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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

If Reddit goes IPO, will it have to shed its soul?

(EDITORIAL) Reddit is known as a firebrand, a bastion of free speech, but if they go public, will they be able to remain as they are now?

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Reddit, the eighth-most popular website on the Internet, is reportedly considering an IPO. As a site valued at over 1.8 billion dollars, this is great news for the company itself – but how much of Reddit will remain if the IPO goes through?

Reddit’s history is steeped in controversy, from minor incidents such as invasion of privacy and a few creepily quirky community members to allegations of child pornography and egregious hate speech. While Reddit’s policy has allowed it to tighten posting restrictions regarding the latter two, the fact remains that Reddit – for all its usefulness – is viewed by many as a ticking time bomb.

An IPO would certainly lend back to Reddit a degree of credibility not seen since its inception, but the problem is that Reddit itself (the haven of free speech and original content that made it so popular in the first place) might not survive the offering. Given the platform’s controversial past, many believe it likely that stakeholders would move to tighten further the restrictions on the platform, ultimately ending a significant era in Reddit’s history.

Admittedly, Reddit has come a long way since its early days of supporting user-created content regardless of persuasion: this past year saw entire subreddits shut down for violating the terms of use regarding hate speech, and the platform certainly has cracked down on illegal and abusive content. Unfortunately, the history might be too much to shake off going forward, which is why we think that Reddit’s branding won’t be a part of the final IPO.

The platform’s developers’ dedication to free speech and truth-seeking is what makes Reddit so fantastic, and that’s not liable to change – it’s the most marketable aspect of the site, after all – but perhaps the rationale behind going public lies in a sense of duty rather than routine. 2017 has seen some of the most reprehensible instances of false reporting and deliberate misguidance in recent history; maybe Reddit’s team feels that they can provide a stable news platform at the cost of some personality.

At any rate, the IPO itself isn’t set in stone, and is unlikely to take place for quite some time. As the situation develops, it will be interesting to see if Reddit embraces its past, or sheds it altogether.

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Opinion Editorials

‘Follow your passion and the money will follow’ is bulls**t advice

(EDITORIAL) Following your passion can create success, though it may not be financial. So should you really just “do what you love” and hope for the best?

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If you asked anyone who knows me, they would tell you that I’m a strong advocate for people following their passion. However, when I encourage people to pursue their dreams, this comes with a big asterisk.

I recently heard someone use a phrase along the lines of, “if you do what you love, the money will follow.” Um… no.

While it’s great that you’ve found something you’re passionate about, that’s only a trillionth of the battle. You need to be willing to work your ass off and be willing to sacrifice everything in order to make that enthusiasm into a success.

Most people that have started their own business will tell you that it took a while into the process to begin paying themselves. Again, if it truly is your passion, this is all worth it in the end. But if you like food and shelter, it might not be.

Say, for example, your passion is acting and your goal in life is to become a famous movie star. Now, you can’t pull a Tobias Funke and simply say, “I’m an actor” and then expect everything to miraculously fall into place.

Like any other passion, you need to invest in yourself. You’ll need to get headshots, take acting classes, and find a flexible day job that allows you to go on auditions. Cutting corners on any of this in order to expedite the process or save a few bucks will end up hurting you in the long run.

For the sake of this article, let’s define “passion” as loving something so much you couldn’t imagine doing anything else… you would even do it for free. And, as there is no correlation between having passion for something and money, you just might.

While doing what you love is admirable, be aware that it may take an incredibly long time to see results in the form of numbers. Because of this, it’s wise to always have a back up plan to support yourself financially and pursue passion with a strong business plan in tact.

It is never wrong to want to follow your passion. I personally think that everyone should give it at least something of a shot during the course of their career so that you never ask “what if?” But following passion because you read a cliche statement can lead to major financial and emotional losses, so put on your business hat before blindly chasing dreams.

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Opinion Editorials

Tech CEO tweet ruins years of a young designer’s hard work

(EDITORIAL) With a tweet here and there, thoughtless questions have potentially bullied a young Asian woman in tech out of her career.

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It’s hard enough for women, particularly women of color, to make it in the world of tech, without rude jerks questioning if you literally exist.

Sadly, that’s what happened to Naomi Wu, also known as “SexyCyborg,” a 23-year old cyberpunk superstar from Shenzhen, China who has amassed a huge following for her 3D printing experiments and other techie pursuits. Wu has 140,000 followers and millions of views for her YouTube channel, where she shows off her experiments and provides educational tutorials.

Unfortunately, some rude dudes from America can’t seem to imagine that a young Asian woman is capable of the feats that Wu has accomplished.

Dale Dougherty, CEO of the DIY magazine Maker (and an official schmuck), has cyberbullied Wu so badly that it is said to have damaged her career. He tweeted, “I am questioning who she really is. Naomi is a persona, not a real person. She is several or many people.”

This despite the fact that Wu says that she has actually spoken to Dougherty, and that he knows she is real. “For Westerners who don’t understand the important of reputation in China it seems like a very minor thing,” says Wu, “it is everything here and there’s no repairing this.”

Wu has even lost a sponsorship deal from a 3D printer company over the accusations that she isn’t who she says she is.

Dougherty eventually apologized, but Wu says that “the damage had been done” at that point, and that Dougherty knew the accusations would be “devastating” to her “reputation and professional prospects.”

Wu says that the attack is motivated by white male entitlement to tech spaces.

She says that she can’t imagine Dougherty attacking “a white lady from San Francisco.” Wu has been an advocate for diversity in tech and maker spaces. “I kept pushing for more inclusion – not just me, other underrepresented people,” she says. “They didn’t like being pushed. This is payback.”

We stand behind Wu as she continues to push the edge in tech spaces, and say shame on you to bullies who won’t make space for women and racial minorities. Sorry you’re not as cool as SexyCyborg, but that’s on you and you need to get over it.

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