Nearly 30% of professionals believe their skills will be redundant in the next 1-2 years, if they aren’t already, with another 38% stating they believe their skills will be outdated within the next 4-5 years. – LinkedIn Economic Graph
Has anyone told the students who are putting down 10K for graduate certificates or taking on $90k in debt to pursue uncertain career paths that are at risk for AI disruption? Who’s working to make sure that these programs – especially those outside of elite schools – prepare students for emerging jobs?
Who is responsible for that discussion? Admissions? Career services? Deans?
UPDATE: Thanks for your emails! If you’re interested in career services support for international students, check out Get Hired: The US Job Search for International Students. For $29/month, international students get access to online career training courses designed specifically for them.
I’m breaking from my usual posts on algorithms taking over our lives to share insights from the new report by WENR: Career Prospects and Outcomes of U.S.-Educated International Students: Improving Services, Bolstering Success. If you’re new to working with international students it’s worth the full read to better understand your international students’ career ambitions. If you’re a career services director the data can help you build out a stronger international student engagement strategy and support your training efforts. I work with international students through my company GlobalMe School. I’ve got recommendations aplenty to add to this report. So fair warning: #longread ahead (or at least longer than what I normally write. I’m a proponent of lazy blogging)
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Algorithms are everywhere. They make decisions for us and most the time we don’t realize it. Remember the United story where the passenger was violently ripped out of his seat? The decision to remove that specific was the result of an algorithm.
As more algorithms shape our life we must ask questions like who’s designing these algorithms, what assumptions do these designers make, and what are the implications of those assumptions?
So I’m giving a huge shout out to the podcast 99% Design for their episode on how algorithms are designed.
The Age of the Algorithm
Featuring the author of Weapons of Math Destruction, the episode takes a look at the subjective data used for algorithms that determine recidivism rates and reject job applicants. The examples used and questioned raised in this episode should have us asking more questions about the people and companies designing the algorithms that run in the background of our online and offline lives.
“Algorithms … remain unaudited and unregulated, and it’s a problem when algorithms are basically black boxes. In many cases, they’re designed by private companies who sell them to other companies. The exact details of how they work are kept secret.”