One can learn a lot about AI from fish. The 1990s were a terrible time for the toothfish. An ugly fish inhabiting the deep seas, the toothfish (pictured above) was long considered a “trash fish,” undesirable to eat, a worthless catch.
The toothfish’s fate was fine until overfishing decimated the stocks of the long-popular fish, and the fishing industry looked for something more plentiful to make its way to people’s plates.
The toothfish was discovered. It was the perfect fit for the American palate – tasteless and bland, but not fishy, and with a smooth and buttery texture. But it needed something with pizazz to take off, and with most things these days, the magic was in the branding. The toothfish was rebranded “Chilean sea bass” – even though it isn’t a bass. And the rest is history. The fish became a popular menu item – a luxury one, a fish of distinction, a fish fit for sophisticated palates and big bucks. This happy story for the fishing industry is an unhappy one for the toothfish. It’s now overfished and its numbers are dwindling.
The rebranding story is similar for other fish. The slimehead was rebranded Orange Roughy. Goosefish became Monkfish. Whore’s Egg was rebranded as Sea Urchin. Hog Fish became King mackerel.
AI as Branding
The story of the toothfish reminds me a lot of the story of AI. Technologies that have long been around have been rebranded as “AI” even though they technically are not AI. And the rebrand has led to wild success. Now, nearly everything with an algorithm is called “AI.” Mention the word “AI” and ears perk up, reporters swarm like insects to the light, and money pours in.
Eric Siegel proclaims that “A.I. is a big fat lie.” AI is “a hyped-up buzzword that confuses and deceives. . . . AI is nothing but a brand.” AI is not intelligent or sentient; what is referred to as AI today primarily involves a technology called machine learning, which hearkens all the way back to the 1940s.
Avoiding AI Exceptionalism:
AI Isn’t a Radical New Invention
As I’ve written in my article, AI and Privacy, AI is of critical importance that we avoid falling into what I call “AI exceptionalism” – treating AI as if it were a big break from the past. Instead, AI is a continuation of the past, a set of old technologies that have evolved and finally attracted the spotlight.
Why does it matter whether we see AI as old or new? In my field of privacy law, it matters because if policymakers see AI is totally new, they might neglect revisiting old privacy laws. Policymakers might view AI as so new and different, that they’ll leave existing privacy laws behind. As I wrote in the article:
Overall, AI is not an unexpected upheaval for privacy; it is, in many ways, the future that has long been predicted. But AI starkly exposes the longstanding shortcomings, infirmities, and wrong approaches of existing privacy laws.
AI’s rebrand brings both good and bad results. Fears of AI becoming sentient and killing us all might motivate policymakers to act, but these fears can distract from real problems occurring right now.
Turning back to fish rebranding, there are at least two important lessons to be learned for AI.
The Perils of Popularity
First, once something becomes hot, the result is a craze, and it is desired in undesirable ways. When a fish becomes famous, it is overfished and risks extinction. Fame isn’t a friend to fish. Rarely do we embrace something in a balanced way – people either love it too much or too little.
AI is being embraced too hastily, in clunky and ill-fitting ways. People are rushing to sell AI to do anything and use AI to do anything, even when these AI tools are not optimized to do all these things. Ai these days is like a hammer, and people are trying to use it as a saw or screwdriver. They call these screwups “hallucinations,” but these errors are really trying to make AI do things it isn’t designed to do. Generative AI works best to generate content based on popularity, not authority, so it will make up details and sources.
How We Perceive AI Affects Its Power
Second, the power and spread of technology is not just about the technology itself. Some proponents of technology think that technology is itself the main engine for its proliferation and use, but we must not forget the importance of the framing and narratives around technology, which as a tremendous impact in how technology is used, how it becomes popular, and how it is integrated into society. Again, consider fish. As an article in the Washington Post observes, “Today’s seafood is often yesterday’s trash fish and monsters.” Lobster evolved from a food fit for lower classes into an expensive luxury item.
Reframe something with a fancy name, and suddenly it goes from undesirable to indispensable. It is astounding the power that framing has on human perception, desire, and demand. As Alex Mayyasi writes:
[T]he line between bycatch and fancy seafood is not a great wall defended by the impregnability of taste, but a porous border susceptible to the effects of supply and demand, technology, and fickle trends. This is true of formerly low-class seafood like oysters and, most of all, the once humble lobster.
The story of technology is one told and shaped by people and institutions, who have incentives and intentions. The power of AI emerges significantly from the way we perceive it.
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Professor Daniel J. Solove is a law professor at George Washington University Law School. Through his company, TeachPrivacy, he has created the largest library of computer-based privacy and data security training, with more than 180 courses.
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