Continuing on…
In some technical boom times, the companies profiting most have been those providing supporting services. In The Economist’s The Bottom Line newsletter on June 3rd, Guy Scriven looked at that for AI in “Selling shovels in a gold rush.” He named Amazon Web Services and Microsoft Azure for storage, Digital Realty and Equinix for entire data centers, Wistron and Inventec which “assemble servers for the cloud giants and for local data centres,” and “80-odd” more firms with other services.
We know something about which positions won’t be affected much by AI, but how about those in the front lines? Per Aaron Mok and Jacob Zinkula in Insider on June 4th, “ChatGPT may be coming for our jobs. Here are the 10 roles that AI is most likely to replace.” First mentioned is “tech jobs,” namely “coders, computer programmers, software engineers, and data analysts.” I wrote in 2012’s Work’s New Age that these positions were unusually susceptible to automation, got little published agreement elsewhere, and now that may finally come true. Others were “media jobs (advertising, content creation, technical writing, journalism),” “legal industry jobs (paralegals, legal assistants),” market research analysts, teachers, “finance jobs (financial analysts, personal financial advisors),” traders, graphic designers, accountants, and customer service agents. It is easy to see that all will be replaceable by what AI and other electronic services can offer, but as we saw before, embedded worker bases are resistant.
One view bound to get attention is “Big Tech Is Bad. Big A.I. Will Be Worse” (Daron Acemoglu and Simon Johnson, The New York Times, June 9th). With billions of people benefiting from these products, I don’t care for that premise, but if you substitute, say, “dominating” for the adjective, it makes sense. It’s unavoidable, though, as such nonphysical and portable things are natural monopoly or oligopoly fields, and regulation will be developed along with, or at least soon after, its proliferation.
We reached a landmark earlier this month. Per Bloomberg Technology’s “This Week in AI” on June 10th, “ChatGPT creator OpenAI was hit with its first defamation lawsuit over its chatbot’s hallucinations,” as “a Georgia radio host says it made up a legal complaint accusing him of embezzling money.” The suit is strong, and we’re about to get some precedents – nonfictional ones – on this issue that could soon become depressingly commonplace.
Cade Metz asked, in the June 10thNew York Times, “How Could A.I. Destroy Humanity?”. The problem seems to center around autonomy, especially if such systems were allowed access into “vital infrastructure, including power grids, stock markets and military weapons.” Though still limited and not successful, “researchers are transforming chatbots like ChatGPT into systems that can take actions based on the text they generate.” Given goals, such software will do anything it can to achieve them, for example, “researchers recently showed that one system was able to hire a human online to defeat a Captcha test. When the human asked if it was “a robot,” the system lied and said it was a person with a visual impairment.” We will end up blocking off the pathways to true action, but if there are gaps, automata will find them.
Writing about “the Singularity,” or “the moment when a new technology… would unite human and machine, probably for the better but possibly for the worse,” an idea originated by computer scientist John von Neumann in the 1950s, has made a sharp comeback. And now, we have “Silicon Valley Confronts the Idea That the ‘Singularity’ Is Here” (David Streitfeld, The New York Times, June 11th). As AI “is roiling tech, business and politics like nothing in recent memory,” resulting in “extravagant claims and wild assertions,” some think that massive transition is at hand or nearly so. One long-time advocate, author and inventor Ray Kurzweil, now forecasts it to arrive by the 2040s, but “critics counter that even the impressive results of (large language models) are a far cry from the enormous, global intelligence long promised by the Singularity.” So we will see, but not today or tomorrow.
Finally, back to the counting-house. Per Yiwen Lu, on June 14th and also in the Times, “Generative A.I. Can Add $4.4 Trillion in Value to Global Economy, Study Says.” I’ve seen a lot of trillions in the news lately, especially in American deficits and capitalization of the hugest companies, and here is another. Per this McKinsey effort, this one is annually, but “up to,” as “the vast majority of generative A.I.’s economic value will most likely come from helping workers automate tasks in customer operations, sales, software engineering, and research and development” – mostly consistent with the Insider article above. Just one trillion dollars is $1,000,000,000,000 – how long will it be before we start talking about quadrillions? And what will the status of artificial intelligence be then?
