As orgs move past traditional solutions in tech to advance their business during the pandemic, one thing is clear: the way they operate today has been forever changed.
Get the full story from Former Grand Chess Champion @kasparov63 here: https://t.co/77PVzTN8Od#lowcode #AI pic.twitter.com/ERLUTPWbCY
— Appian (@Appian) February 3, 2022
This article is a reprint. You can see the original at Appian.
“Despite the challenges of the past two years, I’ve been speaking regularly on AI and the future of the human-machine relationship. Often I’ve done it thanks only to some of those machines, using remote tech that was previously seen as a gimmick, a convenience, or an annoyance.
When pushed by a crisis, it’s remarkable what we can accomplish. The old saying that “necessity is the mother of invention” also applies to inventions that already existed but weren’t considered necessities. Suddenly, when need arises, the barriers turn out to have been artificial, temporary, even psychological.
The modern city is defined by skyscrapers, amazing monuments to our mastery over concrete and steel. But they wouldn’t be practical without elevators! And for decades, every elevator had an operator, so many of them that their union in New York City was 17,000 strong in 1920. This may sound reasonable, as early elevators could be quite complicated and operators knew how to keep the sensitive machinery running well.
But I learned something surprising when I was invited to speak to the Otis Elevator Company in Connecticut in 2006. The technology for automatic elevators had existed since 1900, but people were too uncomfortable to ride in one without an operator. It took the 1945 operators strike (a crisis, if a small one) and an industry PR push to change people’s minds, a process that is today repeating with driverless cars and other automated technology. The cycle of automation, discomfort, acceptance, and, steadily, massive gains in productivity and living standards goes on.
While a few jobs like elevator operator are destined to be trivially automated and made redundant, most are modernized, integrated with powerful new tools. Artists weren’t put out of work by digital art; they were given tremendous new scope for their creativity. Musicians eventually embraced synthesizers (pioneered by the remarkable Ray Kurzweil, better known in AI circles for his books and theory of the singularity), and drum machines still need musicians to turn their sounds into songs.
Returning to my recent lectures, in several I found myself defending the critical role of humans in a world obsessed with the latest technology. At a cybersecurity conference in Israel, the described billions of threats per second could only be met by AI that could keep pace. The bad guys also used AI to adapt and generate new threats, of course, in an endless cycle.
But machines aren’t bad or good, they are tools, tools used by humans. A big drop in cyberattacks occur not when the firewalls and other defenses get good enough, but when the hackers are tracked and arrested! That’s a negative example of the human element, to be sure, but the moral of the story applies as well to the good guys trying to use tech to make our work easier, our companies more profitable, and our lives better. They succeed when they center the human element, as well as the human experience in the outcome.
This isn’t only important for attracting and keeping talent to your company, although that’s a good thing to remember. There are concrete, bottom-line reasons to embrace tools that make human-machine collaboration easier and more powerful. There simply aren’t enough high-level coders to meet demand.
A recent IT industry report marked several unmistakable trends in IT, all exacerbated by the pandemic that has put an urgent emphasis on the ability of companies to adapt quickly. First, that developers are in the highest demand ever. Second, that a majority of software projects are being delivered behind schedule. Third, costs of development are rising relative to other costs.
When such a perfect storm is brewing, you have to look past traditional solutions and find new frameworks. In 2006, I was invited to speak in Vienna at an event honoring great mathematician Kurt Gödel on the 100th anniversary of his birth. (Many assume that chessplayers are all gifted in mathematics, but I assure you that in my school years I much preferred history and literature, a tendency that continues today!)
I did not attempt to fool a room full of experts with comparisons between chess and Gödel’s famous theories of mathematical incompleteness. On a very superficial level there exist some analogies, since I believe there are always true things in chess that cannot be conclusively proven. And while it’s a stretch to apply his statements about mathematics to other endeavors, I believe one in particular applies very well to other areas. To paraphrase, Gödel wrote that every system will contain a problem that cannot be solved from within the system itself.
That is, it’s vital to not just look around, to look for solutions within the system, but to step back and look above, to look outside of the system where the problem was created. Hiring more coders, for example, is the standard systemic solution to development slowdowns. And recruiting and hiring better ones, competing to the sky against other companies in the same dilemma.
The supply of expert coders cannot be increased easily or quickly, so the answer must come from the other direction, from a different framework: making tools that don’t require expert coding proficiency but that can still solve the problems. As Ray Kurzweil said when critics of his music synthesizer complained, “But now anybody can make music!” “Yes, exactly!”
Study after study has shown that industries with more technological disruption do better, not worse. They hire more people, not fewer. Their employees are better paid and enjoy their work more than in industries insulated from tech, including AI automation.
The reason is obvious to any follower of economists like Joseph Schumpeter, the prophet of what he called creative destruction. The “deliberate dismantling of established processes to make way for improved methods of production” is always a big and necessary boost to the economy, from the railroads to Henry Ford’s assembly line to the internet. And it’s not just GDP, but real workers, people, let’s not forget, who are freed from routine work better done by machines.
This is not to be callous. AI automation and rapid change will not have only winners—no change ever does. A key goal to make the most winners, to share the benefits broadly. The more we can democratize technology to include the widest breadth of humanity, the more the gains will be shared. To put on my human rights advocate hat for a moment, this goal is as important to me as any bottom line. The good news is that they can be connected, not opposed, if we keep centering people and how tech effects them.
Tech that puts power into more hands, into more diverse environments, and empowers people of different ages, backgrounds, and talents, is the best kind of technology. What we must remember, always, is that we make those choices.
As AI pioneer Joseph Weizenbaum wrote, “Deciding is a computational activity, something that can ultimately be programmed. Choice, however, is the product of judgment, not calculation.”
If we want the right things, if we make the right choices, we will use these powerful new tools to reach our dreams as well as our budgets!
In the last two years, some companies have had to move past traditional solutions to scale or automate tasks while others adopted advanced technologies just to stay afloat. One thing is certain: the way companies operate today has been forever changed. For more on technology’s role in business advancement, read Grand Chess Champion Garry Kasparov’s thoughts here:
As orgs move past traditional solutions in tech to advance their business during the pandemic, one thing is certain: the way they operate today has been forever changed.
To learn more about Garry Kasparov’s thoughts on all things low-code and key trends in the technology space, head to his inaugural blog, “The Real World AI Experiment”.”