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Degree holders are shifting tech hubs and affordability

(TECH NEWS) Tech hubs are shifting as degree holders move, but it’s causing some other issues and raising some interesting questions about the future of jobs

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Bloomberg recently announced their annual “Brain” Indexes. The indexes are an annual reckoning of STEM (Science, Technology, Engineering and Mathematics) jobs and degree holders. The “Brain Concentration Index” approximates the number of people working full time in computer, engineering, and science jobs (including math and architecture.) It measures the median earnings for people in those jobs. It also counts how many people have a bachelor’s degree in a STEM field, or an advanced degree of any kind. It blends those things together to determine how “brainy” a city is.

Since they started in 2016, Boulder, CO has been at the top of the list. This year it’s followed by San Jose, CA, which many people might expect to be at the top. Many of the more surprising cities, like Ann Arbor, MI, Ithaca, NY, and even Lawrence, KS, are bolstered by the presence of a strong university.

It’s an interesting methodology. It’s worth noting that anyone with an advanced degree, whether it’s an MBA, a law degree, or a Ph.D. in literature, contributes to which city is a “tech hub.” It’s also worth noting how expensive many of these places are to live.

If you follow this kind of national data collection at all, you may also know that Boulder is one of the least-affordable cities in the country. So is the San Jose/Sunnyvale/Santa Clara metro area, with a median home price of 1.25 million dollars and a median household income of $117,474. (That means that the average mortgage is more than half of the average paycheck). However many people tech hubs like San Jose and San Francisco attract, they’re also hemorrhaging talent. Every day, 8 Californians move to Austin. Of the people who stay, more than half are thinking of moving.

They aren’t doing that for fun. As much flak as Californians get for gentrifying places like Austin, they’re being megagentrified out of their own homes. As salaries rise and CEO gigs attract the wealthy (and turn them into the Uberwealthy), the people who wait on tables or teach their children can’t afford to stay there anymore.

Speaking of people leaving, Bloomberg also measured what they call “brain drain,” the flow of advanced degree holders out of cities. They pair that with a decline in white-collar jobs and a decline in STEM pay to come up with their annual list. It includes places like Lebanon, PA and Kahului, HI.

All in all, it’s interesting information. But there are other factors at work that it can’t speak to. What does wage stagnation in the U.S. mean for the flow of education workers? If San Jose and San Francisco can be tech hubs based on the number of people with degrees, but people are still fleeing, what does that say about rankings like these? What human stories get lost in the shuffle? And is “tech hub” even something a city wants to be if that means running out of teachers (or making them sleep in garages)? Where does the next generation of tech hub workers come from?

Knowing the people behind the numbers makes it clear just what a mixed bag this is. Maybe we need more tech hubs like Lawrence, Kansas. Or maybe we need rent control. Or maybe we need to embrace remote work. Maybe there are no answers. As interesting as data like this is, there’s something sort of wistful about it, too.

Staff Writer, Garrett Steele is your friend. He writes lyrics, critique, and copy for ads, schools, health organizations, and more. He’s also a composer for film and video games, when he’s lucky. (One of his songs is an Xbox achievement!)

Tech News

Career consultants help job seekers beat AI robot interviews

(TECH NEWS) With the growth of artificial intelligence conducting the job screening, consultants in South Korea have come up with an innovative response.

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When it comes to resume screenings, women and people of color are regularly passed over, even if they have the exact same resume as a man. In order to give everyone a fair try, we need a system that’s less biased. With the cool, calculating depictions of artificial intelligence in modern media, it’s tempting to say that AI could help us solve our resume screening woes. After all, nothing says unbiased like a machine…right?

Wrong.

I mean, if you need an example of what can go wrong with AI, look no further than Microsoft’s Tay, which went from making banal conversation to spouting racist and misogynistic nonsense in less than 24 hours. Not exactly the ideal.

Sure, Tay was learning from Twitter, which is a hotbed of cruelty and conflict, but the thing is, professional software isn’t always much better. Google’s software has been caught offering biased translations (assuming, for example, if you wrote “engineer” you were referring to a man) and Amazon has been called out for using job screening software that was biased against women.

And that’s just part of what could go wrong with AI scanning your resume. After all, even if gender and race are accounted for (which, again, all bets are off), you’d better bet there are other things – like specific phrases – that these machines are on the lookout for.

So, how do you stand out when it’s a machine, not a human, judging your work? Consultants in South Korea have a solution: teach people how to work around the bots. This includes anything from resume work to learning what facial expressions are ideal for filmed interviews.

It helps that many companies use the same software to do screening. Instead of trying to prepare to impress a wide variety of humans, if someone knew the right tricks for handling an AI system, they could potentially put in much less work. For example, maybe one human interviewer likes big smiles, while the other is put off by them. The AI system, on the other hand, won’t waver from company to company.

Granted, this solution isn’t foolproof either. Not every business uses the same program to scan applicants, for instance. Plus, this tech is still in its relative infancy – a program could easily be in flux as requirements are tweaked. Who knows, maybe someday we’ll actually have application software that can more accurately serve as a judge of applicant quality.

In the meantime, there’s always AI interview classes.

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Google chrome: The anti-cookie monster in 2022

(TECH NEWS) If you are tired of third party cookies trying to grab every bit of data about you, google has heard and responded with their new updates.

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Google has announced the end of third-party tracking cookies on its Chrome browser within the next two years in an effort to grant users better means of security and privacy. With third-party cookies having been relied upon by advertising and social media networks, this move will undoubtedly have ramifications on the digital ad sector.

Google’s announcement was made in a blog post by Chrome engineering director, Justin Schuh. This follows Google’s Privacy Sandbox launch back in August, an initiative meant to brainstorm ideas concerning behavioral advertising online without using third-party cookies.

Chrome is currently the most popular browser, comprising of 64% of the global browser market. Additionally, Google has staked out its role as the world’s largest online ad company with countless partners and intermediaries. This change and any others made by Google will affect this army of partnerships.

This comes in the wake of rising popularity for anti-tracking features on web browsers across the board. Safari and Firefox have both launched updates (Intelligent Tracking Prevention for Safari and the Enhanced Tracking Prevention for Firefox) with Microsoft having recently released the new Edge browser which automatically utilizes tracking prevention. These changes have rocked share prices for ad tech companies since last year.

The two-year grace period before Chrome goes cookie-less has given the ad and media industries time to absorb the shock and develop plans of action. The transition has soften the blow, demonstrating Google’s willingness to keep positive working relations with ad partnerships. Although users can look forward to better privacy protection and choice over how their data is used, Google has made it clear it’s trying to keep balance in the web ecosystems which will likely mean compromises for everyone involved.

Chrome’s SameSite cookie update will launch in February, requiring publishers and ad tech vendors to label third-party cookies that can be used elsewhere on the web.

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Computer vision helps AI create a recipe from just a photo

(TECH NEWS) It’s so hard to find the right recipe for that beautiful meal you saw on tv or online. Well computer vision helps AI recreate it from a picture!

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Ever seen at a photo of a delicious looking meal on Instagram and wondered how the heck to make that? Now there’s an AI for that, kind of.

Facebook’s AI research lab has been developing a system that can analyze a photo of food and then create a recipe. So, is Facebook trying to take on all the food bloggers of the world now too?

Well, not exactly, the AI is part of an ongoing effort to teach AI how to see and then understand the visual world. Food is just a fun and challenging training exercise. They have been referring to it as “inverse cooking.”

According to Facebook, “The “inverse cooking” system uses computer vision, technology that extracts information from digital images and videos to give computers a high level of understanding of the visual world,”

The concept of computer vision isn’t new. Computer vision is the guiding force behind mobile apps that can identify something just by snapping a picture. If you’ve ever taken a photo of your credit card on an app instead of typing out all the numbers, then you’ve seen computer vision in action.

Facebook researchers insist that this is no ordinary computer vision because their system uses two networks to arrive at the solution, therefore increasing accuracy. According to Facebook research scientist Michal Drozdzal, the system works by dividing the problem into two parts. A neutral network works to identify ingredients that are visible in the image, while the second network pulls a recipe from a kind of database.

These two networks have been the key to researcher’s success with more complicated dishes where you can’t necessarily see every ingredient. Of course, the tech team hasn’t stepped foot in the kitchen yet, so the jury is still out.

This sounds neat and all, but why should you care if the computer is learning how to cook?

Research projects like this one carry AI technology a long way. As the AI gets smarter and expands its limits, researchers are able to conceptualize new ways to put the technology to use in our everyday lives. For now, AI like this is saving you the trouble of typing out your entire credit card number, but someday it could analyze images on a much grander scale.

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