A recent Wall Street Journal article was entitled “Business Schools Are Going All In on AI.” It says: “Blake Bergeron, a 27-year-old M.B.A. student at Columbia, used generative AI to brainstorm new business ideas for a project last fall. One it returned was a travel service that recommends destinations based on a person’s social networks, pulling data from their friends’ posts. Bergeron’s team asked the AI to pressure-test the idea, coming up with pros and cons, and for potential business models.” Can a new travel service have the same impact on America’s productivity that big breakthroughs such as semiconductors, new drugs, and better crop yields had on productivity in the 20th century? Gary and I believe that the student didn’t pursue this line of questioning, and even if he had, the generative AI software wouldn’t have answered this question. Instead, the student and the AI addressed something else. According to the Wall Street Journal: “Bergeron said he noticed pitfalls as he experimented. When his team asked the generative AI tool for ways to market the travel service, it spit out a group of very similar ideas. From there, Bergeron said, the students had to coax the tool to get creative, asking for one out-of-the-box idea at a time.” We are not surprised that AI would be unable to understand the big picture of #innovation, focusing instead on one type of idea that lots of people have had in the last decade. After all, social media, travel, and thousands of other apps have been the focus of #startups, including those of unicorns, those valued at $1billion or more before they have gone public. And none of them have impacted on productivity and improvements in standard of living that are close to what innovations in semiconductors, drugs, and crop yield have accomplished. Gary and I have been writing about big #startup losses for years, losses that are far bigger than they were decades ago. Robert Gordon has been writing about slowing productivity growth for even longer, as have other economists. Our reference to semiconductors, drugs, and crop yield come from a famous article entitled Are Ideas Getting Harder to Find, in which the authors demonstrated that the cost of extending Moore’s Law, developing new drugs, and extending improvements in crop yields has risen over the last few decades. #Entrepreneurship programs, which have grown considerably over the last 30 years in American #universities, are supposed to address some of these issues. “They are supposed to help students create and commercialize new ideas for businesses, but it is unclear whether, like the presence of libraries in some neighborhoods, their successes are more a reflection of the students who take these courses than of the courses themselves. Outsourcing entrepreneurship to #AI is not likely to fix the problem.” #technology #hype #artificialintelligence
A recent Wall Street Journal article was entitled “Business Schools Are Going All In on AI.” It says: “Blake Bergeron, a 27-year-old M.B.A. student at Columbia, used generative AI to brainstorm new business ideas for a project last fall. One it returned was a travel service that recommends destinations based on a person’s social networks, pulling data from their friends’ posts. Bergeron’s team asked the AI to pressure-test the idea, coming up with pros and cons, and for potential business models.” Can a new travel service have the same impact on America’s productivity that big breakthroughs such as semiconductors, new drugs, and better crop yields had on productivity in the 20th century? Gary and I believe that the student didn’t pursue this line of questioning, and even if he had, the generative AI software wouldn’t have answered this question. Instead, the student and the AI addressed something else. According to the Wall Street Journal: “Bergeron said he noticed pitfalls as he experimented. When his team asked the generative AI tool for ways to market the travel service, it spit out a group of very similar ideas. From there, Bergeron said, the students had to coax the tool to get creative, asking for one out-of-the-box idea at a time.” We are not surprised that AI would be unable to understand the big picture of #innovation, focusing instead on one type of idea that lots of people have had in the last decade. After all, social media, travel, and thousands of other apps have been the focus of #startups, including those of unicorns, those valued at $1billion or more before they have gone public. And none of them have impacted on productivity and improvements in standard of living that are close to what innovations in semiconductors, drugs, and crop yield have accomplished. Gary and I have been writing about big #startup losses for years, losses that are far bigger than they were decades ago. Robert Gordon has been writing about slowing productivity growth for even longer, as have other economists. Our reference to semiconductors, drugs, and crop yield come from a famous article entitled Are Ideas Getting Harder to Find, in which the authors demonstrated that the cost of extending Moore’s Law, developing new drugs, and extending improvements in crop yields has risen over the last few decades. #Entrepreneurship programs, which have grown considerably over the last 30 years in American #universities, are supposed to address some of these issues. “They are supposed to help students create and commercialize new ideas for businesses, but it is unclear whether, like the presence of libraries in some neighborhoods, their successes are more a reflection of the students who take these courses than of the courses themselves. Outsourcing entrepreneurship to #AI is not likely to fix the problem.” #technology #hype #artificialintelligence https://lnkd.in/gjQbn9aA