There is a chorus of “thought leaders” who argue that AI will not replace managers.of harvard business review has spearheaded a series of articles arguing that AI will not replace human decision makers and that AI will not replace human decision makers. “It enables knowledge workers to focus on value-added activities where human expertise is essential.” (Saenz, 2023). De Cremer and Kasparov (2021) argue that: “AI should augment human intelligence, not replace it.Martela and Luoma (2021) declare: “AI will never replace managers.” Because, at least for now, humans are better at “reframing” problems than machines.Other papers HBR Focusing too much on AI can actually lead toIt creates more problems than it solves.” (Acar, 2024), Shrier (2023) uses a simple title to explain the jobs most and least affected by AI. “Is your job AI-proof?” Finally, Lakhani (2023) argues that: “AI will not replace humans, but humans with AI will replace humans without AI. The general conclusion is that humans and their uniqueness don't need to worry too much about losing their jobs to algorithms, and that AI is an assistant, not a partner, and certainly not a boss. This is like an employee deciding to stay in their job forever. No matter how well he or she performs.
thought leaders make mistakes
What if the thought leaders are wrong? There's no guarantee they're right, right? The history of technology is full of cases where experts got it wrong. Thought leaders and experts overlooked the impact social media has on communication, activism, and commerce. They didn't realize the collapse of the Internet business model. They have overlooked the decline in the EV market that we are currently experiencing, and let's not forget the adoption of the Metaverse, Google Glass, self-driving cars, NFTs, VR and AR.
Here are some of the funniest stories Gemini has told me over the years.
“The Internet is going to collapse” (1995): Bob Metcalf, the inventor of Ethernet, famously declared that the Internet would collapse. Thankfully, he later took his word for it.
“No one needs a computer at home” (1977): Ken Olsen, founder of Digital Equipment Corp (DEC), failed to see the potential of personal computers. DEC is now a footnote in history
“The cell phone will never replace the wired phone” (1998): Marty Cooper, the inventor of the cell phone, ironically underestimated its disruptive potential.
“Television won't last long. People will soon get tired of staring at a box every night.” (1946): 20th Century Fox president Daryl Zanuck completely overlooked the power of television as a medium. .
“Video games do not change the way we interact with computers, and they do not have an impact on the computer enthusiast market.” (1975): Popular Electronics, a magazine for enthusiasts, I completely missed out on future advantages.
“Nuclear-powered vacuum cleaners will be in every home by 1995” (1955): Alex Lewitt, CEO of a vacuum cleaner company, says this far-fetched (and frankly dangerous) I made a prediction.
Christensen's The innovator's dilemma (1997) is a tour of how companies that should know better escape reality.
So people who claim that AI won't take our jobs could be very wrong. But how wrong are they?you can't argue with me HBR's While we commonly think about the role of AI in business problem-solving and decision-making, there are other ways to look at the power of AI and its impact on the knowledge professions. AI will replace knowledge workers in far greater numbers than anyone thinks possible. We make it as easy as possible to guarantee that AI won't take your job.
Let's assume they're wrong
So, if Are thought leaders wrong?of harvard business review It fills me with a sense of security. The magazine's assertion that AI will not replace managers is dangerously reassuring. What if AI is destined to obliterate knowledge workers and completely and completely replace them even in so-called high-value decisions? Remember that this is new to . We are on his 1st step of his 10 step journey.th The steps are always in motion. No one knows how this situation will end, except that it won't. That's why determining which jobs are resilient and which are currently not is understandably misleading. Thought leaders are wondering what the power of AI will be 10 or 20 years from now, and what professions (many of which have yet to be invented) will grow, shrink, or disappear entirely. How can we know?
Ideally, you would make short-term predictions based on defined processes and current AI capabilities, and speculate a little about future capabilities. This is safe territory for professionals. It would be a mistake to base an opinion on something based on general principles, such as that humans have unique problem-solving abilities that AI can never replace. However, it is unclear whether such principles will continue into the future.
Domain and timing
You can't talk about the role of AI without talking about segmentation. We need a matrix of domains and timelines. Some areas, such as medical imaging, will move to machine learning and generative AI faster than others. Which is which? The nature of the problem and work must also be specified. All well-bounded domains, regardless of their complexity, are fair game.
Gemini tells us: “Generative AI … often excels at tasks that involve creating new data that is creative in nature. Generative AI shines in image and video generation, content creation, data augmentation, drug discovery, and more.” Here are some problem areas.
I recently argued that higher education and the staff who make it possible are all targets of AI. These “predictions” are based on an area of higher education that is described around the tasks, or processes, that professors and students perform in order to “learn.” today – Especially suitable for AI tools. Higher education is not the only area of vulnerability. Domains with similarly well-defined processes are also targeted.
Please stop trying to reassure me
It’s time to stop feeling comfortable about things that cannot be replaced by AI. If technology trends are any indication of impact, machine learning and generative AI are far more likely to replace knowledge workers than to retain them. It will take some time for this prediction to be verified or rejected, but the argument that AI has limitations and humans are qualified to make certain decisions is false. It is impossible to know what will happen in 10 years, but there is no doubt that machine learning and generative AI will replace more and more knowledge workers in the next 3-5 years. Probably more than we imagine.