Mind Matters Natural and Artificial Intelligence News and Analysis
Go-game

Would AI Still Win at Go If the Board Shrunk: 19 to 17 Spaces?

No, say Jeffrey Funk and Gary Smith — and would-be investors need to grasp AI’s weaknesses as well as strengths, for success
Share
Facebook
Twitter
LinkedIn
Flipboard
Print
Email

Statistician Jeffrey Lee Funk and business prof Gary N. Smith offer a warning for investors: Some AI stocks have been good investments but most high tech unicorns never pay off.

It’s a not surprising, they say, when we consider that AI is powerful but brittle. An example they offer: AI easily beats humans at the game of go which features a 19 × 19-square board. If the game switched to a 17 × 17-square board, humans would quickly adjust but AI would flounder.

They offer examples of how this sort of limitation plays out in the real world, including the true tale of a hapless AI-driven insurance company:

An insurance company with the quirky name Lemonade was founded in 2015 and went public on July 2, 2020, with its stock price closing at $69.41, more than double its $29 IPO price. On January 22, 2021, shares hit a high of $183.26.

What was the buzz? Lemonade sets its insurance rates by using an AI algorithm to analyze user answers to 13 questions posed by an AI chatbot. CEO and co-founder Daniel Schreiber argued that, “AI crushes humans at chess, for example, because it uses algorithms that no human could create, and none fully understand” and, in the same way, “Algorithms we can’t understand can make insurance fairer.”

How does Lemonade know that its algorithm is “remarkably predictive” when the company has been in business only for a few years? They don’t. Lemonade’s losses have grown every quarter and its stock now trades for less than $20 a share.

Jeffrey Lee Funk and Gary N. Smith, “Delivery drones, robotaxis, even insurance — wildly hyped dreams for AI startups are giving tech investors nightmares” at MarketWatch (June 13, 2022)

It’s the same story with industrial drones (“still grappling with basic problems including noise pollution, privacy invasion, bird attacks and drones being used for target practice”):

The real world is full of unanticipated problems for which humans must develop a solution to program into AI. AI won’t just think one up on its own.

It’s best to keep these basic limitations in mind if we are told, for example, that the new Ultra-Robo-SnipTM will render hair salons obsolete… 😉


You may also wish to read:

How far will unicorn share prices fall? Cumulative losses give us some insights. With 56% of the 140 publicly traded Unicorns having cumulative losses greater than or equal to revenues, many may never erase their cumulative losses. (Jeffrey Funk)

Turing tests are terribly misleading. Black box algorithms are now being trusted to approve loans, price insurance, screen job applicants, trade stocks, determine prison sentences, and much more. Is that wise? My tests of a large language model (LLM) showed that the powerful computer could discuss a topic without showing any understanding at all. (Gary Smith)

and

Are computers that win at chess smarter than geniuses? No, and we need to look at why they can win at chess without showing even basic common sense. AI succeeds where the skill required to win is massive calculation and the map IS the territory. Alone in the real world, it is helpless. (George Gilder)


Mind Matters News

Breaking and noteworthy news from the exciting world of natural and artificial intelligence at MindMatters.ai.

Would AI Still Win at Go If the Board Shrunk: 19 to 17 Spaces?