Apples and Orangutans.

There was a discussion on Facebook about whether Apple products were worthy of the Enterprise, and there was some CTO of some company that processes data (just like everyone else) who put her title in front of her arguments – a nasty habit that diminishes a point – saying that Apple products are.

When it comes to processing and ability, Apple products are often superior to Windows products – but typically not within the same price range, so it’s an odd comparison of Apples and… well, you get the drift. But ability of a single machine wasn’t at issue, it was whether it could work within the Enterprise. At this time, I contend that Apple isn’t Enterprise-friendly because it’s not as cost effective – and let’s be serious, that’s not the market that Apple has really been going after. Yet? Historically, it never has.

But in this discussion, I was trying to tease out the importance of cost effectiveness and cross-compatibility between Apples and other machines on a network by pointing out that the developing world simply can’t afford the Apple-esque thought of the Enterprise, and that in turn got us into the Lowest Common Denominator (LCD)’discussion’ – where our opinions were drastically different. Her contention was not to worry about the LCD, she doesn’t care about them. Well, really, of course she doesn’t because the company she worked for at the time (and maybe now) doesn’t deal with users, and it hordes the processing. That’s their business model. But she couldn’t seem to make that distinction.

That’s a problem for the Enterprise, more so than the cost of Apples. The Enterprise, whether companies like it or not, extends beyond their infrastructure to other infrastructures – which are largely Windows and Linux hybrids. Why? Cost. And where does cost come to be a factor?

Oh. The Enterprise and the Developing world. And – excuse me, I need to twist this into a ending you didn’t expect  – it’s really about mobile devices (thin clients) and access to data.

Natural Language Processing, Health Records and the Developing World.

Case Investigation Team

The Veterans Administration will be using Natural Language Processing (NLP) for their medical records. It can be a powerful tool for searching for trends and getting the right people to the right treatments in a timely manner. That’s a gross oversimplification.

I know a bit about medical records1. I also happen to know quite a bit about Natural Language Processing, since I’ve worked with it in the context of documentation management.

And, as it happens, I know a bit about the developing world – the Caribbean and Latin America. And I know a bit about the hospitals in the region, where hand written records are kept, but lack the rigor and discipline necessary for them to truly be useful. I recently looked at the medical record of someone in Trinidad and Tobago, if you could call it that, since I found it odd that the Doctors and Nurses didn’t seem to communicate not only with each other but their own subgroups. I saw why.

I know of one doctor who keeps patient records in Microsoft Word documents – a step in the right direction.

There is an opportunity here for the developing world in general, but it’s a technology leap that must be undertaken with the discipline of good medical records in the first place. These delapidated medical systems, despite new buildings, need to have medical records that enable good care in the first place.

There’s no reason that medical care in the developing world should suffer; it can be done much more cheaply than in the developed world and with the advancements such as NLP already being implemented, it’s vacuous to build shiny buildings when the discipline of the medical records themselves should be paramount.

But then, maybe implementing electronic medical records properly would be a good start to building that discipline. 

1Medical Records have interested me from my days as a U.S. Navy Corpsman, where we were assiduous about medical records – Doctor’s orders, nursing SOAP notes, lab results – all had their place within a folder. It was just on the very edge of the medical databases that the U.S. Navy rolled out. When I was at my first USMC command, myself and other corpsmen’s first job was  to get the medical records ready enough to allow us to deploy – and it was an onerous task, with those who had gone before not having taken the records as seriously as they should. Later, I would work with a Reserve USMC unit at Floyd Bennet Field where I would be commended for my database work as related to their medical records.

The AI Future On Mankind’s Canvas

Doctor Leia.I met her and the young Brazilian woman on the flight from Miami to Orlando, this young Doctor who had an interview in Ocala. She was to drive across to Ocala, to the East, to see if she would get the job. She didn’t look old enough to be a Doctor, but I’ve passed the age threshold where doctors were younger than myself years ago. We talked about medicine and medical administration for a while even as I checked up on the nervous Brazilian high school graduate. I sat, a thorn between two roses, all the while thinking:

What sort of world were they entering? Doc Leia, a graduate from The University of the West Indies, off to Ocala, and the young woman to my right, off to see the sights as a reward for having survived so many years of schooling. They were both easily younger than most of my nieces. The Doctor had already become heavily invested in her future – medical school was a daunting path and might have been one I would have pursued with the right opportunities. The other was about to invest in her future and it bothered me that there wasn’t as clear a path as there used to be.

Artificial intelligence – diagnosing patients on the other side of the world – is promising to change medicine itself. The first AI attorney, ‘Ross’, had been hired by a NYC firm. The education system in the United States wasn’t factoring this sort of thing in (unless maybe if you’re in the MIT Media Lab), so I was pretty sure that the education systems in the Caribbean and Latin America weren’t factoring it in. I’ve been playing with Natural Language Processing and Deep Learning myself, and was amazed at what already could be done.

The technology threat to jobs – to employment – has historically been robotics, something that has displaced enough workers to cause a stir over the last decades – but it has been largely thought that technology would only replace the blue collar jobs. Hubris. Any job that requires research, repetition, and can allow for reduced costs for companies is a target. Watson’s bedside manner might be a little more icy than House, but the results aren’t fiction.

What are the jobs of the future, for those kids in, starting or just finished with a tertiary education? It’s a gamble by present reckoning. Here are a few thoughts, though:

  • A job that requires legal responsibility is pretty safe, so far. While Watson made that diagnosis, for legal reasons I am certain that licensed doctors were the ones that dealt with the patient, as well as gave the legal diagnosis.
  • Dealing well with humans, which has been important for centuries, has just become much more important – it separates us from AI. So far.
  • Understanding the technology and, more importantly, the dynamic limits of the technology will be key.

Even with that, even as fast food outlets switch to touchscreens for ordering their food (imagine the disease vectors off of that!), even as AI’s become more and more prominent, the landscape is being shaken by technology driven by financial profit.

And I don’t think that it’s right that there’s no real plan for that. It’s coming, there is no stopping that, but what are we as a society doing to prepare the new work force for what is to come? What can be done?

Conversations might be a good place to start.






Reinvention, Recursive.

Art evolvesWarning: This is kind of long and is a rant-ble. The short of it is that I’m not on the market anymore.

It’s time to evolve again.1

No, this is not the announcement of some Silicon Valley startup that will make you better elbows to stick in your ears or, heaven forbid, something useful.

No, this is about the site, myself, and the career path. To cut to the chase, I’m no longer looking for work or contracts in technology.

There’s a few reasons for this.

  • After 2 and a half decades, it gets boring when done right and annoyingly exciting when done wrong. More often than not in most companies, it’s being done wrong and it’s no fun getting excited for the wrong reasons.
  • Everyone wants a specialist and I’m a generalist.
  • Management doesn’t like me wandering around outside the building. They don’t think I’m working just because of the GIS coordinates of my body during thought.
  • AI is gonna take over at least some programming jobs (advances in programming in the past have had the reverse effect, broadening the field – something else for another time). It will only take one programmer who will because s/he can, and then an ecosystem to evolve it.
  • Did I mention I’m bored?
  • I have other options.

Plugging tech together can only be done in so many permutations. It’s a mathematical fact if you factor in that the geometric progression is necessary for evolution through the permutations.  

I’m not sure I like how the ecosystem is plugging tech together. Frankly, while it’s nice that the iFart application created a few jobs (don’t be the guy with the microphone), and while it will be seen as invaluable to those who pay for it, it’s crap and really doesn’t advance anything but a paycheck. Because, really, money got mistaken for something of value somewhere in the history of mankind.

Because I don’t like the way things are getting plugged together, to work means to evolve again, and the value of working on things I increasingly don’t like is… silly in a human and financial perspective. I’ve always believed that people should do what they want to, then later understood that people should do what they want to only if they’re good at it. I’m still good at it, but I don’t want to think about that too much.

There are other things I’m good at, and it’s time to go do them. It’s not that I’m becoming a Luddite – far from, you should see this heap of silicon I just bought – but that it’s not a career for me, at least for a few years. I’ll be using tech in other endeavors, and a great way to spend time waiting on others is to solve problems: Write code, design systems, or make a better mousetrap. But it’s not my main thrust, and oddly, I’ve been telling kids starting college not to do tech but to do other things with tech.

And in the meanwhile, things that I put my own sweat equity into over 5 years ago are paying, and require some attention.

1 Now there’s a marketing line…