I suspect just about everyone is aware of the flap over an opinion piece in the Wall Street Journal regarding our soon-to-be First Lady’s credentials. Written by Joseph Epstein, it’s entitled “Is There a Doctor in the White House? Not if You Need an M.D.” and subtitled “Jill Biden should think about dropping the honorific, which feels fraudulent, even comic.”
My most recent job was as the Business Manager for a Machine Learning (AI) Software Development firm, the co-founder of which had a PhD in computer science. When last I spoke with her, which was at least a year ago, she was not using her title, which she feared was seen as somewhat presumptuous. I’m not sure how she feels about it now, and I’m inclined to agree with those who see this op/ed piece as misogynistic and hollow. Frankly, I have often wondered if I could use the honorific “Dr.” in front of my name because I have earned a Juris Doctorate (JD) when I graduated Law School in 1976. However, I’ve never done so because the amount of schooling, and the quality of work, required for the degree don’t match up to that of a PhD or EdD. Actually, I tend to agree with those who suggest calling oneself “Dr.” when in possession of a law degree is ridiculous and pedantic.
It’s been discussed at great length by now, torn apart and analyzed by people far better at it than I, but I’d like to bring up what I think is an ancillary issue to that of the rank sexism and hypocrisy that exists wrt men and their seeming inability to accept women as their equals. What I’m referring to, which affects both men and women, regardless of race, creed, or color (though there are differences in degree and approach) is the depth of anti-intellectualism that has come to seemingly dominate our public life.
Just look at how many people are not only comfortable with, but are absolutely adamant about, ignoring science, facts, and reality-based analysis/synthesis. The number of people who believe most scientists are only doing what they do for the money is astounding. It’s likely one of, if not the, main reasons we’re doing so poorly in handling the pandemic here in the States.
This isn’t a new phenomenon. Hardly! I recall deciding in the third grade (that would have been around 1955) I didn’t want to be seen by everybody as an egghead, which changed the trajectory of my life . . . and probably not in the best way it could have. I remember feeling at the time that I wouldn’t have any friends if I continued on the path of academic excellence I had been on. Part of me wishes I hadn’t made that choice, though my life turned out pretty well regardless. It’s just that, in retrospect, the decision was made because of the negative view most people I knew seemed to have about being too intelligent; or, at least, being willing to use that intelligence in a positive way.
I believe this is one of the reasons the United States is in the bind it’s in right now. We’re just coming off of a four-year bender with the sleaziest and dumbest President in our nation’s history. He came to power as the result of years of anti-intellectual posturing and reality TV-informed ignorance. I am thankful I have never watched one reality TV show, especially not The Apprentice or Celebrity Apprentice. It’s clear Donald Chrump managed to suck a large portion of the nation into believing he was a highly successful businessman when, in fact, he’s a serial fuck-up who managed to burn through tens, if not hundreds, of millions of dollars given to him by his father.
These past four years of the worst “leadership” of my lifetime has been brought to us by our nation’s well-developed sense of anti-intellectualism. This does not bode well for maintaining our position as a preeminent nation of entrepreneurs and innovators. Our quality of life in the United States is what it is in large part because of our scientific accomplishments. It amazes me so many people don’t recognize the value that science has added to our lives, be it at work, home, or play. Virtually every aspect of our lives is enhanced by science and the products and enhancements it brings to us on a heretofore regular basis. I fear we’re going to lose that edge. Perhaps we already have. More the pity.
I have no doubt I am a very lucky person. Although I do not have an education in any science, I was able to spend approximately two decades working on the Space Shuttle Main Engine (SSME) program at Rocketdyne (through four major aerospace corporations). I spent a lot of time working with some of the brightest rocket scientists (for realz) as well as world-class engineers and scientists in literally dozens of disciplines.
Since my retirement from (what was then) Pratt & Whitney Rocketdyne, I have worked intermittently with Quantellia, LLC, an artificial intelligence / machine learning software development firm. Needles to say, I have no formal education in any computer field, with the exception of two Visual Basic classes I took at a nearby Junior College. I was introduced to one of the co-founders of Quantellia shortly after my retirement. She showed me a tool they had been developing called “World Modeler”. It was the most exciting thing I’d seen in a long time, and I was especially impressed with how it brought a highly systemic approach to modeling and forecasting in complex situations. I ended up writing several papers and a bunch of case studies for them.
In 2015 I returned to work at what was then Aerojet Rocketdyne (still is, for now) where I worked on a small rocket engine program for a little over two years. After leaving, I started doing some selling for Quantellia and, beginning in March of 2018, I became the company’s Business Manager, a position I’m still working at.
Last year we held a summit, in conjunction with SAP Global Services, at their Labs in Palo Alto. It was called the “Responsible AI/DI Summit.” In this context AI stands for “Artificial Intelligence” and DI stands for “Decision Intelligence.” One of the main purposes of the summit was to discuss how we can develop artificial and decision intelligence such that we concentrate on using them to solve humanity’s most “wicked” problems, rather than merely work at developing apps, the main purpose of which is to make money for the developers, investors, and entrepreneurs involved in the business.
Below are some of the folks who worked on the Summit, including me (the long-haired guy in the middle of the back row). Also, here’s a link to this year’s second Summit – Responsible AI/DI Summit 2019, as well as a link to the RAIDI Blog.
As I learn more about machine learning, artificial intelligence, and decision intelligence, I will work at sharing my knowledge and understanding of these tools, and the issues they raise. I know the people I’m working with are dedicated to serving humanity, not merely milking it for profit. That pleases me and I hope we’ll be able to prove we’re doing the right things to ensure such service continues to exist and grow.
In the 2020 General Election, coming up waaaaay sooner than you think, time being what it is, there are eight (count ’em, eight) Republican Senators who are up for election unopposed. Actually, two of the eight are retiring but, in all cases, whether it’s a replacement or the incumbent, they’re all running unopposed. This is an intolerable situation, IMO.
Allowing any Republican, all (save for Justin Amash) of whom have shown themselves to be hapless sycophants, bowing to the whims of the most destructive and inhumane President in modern history, to run without any Democratic opposition is something we should avoid at all costs.
Bill Cassidy, Louisiana (In 2014 he beat three-term incumbent, Democrat Mary Landrieu, 56 percent to 44 percent. Don’t know if there are any Democrats in the running at present.)
Mike Enzi, Wyoming (Retiring – This seat is considered safe by most people.)
Cindy Hyde-Smith, Mississippi (Hyde-Smith defeated Mike Espy last November in a racially charged campaign.)
James Inhofe, Oklahoma (This is the schmuck who brought a snowball into the Senate chambers to make the argument that global warming can’t be possible because it’s still cold somewhere.)
Pat Roberts, Kansas (Retiring – Maybe a lost cause, as he ran unopposed last time and Kansas is a deep red state)
Mike Rounds, South Dakota (The entire state has approximately a quarter of a million voters. Unknown if there are enough Democrats to matter.)
Ben Sasse, Nebraska (In the 2014 election, there were a little over a half million voters; Sasse won every county in the State – 64% to 31%)
Dan Sullivan, Alaska (In the 2014 election, Sullivan won by 2.2% with a total of only a little over a quarter million voters. This state could be ripe for a flip.)
After the 2016 General Election, I worked with a group of people who were creating a canvassing tool that was designed to use AI to better prepare people who were out knocking on doors. It would have used demographics and historical voting data to train a machine learning algorithm on the patterns to be found in the data. Unfortunately, our primary investor kept adding requirements and ultimately squeezed the value right out of the app.
Nevertheless, our original concept we had discussed was to use machine learning to help political organizations make the most effective (not merely efficient) use of their various resources, e.g. time, money, people, connections, as well as understanding the political environment based on polls and overall news coverage.
Frankly, nobody I know of has sat down and begun to develop such a decision model, though I would dearly love to see it happen. It’s what we envisioned after Trump “won” and I still think it’s a viable approach. It does look like it’s a somewhat daunting challenge, however, when it comes to how expensive it would be to gather all the data we’d need access to, as well as develop the algorithms that would analyze and correlate the data.
Regardless, it seems a shame so many Republicans might run without any Democratic opposition. You’d think the least we can do is make them fight for their seats, which would include forcing them to shift resources around as well. It should be part of the overall pattern of the elections, which I’m unconvinced the Democratic Party really understands.
I know it’s been quite a while since last I posted here. I’ve been continuously active on Facebook and have begun tweeting quite a bit as well, but that’s not why I haven’t posted to this blog in the past nearly three months. As of March 1 I began a new career, probably not the kind of thing you hear about 70-year-olds doing all that often. Since then I have been working as the Business Manager for Quantellia, LLC. You may recall I’ve done work for and with Quantellia on and off for the past six years.
Quantellia is a small AI/ML software development house and, until now, one of the co-founders has been running the business. Inasmuch as she is also the organization’s Chief Scientist, and a well-known pioneer in Machine Learning, this was not exactly the optimal thing for her to be doing. I had been touching on the subject and, since she was having such a hard time getting someone competent to run the business, I pressed my offer to do so. She finally relented and things have been going swimmingly, although there have been times I was swimming against the current. I’m definitely climbing a steep learning curve, which sometimes has me questioning if I’m losing my edge.
Actually, at times I can’t quite tell if my intellect is slipping a little bit, or if I just don’t care as much as I used to and I’m not quite as arrogantly sure of myself. My memory seems to be intact, along with my ability to learn and adapt. I’m going to go with the “I just don’t care as much about things as I used to; I’m more sanguine about life, work, and the need to control everything.
At any rate, I’m having a lot of fun. I was once partnered with two CPAs, doing royalty accounting for some big acts: Jackson Browne, Joni Mitchell, The Cars, Dollie Parton, Ronnie Milsap, The Commodores, even Jimi Hendrix’s estate. I learned a fair amount about accounting back then, and now I’m getting the opportunity to revisit what I learned, applying it in different circumstances. I’m also learning about artificial intelligence and machine learning, and hope to convey some of what’s going on in these fields. Although not a data scientist, I am quite capable of seeing where AI can be applied in business to assist with all kinds of issues. I’m sure you can as well.
Despite this foosball playing robot’s ability, it will be a long time (if ever) before robots or artificial intelligence actually displace us. More likely, they will augment our capabilities and free us up from most of the drudgery we’ve been dealing with for millennia. I find it easy to imagine a day when humans will evolve into cyborgs; part flesh, part machine. In some ways it’s already happening with prosthetics and it’s almost certainly going to accelerate with DNA testing and in utero surgery.
When I joined the Space Shuttle Main Engine program at what was then Rockwell International’s Rocketdyne division, I had never heard the men in my life use the word “retirement.” The reason; they were mostly small businessmen who expected to work until they dropped dead. And that’s exactly what happened to every one of them.
At Rocketdyne, however, it seemed everyone I worked with talked incessantly about retirement. They also talked a lot about what they’d do if they won the lottery, but that’s another story.
A year later, I secured a position as a regular employee (I had been a temp; what they called a “job shopper”) and had to make decisions regarding my future retirement. Most notable of those decisions was whether or not to participate in the company’s 401K program. At the time, the decision was a no-brainer. The company matched employee contributions dollar for dollar, up to 8% of one’s gross income. It was a way to save up a fair amount of money as a nest egg.
Even so, I never saw myself as retiring; I felt I needed to work at something until I either died or was so infirm or incapacitated I wouldn’t be capable of anything useful. I fully expected to work at Rocketdyne until I was at least eighty, despite the fact I had little reason to believe I would live that long.
I ended up leaving what by that time was United Technologies’ Pratt & Whitney Rocketdyne division. That was over seven years ago and I’m still not retired. I don’t expect I ever will retire and, frankly, the concept still means little to me. I do, however, enjoy some retirement income from that original 401K, as well as a small pension and social security. It’s not enough for me to stop working, but I really don’t want to stop. Here’s why.
Yesterday, Jeremiah Owyang posted a graphic on Facebook that caught my eye. It depicts a Japanese concept called Ikigai, which the people who live in Okinawa, Japan live — and live long — by. The concept translates roughly into “the reason you get out of bed in the morning.” It makes an interesting Venn diagram, as you can see below.
The “Sweet Spot” Most All of us Would Like to Achieve
I shared his post with the following comment:
I believe I’ve hit this sweet spot a couple of times in my life, most notably when I worked on the Space Shuttle Main Engine program. I’m pretty close to it now as well, working with Quantellia and machine learning. How about you?
A few of my former colleagues chimed in and one of them actually found the original article in which the graphic had appeared. It’s short and not that old. The title is “Why North Americans should consider dumping age-old retirement.” You can find it here if you’d care to read it.
This is what I think we should all strive for. This is the kind of balance that brings peace of mind and contentment. I’m lucky to have experienced Ikigai in much of my work life. In explanation of how I felt I was working on “What the world needs,” I later commented:
I should point out, especially, I believe we need to establish not merely a scientific outpost off-planet, but a cultural outpost as well. I have no doubt Earth will experience an ELE someday and we need to get established elsewhere, if for no other reason than to repopulate the Earth after such an event, and have a leg up recalling all that we’d accomplished until that unfortunate event. Perhaps we’ll be able to divert any asteroids or comets we discover heading our way, and such a place won’t be necessary, but there’s no way to be completely sure of our ability to avoid catastrophe. I, therefore, felt it was somewhat of a sacred duty to play whatever small role I could to get humans into space. It’s why the cancellation of the Shuttle program – when there was nothing in the pipeline to replace it – was so disconcerting to me. It was a big reason I accepted an early severance package offered to all employees over 60 (I was almost 63 when they made it).
Now, over seven years since my “retirement”, I’m still fortunate to be working on something I believe the world needs (though there’s considerable dispute over whether it will destroy us in the long run). The only place I fall short is in the area of doing what I’m good at. This is because I’m not a data scientist or a designer or programmer. I am, however, a reasonably good salesman and have other skills I’m bringing to bear on my work with Quantellia. I expect my studies and experiences will fill up this hole reasonably soon.
I do believe everyone should be able to approach Ikigai. There is much the world needs and, despite the predicted crisis expected when the machines take over the world and millions of jobs disappear, there will still be lots we can do to lead fulfilling lives. I am a supporter of universal basic income (UBI) and find Jeremiah’s closing words from his Facebook post instructive:
Soon, automation will disrupt Ikigai, in the looming Autonomous World, and we’ll need to reset what our “reason for being” is.
I’m betting that we’ll accept the imperfect arts, humanities, and engage in wellness and fitness for longevity.
I happen to go along with those who believe UBI will unleash creativity and entrepreneurship, though I recognize the pitfalls it may present as well. Regardless, there is a looming crisis and, frankly, my current efforts in selling machine learning services and products, is accelerating it. I doubt we can step back from the cliff, so it may be time to give everyone a kind of “golden parachute”; at least one sufficient to allow them a soft landing when that crisis arrives.
When I was in High School (1962 – 1966) it took me three and a half years to escape) there were no computer classes. Although there seems to be some disagreement on when the first personal computer was invented, even the earliest claim puts the date six years after I graduated. There was no such thing as a computer, let alone a programming or coding, class. Also, I did not attend university and, to my recollection, nobody I knew at the time was interested in computers or information technology. Actually, I was a terrible student and wasn’t interested in much of anything by the time I finished High School.
The IBM Memory 50 Typewriter
Fast forward to 1974. Despite having no undergraduate education, I was able to secure admission to an accredited Law School, located not far from my home in the San Fernando Valley. I began in the fall of 1973 and the following year I managed to get a job in the law office of a sole practitioner in Beverly Hills as a legal secretary/law clerk. Shortly after I began, the lawyer I worked for purchased an IBM Memory 50 Typewriter. I attended a one-day class where I learned how to use it. This was my first introduction to anything resembling “computing.”
The office later upgraded to an Artec Display 2000, which had an LED readout of approximately 30 characters. There was no CRT display. It used two 8″ floppy disks and had a document/data merge capability that made it perfect for boilerplate documents, e.g. Pleadings, Interrogatories, Summonses, etc. It was a great leap forward in word processing.
The Family’s Wholesale Food Business
Shortly after graduating from law school I had, for numerous reasons, decided spending the rest of my work life around the judicial system was not something I really had my heart in and, after much gnashing of teeth and going over my alternatives, I decided to join my family’s wholesale food distribution business. One large factor in making this determination was my father suffering his second major heart attack. The business was supporting my mother and my sister, who was only 10 years old at the time. I felt the need to help the business grow, ensuring they would be taken care of if my father were to die . . . which he did eight years later.
Our company jackets. Logo design by me, jackets created by Cat’s Pyjamas.
After a couple of years, the business had grown substantially and, given my desire for another type of challenge, I once again struck off on my own. I dabbled in a few things, then joined forces with a couple of CPAs and formed a royalty auditing business, serving some very high-end artists. The company first purchased an Apple computer (I can’t recall if it was a II or a IIe but, based on the release dates of the two, I’m inclined to think it was a II). We later purchased a Northstar Advantage, which used the CP/M OS and two 160 KB, 5.25″ floppy disks. We also purchased a dot matrix printer and, in anticipation of taking the system out on the road, we had Anvil make a hardened case for the two, with room for cabling, paper, and instructions to be packed inside.
At that point our audits required us to visit the artists’ recording companies, and my first visit was to RCA records in the Meadowlands of New Jersey. Standard procedure for the record company was to stick us somewhere that was relatively uncomfortable, then bring us stacks of paper, which we then transferred to ledger pages. Upon returning to our office in Playa del Rey, we would then have to transfer all the data to a spreadsheet; we were using SuperCalc on the Northstar Advantage, though we had started with VisiCalc on the Apple.
I suggested taking the computer with us when we performed audits, so the people who went out on the road could enter the numbers they received directly into an electronic spreadsheet, thereby saving a huge amount of time and stress. We were also using WordStar at the time for writing the narratives that would accompany our audit analysis.
My first experience with programming came when we were contemplating taking the system out on a European tour with Neil Young. I sat with my friend and partner, who had performed many a box office reconciliation, and we sketched out the different scenarios that were used to close out the night’s receipts. Doing so required the use of nested “if” statements, which determined the precise equation to use for each venue. Unfortunately, that same friend who had worked so diligently with me to create the formulae that would power the spreadsheet never felt comfortable with using it by himself and it never went out on the road.
My Very First Computer, the Sinclair ZX81
It was also around this time I purchased a Sinclair ZX81, which was a small computer that had a membrane keyboard and used a cassette recorder to save programs on. It also had its own OS, as well as its own version of Basic, which I endeavored to learn. The first program I wrote, which took me all night to complete, counted down from 10 to 0, in the center of the screen. It then plotted a single pixel (resolution was 64 x 48) at a time, starting from the bottom and, after reaching a height of six pixels, began plotting another pixel above the previous six and erasing a pixel from the bottom of the stack, until it left the screen at the top. This required me to learn how to use either (I don’t recall the exact commands; it’s only been a little over thirty-five years) nested “if” statements or “do while” commands.
Fast forward to 1984, the year my father died. Shortly afterward, I returned to help my brother keep the business going. We purchased a more advanced Northstar Advantage, which had a huge hard disk that could store 5MB of data! At the time, we also purchased a copy of dBase II, which was one of the first database systems written for microcomputers. I taught myself how to write systems using their programming language, which I wrote using WordStar. I wrote an entire accounting system for the business. My favorite component was the preparation of a deposit ticket, where I laboriously emulated the workings of a calculator in allowing for numerous methods of inputting dollars and cents (whether or not a decimal point was included) was the real differentiator and sticking point for me but, after much trial and error, I figured it out.
Unfortunately, my brother and I didn’t see eye-to-eye on the direction the business should go in and, after a while I left again, this time taking temporary jobs to keep me afloat. It was during this time I worked for a while at a litigation support firm that used a DEC minicomputer and several of the earliest versions of the Macintosh. All of my work with computers was novel for me, as I never took any classes — with the exception of that class I took to learn how to use the IBM Memory 50 typewriter. I taught myself how to program through reading and doing, sometimes taking dozens of iterations to get a bit of code correct.
In 1987, I had been working for a company that made hard drives (Micropolis). Their business was highly seasonal and, on one particular Friday, all the temps got summarily laid off. I was using Apple One at the time to send me out on engagements and, thanks to my willingness to show up wherever, and whenever, they would offer me a job, I got a call from them on that very Friday, telling me to report to Rocketdyne the following Monday.
By this time I had been shifting my focus from working under the hood, to figuring out how to best use the systems and tools that were rapidly evolving as business tools. I was beginning to focus more on business results with whatever was available. My first responsibility at Rocketdyne was to enter text I received from Engineers into a document called a Failure Modes and Effects Analysis / Critical Items List (FMEA/CIL). It was in direct support of recertifying the Space Shuttle Main Engine (SSME) for eventual return to flight after the Challenger disaster.
SSME Hotfire Test
It was a strange task, as the document was clearly text-based, yet we were using a spreadsheet to create it. I suppose it made some sort of sense, as the company was an engineering company and that’s kind of how engineers see the world; in numbers, rather than words.
I also worked with a stress engineer on creating an app (we didn’t use the term back then, but that’s what it was) that could be used to predict crack propagation and its effects. I was unfamiliar with the equations behind the program, but my job was to use dBase II to create an interface that allowed for data input and crunched the numbers. It was fun and was successfully used for some time after that.
One year after joining as a temp (referred to as a “job shopper”) I hired in full-time and began working with the Flight Ops team. It was exciting and I spent much of my time massaging telemetry data from hot fire tests of the SSME. I received flat files from a Perkin-Elmer mainframe and eventually ported the data to Microsoft Access, which allowed for further massaging and reporting.
In October of 1988, a little over eight months after hiring in, the U.S. Space Program returned to flight with the successful launch of Discovery. At a celebratory event that evening I met one of the managers of the Program Office. As we talked and he discovered my background, he offered me a job. I did some research and talked to my current managers, who advised me to take it, which I did. As time went on, I moved further away from anything resembling coding and, eventually, wound up concentrating on the use of software and computing tools to increase the effectiveness of me and my colleagues.
Not quite 22 years later, I took an early severance package (which was offered to everyone over 60) and retired. I would turn 63 less than a month after leaving the company. In 2015, I returned as a contractor doing something I had done nearly 20 years previously. I spent the next two years (until February 17 of 2017, to be exact) providing program scheduling for two small rocket engine programs.
Last month I turned 70. I recently signed a referral partnership agreement with an organization I worked with a few years ago. They specialize in machine learning (ML) though I was unaware of that back then. My primary responsibility will be selling their services and, when possible, any product they may create. In order to be effective, I am now studying statistics and ML, partly to better understand what it is I’m selling and partly because I’m fascinated by the algorithms that power these efforts.
I do worry that my comprehension is somewhat hampered by, if not the years, the considerable mileage I’ve managed to accumulate. There’s also a minor problem with my “just don’t give a shit” attitude about a lot of things. Nevertheless, I will persist. I intend to share what I’m learning but, as with most things these days, it may be sporadic and somewhat unfocused.
I do believe machine learning is going to drastically change just about everything humans do and I’m well aware of the disruption it might entail. I don’t however, believe that to be a show stopper. We’ve opened Pandora’s box and there is no closing it. Let’s roll!
Since my retirement from Pratt & Whitney Rocketdyne in 2010, I have spent quite a bit of energy on developing work as a social media marketer for small business, a business manager for an AI software development firm, and as an editor/proofreader for a number of business books and a couple of novels, as well as a two-year return engagement at Rocketdyne from 2015 to 2017.
I have decided to stop actively pursuing business in these fields and am now positioning myself to be a writer. I have done quite a bit of writing over the years, but I’ve never really attempted to make any money at it; at least not specifically. I’m starting out with a couple of memoirs and, currently, I’m studying the craft, creating a detailed outline and timeline, and honing my skills as a storyteller. Pretty sure I’ll be writing some fiction as well.
The views expressed herein are those of the author. Any opinions regarding the value or worth of particular business processes, tools, or procedures, whether at his former place of employment, at a current client's enterprise, or in general, are his responsibility alone.