Abstract
The future generality of technologies is hard to determine. The sources of these difficulties lie not only in technological factors, but also cognitive and organizational ones. However, with the advent of artificial intelligence (AI), can machine learning (ML) techniques be used to predict general purpose technologies? We find that an ensemble of deep learning models that analyze both the text of patents and their bibliometric information can ex-ante identify such technologies, accurately identifying 80 of the top 100 high generality patents in the hold-out sample. This ability to identify and adopt promising general technologies early in nascent stages can be highly valuable for firms and society as a whole, with implications for firm competitive advantage as well as national technology policy and R&D strategies.
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