‘Data Director’ Donal fondly remembers his early days in the IT business and still finds it hard to believe it was more than 40 years ago.
He remembers his first role; a morning milk run pushing a cart piled high with green bar computer reports, generated overnight on the bright shiny mainframes of the recently arrived California chip manufacturer.
As he placed them without mercy on the desks of overworked accountants and engineers, he silently agreed with his mother’s twice-daily wisdom: “Work hard. You were lucky to get started.”
Now Donal’s retirement day has arrived and there is only one meeting left on his empty calendar. ‘New Grad Gretchen’ has become increasingly concerned about the growing unrest known as ‘Artificial Intelligence’ and has sought his advice on how best to use it to serve her lofty career ambitions. Should she retrain, upskill, upskill or just do something completely different with her life?
As he ponders his response, his mind’s eye wanders back to some of the technological transformations he’s witnessed since that first milk run, all of which also caused unrest. Dumb terminals, floppy disks, desktop computers powered by Seattle software. Global ERP installations, WAN networks, internet everything, automation, cloud computing, cybersecurity and much, much more.
And now, just as he reaches for the exit door handle, along comes generative artificial intelligence, perhaps the greatest technological disruptor since the invention of the transistor. He has no idea what to tell Gretchen, but if he were to ask Peter Rose for advice, it would go like this: “Tell her not to panic. Once upon a time everything was new and scary.”
Like the fictional Donal, the real Peter Rose has had a long and interesting career in the digital world. In 2002, he founded Dublin-based TEKenable, a specialist in Low Code Platforms, Data, AI and digital transformation services and solutions.
Peter Rose’s mission is to help TEKenable’s customers – large and small, national and international – safely navigate the dangerous jungle of complex digital transformations.
“The skills don’t change with AI,” says Rose, who warms to his subject. “The skills are not about understanding individual technologies or the latest ‘state of the art’ developments. The skills are, always have been and always will be: critical thinking. The ability to break down a problem into individual components that can be solved with whatever tools you happen to have in your toolbox that day. And know that your toolbox changes regularly. The only thing that has happened is that we have acquired a new tool, namely artificial intelligence.”
Unsurprisingly, the noisy and increasing presence of artificial intelligence in the public consciousness means that Rose is extremely busy at the moment. He and his team are fighting on the front lines of a chilling clash between the ‘dry’ digital world, where trillions of ones and zeros are moved quickly by semiconductors and stored in data parks, and the ‘wet’ world of humans where emotions are moved quickly by ruthless uncertainty and stored in restless souls.
His goal is to provide operational clarity and hopefully some personal peace of mind to customers whose media headlines scream that “the end of the world is nigh,” that humans are about to be enslaved by machines, that massive job losses are inevitable and that the resulting social unrest will be tumultuous.
It is not surprising that Peter Rose does not see things so clearly.
“The fact that it looks, sounds and talks like a human is new. It has the ability to be more human than any other system has ever been and that can lead to false expectations and wrong insights,” he explains. “AI is generated probabilistically, so it is not the final set of steps that lead to a defined outcome. Each time it is asked it generates different answers to the same question. Therefore, it should be treated with a high degree of skepticism, as it does not have the same degree of reliability as previous computer programs.”
A subtle but crucial point. Historically, programs were designed to generate predictable results; if a computer gave a wrong answer, there was simply a bug in it, and bugs could always be fixed. In contrast, artificial intelligence produces results that are neither predictable nor necessarily accurate. New Grad Gretchen and millions like her will have to adapt to this new ambiguity in their future work, where certainty and predictability can be replaced by choice and interpretation.
But first of all, Peter. Will she still have a job in five years?
“It’s not where people think it necessarily needs to happen,” assures Rose. “In manufacturing, for example, most of the conceivable automation has already been completed and much of the impact of technology on production has already taken place. The biggest impact will likely be in areas like middle management, where they do things like preparing reports, building content, and so on. That’s the kind of thing AI can certainly do faster than a human. It still needs to be critically reviewed, but it’s a lot easier and faster to review it than to write it from scratch.”
Yet the relentless pace of the impending AI work disruption still leaves countless workers feeling like they are trying to drink water from a fire hose, and that feeling of anxiety just won’t go away.
Furthermore, AI programs now consistently beat the world’s smartest PHD graduates in science and math in open competition, opening up a whole new vein of uncertainty. The traditional approach to raising educational levels no longer guarantees career advancement or longevity.
In light of such changes, what practical steps and detailed actions would TEKenable recommend to employees like Gretchen to maximize future career opportunities in these new workplaces?
“She should be looking at the technologies she is going to bring to her team or her position,” Rose said. “She must be familiar with the automation markets. Gretchen doesn’t have to be an AI expert by any means, because the AI she will use will be used commercially. The most complex AI technologies are packaged in a beautiful model, so she doesn’t have to worry about the level of complexity. She must be familiar with what is possible, what she should pay attention to. There is a need for someone to oversee that level of control and governance.”
He then looks at a constructed example of, for example, an employee in a traditional credit management position. How will that new AI tool in the toolbox impact the day-to-day work of cash collection?
“These types of crucial decisions, which have far-reaching consequences, require a human being involved and that is the opportunity for the company. To understand far beyond the machine’s capability, to understand the situation the customer is in. That’s where critical thinking skills come in handy. These tools are accelerators rather than pure decision engines,” he continues.
“Because of its probabilistic nature, you can’t put AI in charge, it can’t have an autopilot mode. Dealing with the needs of key customers has a human touch and not just a set of rules. Governance and justification for decisions will not go away, so you will always need a human. You cannot allow an AI service to simply put a customer on hold, as this will have unexpected consequences for that customer, and could create potential liabilities for a company that does so.”
That company is led by a board of directors and senior executives, a cohort that is often difficult to convince that real change is coming. The major shifts in the computing paradigm that both Donal and Peter have experienced over the years have all been disruptive and expensive, and those at the top resent both the cost and the disruption. The sheer amount of ‘unknown unknowns’ surrounding AI has many CEOs frozen like rabbits in the face of oncoming headlights.
When Rose meets with leadership, he first tries to convince them to avoid “mistake number one” and view AI merely as a technical problem to be handed off to the IT department. He urges them to embrace the AI challenge above all as a challenge of organizational change and cultural redesign.
“First you need an AI strategy for what your company will do in the short and medium term. The long term is far too unpredictable,” he says. “The second is education, where you give your workforce the skills to work with these tools so that when employees come into your organization, they understand that your purpose is to support and help them, not replace them .
“Companies are generally not interested in replacing their experienced staff. But you must prioritize a level playing field at board level and among the senior team. Define the risks, discuss the impact on compliance and governance and then move on to the efficiency analysis, then change management and education.”
Despite his dry analysis of the ongoing data revolution, Peter Rose also lives in the wet world. He has family, friends, employees, customers and a continuing interest in a progressive and functioning civil society. So when his head hits the pillow after another busy day, what’s the one thing about AI that keeps him awake at night? What is the sum of all his fears?
“I think I see it already,” he replies, chuckling. “It’s about the cyber security side. The dynamic until recently was people creating ‘malware and phishing’ that were somewhat detected by software, but mostly we relied on the cleverness of the person behind the machine. What is now happening very, very quickly is that the machines are discovering vulnerabilities and are now able to link vulnerabilities together.
“The machines are developing increasingly sophisticated attacks that humans haven’t even thought of, and they’re moving at a pace too fast for human defenders to actually recognize. The AI defenders are engaged in an arms race with the attackers that is already beyond human comprehension. Those with the greatest resources who can train the largest models with the largest amount of content will win.
On his very last day in the IT business, Data Director Donal sits alone in his office, booking plane seats to southern Spain and grimacing because he has to bring his golf clubs. As he presses the ‘buy’ button, he hears a tap on the door and Gretchen walks in. He invites her to sit down and apologizes that he only has a few minutes before the people will gather for friendly speeches and warm farewells. He notices how restless and nervous she seems.
“The only advice I can give you after forty years in this game,” he soothes, “is this. Don’t panic. Once upon a time everything was new and scary.”
