Jaron Lanier on AI — the good, bad and ugly of Lanier

"There is no AI": An interesting piece by Jaron Lanier. He notes that it's not intelligent and not an independent mind, among other things.

These are all things I've been saying, including about the hyped new ChatGPT et cetera.

He then says if we treat it as a tool, not a person, we'll worry less.

He then becomes Jaron Lanier, saying he disagreed with a petition against AI invading privacy because "we don't know what privacy is," going on to:

It’s a term we use every day, and it can make sense in context, but we can’t nail it down well enough to generalize. The closest we have come to a definition of privacy is probably “the right to be left alone,” but that seems quaint in an age when we are constantly dependent on digital services. In the context of A.I., “the right to not be manipulated by computation” seems almost correct, but doesn’t quite say everything we’d like it to.

First, what's wrong with the first half of that and why can't it be updated to today's age? Lanier offers no explanation. Did it seem quaint when, after the telephone was invented, the predecessor of the FBI did wiretaps without warrants at first?

Second, I can't believe that he missed the parallel to Potter Stewart's famous:

I shall not today attempt further to define the kinds of material I understand to be embraced within that shorthand description ["hard-core pornography"], and perhaps I could never succeed in intelligibly doing so. But I know it when I see it, and the motion picture involved in this case is not that.

Because there is at least some degree of parallel.

He goes on to note that AI researchers he notes agree that things like deepfakes need to be labeled as such, but that there might be problems getting there.

In all of this, he sounds like the Lanier of reality not legend of a decade ago, when Yevgeny Morozov nailed him for handwaving, strawmanning vagueness and other things. He's also, per that piece, got a history of positioning himself as an outsider when the reality is not so much.

Lanier also, way back then, was already talking about surrendering to digital snooping, rather than fighting it.

Near the end of the piece, he notes that AI might produce a movie that has no "backstory." Well, Jaron, I don't know about movies, but novelists talk about their stories taking on a life of their own to the degree that the original backstory bears little resemblance to the final work.

In the jobs world, he talks about "data dignity." This sounds halfway convincing, but "data dignity" re AI-driven tree trimming robots does not. But, given the "nailed him," where Lanier a decade ago talked about us all becoming internet entrepreneurs, not surprising. It also, per that piece, sounds as naive on issues like this as he was a decade ago. Or, if not naive, grifting for some legendary "better angels of Silicon Valley's nature."

Then, Jaron Lanier becomes, once again, the Lanier of reality not legend:

Many people in Silicon Valley see universal basic income as a solution to potential economic problems created by A.I. But U.B.I. amounts to putting everyone on the dole in order to preserve the idea of black-box artificial intelligence.

Knowing the Lanier of reality — while knowing that there are multiple varieties of BI, despite the lies on that by Scott Santens, and knowing that Silicon Valley promotes the tech-libertarian type — this is still not surprising out of his mouth. And, per that link above, the "nailed him," he's still ultimately a libertarian, so that's also why this isn't surprising.

Now, if he wanted to say that BI is insufficient, like Douglas Rushkoff's push for "basic assets," THEN we'd be talking. But, that's not his idea.

As for Santens? Basic laundry list:

• Called Trump "the basic income Moses," per a piece where Scott is himself associated with the World Economic Forum, as in Davos, while getting more alarmist about AI then than Lanier is today;
• Wants to junk entitlements, including even trimming Social Security — more here;
  
• Is a crypto-bro;
• Denies that there are libertarian and non-libertarian versions of BI that don't square with each other;
• And on all of this, can't do math on how to pay for his ideas.
  

Anyway, read the whole thing. It's a definite longform. 

And, make sure to get to the bottom, to note that his tagline notes he works for Microslob. Why would you trust a Bill Gates minion on any of this?

Does AI engage in behavioralism?

Noam Chomsky/From The Atlantic

Noam Chomsky, a long and persistent critic of artificial intelligence, says yes, or that it at least engages in the equivalent thereof, as related in this extended interview with the Atlantic.

If he is right, and I think he’s at least in the right ballpark, I think this arguably explains why AI, for all its self-touting, is the biggest research science and technology failure this side of peaceful fusion power. Indeed, progress on the two shares a remarkably similar arc.

The interview is indeed worth a read. It’s in-depth, and as the Atlantic editor-reporter notes, it’s rare these days, because everybody wants to interview Chomsky on political topics, not scientific ones.

Beyond his “behaviorist” comments, he suggests AI researchers, and at least some people in fields such as his own cognitive science, are still doing research on mind and intelligence at what might be called the wrong level of abstraction. It brings to mind Dan Dennett’s comment (ironic at times, given Dennett) of “greedy reductionism.”

It also brings to mind Paul Davies’ book “The Eerie Silence,” which criticizes SETI, the Search for Extra-Terrestrial Intelligence, for various blinders it may be wearing in its search.

Chomsky, in the interview, also veers at least a bit into his home turf of linguistics. As part of that, he doesn’t have a lot of good to say about Bayesian statistics.

He says there are better ways for us to try to understand the “noise” with which we are bombarded on a daily basis.

To me, Bayesian statistics seems like “the hip thing” for pop and semi-pop observers of human cultural sociology. All it needs is a new book by Malcolm Gladwell.

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For a more in-depth analysis of what I see Chomsky’s meaning, go here at my philosophy and arts blog.

Our probabilistic brains

Setting jokes about "Neanderthal conservatives" with their black-and-white thinking aside, and setting aside more serious issues about whether or not Bayes' theorem is the best way to handle how we adjust our thinking to changed scenarios, there's growing evidence that our brains evolved to handle probabilities.

If this is true, there's other fallout.

Above all (sorry, Ray Kurzweil, other singularity touters, etc.) this is another major dent for those who say major advances in artificial intelligence are just around the corner. There's nothing to indicate that robots, or even Watson-like computers regularly engage in this type of thinking evaluation. At the least, as the story notes, robots don't have anything close to the sensory skills to do something like this, and Watson has no sensory inputs of that sort at all.

Watson, go away — I don't want you

How does IBM's Jeopardy-playing computer, Watson, make you feel? Intrigued? Curious? Diffident? Dismissive because it can't laugh at its mistakes, or at jokes of its human competitors?

Seriously, in that area, while plenty of humans lack senses of humor, we all have the ability to be humorous, short of a mental condition such as autism. And, Watson doesn't have that.

But, that's not the reason we might want to tell Watson to go away.

Rather, what if, with its language recognition capabilities, Watson's "progeny" — Watson II, etc. — start replacing human jobs?

Don't laugh, and don't scoff, either.

Is it theoretically possible that Son of Watson could be the "person" answering the customer service phones at your bank in 20 years? Damn skippy it is.

Sure, you might have one human as backup — to one Watson that could, say, simultaneously handle 50 phone calls. Or 250.

People who have read much about artificial intelligence are familiar with the low-grade software program ELIZA, which did a crude-level mock psychologist — and got people to spill their guts to it!

ELIZA had a limited stock of canned phrases and, to anyone not in need of an ear to bend, if not full-blown counseling, its limited stock phrases and rigid responses were clear to all.

But, substitute Watson II, a machine that can understand language nuance and respond with at least a Level II or Level III canned phrase, if not something more?

What's to stop Fortune 500 companies from making such a machine the front line of their employee assistance programs?

I'm probably just scratching the surface here.

You say, "What if Watson II doesn't understand my call?"

I say, "Could it understand it worse than an outsourced worker in Mumbai?"

And, with that, note that not all customer service jobs Watson replaces will be American.

But, among American ones, I'm probably just scratching the surface.

Watson II could call you in the future asking your opinion for a Gallup Poll. For simpler products, Watson II could be your next telemarketer — no sales commissions to be paid, and no hurt feelings over phones slammed in a computer "ear."

And, lest you think I'm joking?

Claims processing is an area where Watson II "employment" is already getting serious discussion.

The human brain, v. 2.0, on simulation?

Science fiction? Well, maybe today, but maybe not in a decade or two, if cognitive science can keep up its current rate of advance, with (admittedly crude and imprecise) animal brain simulations on computer.

That, then, of course, lead to questions of ethics and related issues. What if a brain simulation could be used to vastly improve current, crude, brain scanners? And, could do so without a person's cranium being stuck inside an MRI? In other words, what if an anti-theft portal at a business's front door could be ramped up, massively, via RFID-type tech, to scan your mind for commercial reasons?

Just how conscious are we?

New Scientist appears to transcend its slide into the crapper of the past few years with a serious of vignettes on different aspects of consciousness.

First, unconscious reactions that we later label as products of conscious free will appear to occur seconds before a "conscious determination," not just Benjamin Libet's well-known 300 millisecond delay.

Second, it appears that consciousness is not "vs." unconsciousness, but that the two are on a spectrum.

In light of all of this, in addition to it becoming clearer that the human mind does not operate like a computer, it's clearer that we are a long ways away from creating a conscious machine, something that would pass a Turing test when viewed by a true skeptic.

AI, computers, minds, algorithms, evolution, Dennett

If even artificial intelligence advocates have largely abandoned the idea that AI is ultimately algorithmic, it’s time to question a lot of related assumptions, some of which I already have.

First, the human mind, then, is clearly not algorithmic. And, it’s likely even less algorithmic than a computer.

Second, being “kludged” together by evolution, it’s most surely not a black box, like a modern software program, routine, or subroutine.

Third, running off that point, contra Dan Dennett, evolution is most assuredly not algorithmic, either, as I’ve said before.

Fourth, the Turing test, as stipulated by Alan Turing himself, was NOT about whether a machine could think, but about whether a machine could simulate thinking. In other words, in modern philosophy terminology, Turing was a functionalist, as is Dennett (on this issue, at least), even as he continues to deny it.

Anyway, read the full story linked above.

Artificial intelligence to be afraid of

What if the newest in computerized stock trading leads us into financial trouble too fast for humans to intervene? Do we really want machines playing this level of games with human money — and human work?

‘Emotional’ computers improve performance

Computers that show something like “regret” can improve their performance, Italian scientists say, and so help model human behavior for research:

Davide Marchiori of the University of Trento and Massimo Warglien of Ca’ Foscari University in Venice built mathematical models based on biological neural networks. These use simulated networks of “brain cells” to arrive at decisions and learn by trial and error.

Introducing an approximation of regret allowed the models to predict human behavior more precisely than conventional economic learning theories, the researchers said. Their findings appear in the Feb. 22 issue of the research journal Science.

Will we someday remove the scare quotes from “regret”?