In a comprehensive Q&A, Peter Denning, the editor-in-chief of Ubiquity, offers his thoughts on the future of computer science and how he has translated his unique insights into the design and execution of the Ubiquity mission. Denning discusses the art of making predictions about the future, noting that the most valuable predictions are typically those based on some sort of recurrence. Denning also offers thoughts on how to deal with a future that is inherently unpredictable and discusses how different approaches to innovation help to determine the future. Denning also offers background on new editorial features, such as the Ubiquity symposium, that enable a group of participants to explore a particular proposition.
In the face of all that uncertainty about the future, Denning says, the worst thing we can do is to become resigned and inactive. As Denning suggests, there are eight practices by which people influence the future by bringing about change in their communities. Uncertainty produces discomfort and disruption. Most of us would rather keep improving our lots in life and not have to put up with disruption. We see technology as progressive, always pulling the world in a better direction. Yet, trying to predict the future is a losing proposition. With few exceptions, such as predicting events with definite recurrences, we get it wrong. Denning also takes a closer look at technology projections, such as Moore's Law, and how they enable technologists to predict dramatic changes in specific industries. Most predictions are based on extrapolations of technology trends discernable for several years prior, he says.
While futurists may be right about the direction of technology, people's reactions and adaptations to technology are harder to gauge. With that in mind, Denning ruminates about the role of innovation and inventors in changing society's technology adoption patterns. We are not hurting for ideas as much as we are for people skilled in bringing about adoption of ideas. Denning also explores the basic underpinnings of chaos theory, gives his opinion on trend extrapolations and scenarios, and emphasizes the value of learning from failures.
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