futuretech January 22, 2024: “Neil Thompson along with Maja S. Svanberg and Wensu Li from the MIT FutureTech, Martin Fleming from The Productivity Institute, and Brian C. Goehring from IBM’s Institute for Business Value, have published a new article. This article introduces an innovative AI task automation model. It offers an end-to-end assessment framework, focusing on determining the necessary technical performance for tasks, defining the characteristics of AI systems capable of this performance, and making economic decisions about their development and deployment”

For a comprehensive overview of their research and insights, you can access the article. “The faster AI automation spreads through the economy, the more profound its potential impacts, both positive (improved productivity) and negative (worker displacement). The previous literature on “AI Exposure” cannot predict this pace of automation since it attempts to measure an overall potential for AI to affect an area, not the technical feasibility and economic attractiveness of building such systems. In this article, we present a new type of AI task automation model that is end-to end, estimating: the level of technical performance needed to do a task, the characteristics of an AI system capable of that performance, and the economic choice of whether to build and deploy such a system. The result is a first estimate of which tasks are technically feasible and economically attractive to automate – and which are not. We focus on computer vision, where cost modeling is more developed. We find that at today’s costs U.S. businesses would choose not to automate most vision tasks that have “AI Exposure,” and that only 23% of worker wages being paid for vision tasks would be attractive to automate. This slower roll-out of AI can be accelerated if costs falls rapidly or if it is deployed via AI-as-a-service platforms that have greater scale than individual firms, both of which we quantify. Overall, our findings suggest that AI job displacement will be substantial, but also gradual – and therefore there is room for policy and retraining to mitigate unemployment impacts.”