This is good from Harvard's Managing the Future of Work Joseph Fuller : ""AI will create the data that will allow us to do a whole lot more skills-based hiring by eliminating the taxonomy problem we have in the U.S. We don’t have the 8K employer committees in Switzerland. There are literally 8K committees that define what are the skills associated with each major job. And we don’t have federally controlled K-12 education, which provides some countries with a leg up. But when you’ve got AI looking out there, and a program director at company X and a project manager at company Y and a director at company Z—the people who occupy those jobs per LinkedIn all look pretty similar. And the job descriptions of those jobs have the same keywords. They’re really the same job.
Let’s say I’m running a multi-hundred thousand employee company, UPS let’s say. Now I can say what are the attributes of people who got promoted rapidly. And it isn’t, they went to Harvard or they went to Caltech or something. You’ll find, by the way, often they had highly rated supervisors. That’s going to allow us to match skills and experiences more accurately and to not rely on proxies like degrees or grade point averages or even the proxy of what someone currently makes or how fast they’ve gotten promoted on their résumé, but more legitimately based in an examination of what backgrounds seem to correlate with success and help with the upward mobility questions." https://workshift.opencampusmedia.org/the-future-of-opportunity-a-conversation-with-harvards-joseph-fuller/?utm_source=the-job.beehiiv.com&utm_medium=newsletter&utm_campaign=how-workers-rise
JHU takes a research-first approach: "In addition to the three keynote presentations, the symposium included brief lightning talks by graduate students across many of the university's divisions, along with a panel discussion moderated by Stephanie Hicks, an associate professor of biomedical engineering and biostatistics in the Bloomberg School of Public Health. A poster session followed in Shriver Hall's Great Hall and Glass Pavilion, with 62 faculty members and graduate students presenting AI-related research. Here, topics ranged from using AI to aid everything from medical imaging and gene delivery to airplane safety and social media analysis." https://hub.jhu.edu/2023/10/04/ai-x-foundry-fall-2023-symposium/
This is good from Harvard's Managing the Future of Work Joseph Fuller : ""AI will create the data that will allow us to do a whole lot more skills-based hiring by eliminating the taxonomy problem we have in the U.S. We don’t have the 8K employer committees in Switzerland. There are literally 8K committees that define what are the skills associated with each major job. And we don’t have federally controlled K-12 education, which provides some countries with a leg up. But when you’ve got AI looking out there, and a program director at company X and a project manager at company Y and a director at company Z—the people who occupy those jobs per LinkedIn all look pretty similar. And the job descriptions of those jobs have the same keywords. They’re really the same job.
Let’s say I’m running a multi-hundred thousand employee company, UPS let’s say. Now I can say what are the attributes of people who got promoted rapidly. And it isn’t, they went to Harvard or they went to Caltech or something. You’ll find, by the way, often they had highly rated supervisors. That’s going to allow us to match skills and experiences more accurately and to not rely on proxies like degrees or grade point averages or even the proxy of what someone currently makes or how fast they’ve gotten promoted on their résumé, but more legitimately based in an examination of what backgrounds seem to correlate with success and help with the upward mobility questions." https://workshift.opencampusmedia.org/the-future-of-opportunity-a-conversation-with-harvards-joseph-fuller/?utm_source=the-job.beehiiv.com&utm_medium=newsletter&utm_campaign=how-workers-rise
WaPo, w/ similar sentiments: https://www.washingtonpost.com/opinions/2023/12/12/ai-chatgpt-universities-learning/ "There is no better place to see the promise and the peril of generative artificial intelligence playing out than in academia. "
JHU takes a research-first approach: "In addition to the three keynote presentations, the symposium included brief lightning talks by graduate students across many of the university's divisions, along with a panel discussion moderated by Stephanie Hicks, an associate professor of biomedical engineering and biostatistics in the Bloomberg School of Public Health. A poster session followed in Shriver Hall's Great Hall and Glass Pavilion, with 62 faculty members and graduate students presenting AI-related research. Here, topics ranged from using AI to aid everything from medical imaging and gene delivery to airplane safety and social media analysis." https://hub.jhu.edu/2023/10/04/ai-x-foundry-fall-2023-symposium/
One University's approach; https://www.cavalierdaily.com/article/2023/11/u-va-futures-initiative-tackles-questions-of-generative-a-i-the-future-of-higher-education . Not fast, but very University-ish; "One way the University has attempted to address the technological advance of A.I is with a Generative A.I. Task Force, which has hosted a series of town halls to collect input on the topic from the University community. "