This year I’ve spoken about little else but AI, and appropriately so: while artificial intelligence has been an emerging technology for some decades, the rise of so-called generative AI, typified by ChatGPT, has been a turning point in public attention.  

Audiences have countless questions: How will AI impact employment?  What will it mean for content owners and copyright?  What are the social implications of flawless deep fakes?  What regulations are needed to prevent abuses?  Will those regulations stifle innovation?  Recently I wrote about how AI could change education.

And much more.  Yet thus far I’ve been asked little about what is most certainly the most radical AI prediction: that it will evolve to threaten humanity.  Leading AI scientists have warned that this invention may lead to our own extinction. 

There’s an interesting historical parallel to those fears, one I recently wrote about for the Los Angeles Times: 

​JUNE 25, 2023 3 AM PT - In the summer of 1974, a group of international researchers published an urgent open letter asking their colleagues to suspend work on a potentially dangerous new technology.

The letter was a first in the history of science — and now, half a century later, it has happened again.The first letter, “Potential Hazards of Recombinant DNA Molecules,” called for a moratorium on certain experiments that transferred genes between different species, a technology fundamental to genetic engineering.

The letter this March, “Pause Giant AI Experiments,” came from leading artificial intelligence researchers and notables such as Elon Musk and Steve Wozniak. Just as in the recombinant DNA letter, the researchers called for a moratorium on certain AI projects, warning of a possible “AI extinction event.”

Some AI scientists had already called for cautious AI research back in 2017, but their concern drew little public attention until the arrival of generative AI, first released publicly as ChatGPT. Suddenly, an AI tool could write stories, paint pictures, conduct conversations, even write songs — all previously unique human abilities. The March letter suggested that AI might someday turn hostile and even possibly become our evolutionary replacement.

Although 50 years apart, the debates that followed the DNA and AI letters have a key similarity: In both, a relatively specific concern raised by the researchers quickly became a public proxy for a whole range of political, social and even spiritual worries.

The recombinant DNA letter focused on the risk of accidentally creating novel fatal diseases. Opponents of genetic engineering broadened that concern into various disaster scenarios: a genocidal virus programmed to kill only one racial group, genetically engineered salmon so vigorous they could escape fish farms and destroy coastal ecosystems, fetal intelligence augmentation affordable only by the wealthy. There were even street protests against recombinant DNA experimentation in key research cities, including San Francisco and Cambridge, Mass. The mayor of Cambridge warned of bioengineered “monsters” and asked: “Is this the answer to Dr. Frankenstein’s dream?”

In the months since the “Pause Giant AI Experiments” letter, disaster scenarios have also proliferated: AI enables the ultimate totalitarian surveillance state, a crazed military AI application launches a nuclear war, super-intelligent AIs collaborate to undermine the planet’s infrastructure. And there are less apocalyptic forebodings as well: unstoppable AI-powered hackers, massive global AI misinformation campaigns, rampant unemployment as artificial intelligence takes our jobs.

The recombinant DNA letter led to a four-day meeting at the Asilomar Conference Grounds on the Monterey Peninsula, where 140 researchers gathered to draft safety guidelines for the new work. I covered that conference as a journalist, and the proceedings radiated history-in-the-making: a who’s who of top molecular geneticists, including Nobel laureates as well as younger researchers who added 1960s idealism to the mix. The discussion in session after session was contentious; careers, work in progress, the freedom of scientific inquiry were all potentially at stake. But there was also the implicit fear that if researchers didn’t draft their own regulations, Congress would do it for them, in a far more heavy-handed fashion.

With only hours to spare on the last day, the conference voted to approve guidelines that would then be codified and enforced by the National Institutes of Health; versions of those rules still exist today and must be followed by any research organization that receives federal funding. The guidelines also indirectly influence the commercial biotech industry, which depends in large part on federally funded science for new ideas. The rules aren’t perfect, but they have worked well enough. In the 50 years since, we’ve had no genetic engineering disasters. (Even if the COVID-19 virus escaped from a laboratory, its genome did not show evidence of genetic engineering.)

The artificial intelligence challenge is a more complicated problem. Much of the new AI research is done in the private sector, by hundreds of companies ranging from tiny startups to multinational tech mammoths — none as easily regulated as academic institutions. And there are already existing laws about cybercrime, privacy, racial bias and more that cover many of the fears around advanced AI; how many new laws are actually needed? Finally, unlike the genetic engineering guidelines, the AI rules will probably be drafted by politicians. In June the European Union Parliament passed its draft AI Act, a far-reaching proposal to regulate AI that could be ratified by the end of the year but that has already been criticized by researchers as prohibitively strict.

No proposed legislation so far addresses the most dramatic concern of the AI moratorium letter: human extinction. But the history of genetic engineering since the Asilomar Conference suggests we may have some time to consider our options before any potential AI apocalypse.

Genetic engineering has proven far more complicated than anyone expected 50 years ago. After the initial fears and optimism of the 1970s, each decade has confronted researchers with new puzzles. A genome can have huge runs of repetitive, identical genes, for reasons still not fully understood. Human diseases often involve hundreds of individual genes. Epigenetics research has revealed that external circumstances — diet, exercise, emotional stress — can significantly influence how genes function. And RNA, once thought simply a chemical messenger, turns out to have a much more powerful role in the genome.

That unfolding complexity may prove true for AI as well. Even the most humanlike poems or paintings or conversations produced by AI are generated by a purely statistical analysis of the vast database that is the internet. Producing human extinction will require much more from AI: specifically, a self-awareness able to ignore its creators’ wishes and instead act in AI’s own interests. In short, consciousness. And, like the genome, consciousness will certainly grow far more complicated the more we study it.

Both the genome and consciousness evolved over millions of years, and to assume that we can reverse-engineer either in a few decades is a tad presumptuous. Yet if such hubris leads to excess caution, that is a good thing. Before we actually have our hands on the full controls of either evolution or consciousness, we will have plenty of time to figure out how to proceed like responsible adults.

Can government keep up with the accelerating rate of technologic change?  The answer is, usually not. In the US, at least, government moves slowly and is captive to multiple conflicting influences.  Legislators react after problems arise, and even then may not fully understand the underlying technology.      

Instead, insurance companies may become the real regulators of new technology.

Consider autonomous vehicles.  Some states are passing legislation to allow self-driving cars, in part hoping to attract Google or Tesla or Uber dollars.  But insurance companies are taking a wait-and-see attitude.  They’re already planning how they’ll insure self-driving cars (who has the liability?), but they’re in no rush to do so--there are still too many unknowns. 

As one insurance executive told me: “Politicians can make self-driving cars legal. The real question will be: can you insure one?”

Or take climate change. One immediate step, given increased extreme weather and sea-level rise, might be to limit construction on low-lying  coastal land in hurricane zones.  But government doesn’t want to tell voters, no, you can’t build a house there.  Insurance companies, on the other hand, are perfectly willing to say they won’t insure it.

And insurers aren’t just saying “no.” One company I work with, for example, has a laboratory that tests building materials in extreme weather conditions.  The goal: requiring resilient materials as a prerequisite for insurance coverage.

A very recent example is computer security.  Security experts will tell you that most corporate hacking cases are not the result of brilliant hackers.  They’re the result of careless security.   And bad cybersecurity is starting to impact the market value of companies.

Sounds like another role for insurance.  But until recently, cybersecurity insurance was a tricky proposition--insurance companies weren’t sure how to assess the risk. Now, however, insurance companies are beginning to formulate security requirements for companies who seek cyberattack coverage.

In the early 20th century, insurance companies had real impact on increasing factory safety, because they required certain levels of safety before issuing workers’ compensation insurance.  A full century later, they may well do the same with cybersafety.

I spent last summer writing in the farm country of Sicily, a place that usually seems very far from the future.  It’s the land where ancient Greek myths lurk in the landscape and the local language, still widely spoken in lieu of Italian, is the oldest in Europe.

The other day I was talking to a young friend, Fabio.  Fabio deftly uses all the latest tools of technology to promote his agriturismo business, but keeps them in a clear perspective.  “The future,” he told me over a lunch of pasta con limone, “is sometimes the past.”

Fabio offered an example: when he inherited his grandfather’s citrus orchards they had fallen into disuse.  Cheaper fruit from Spain and Morocco and Egypt had flooded the European market.  But then organic food became popular and Sicily proved to be the gold standard for organic; most farmers there had never used chemicals in the first place.  Now Fabio’s lemons are profitable again.

In a similar way I suspect that as artificial intelligence and robotics remove the human element from more and more of what we do, we will find skills from the past become more relevant again.  The resurgence of handcrafted goods and food is one example; the art of conversation is another.

When we use new technology to reshape how we work or live, we shouldn’t forget the value of what has come before.  As Fabio learned: sometimes the future turns out to need the past.

Amazon continues to expand its enormous presence in the robotics industry, particularly in terms of warehouse automation.   Now both retail and fast food companies are also pushing forward in automating all aspects of their business.

Even so, employers continue to argue that automation will simply create new jobs for humans.

As employers struggle post-COVID to hire workers, it's growing clearer and clearer that the majority who can afford to do so will invest in artificial intelligence and automation.  Unlike human employees, technology gets cheaper as it gets better at the job, and as a capital expense it's handy for company finances.

Long-term, robotics and artificial intelligence will fundamentally alter the face of work in ways that our society is very poorly equipped to handle.  The "new jobs" will not appear out of thin air--smart management will need to look ahead to how to use existing staff to improve their quality of service.

It's a topic that very few politicians want to address, but which at some point later in this decade will rise to the level of a potential workforce disaster.