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Opinion Editorials

Should you be scared or fascinated by self-learning AI? Answer: both

(EDITORIAL) As Google’s AI begins to teach itself, how should we non-robot humans react to the self-educating tech?

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Future technology

According to iRobot and Asimov’s three laws, there are only 4 results that can happen from a computer/robot driven future; a Balanced World, a Frustrating World, a Killbot Hellscape or a Frustrating Standoff.

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Now, if you’re like me and have only watched the movie iRobot you’re probably wondering what exactly I’m on about. Good question. I have an answer (well sort of), I promise.

AI Inception in real life?

Recently the creators of Google Home announced that Google’s AI had begun to generate it’s own AI. While on the surface, the sentence, “Google’s AI has begun to generate its own AI” is utterly terrifying.

If you look just a tad deeper, is just about as alarming as burning your morning toast.

You see Google’s AI is actually just a series of algorithms that predict outcomes and then are typically layered on top of one another to create what are called neural networks.

Again, what does this mean?

Well, think of it this way: A Google Home is a machine that can predict results based on a past data set and thus is only one network. Multiple Google AIs are just that – multiple prediction machines working on top of each other, narrowing down the field as much as possible creating in essence a cyber-brain… a neural network… a very precise prediction.

You might have heard the term Auto ML thrown around in the AI conversation. ML (meaning Machine Learning) is used to create neural networks.

ML historically has been a computer, given a data set and then asked to perform a prediction exactly as humans have, but in a much smaller time frame- i.e. data processing on speed. These neural networks created by Auto ML are pretty self-explanatory. They are data sets forced into a computer that is given the capabilities to analyze each data set separately and then against one another and find specific outliers, commonalities, etc.

So Google AI hasn’t really created it’s own AI, it’s just gotten exponentially better at doing what humans do in a fraction of the time.

The tough questions

Where all of this AI business starts to get a bit dodgy is when we can’t figure out how a machine taught itself something or how it came to that rationale.

For instance, the algorithms in the Nvidia autonomous car test. Nvidia is a tech company that provides cars with computer chips that have learned how to drive by watching a human driver.

Learning from humans is all well and good until you provide some hypotheticals.

Hypotheticals such as what if one day the car decides not to stop at a red light and instead hits other cars and pedestrians. The engineers behind the chip and the car can’t explicitly outline how the actions are learned and thus can’t provide any information on how or why an action takes place.

In another instance, 700,000 patient records of actual patients of Mount Sinai Hospital in New York city were put into a computer for analysis. More or less to confirm what doctors had already established but what the computer spit out was beyond what people thought capable. This test, Deep Patient, provided additional diagnoses including predicting schizophrenia, which is a notoriously hard psychiatric disorder to diagnose with relative ease.

Where we’re at

So has google AI created it’s own AI? Has a self driving car learned to drive like a human from a human? Has a computer gotten better at diagnosing mental disorders than a psychologist? No, yes and yes. All of these AI ideas are really quite simple.

They are given input and produce an output.

Where the problem lies is in our abilities to understand how they got from the source to the conclusion. It is like failing math class all over again. One week you get it and the next week, you’re clueless. Google’s creation of it’s own AI is really just its ability to stack on top of itself with precision and ease. As for Nvidia and Deep Patient, it is layered data sets of top of data sets.

Precise to a fault

All of these things, in truth, didn’t just create themselves nor did they create themselves from the data sets we gave them. They created what we asked for, just a much more precise version than we predicted.

As humans, we expect to understand data and trust it, and the next phase of AI will have to include production of rational by these AI machines so we don’t collectively fear it.

#FollowingOrders

Pam Garner is a Staff Writer for The American Genius with a bachelor's degree from the University of Texas, currently pursuing her master's degree in graphic and web design. Pam is a multi-disciplined creative who hopes to one day actually finish her book on all of her crazy adventures.

Opinion Editorials

The *actual* reasons people choose to work at startups

(EDITORIAL) Startups have a lot going for them, environment, communication, visible growth. So it is easy to see why they are so popular now

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Startups are perpetually viewed as the quintessential millennial paradise with all of the accompanying perks: flexible hours, in-house table tennis, and long holidays. With this reputation so massively ingrained in popular perception of startups, is it foolish to think that their employees actually care about the work that startup companies accomplish?

Well, yes and no.

The average startup has a few benefits that traditional business models can’t touch. These benefits often include things like open communication, a relaxed social hierarchy, and proximity to the startup’s mission. That last one is especially important: While larger businesses keep several degrees of separation between their employees and their end goals, startups put the stakes out in the open, allowing employees to find personal motivation to succeed.

When an employee can find themself personally fulfilled by their work, that work reaps many of the benefits of the employee’s dedication, which in turn helps the startup propagate. Many aspiring startup employees know this and are eager to “find themselves” through their work.

Nevertheless, the allure of your average startup doesn’t always come from the opportunity to work on “something that matters.”

Tiffany Philippou touches on this concept by pointing out that “People come to work for you because they need money to live… [s]tartups actually offer pretty decent salaries these days.”

It’s true that many employees in their early to late twenties will likely take any available job, so assuming that your startup’s 25-and-under employee base is as committed to finding new uses for plastic as you are may be a bit naïve—indeed, this is a notion that holds true for any business, regardless of size or persuasion.

However, startup experience can color a young employee’s perception of their own self-worth, thus allowing them to pursue more personally tailored employment opportunities down the road—and that’s not a bad legacy to have.

Additionally, startups often offer—and even encourage—a level of personal connection and interactivity that employees simply won’t find in larger, more established workplaces. That isn’t symptomatic of startups being too laid-back or operating under loosely defined parameters; instead, it’s a clue that work environments which facilitate personalities rather than rote productivity may stand to get more out of their employees.

Finally, your average startup has a limited number of spots, each of which has a clearly defined role and a possibility for massive growth. An employee of a startup doesn’t typically have to question their purpose in the company—it’s laid out for them; who are we to question their dedication to fulfilling it?

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Opinion Editorials

People saying “I love you” at work casually – yay or nay?

(EDITORIAL) Is saying “I love you” in the workplace acceptable in the current harassment and lawsuit climate? Let’s take a look at the factors.

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Anyone who works in “The Office” knows sometimes there is a failure to communicate. Per email conversation, context can get lost in translation.

So, why then, in the age of the Me Too Movement, are coworkers saying: I Love You?

I’m guessing it’s thanks to our digital lifestyle?

No, I’m not a Boomer. Thank you very much. That’s a different editorial. But, I’ve been working since way back in the day. A time when we wore tennis shoes with nylons. Wait, that’s still a thing?

Alas, I digress.

If we consider the culture of work, particularly in the case of some start-ups, it’s not uncommon for there to be beer in the workplace, casual dress – meaning you have clothes on – and possibly a more youthful expectation around communication.

So, f*ck yeah, dude, I love you!

With the use of workflow apps like Slack, where people can text you – while on the toilet, no less. I mean, who hasn’t told a colleague, “OMG! You are a f@cking ?” after dealing with a challenging situation/customer/boss/client and that colleague comes to the rescue.

Just me? Oops.

Maybe it started back with the I Love You Man commercial, which also became the title of a bromance.

If the bros can have their bromance, then why can’t we all say those three words in the workplace?

I’m not gonna spoil the party and say never. I’m just going to suggest some things are better left unsaid.

First, words are powerful.

Because this is the era of Me Too, it’s easy for there to be misinterpretation. What if a woman says it to a male colleague. A boss says to a much junior employee.

Can you say harassment?

One of my former managers didn’t even like me saying her name. I can’t imagine what she’d do if I said: “I love you.”

But, here’s a real reason. People are happy with us one day and not the next.

Keeping it chill and professional is important. For example, I once called my co-worker – and very good friend – a nasty Spanish word and it almost resulted in a knife fight. What I learned is one day you are joking around and your friend isn’t.

Second, a laissez-faire attitude toward communication can become second nature. You can’t be accidentally telling your client, you love them, now can you? I mean, beyond being authentic, those words mean a lot to some people, just tossing them about shows a real lack of judgment and can result in an extremely negative response.

Which leads me to my last point.

“Et, tu Cheryl”

One company I worked at hired Gallup to do a survey of staff. One of the questions was about having a work BFF, which is important in the workplace. Often we have our work husband or wife or sister, even. We all need someone we can lean on.

In the workplace, depending on the culture and environment, it may be a good place to keep it 100 or, if too toxic, a better place to fake it. Even people who seem to be on your side might be just waiting to pounce.

Get too close, say the wrong thing and Cheryl gets your office with the window and the red stapler too.

All I’m saying is keep it real, but maybe not too real.

Oh, and btw, I <3 U.

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Opinion Editorials

Audi paves the way for how to thoughtfully reduce a workforce

(BUSINESS NEWS) Audi has a new electric car plan that will eliminate 9,500 employees…but in a shocking twist, we’re not even mad. WATT’s going on here?

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Audi E-tron

12 billion motivational posters/yoga tops/specialty ziploc bags can’t all be wrong: Positive change always comes with loss.

For German Audi workers, the company shifting gears to focus on manufacturing electric vehicles will see employee losses to the tune of 7.5k people being Audi of a job there. In the next five years, another 2,000 jobs are expected to get the axe as well.

So they should be panicking, right? Audi workers should mask up and be out in the streets?

Well, considering the general state of the world, yes. But if we’re isolating to just this change, no!

See, Audi’s not actually shoving people out of the door to make room for younger, sexier, more fuel-efficient staff. The jobs they’re cutting are going to be cut due to employees leaving on their own for different pastures and retirement. As in, no one’s getting laid off through 2029.

Now there’s an electric slide I can get behind!

Audi’s top brass, in an Ohm-My-God twist (see what I did there), actually sat down with worker reps and talked this move out. This kinder, gentler, distinctly NON-assy arangement will save the company over 6.6 billion dollars over the next decade, and all of that cash is going to boogie-woogie-woogie into their ‘lightning car development’ piggy banks.

Yay for them!

And yay for us.

See, Germany has a (recent) history of not being horrible to their employees. It’s why Walmart’s attempt to claw its way into Deutschland went up in so much smoke. And that history is accompanied by a reputation for stunningly positive change for everyone from white tie to black apron.

With a brand as giant, trusted, and drooled over as Audi is managing to conduct massively profitable business without schwantzing anyone over, everyone here in the US has a shining example to point to and follow when making massive company moves.

Notably, Tesla, America’s favorite electric car company is almost cartoonishly anti-union, anti-worker, and anti-running dress rehearsals on expectation/glass shattering exhibitions. The prevailing thought is that it’s a necessity to be some kind of moustache twirling villain to get ahead because so many businesses insist upon it.

But that chestnut cracks here.

No more ‘Businesses exist to make money’ excuses. No more ‘You have to be ruthless to get ahead’ BS. Those selective-sociopathy inducing phrases never made any sense to begin with, but now, we’ve got a shining example of towering projected #GAINZ for a company doing right by its people without a single head rolling on the factory floors or a single decimal point moved left in the ledgers.

Ya done good, Audi.

Here’s hoping more businesses stateside follow in your tire tracks.

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