Tag Archives: big data

Election lessons. Beware who you ignore.

It was election week here in America, but unless you’ve been living under a rock for the last eight months, you already know that. Not unlike the Brexit vote from earlier this year, a lot of people were genuinely surprised by the outcome. Perhaps most surprising to me is that the people who seem to be the most surprised are the people who claimed to know—for certain—that the outcome would be otherwise. Why do you suppose that is? There is a lot of finger-pointing and head-scratching going on but from what I’ve seen so far none of these so-called experts has a clue why they were wrong.

Most of them are blaming polls for their miscalculations. And it’s starting to look like their error came not in who they polled but who they thought irrelevant and ignored. Many in the media are in denial that their efforts to shape the election may have even fueled the fire for the underdog. What has become of American Journalism is shameful. Wikileaks proves that ninety percent of the media was kissing up to the left, with pre-approved interviews, stories and marching orders to “shape the narrative.” I don’t care who you were voting for, that kind of collusion is a disgrace for democracy. Call it Pravda. But I don’t want to turn this blog into a political commentary, but it was amusing to watch them all wearing the stupid hat on Wednesday morning. What I do want to talk about, however, is how we look at data to reach a conclusion.

In a morning-after article from the LinkedIn network, futurist Peter Diamandis posted the topic, “Here’s what election campaign marketing will look like in 2020.” It was less about the election and more about future tech with an occasional reference to the election and campaign processes. He has five predictions. First is, the news flash that “Social media will have continued to explode. [and that] The single most important factor influencing your voting decision is your social network.” Diamandis says that “162 million people log onto Facebook at least once a month.” I agree with the first part of his statement but what about the people the other 50% and those that don’t share their opinions on politics. A lot of pollsters are looking at the huge disparity in projections vs. actuals in the 2016 election. They are acknowledging that a lot of people simply weren’t forthcoming in pre-election polling. Those planning to vote Trump, for example, knew that Trump was a polarizing figure and they weren’t going to get into it with their friends on social media or even a stranger taking a poll. Then, I’m willing to bet that a lot of voters who put the election over the top are in the fifty percent that isn’t on social media. Just look at the demographics for social media.

Peter Diamandis is a brilliant guy, and I’m not here to pick on him. Many of his predictions are quite conceivable. Mostly he’s talking about an increase in data mining, and AI is getting better at learning from it, with a laser focus on the individual. If you add this together with programmable avatars, facial recognition improvements and the Internet of Things, the future means that we are all going to be tracked with increasing levels of detail. And though our face is probably not something we can keep secret, if it all creeps you out, remember that much of this is based on what we choose to share. Fortunately, it will take a little bit longer than 2020 for all of these new technologies to read our minds—so until then we still hold the cards. As long as you don’t share our most private thoughts on social media or with pollsters, you’ll keep them guessing.

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A paralyzing electro magnetic laser: future possibility or sheer fantasy?

In episode 134, the Techman is paralyzed, lifted off the ground and thumped back to the floor. Whether it’s electrostatic, electromagnetic or superconductor electricity reduced to a hand-held device, the concept seems valid, especially 144 years from now. Part of my challenge is to make this design fiction logical by pulling threads of current research and technology to extrapolate possible futures. Mind you, it’s not a prediction, but a possibility. Here is my thinking:

Keiji’s weapon assumes that at least four technologies come together sometime in the next 14 decades. Safe bet? To start with the beam has to penetrate the door and significantly stun the subject. This idea is not that far-fetched. Weapons like this are already on the drawing board. For instance, the military is currently working on something called laser-guided directed-energy weapons. They work like “artificial lightning” to disable human targets. According to Defense Update,

Laser-Induced Plasma Channel (LIPC) technology was developed by Ionatron to channel electrical energy through the air at the target. The interaction of the air and laser light at specific wavelength, causes light to break into filaments, which form a plasma channel that conducts the energy like a virtual wire. This technology can be adjusted for non-lethal or lethal use. “

The imaginative leap here is that the beam can penetrate the wall to find it’s target. Given the other advancements, I feel reasonably safe stretching on this one.

LIPC at work.
LIPC at work.

Next, you have to get the subject off the ground. Lifting a 200-pound human would require at least two technologies assisted by a third. First is a levitating superconductor. A levitating superconductor uses electric current from a superconductor to produce magnetic forces that could counter the force of gravity. According to physics.org:

“Like frogs, humans are about two-thirds water, so if you had a big enough Bitter electromagnet, there’s no reason why a human couldn’t be levitated diamagnetically. None of the frogs that have taken part in the diamagnetic levitation experiments have experienced any adverse effects, which bodes well for any future human guinea pigs.”

The other ingredient is a highly powerful magnet. If we had a superconductor with a few decades of refinement and miniaturization, it’s conceivable that it could produce magnetic forces counter to the force of gravity. 1

The final component would be the power source small enough to fit inside the weapon and carrying enough juice to generate the plasma, and magnetic field for at least fifteen seconds. Today, you can buy a million-volt stun device on Amazon.com for around $50 and thyristor semiconductor technology could help ramp up the power surge necessary to sustain the arc.  Obviously, I’m not an engineer, but if you are, please feel free to chime in.

1. http://helios.gsfc.nasa.gov/qa_gp_elm.html

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What could happen.

1.  about last week

I’ll be the first to acknowledge that my blog last week was a bit depressing. However, if I thought, the situation was hopeless, I wouldn’t be doing this in the first place. I believe we have to acknowledge our uncanny ability to foul things up and, as best we can, design the gates and barriers into new technology to help prevent its abuse. And even though it may seem that way sometimes, I am not a technology pessimist or purely dystopian futurist. In truth, I’m tremendously excited about a plethora of new technologies and what they promise for the future.

2.  see the future

Also last week (by way of asiaone.com) Dr. Michio Kaku spoke in Singapore served up this future within the next 50 years.

“Imagine buying things just by blinking. Imagine doctors making an artificial heart for you within 20 hours. Imagine a world where garbage costs more than computer chips.”

Personally, I believe he’s too conservative. I see it happening much sooner. Kaku is a one of a handful of famous futurists, and his “predictions” have a lot of science behind them. So who am I to argue with him? He’s a brilliant scientist, prolific author, and educator. Most futurists or forecasters will be the first to tell you that their futures are not predictions but rather possible futures. According to forecaster Paul Saffo, “The goal of forecasting is not to predict the future but to tell you what you need to know to take meaningful action in the present.”1

According to Saffo “… little is certain, nothing is preordained, and what we do in the present affects how events unfold, often in significant, unexpected ways.”

Though my work is design fiction, I agree with Saffo. We both look at the future the same way. The objective behind my fictions is to jar us into thinking about the future so that it doesn’t surprise us. The more that our global citizenry thinks about the future and how it may impact them, the more likely that they will get involved. At least that is my hope. Hence, it is why I look for design fictions that will break out of the academy or the gallery show and seep into popular culture. The future needs to be an inclusive conversation.

Of course, the future is a broad topic: it impacts everything and everyone. So much of what we take for granted today could be entirely different—possibly even unrecognizable—tomorrow. Food, medicine, commerce, communication, privacy, security, entertainment, transportation, education, and jobs are just a few of the enormously important areas for potentially radical change. Saffo and Kaku don’t know what the future will bring any more than I do. We just look at what it could bring. I tend to approach it from the perspective of “What could go wrong?” Others take a more balanced view, and some look only at the positives. It is these perspectives that create the dialog and debate, which is what they are supposed to do. We also have to be careful that we don’t see these opinions as fact. Ray Kurzweil sees the equivalent of 20,000 years of change packed into the 21st century. Kaku (from the article mentioned above) sees computers being relegated to the

“‘dull, dangerous and dirty’ jobs that are repetitive, such as punching in data, assembling cars and any activity involving middlemen who do not contribute insights, analyses or gossip.’ To be employable, he stresses, you now have to excel in two areas: common sense and pattern recognition. Professionals such as doctors, lawyers and engineers who make value judgments will continue to thrive, as will gardeners, policemen, construction workers and garbage collectors.”

Looks like Michio and I disagree again. The whole idea behind artificial intelligence is in the area of predictive algorithms that use big data to learn. Machine learning programs detect patterns in data and adjust program actions accordingly.2 The idea of diagnosing illnesses, advising humans on potential human behaviors,  analyzing soil, site conditions and limitations, or even collecting trash are will within the realm of artificial intelligence. I see these jobs every bit as vulnerable as those of assembly line workers.

That, of course, is all part of the discussion—that we need to have.

 

1 Harvard Business Review | July–August 2007 | hbr.org
2. http://www.machinelearningalgorithms.com
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