“Robots are not going to replace humans, they are going to make their jobs much more humane. Difficult, demeaning, demanding, dangerous, dull – these are the jobs robots will be taking.”

— Sabine Hauert, Co-founder of Robohub.org

“The development of full artificial intelligence could spell the end of the human race….It would take off on its own, and re-design itself at an ever-increasing rate. Humans, who are limited by slow biological evolution, couldn’t compete, and would be superseded.”

— Stephen Hawking, Physicist

“As more and more artificial intelligence is entering into the world, more and more emotional intelligence must enter into leadership.”

— Amit Ray, AI Scientist

“It’s natural to wonder if there will be a jobless future or not. What we’ve concluded, based on much research, is that there will be jobs lost, but also gained, and changed. The number of jobs gained and changed is going to be a much larger number, so if you ask me if I worry about a jobless future, I actually don’t. That’s the least of my worries.”

— James Manyika, Chairman and Director, McKinsey Global Institute (MGI)

The above quotes suggest, to me at least, that nobody has any real idea about where automation and AI are taking us. Things are changing, quite unpredictably, and in huge ways. Guessing and conjecture abound today but mostly not in a helpful manner.

Automation and artificial intelligence, despite their common usage, are basically techie terms. For purposes here, a couple of sort-of definitions:

Automation: The technique, method, or system of operating or controlling a process by highly automatic means, as by electronic devices, reducing human intervention to a minimum. a mechanical device, operated electronically, that functions automatically, without continuous input from an operator.

Umm … okay. In other words, a machine that does something useful without much or any involvement of a human operator. Replacing human-labor with machine-labor. Goodbye human-labor jobs? Anything but.

Artificial Intelligence (AI): The theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.

Apart from the cynical observation that much intelligence of all sorts today seems effectively artificial, AI seems to involve augmenting whatever it is that humans do with a much smarter machine (computer). Can a smart machine not just augment but replace an increasingly not-so-smart human? Of course, but only in certain places. Goodbye more human-smarts? Again, not really.

Early model of AI?

We are really talking about human progress

Much of human progress has involved replacement of nasty, difficult, and generally undesirable human tasks with machinery of one kind or another. Over eons. In uncountable ways. Nothing new today except specifics.

Each step forward in this respect released some people from a crummy job to one mostly less-crummy. In many cases, the new machinery did things that humans simply could not – such as lifting and rapidly transporting heavy weights and moving about underwater for extended periods. I’m sure that you all can think of a few more examples.

Many, and probably most, of these steps involved changing what some people did for a living (and other activities). This required a job loss followed by – assuming survival of those impacted – by a changed or new occupation.

The McKinsey quote above really captures the essence of what is happening – even in the currently-esoteric worlds of automation and AI. It is simply a continuation of change and (mostly) progress that has been going on for approximately forever.

Is the auto really just an automated horse? Of course.

So maybe the issue is not whether automation and AI will make many of us obsolete but instead whether we may well end up working for robots and computers. That is a truly nasty prospect, yes?

Automated horses are most welcome in my humble opinion. To a kid on a ranch whose chores included shoveling very non-automated-horse droppings, cars and trucks were definitely a great improvement. Some might also note that such childhood chores would be a good learning experience for a blogger.

Job “losses” are really job transitions

Getting obsoleted by a machine of some kind has been going on forever. In many cases, the obsoleted person seeks the same kind of work elsewhere. Even using immigration. In other cases, the person may acquire new skills that qualifies them for a different kind of work.

Some unfortunates of course will be unable to make such a transition and will ultimately expire. But expiration at some point is not an option; only timing and means are somewhat controllable.

So long as global population continues to grow at recent rates, huge numbers of new jobs will be required each year. Population stabilization seems to be underway so maybe this job growth can be accomplished without too much pain.

Job-splitting is another stopgap solution but it typically lowers the standard of living of splittees. Universal Basic Income efforts seem to address such situations but the downside is mostly the consequences of money-printing. Like inflation, possibly even of the hyper variety.

Automation and AI impacts are a bit scary

Josh Dzieza writing in The Verge (2020) sets the stage for an increasingly common concern: “HOW HARD WILL THE ROBOTS MAKE US WORK?”:

“In warehouses, call centers, and other sectors, intelligent machines are managing humans, and they’re making work more stressful, grueling, and dangerous. On conference stages and at campaign rallies, tech executives and politicians warn of a looming automation crisis — one where workers are gradually, then all at once, replaced by intelligent machines. But their warnings mask the fact that an automation crisis has already arrived. The robots are here, they’re working in management, and they’re grinding workers into the ground.”

Is this a real concern or it is mainly journalistic hype? This piece highlights Amazon (of course) and worker anecdotes, noting in passing that the “…robots changed the nature of the work…” despite major warehouse job growth.

“There are robots of the ostensibly job-stealing variety in Amazon warehouses, but they’re not the kind that worry most workers. In 2014, Amazon started deploying shelf-carrying robots, which automated the job of walking through the warehouse to retrieve goods. The robots were so efficient that more humans were needed in other roles to keep up, Amazon built more facilities, and the company now employs almost three times the number of full-time warehouse workers it did when the robots came online. But the robots did change the nature of the work: rather than walking around the warehouse, workers stood in cages removing items from the shelves the robots brought them.”

It seems to me that Amazon is probing the limits and structure of highly automated facilities. Worker turnover, injuries, and burnout define such limits. These are costly but probably “necessary” to learn what works and what doesn’t. No one is forced to work under these conditions so it is still up to each worker to decide when enough-is-enough for themselves.

Automation and AI are changing the nature of work

This is probably the key to what is actually going on. Automation and AI are relatively new technologies that are best evaluated and adjusted in real applications. Job losses and redefinitions are part of such evaluations and adjustments. This is sometimes referred to as “change”.

Romil Shah writing in Phrazor gives a helpful example:

“Let’s travel back in time and recollect how bank tellers felt apprehensive about the then newly launched ATMs. The number of bank tellers did fall from 20 per branch in 1988 to 13 per branch in 2004, greatly reducing the cost of running a branch. This allowed banks to open more branches in response to customer demand. The number of branches rose by 43%, thus employing more people whose work now was focused on sales and customer service rather than routine activities.”

He also gives a product pitch that seems like an interesting application:

Robot-Journalism is enabling human journalists to concentrate on investigative journalism and write smarter pieces that involve extensive research and information gathering by generating fact-based, personalized stories from structured data at a faster rate and a lower cost. Robot-Journalists share the workload with humans, instead of stealing it thus favoring the firm’s growth and success.”

Robot-journalism? Might actually be real progress except that so much of journalism today appears to be robotic. The real writers out there are unlikely to be much affected. Thankfully.

Most people who are “obsoleted” will adapt with new skills

This is just what people do. My job making buggies and carriages just bit the dust? No problem – just heard that some guy down the street named Henry Ford is hiring folks to make some kind of new-fangled gadgets. I’m easy and like to eat so I’ll manage to adapt. Henry, here I come.

Workers will learn new skills that are required by changing markets and evolving technologies. Companies will adapt their processes and people to these innovations. When the dust settles, technologies will dominate where they work best and most cost-effectively. Workers will shift to activities that machines can’t do well or at all. Happy ending.

Automation and AI can’t do creativity and people-skills

While automation and AI can perform many tasks, they can’t replace the human creativity and people skills that for example ultimately nurture the relationship with your prospects and customers. To appreciate this fact firsthand, try a few robochat sessions.

There remain huge numbers of jobs where human skills and contact are not just desirable but essential. A major competitive advantage even.

Timothy B. Lee in Vox echoes my sense of the situation: “Automation is making human labor more valuable than ever”:

“The modern economy was built on automation, so it’s natural to assume that the future will be defined by automation as well. It seems like every week there’s a new study or think piece about the job-destroying potential of robotics and artificial intelligence.”

“As automation makes everyday products cheaper and more plentiful, people will increasingly shift their spending to goods and services where a connection to a human provider is seen as a key benefit.”

“Over time, technological progress is steadily wringing inefficiencies out of manufacturing processes. But in service-related industries, the “inefficiencies” involved in talking to other people are often a key benefit.”

This means that automation and AI are actually great news

Life is change. Including job changes. Always has been; always will. What is happening today is that anything that can be automated is rapidly being automated, leaving the activities requiring human creativity and human interactions to, well, us humans. How can this not be a good thing?

AI can help eliminate errors and reduce the need for repetitive tasks. Also good. Anything that helps me work more error-free is welcome.

Personally, I have been obsoleted many times over the years. It even shows. No matter. Each time, so I recall, the transition happened largely out of my control and so often for the better. Post-pain-period of course.

I cannot imagine living in a static world. George Orwell wrote about one version that occurred I think around 1984 but it seems pretty nasty. Being obsoleted now and then is truly the spice of life. Or spice of something.

Bottom line:

Your greater worry in my view is that you are not being obsoleted. This means that you are becoming increasingly vulnerable to inevitable changes that will occur like it or not. You want to be more-or-less keeping up with whatever is obsoleting in your world so that you are always adapting with new and improved skills. With agility and smart-adaptably.

India-based vPhrase Analytics, a global technology company that provides AI-powered business intelligence and reporting automation solutions, writes that: “Phrazor Enters the Arena of Robo Journalism”:

“As the accumulation of data grows at a rapid pace for various industries, automation comes to the rescue and enables businesses to analyze large amounts of data much more efficiently than humans ever can. Phrazor uses Natural Language Generation techniques to help enterprises make the most of their data and communicate it in the form of written narratives in a human-like manner.”

“While our expertise in analytics and reporting has helped several businesses across industries to get insights out of their data, the new use case of Phrazor encompasses the generation of AI-powered high-quality content at the click of a button. So, what does Phrazor do?”

“Over the past several years, capturing of play-by-play data has become a standard in sports, which has leveled up the data volume. Handling this huge amount of data in real-time becomes too time-consuming and hard to digest for journalists and data analysts. This is where NLG tools like Phrazor can help. Phrazor writes detailed commentary after every 5 overs of the IPL match for the client, which is published on their live feed in real-time. Here are a few snapshots of commentary written by Phrazor.”

Christine Jones wring in TheEarthAwards offers a simple list of pro’s and con’s:

“The Pros of Automation
> Efficiency
> Reliability and Consistent Output
> Lower Production Costs
> Increased Safety”

“The Cons of Automation
> Initial Investment
> Incompatible with Customization
> Job Uncertainty”