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Context and why it matters that AI doesn’t have a clue what it is

(TECHNOLOGY NEWS) AI is learning and growing faster than ever. However, one flaw that AI cannot seem to get around is context.

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Contextual oops

Let’s start with a story. This might be my favorite story in all the annals of geekdom, which is saying something for someone whose literal job is “purveyor of geeky stories.” On March 1, 1990, in AG’s beloved hometown of Austin, Texas, the United States Secret Service raided a “suspected ring of hackers.”

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It was a full-on, TV level bust: armed agents broke locks, tore up files, carted off computers, even did that “simultaneous raid so the masterminds can’t get word to their button men” thing at the home of one of the people involved. Hooray! The cops beat the bad guys! Not so much.

Right reason, wrong time

Three years and a court decision later, the Secret Service had to fess up: they’d raided a game company. A tabletop game company. As in paper and dice, neither noted for being connected to the Internet. They weren’t hackers. At all. They’d written a game about hackers, and in the grim darkness of 1990, the Secret Service was fuzzy on the difference. That poor guy who got his very own private raid? He wrote their cyberpunk setting, and had dared to do research on the subject.

That’s as close as anyone there got to l33t h4x0r doings, and it turned out to be close enough for armed cops in a private citizen’s living room without an invitation.

There’s a halfway happy ending to that story, involving money paid to the company, an epic tonguelashing from a circuit court judge, and the founding of the leading advocacy organization for digital privacy rights, but the point is the Secret Service. Their actions weren’t malicious. Stupid, yes. Hilarious in hindsight, absolutely. Catastrophic to a small business innocent of any wrongdoing, big time. But they thought they were doing the right thing. They just Did It Wrong.

Doing It Wrong

As AI saturates our lives, I reflect, as I often do, on Doing It Wrong. Fundamentally, that ridiculous case came down to a misunderstanding of context. The Secret Service didn’t have the background or expertise to differentiate between hacking and a game about hacking. That’s absurd, that’s their job, but they didn’t.

Hacking, at least most hacking, is still a bad thing.

As simultaneously hilarious and horrible as it is to pull the equivalent of yanking a guy off his couch and charging him with murder for shooting someone in “Call of Duty,” shooting people is generally undesirable outside a fictional context.

Does AI know that?

Can AI make the distinction between “die, [expletive here]” in your favorite combat simulator and “die, [expletive here]” when an unpleasant person attempts to end the pizza guy with a fork? Because the Secret Service couldn’t, and they were human. Humans are pre-built for context. Computers have to be made that way, and it’s usually really hard. That’s a shade worrisome, what with AI growing like kudzu and the data it collects being used for everything from market analysis to, yes, murder investigations.

So consider this a gentle reminder that even the smartest computer is still fundamentally a box of switches.

Zero and one, off and on, puts certain limitations on a binary system’s ability to comprehend the complex, subjective, frankly weird human condition. Getting AI to understand context is a top priority for some of the best minds in computer science, but while they’re working we h. sapiens will have to double down on patience and nuance, because one of our most pervasive tools won’t be very good at either. They may never be as good at it as we are, though three years ago I’d have said that about go.

Mind your audience

For at least the next few years, everyone from multinational corporations and national governments down to the data junkies and media consumers reading this article will need to exercise some extra caution when it comes to AI and its assessment of people and their doings.AI doesn’t understand us quite yet.

It is, if not blind, at least a little nearsighted when it comes to context, which is basically the most important human thing.Click To Tweet

We’re going to have to keep doing that part ourselves. Fail in this, and you risk becoming your own hilarious Doing It Wrong cautionary tale. Nobody wants that.

This story originally ran on July 26, 2017.

Matt Salter is a writer and former fundraising and communications officer for nonprofit organizations, including Volunteers of America and PICO National Network. He’s excited to put his knowledge of fundraising, marketing, and all things digital to work for your reading enjoyment. When not writing about himself in the third person, Matt enjoys horror movies and tabletop gaming, and can usually be found somewhere in the DFW Metroplex with WiFi and a good all-day breakfast.

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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Tech News

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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Tech News

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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