Expert Urges Employers to Weigh More Than Just Profits When Considering AI
Amy Webb, a futurist specializing in emerging technologies, is optimistic about the unprecedented advancements in AI that have propelled the world into unknown realms. Webb utilizes both quantitative and qualitative modeling to predict the potential effects of these technologies on various aspects of society and business.
As founder and CEO of the Future Today Institute, Webb has wrestled with artificial intelligence and all the associated fears, from doomsday scenarios to market crashes and job destruction.
We caught up with Webb earlier this week at the SXSW conference in Sydney. (The questions and answers have been edited and condensed.)
We are now on WhatsApp. Click to join.
How does artificial intelligence affect employee productivity?
AI can greatly improve productivity in cognitive jobs that involve a lot of reading, sorting, and tagging. These are often found in professional services, law firms and investment banks. Fewer man-hours are required to complete these tasks, and you can ask the AI system to look for patterns you may have missed. That said, people still use technology. There are many cases where there is an abundance of technology around us and people are somehow less productive. Humans are kind of biologically wired to consume as little energy as possible – it’s literally within our cellular structure – so I’m curious to know if this is positive for our innate sense of laziness going forward, and what that might mean.
What will artificial intelligence do to the labor market?
People ask, “will AI take my job? Or take a bunch of jobs?” But no one asks what it takes to make it true. We don’t have enough plumbers anywhere, do we? We have come a long way in medicine. You can use artificial intelligence systems with computer vision to detect anomalies. But for AI to truly replace the knowledge worker, workers themselves must undergo training to train these AI systems.
For example, medical students in certain parts of the world are offered money to sit eight hours a day and click “Yes or No” through so-called reinforcement learning with human feedback as training. But it’s a drop in the ocean in the end. It is much more productive to ask, “How will the business model change in the future?” For example, the structure of billable hourly wages must be changed in some industries.
What do C-suite executives tell you about AI and new technologies?
They are interested in fundamental discussions. Having more advanced nuanced conversations requires leaning into uncertainty. A bank CEO recently asked me how AI can reduce headcount. But if you start adopting AI as a way to just improve your bottom line by lowering wages, you’re going to run into a problem in a couple of years, if not sooner.
What should they think?
Artificial intelligence is a set of different technologies and can be used to create tools. In a few years, they will be different jobs needed, so CEOs have to be very careful about making short-term decisions because it improves the bottom line. The real opportunity is in top-level growth and figuring out where they can create new revenue streams, improve relationships and turn it into a force multiplier. That’s where most leaders should be putting their energy right now, but I don’t see that happening in any country around the world.
What are some good AI-related questions CEOs ask you?
They ask what it takes for us to be flexible versus how soon we can lay people off.
What confuses people?
At the moment, AI has become a kind of shorthand for ChatGPT. The non-technical side of organizations only talk about it as a text-based system that provides answers.
What concerns you?
After your data has been used to train a system, how do you know who owns it and how you can monetize it in the future? The real questions should be, “Where does it get its information? Am I okay with it. Do I trust it?” Once you hand over your archive and let it be used to train an AI system, you can’t get it back out.
What next?
Multimodal. This is an artificial intelligence system that can do multiple things at once. Utilize different forms of logic, reasoning and analysis. So it can be used for more complex challenges or decision points that a manager might face during the day, provided there is enough context.
Do you have interesting examples where you have tested AI?
I was a keynote speaker at a major financial services conference, and before my panel was loan syndication, which was far outside my area of expertise. I copied and pasted the description of the show and panelists into a few AI chat tools and asked each system to hold a panel and tell me what insights it would have. Aside from the diagrams, charts, and linguistic reflections that each person brought, there really wasn’t a discernible difference to the actual panel.
One more thing! ReturnByte is now on WhatsApp channels! Follow us by clicking the link to never miss any updates from the world of technology. Click here to join now!
