Artificial Intelligence Isn't Nearly 'as Smart as 3-Year Olds.'

Is AI about to take over? Or does it struggle to be as smart as a toddler? 


Why should AI scare us? Let’s compare natural vs. artificial intelligence, using Edge’s 2015 big question: What to think about machines that think?

1. Despite the AI fuss, “deep learning ... is conceptually shallow,” explains Seth Lloyd. “Deep” here means more interconnected "neural network" layers, not profound learning.

2. Alison Gopnik feels machines aren’t nearly “as smart as 3-year-olds.” While AI sometimes outwits Garry Kasparov, it needs millions of pictures (labeled by humans) to learn to recognize cats. Infants need a handful (amazing pattern detectors, + see what babies know, but scientists often ignore).

3. Biology has information-processing cells with hardware and software “vastly more complex than ... Intel's latest i7” chip, says Rolf Dobelli. Chips are faster, but the i7 does 4 things at a time; biology’s “processors” do thousands. Supercomputers ≈80k CPUs, brains ≈80 billion cells. 

4. Lawrence Krauss estimates a computer would need ~10 terrawats of power (≈all humanity’s power plants) to match what the human brain does with just 10 watts (=million million times less power, = 40 doublings, ~ 120 years).

5. Intelligence, and many mind-related terms, are “suitcase” words (Marvin Minsky). They pack jumbled ideas.

6. Intelligence must process information. But many things that process information aren’t deemed intelligent. Harry Collins says sieves, trees, calculators, and cats, do what they do, and process information, the way rivers do, ~basically “mechanistically.”

7. Information processing isn’t limited to minds. Inanimate objects routinely process information. Information is “physical order,” says Cesar Hidalgo. So any interaction that alters physical order, processes information. Matter computes.

8. Until recently our tools were mostly like sieves or axes = “solidified chunks of order” — objects embodying and enacting simple fixed logic — crystallized information. But computers mean single objects can embody multiple complex, updatable logics.

9. The flexible logic of computers generally require detailed step-by-step instructions, or algorithms. (Note: Life needs what algorithms do; DNA is 2-billion-year-old software.)

10. “Little has changed algorithmically” in AI recently, notes Bart Kosko. What’s new is running old algorithms faster and cheaper. Which means IBM’s Watson, while impressive, is glorified Googling (Roger Schank). And AI can teach itself elite chess only because it’s easily algorithmized (it has fixed rules, unlike human life).

11. Humans are “machines that think,” says Sean Carroll. But our information-processing logic is uniquely flexible. Our software isn’t only in our genes.

Those close to AI’s innards aren’t afraid. It’s up to us to use our natural intelligence well, to leverage AI's narrow powers intelligently.

 --

Illustration by Julia SuitsThe New Yorker cartoonist & author of The Extraordinary Catalog of Peculiar Inventions

Big Think
Sponsored by Lumina Foundation

Upvote/downvote each of the videos below!

As you vote, keep in mind that we are looking for a winner with the most engaging social venture pitch - an idea you would want to invest in.

Keep reading Show less
Videos
  • What distinguishes humans is social learning — and teaching.
  • Crucial to learning and teaching is the value of free expression.
  • And we need political leaders who support environments of social peace and cooperation.


A bionic lens undergoing clinical trials could soon give you superhuman abilities

We're talking Ghost in the Shell type of stuff. 

popular

Maybe you watched Ghost in the Shell and maybe afterwards you and your friend had a conversation about whether or not you would opt in for some bionic upgrades if that was possible - like a liver that could let you drink unlimitedly or an eye that could give you superhuman vision. And maybe you had differing opinions but you concluded that it's irrelevant because the time to make such choices is far in the future. Well, it turns out, it's two years away.

Keep reading Show less

The philosophy of tragedy & the tragedy of philosophy - with Simon Critchley

Tragedy in art, from Ancient Greece to Breaking Bad, resists all our efforts to tie reality up in a neat bow, to draw some edifying lesson from it. Instead it confronts us with our own limitations, leaving us scrabbling in the rubble of certainty to figure out what's next.

Think Again Podcasts
  • Why democracy has been unpopular with philosophers
  • Tragedy's reminder that the past isn't finished with us
  • …and why we need art in the first place
Keep reading Show less