A Directionless Month for AI – What Do Its Scattered Reports Say?

Artificial intelligence seems to be moving into another phase, or subphase.  There have never been so many concerns, not about the technology causing a major disaster, but about it being adequate and worthwhile at all.  At the same time, there are new perceptions and more progress in related employment, and, if I am perceiving it correctly, growing acceptance that where AI is now might be where it is for months or even years, so stakeholders are realizing they cannot just wait for the next big eruption. 

A look at one chronic AI problem is the subject of “How Game Theory Can Make AI More Reliable” (Steve Nadis, Wired.com, June 9^th).  The author bemoaned the tendency of large language models to give different answers, not all correct, to generative (open-ended) and discriminative (choice of options) questions.  Researchers have invented a game of sorts where “two modes” of LLMs are asked to agree on answers.  Excellence at games is a long-time AI strength, so engineers have reason to be optimistic such inconsistencies will go away.

Top AI workers are scarce, and many, soon after starting work with an organization, move on to another for more pay.  That is why, on one level, “Retention is all you need” (The Economist, June 15^th).  As, per a market analyst, “20,000 companies in the West are hiring AI experts,” “AI talent, previously hoarded at tech giants, is becoming more distributed.”  Indeed, AI hiring at Amazon, Apple, Google, Meta, and Microsoft has only about broken even since the beginning of 2023.  Advertisements for many more software positions now mention AI, as do those for math, scientific research and development, and information design.

Defining another clear problem, Sherin Shibu’s “How Can AI Help Small Businesses?  It’s A Matter of Trust, According to a New Report” (Entrepreneur, June 17^th), tells us that “just 7% of U.S. desk workers see AI answers as completely trustworthy,” the share of American businesses as of June was only 5% although 96% of “surveyed executives felt pressure to bring AI into their business,” and “privacy” and “data quality” were the other two top issues.  These tell AI companies where they should focus, perhaps above all other considerations.

Unsurprisingly, more universities and technical schools are preparing students for jobs using the technology.  A Brock Dumas June 17^th Fox Business piece, “Want an AI career?  These colleges offer degrees for the best chance” provides a current look.  “A new study by software development firm Vention shows which U.S. colleges are offering bachelor’s degrees with the best chance of landing a job fresh out of school – and the potential for the biggest paychecks.”  The top five were California Polytechnic State University, Wake Forest University in North Carolina, Trinity University in Texas, Clarkson University in New York state, and Knox College in Illinois.  There are more, and this list will change, but these may be the ones currently most worth investigating.

Also, for now, “We’re Still Waiting for the Next Big Leap in AI” (Will Knight, Wired.com, June 20^th).  Knight wrote that “the world is still waiting for another AI leap forward… akin to that delivered by GPT-4” 16 months ago.  He described possible contenders, but then concluded “it’s unclear how long the world must wait for that next big leap in AI.  OpenAI has said it has started training its next big model.  In the meantime, we will need to figure out new ways to measure how useful the technology really is.”

On June 27^th, Fox News released “US tops world ratings for AI preparedness:  China, Russia and Iran lag in key measures, report finds” (Peter Aitken).  The rankings were on countries’ “ability to immediately adopt artificial intelligence… into their economies.”  The American “value of preparedness” tied the Netherlands, and was followed by Finland, Estonia, New Zealand, Germany, Sweden, Australia, Japan, and Israel.  That may or may not prove to be valuable information.

There must be something noteworthy about a source called Futurism.com having the most consistently negative AI articles of anyone.  Here are two more.  The first is “There’s a Small Problem with the AI Industry:  It’s Making Absolutely No Money” (July 4^th).  Author Sharon Adarlo noted that “Goldman Sachs analysts have concluded… that AI just isn’t making any serious money yet,” and that “Goldman found that companies that hoped to profit from using AI to boost productivity – ranging from H&R Block to Walmart – have seen their shares vastly underperform the broader stock market since the tail end of 2022.”  She also found that “the only companies making much actual revenue off AI are the ones selling the hardware it needs, like Nvidia.”  While “companies using it want to see major returns,” “so far, it sounds like they aren’t.  Maybe the real question is how much runway the AI industry has before business leaders move onto the next thing.”  This piece is consistent with my previous comments.

The second Futurism.com piece was “Expert Warns That AI Industry Due for Huge Collapse” (Victor Tangermann, July 9^th).  He named a “founding partner” at a “macroeconomic research firm” calling AI “completely unproven,” saying that its hallucinations may never go away and that it was “too energy hungry,” along with a previous Stability AI CEO telling bankers that “this will be the biggest bubble of all time.”  Hardly universal views, but with merit.

Overall, is it true that, per New York Times columnist Thomas Friedman on July 9^th, “the artificial intelligence revolution of the past four years is widely expected to slam into the white-collar job market in the next four like a Category 5 hurricane”?  We don’t know that.  As with actual storms, we will benefit from tracking them and projecting their courses and times of landfall, but this one is way too weak and distant to fear.  We don’t need to buy flashlights, batteries, and water, and may never need to.  The future of artificial intelligence is still up in the air – and it may never come down.