Beyond AI Exposure: Which Tasks are Cost-Effective to Automate with Computer Vision?

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 release of the paper was accompanied by media coverage, including:

• MIT Sloan: Automation may be possible — but when will businesses want to do it?
• TechCrunch: New MIT CSAIL study suggests that AI won't steal as many jobs expected
• Forbes: AI will not steal your job anytime soon, say MIT researchers
• Forbes again: Business Tech Roundup: AI voice is coming for Gmail
• CNN: AI and the labor market: MIT study findings
• TIME: AI job replacement fears and the MIT study
• Boston Globe: AI's impact on jobs according to MIT
• Bloomberg: Humans still cheaper than AI in vast majority of jobs, MIT finds
• Yahoo! Finance: Humans still cheaper than AI in vast majority of jobs
• Fortune: AI, jobs, and costs: insights from MIT study
• CNET: AI and you: ChatGPT helps author win literary prize, Taylor Swift isn't pitching cookware
• The Register: MIT AI jobs report overview
• New Scientist: AI costs too much to automate vision-related jobs for now
• Marketplace: AI might not take your job after all
• Politico: AI investors are running the numbers
• Business Insider: AI probably will not take your job just yet
• CNBC: MIT study: Using AI to replace humans may be too expensive
• CNET again: AI and you - the job debate continues, social media isn't so swift handling porn deepfakes

‍

‍

‍

‍