Exploding Brain

My brain literally exploded with new ideas this morning.

 

Oh, the mess. My brain blew completely through my skull cap, littering brain and skull accoutrements all over my laptop and desk. Hearing the noise, the cats awoke to investigate, wandering about, sniffing the pieces, licking a few, asking, “Hey, is this edible? Mind if I eat this?”

“Shoo, shoo,” I told them with accompanying actions, which they ignored. I enticed them away with kitty crack, the addictive treats that cats crave. After closing the door to ensure the cats didn’t return, I commenced collecting pieces and putting myself together. It didn’t take long and my ability to function with an exploded brain impressed me. There were some pieces left over. I couldn’t for the life of me discern where they went, so I put them in a Ziplock in a drawer. That way, I have them later, in case I do discover where the pieces fit. Chances are, I'll find that baggy years from now and wonder, "What is this garbage?" Then I'll throw it away.

An IBM presentation analyzing twitter content with big data analytics was presented, with supporting business cases provided, and that's what exploded my brain. And as I listened with the rest, many of us gleaned the insights into how effectively this could be utilized as an almost instantaneous marketing tool. More, though, the scope of what could be done with this regarding politics staggered me. Analyze the twitter sphere and feel the pulse. Inherent dangers exist with that model. Rural America doesn’t tend to twitter as much as urban America. Urban America leans toward being liberal with pockets of Republican leaning businesses.

I can’t go into the business cases as it’s proprietary information, but it was noted that 70% of twitter feeds originate outside of the US. After the case analysis was given, it was asked, so what percentage of the US population is on twitter? That wasn’t known but it’s known that there are over 300,000,000 twitter accounts.

After I put together my exploded brain, I researched more regarding twitter, signed up for twitter, found some entities to follow, and began tasting it. All the while, I was thinking about how, with the proper hardware/wetware and software, it would be possible to define the biometrics that can take the pulse of a gathering for interest levels and emotions and develop some seriously predictive models. That took me into research about affective computing, a fascinating discipline.

Back to big data. Big data analytics can be hugely beneficial to humanity. To be able to scale and analyze widespread weather patterns and events, and economics in more timely manner than current methodology would be a boon to planning the future, maintaining stable economies and even growing them, and minimizing weather deaths and damages. But it’s all monetized, sigh, because it is business, and it’s about making money, and that’s our bottom line here in America.

Bottom lines change. History travels in cycles. Perhaps the drought and climate change will generate new cycles. California, which provides 80% of America’s produce, is expected to endure another drought. Down in Berkeley, California, the water is tasting foul because the water levels are dropping to such low levels that the system is now drawing off the top. Back in the northeast, the debilitating weather conditions continue while Florida is suffering from sea water salinization of their drinking supplies as the water levels rise. Meanwhile, here in Oregon, our drought is extending, we're on 'voluntary' water rationing - you can have water if you can pay for it - and we’re grimly bracing for another year of intense forest fires and the pollution they cause.

We will see. Change is inevitable. How much change we’re willing to face and how much we will apply ourselves to solve these problems instead of sucking profits from our problems is really the question. We can begin earlier and perhaps save some lives and pain, or we can wait until profits dry up. Given the financial meltdown of the last decade, I believe it will be the latter, as too many people in power are intoxicated by greed.

Now, with my brain back intact, except for a few missing pieces, and my mind fired up, it’s time to write like crazy, at least one more time.

 

 

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Big Data Analytics

I spent time at work this morning reading big data analytic results. I should add that it’s time like these, when I’m being paid to read and think and nobody is bothering me, that I enjoy my job.

 

Some of the results I read were surprising, challenging assumptions. Ex-convicts make very good call center employees. Where you went to college is not a great indicator for business and professional success. Going to college and finishing are much better indicators.

I don’t know the words for all the things I read and discovered today. Knowledge can become very specialized very quickly. For example, I told my wife about the ex-convict results. Yes, she replied, but can they be trusted with credit card and personal information?

Her response is probably a modern response and I believe it’s typical. I think it’s some sort of transference. American society generally doesn’t trust ex-convicts. They broke a law and were caught and sentenced, therefore, we’ve proven they can’t be trusted. We have also demonstrated that some percentage of convictions is wrongful, numbers that vary by crime and geography, numbers influenced by race and sex. And more people in America are being sentenced for victimless crimes, such as possession of marijuana and other drugs purchased for personal use. We also have evidence that the monetization of penal institutions influences conviction and incarceration rates. Judges and DAs have been caught taking kickbacks from the institutions where they’re sending the convicted.

That highlights the differences between what data analyses can demonstrate against what people believe. I constantly encounter it on my job and weary of explaining the numbers and trends and again. We are people, though. Besides being capable of logic, we’re emotional. Once emotions color our perceptions, it seems difficult for us to drain those colors out.

The problem with acquiring knowledge is that it stimulates my thinking. That’s a lazy way of stating it. Acquiring knowledge and thinking more aren’t issues. Neither is being stimulated to think more. The problem, perhaps, is that I’m frequently perceived as a thinker but that many of my ideas and insights are difficult to follow. I know, it’s my issue, a matter of how I take that information and what I do with it – but I am a thinker, you see – but I’m also insecure, thin-skinned and emotional.

Anyway, I wondered after reading these big data results. I’d recently read that JPMorgan has decided it will only accept applications for analysts positions from Ivy League schools. That reduces their application pool and the subsequent work load to hire new employees, yet I wonder how this flies in the face of the big data results and whether JPMorgan is setting itself up for paradigm failure. I wonder if they’re yielding short term gains for long term losses, saving money by reducing their pool and hiring people fast, but losing money later because better analysts actually go to schools beside Ivy League institutions.

I wonder about how small businesses can be served by big data analytics. I saw numerous ways in which they can, from location and the name to wall paint color and décor decisions to hours, the music being played, and the services and goods being offered. Big data takes money. It’s not an easy process. But I think small businesses could benefit, especially in a place like my small town, where businesses come and go like migratory birds. My answer would be for the small businesses to form a consortium with the goal of having a big data analytics conducted on the businesses and the local economic/environmental influencers.  They could then share the costs. I imagine that as an economic project, loans and grants from the different governments could be found to support such a project.

Of course, I write novels and mull the frustrations of finding publication, creating a brand, marketing myself and my products and earning a living from the pleasure of writing. I mull what big data analytics would show about fiction publishing, especially in this age of self-publishing and digital publishing. One issue constantly encountered is that agents, editors and publishers seek what they enjoy but also try to follow market trends. I’d love to see big data analytics take on the subject.

Writing science fiction, it’s pleasurable toying with big data analytics and human events, like falling in love, committing crimes, finding work, illnesses and death. Isaac Asimov, one of my favorite classic hard science fiction authors, did a terrific job of using big data and analytics in his Foundation series. His scientists predicted a mutant outlier that would cause problems….

 (Aside – I sometimes wonder if my company actually employs big data analytics as much as it could, for surely that would tailor all their sales and marketing efforts and their new product requirements instead of demanding we present business cases and marketing plans to support launching new products and services….)

Big data analytics can’t quite predict everything, then, but the delta between what can be analyzed and what evades analysis is shrinking. I consider myself an artist. I imagined, drew, and painted long before I began writing. I designed cars and interiors and exteriors, and painted and drew in multiple mediums, turning down some small art scholarships to attend college to go do other things. I didn’t know ‘what I wanted to be’ and lacked the insight to realize that learning more would help me understand myself and my desires. I thought, perhaps because that’s how the instruction was geared in the schools I intended, that the goal to schooling was to graduate and find a job and earn a living. Scoffing at that, I joined the military. Problem solved, right? I had a job and I was earning a living.

Eventually I discovered I wanted to try writing fiction to express myself, and here I sit. As an artist, I think some fragment of being human will always evade analysis, a conclusion I share with many thought leaders in AI, robotics and automation. The one thing that can’t be predicted or duplicated remains the human imagination, for now. Some bold new paradigm may be emerging on the horizon, though, that will change that as well.

So, maybe someday some artificial intelligence will sit down to write like crazy and create fiction.

 

I’ll keep trying, though, for at least one more day.

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