Just outstanding. Joy Buolamwini, the founder of notflawless.ai, delivers a spoken word poem on the reality of bias in AI. This organization is a must follow resource for anyone working with AI with topics on the dangers of facial recognition technology and police use of facial recognition tech. Also includes links to books and talks on the subject.
Imagine if every emerging AI engineer read this resources on this site.
“Workers increasingly see assignments and wages doled out by artificial systems rather than human managers, and have to rely on AI, not HR, when things go wrong. According to tech experts, the rise of algorithms is changing not only how we earn a living, but who gets access to jobs and other opportunities — if their data checks out — or not.” – Forbes, Algorithms And ‘Uberland’ Are Driving Us Into Technocratic Serfdom
I rarely link to Forbes pieces because their ad game is excessive (even with my ad blocker) but the quote above captures the workplace transformation quite succinctly. From spying on workers, to replacing managers with AI, to using questionable data and AI insights to determine who gets hired, the world of work is changing in ways that need examining fast.
The Forbes article was referencing the book UBERLAND: How Algorithms Are Rewriting The Rules Of Work, which has just rocketed to the top of my reading list. Until then, I’m definitely looking out for the author on the podcast circuit.
Students are looking for ways to beat AI recruiting tools like HireVue. And now coaching services are offering help:
“A start-up called Finito claims it can coach candidates to beat AI for as long as it takes them to get a job — but at a total cost of nearly £9,000. Candidates are steered through interview dry runs and get tips on what skills are needed to get past robot selections, in sectors including finance, public relations and the arts. They then watch footage back to spot foibles that could be flagged up as nerves.”
Add helping students beat the AI recruiting process to the list of things career services needs to upskill.
Much of the AI and highered interwebs were ablaze in the last week with MIT’s announcement that they’re building an AI college with a cool $1 billion in funding. (side note: I wish I could get into that future interdisciplinary college. Perhaps I’ll just have to wait for the inevitable exec leadership program that comes out of it.)
But I’m far more excited by this news: the African Institute for Mathematical Sciences is launching an African Masters in Machine Intelligence programme. And it’s only 10 months long. Even better? This:
“There are two Rwandans in the first cohort of 35 students, 44 per cent being women – another first at AIMS.”
The students will graduate with a Masters in Mathematical Science specializing in machine learning. The program is backed by tech giants, Google and Facebook. It’s the first of it’s kind in the country.
Maybe Americans might want to considering getting their masters in artificial intelligence abroad. Imagine the perspective they’d gain. Imagine the value they could add to an organization. And they’d do it in less time than a traditional American degree.
A Nigerian colleague shared the article on LinkedIn reminding me yet again of the immense value of global networks.
How much employee data collection is too much? Because it seems our employers – or at least the big corporate ones – want every single piece of your personal data. Is there any option for pushing back on your employer’s personal data grab?
The Kaiser Family Foundation’s annual review of employer-based insurance shows that 21% of large employers collect health information from employees’ mobile apps or wearable devices, as part of their wellness programs — up from 14% last year.
Google definition of plagiarism so we’re all clear. Also the root is kidnapper!
Last week marked a pivotal moment in my entrepreneurial journey: a company I’ve long admired in international education stole my company’s content. The company, GoinGlobal, a global career company, stole my original content from www.internationalstudentcareers.com. Then they repurposed my original content as a blog post, directly copying sentences from my content and passing them off as their own.
The first offense was an original long form article from www.internationalstudentcareers.com on how international students find jobs in the US. I wrote the book, How to Get a Job in the USA, based on this article.
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I originally wrote this as a guest post on Switchboard, an alumni platform that connects students and alumni. Switchboard is one of the few ed-tech companies who understand the nuances of higher education transformation. Their higher education innovation fellowship and upcoming conference ListenUpEDU are models for professional development in higher education. And they kill it with good advice for the future of alumni relations.
By now we’ve all seen the headlines about the future of work. Beyond headlines about job-stealing robots, the reality is that machine learning and artificial intelligence technology are disrupting career paths. According to the World Economic Forum’s latest report, The Future of Jobs 2018, AI will create 58 million new jobs within the next five years. In a 2017 Deloitte report, Catch the Wave: The 21st Century Career, the authors note that only 19 percent of companies even have traditional career pathways. The future of work is filled with ambiguity and non-linear career paths.
With so much change ahead, career centers need to rethink outdated career training models. Career centers’ primary focus should not be to prepare students for linear careers anymore. Instead, they should prepare students for a lifetime of career changes. Navigating these ambiguous career paths requires students and alumni to embrace upskilling and lifelong learning. This same advice applies to careers services staff too.
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Alexa might be checking you into your next hotel room:
David Autor, an economist at M.I.T., says it is plausible to foresee a future in which — as airlines have done — hotels deploy humans to tend to elite guests and automated systems for everybody else. Workers generate costs well beyond their hourly wage, Professor Autor argued. They get sick and take vacations and require managers. “People are messy,” he noted. “Machines are straightforward.”