Santa Fe Institute

Bio

Ever since I can remember I've been fascinated by scientific and technological progress. I'm especially interested in those aspects that we can measure and use for technology forecasting. Examples include how performance improves over time (such as Moore's law) or how costs are coming down as a function of cumulative production volume in industry (that goes by many names: learning curve, experience curve, performance curve, progress function, or Wright's law). My short-term goal is to collect the data necessary for our research group to conceptualize a general model of technology evolution and explore the connections with biological evolution. Possible application areas include information technologies (both hardware and software) and energy technologies (with a special interest in renewable energy). My long-term goal is to develop a data-driven, predictive science of the future that I like to call Quantitative Futurism. A fundamental question is what is predictable and what is not, and how to distinguish the one from the other. Another important issue is to be able to provide error estimates for the forecasts. Computer experiments can help explore multiple scenarios and quantify the uncertainty in the projections.