Everyone seems sure that ChatGPT and other artificial intelligence (AI) systems will either destroy millions of jobs or create just as many. Most seem to be on the side of fear.
The best thing about any dichotomy like this is that it creates left and right-hand boundaries to clarify the conversation about the impacts of AI. So, rather than, “will AI destroy my job, or will I be fine?” the question should now become: “how can AI help me?”
As the great Yogi Berra once said, it's tough to make predictions, especially about the future. But the beauty of seeing things through an intangible asset lens is that it helps a person notice what others may be missing. It makes the valuable visible. The same goes for AI systems.
Intangible assets come in many forms. Some of them are intuitive, others take a bit of thinking. But generally, it doesn’t take long before our clients are nodding along as we enumerate the 12 classes.
The 12 classes include data, industry expertise, relationships, confidential information, design, approvals and certifications, plant varieties, content, invention, brand, software and network effect. The exact mix of intangible assets is what constitutes 90% of the value of a business.
On its own, AI is a mix of two key intangible asset classes: software and data. Confidential information and industry expertise will also have an influence.
Looking at just the ChatGPT system, the intangible asset of the system’s brand has certainly skyrocketed in value over the last few months as people use it as an umbrella term for AI (think of Hoover as a catch-all for vacuum cleaners). That’s a big win for its Silicon Valley-based parent company OpenAI.
It certainly doesn’t hurt that Microsoft invested $US10 billion in OpenAI, effectively providing a massive co-brand endorsement and a huge expansion to its user base through the search engine Bing. In fact, the Bing mobile app saw a 10x jump in downloads since ChatGPT was integrated into its search algorithm.
The way I see it, yes, AI will impact jobs (every new technology does) but I doubt it will be apocalyptic. Instead, many people will see their productivity explode as they deploy these systems into their roles, which will be great for everyone – users and their clients or customers.
Yet some workers are bound to create “human/AI” teams – android-like partnerships – by using AI to perform tasks at levels far above those who just use these systems as a nice tool. If companies can build these “human/AI” teams, might we be dealing with an entirely new intangible asset class?
While advanced “human/AI” teams might radically improve productivity, this combination of human and machine will still be defined by the intangible assets of software, data, confidential information and industry expertise.
Even as workers figure out ways to use AI as an expansion of their brain, that combination would simply be an extension of what’s already happened with smartphones and smartwatches, for example. Without knowing it, modern humans are already cyborgs. These AI partnerships will carry on this trend.
Think about it this way: “human/AI” cooperation not only beats other humans in all kinds of tasks, but it can also outperform any AI system that is operating on its own.
More simply: AI may outcompete humans, but a “human/AI” team beats AI.
How might such a team be valued? Would it begin with the data or the software? If splitting the two components lowers the overall value of the asset, how much value does the human bring to the table compared to the AI? These are the types of questions valuers might ask.
These “human/AI” teams are a good example of a dynamic we often encounter whereby the value of the whole is greater than the sum of the parts. The true value of AI is created when its intangibles are combined. For instance, data is needed to "teach" the AI system (or machine learning) and humans are required to check that the training has worked. It becomes a symbiotic relationship, which means the constituent intangible assets must be valued as a whole.
American economist Tyler Cowen pondered the implications of this symbiosis in his 2013 book Average Is Over. A core thesis of the book was that the creation of “genius” machines would mean that if a person’s skills don’t complement the AI, then that AI will likely be better without humans.
But if that person can figure out a way to collaborate effectively with AI – become a team – then they will have a set of skills that will be highly valuable in the coming world.
They will know which software to use, how and why. They will know when to follow an AI’s guidance and when to overrule it. And they will understand the strengths and weaknesses of AI systems while being honest about their own. These “human/AI” teams will be valuable precisely because they make AI better than it is on its own.
Imagine a “human/AI” team, perhaps of only a handful of individuals, wielding as much productivity as a thousand human workers and drastically outperforming even the smartest AIs operating alone. Intangible asset specialists will be standing ready to value these impressive new systems accurately.
As originally published on Lexology
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