that turned us onto computing. What was it? Why did it catch? How? One of the goals of the summit was to find out how we can create the same conditions for others. The Approach The goal of the workshop was to change the world -- to change how people think about computing. The planning process destroyed the stereotypes that the non-CS facilitators held about CS people. The workshop was organized around Appreciative Inquiry (AI, but not the CS one -- or the one from the ag school!), a process I first heard about in a paper by Kent Beck. It uses a an exploration of positive experiences to help understand a situation and choose action. For the summit, this meant developing a shared positive context about computing before moving on to the choosing of specific goals and plans. Our facilitators used an implementation they characterized as Discovery-Dream-Design-Destiny. The idea was to start by examining the past, then envision the future, and finally to return to the present and make plans. Understanding the past helps us put our dreams into context, and building a shared vision of the future helps us to convert knowledge into actions. One of our facilitators, Frank Barrett, is a former prof jazz musician, said an old saying from his past career is "Great performances create great listeners." He believes, though, that the converse is true: "Great listeners create great performances." He encouraged us to listen to one another's stories carefully and look for common understanding that we could convert into action. Frank also said that the goal of the workshop is really to change how people talk, not just think, about computing. Whenever you propose that kind of change, people will see you as a revolutionary -- or as a lunatic. a photo of one of the workshop posters drawn live An unusual complement to this humanistic approach to the workshop was a graphic artist who was recording the workshop live before our eyes, in image and word. Even when the record was mostly catchphrases that could have become part of a slide presentation, the colors and shapes added a nice touch to the experience. The Spark What excited most of us about computing was solving a problem -- having some something that that was important to us, sometimes bigger than we could do easily by hand, and doing it with a computer. Sometimes we enjoyed the making of things that could serve our needs. Sometimes we were enlivened by making something we found beautiful. Still, a lot of people in the room "stumbled" or "drifted" into CS from other places. Those words carry quite different images of peoples' experiences. However subtle the move, they all seemed to have been working on real problems. One of the beauties of computer science is that it is in and about everything. For many, computing is a lens through which to study problems and create solutions. Like mathematics, but more. One particular comment made the first morning stood out in my mind. The gap between what people want to make with a computer and what they can reasonably make has widened considerably in the last thirty years. What they want to make is influenced by what they see and use every day. Back in 1980 I wanted to write a program to compute chess ratings, and a bit of BASIC was all I needed. Kids these days walk around with computational monsters in their pockets, sometimes a couple, and their desires have grown to match. Show them Java or Python, let alone BASIC, and they may well feel deflated before considering just what they could do. Computing creates a new world. It builds new structures on top of old, day by day. Computing is different today than it was thirty years ago -- and so is the world. What excited us may well not excite today's youth. What about what excited us might? (Like any good computer scientist, I have gone meta.) Educators cannot create learning. Students do that. What can educators provide? A sense of quality. What is good? What is worth doing? Why? History A lot of great history was made and known by the people in this room. The rest of us have lived through some of it. Just hearing some of these lessons reignited the old spark inside of me. Consider Alan Turing's seminal 1935 paper on the Halting Problem. Part of the paper is Turing "thumbing his nose" at his skeptical mathematician colleagues, saying "The very question is computation. You can't escape it." One time, Charles Babbage was working with his friend, the astronomer Herschel. They were using a set of astronomy tables to solve a problem, and Babbage became frustrated by errors in the tables. He threw the book at a wall and said, "I wish these calculations had been executed by steam!" Steam. Ada Lovelace referred to Babbage's Difference Engine as a machine that "weaves patterns of ideas". Alan Kay reminded us of the ultimate importance of what Turing taught us: If you don't like the machine you have, you can make the machine you want. AI -- the computing kind, which was the source of many of my own initial sparks -- has had two positive effects on the wider discipline. First, it has always offered a big vision of what computing can be. Second, even when it struggles to reach that vision, it spins off new technologies it creates along the way. At some point in the two days, Alan Kay chastised us. Know your history! Google has puts all seventy-five or so of Douglas Engelbart's papers at your fingertips. Do you even type the keywords into the search box, let alone read them? About Computing A common thread throughout the workshop was, what are the key ideas and features of computing that we should not lose as we move forward? There were some common answers. People want to solve real problems for real people. They want to find ideas in experience and applications. Another was the virtue of persistence, which one person characterized as "embracing failure" -- a twisted but valuable perspective. Yet another was the idea of "no more black boxes", whether hardware or software. Look inside, and figure out what makes it tick. None of these are unique to CS, but they are in some essential to it. Problem solving came up a lot, too. I think that people in most disciplines "solve problems" and so would claim problem solving as an essential feature of the discipline. Is computer science different? I think so. CS is about the process of solving problems. We seek to understand the nature of algorithms and how they manipulate information. Whichever real problem we have just solved, we ask, "How?" and "Why?" We try to generalize and understand the data and the algorithm. Another common feature that many thought essential to computing is that it is interdisciplinary. CS reaches into everything. This has certainly been one of the things that has attracted me to computing all these years. I am interested in many things, and I love to learn about ideas that transcend disciplines -- or that seem to but don't. What is similar and dissimilar between two problems or solutions? Much of AI comes down to knowing what is similar and what is not, and that idea held my close attention for more than a decade. While talking with one of my table mates at the summit, I realized that this was one of the biggest influences my Ph.D. advisor, Jon Sticklen, had on me. He approached AI from all directions, from the perspectives of people solving problems in all disciplines. He created an environment that sought and respected ideas from everywhere, and he encouraged that mindset in all who studied in his lab. Programming While I respect Denning's dissatisfaction with the idea that computer science == programming, I don't think we should lose the idea of programming whatever we do to reinvigorate computing. Whatever else computing is, in the end, it all comes down to a program running somewhere. When it was my turn to describe part of my vision for the future of computing, I said something like this:
When they have questions, children will routinely walk to the computer and write a program to find the answers, just as they now use Google, Wikipedia, or IMDB to look up answers.
I expected to have my table mates look at me funny, but my vision went over remarkably well. People embraced the idea -- as long as we put it in the context of "solving a problem". When I ventured further to using a program "to communicate an idea", I met resistance. Something unusual happened, though. As the discussion continued, every once in a while someone would say, "I'm still thinking about communicating an idea with a program...". It didn't quite fit, but they were intrigued. I consider that progress. Closing At the end of the second day, we formed action groups around a dozen or so ideas that had a lot of traction across the whole group. I joined a group interested in using problem-based learning to change how we introduce computing to students. That seemed like a moment when we would really get down to business, but unfortunately I had to miss the last day of the summit. This was the first week of winter semester classes at my university, and I could not afford to miss both sessions of my course. I'm waiting to hear from other members of my group, to see what they discussed on Wednesday and what we are going to do next. As I was traveling back home the next day, I thought about whether the workshop had been worth missing most of the first week of my semester. I'll talk more about the process and our use of time in a later entry. But whatever else, the summit put a lot of different people from different parts of the discipline into one room and got us talking about why computing matters and how we can help to change how the world thinks -- and talks -- about it. That was good. Before I left for California, I told a colleague that this summit held the promise of being something special, and that it also bore the the risk of being the same old thing, with visionaries, practitioners, and career educators chasing their tails in a vain effort to tame this discipline of ours. In the end, I think it was -- as so many things turn out to be -- a little of both. -----