You Don't Compute—Or Do You?

 

Technology leaders from Bill Gates to Elon Musk and others have warned us in recent years that one of the biggest threats to humanity is uncontrolled domination by artificial intelligence (AI).  In 2017, Musk said at a conference, "I have exposure to the most cutting edge AI, and I think people should be really concerned about it."  And in 2019, Bill Gates stated that while we will see mainly advantages from AI initially, ". . . a few decades after that, though, the intelligence is strong enough to be a concern."  And the transhumanist camp, led by such zealots as Ray Kurzweil, seems to think that the future takeover of the universe by AI is not only inevitable, but a good thing, because it will leave our old-fashioned mortal meat computers (otherwise known as brains) in the junkpile where they belong. 

 

So in a way, it's refreshing to see a book come out whose author stands up and, in effect, says "Baloney" to all that.  The book is Non-Computable You:  What You Do that Artificial Intelligence Never Will, and the author is Robert J. Marks II. 

 

Marks is a practicing electrical engineer who has made fundamental contributions in the areas of signal processing and computational intelligence.  After spending most of his career at the University of Washington, he moved to Baylor University in 2003, where he now directs the Walter Bradley Center for Natural and Artificial Intelligence.  His book was published by the Discovery Institute, which is an organization that has historically promoted the concept of intelligent design. 

 

That is neither here nor there, at least to judge by the book's contents.  Those looking for a philosophically nuanced and extended argument in favor of the uniqueness of the human mind as compared to present or future computational realizations of what might be called intelligence, had best look elsewhere.   In Marks's view, the question of whether AI will ever match or supersede the general-intelligence abilities of the human mind has a simple answer:  it won't. 

 

He bases his claim on the fact that all computers do nothing more than execute algorithms.  Simply put, algorithms are step-by-step instructions that tell a machine what to do.  Any activity that can be expressed as an algorithm can in principle be performed by a computer.  Just as important, any activity or function that cannot be put into the form of an algorithm cannot be done by a computer, whether it's a pile of vacuum tubes, a bunch of transistors on chips, quantum "qubits," or any conceivable future form of computing machine. 

 

Some examples Marks gives of things that can't be done algorithmically are feeling pain, writing a poem that you and other people truly understand, and inventing a new technology.  These are things that human beings do, but according to Marks, AI will never do. 

 

What about the software we have right now behind conveniences such as Alexa, which gives the fairly strong impression of being intelligent?  Alexa certainly seems to "know" a lot more facts than any particular human being does. 

 

Marks dismisses this claim to intelligence by saying that extensive memory and recall doesn't make something intelligent any more than a well-organized library is intelligent.  Sure, there are lots of facts that Alexa has access to.  But it's what you do with the facts that counts, and AI doesn't understand anything.  It just imitates what it's been told to imitate without knowing what it's doing. 

 

The heart of Marks's book is really the first chapter entitled "The Non-Computable Human." Once he gets clear the difference between algorithmic tasks and non-algorithmic tasks, it's just a matter of sorting.  Yes, computers can do this better than humans, but computers will never do that. 

 

There are lots of other interesting things in the book:  a short history of AI, an extensive critique of the different kinds of AI hype and how not to be fooled by them, and numerous war stories from Marks's work in fields as different as medical care and the stabilization of power grids.  But these other matters are mostly a lot of icing on a rather small cake, because Marks is not inclined to delve into the deeper philosophical waters of what intelligence is and whether we understand it quite as well as Marks thinks we do.

 

As a Christian, Marks is well aware of the dangers posed to both Christians and non-Christians by a thing called idolatry.  Worshipping idols—things made by one's own hands and substituted for the true God—was what got the Hebrews into trouble time and again in the Old Testament, and it continues to be a problem today.  The problem with an idol is not so much what the idol itself can do—carved wooden images tend not to do much of anything on their own—but what it does to the idol-worshipper.  And here is where Marks could have done more of a service in showing how human beings can turn AI into an idol, and effectively worship it. 

 

While an idol-worshipping pagan might burn incense to a wooden image and figure he'd done everything needed to ensure a good crop, a bureaucracy of the future might take a task formerly done at considerable trouble and expense by humans—deciding on how long a prison sentence should be, for example—and turn it over to an AI program.  Actually, that example is not futuristic at all.  Numerous court systems have resorted to AI algorithms (there's that word again) to predict the risk of recidivism for different individuals, and basing the length of their sentences and parole status on the result. 

 

Needless to say, this particular application has come in for criticism, and not only by the defendants and their lawyers.  Many AI systems are famously opaque, meaning even their designers can't give a good reason for why the results are the way they are.  So I'd say in at least that regard, we have already gone pretty far down the road toward turning AI into an idol.

 

No, Marks is right in the sense that machines are, after all, only machines.  But if we make any machine our god, we are simply asking for trouble.  And that's the real risk we face in the future from AI:  making it our god, putting it in charge, and abandoning our regard for the real God.

 

Sources:  Robert J. Marks II's book Non-Computable You was published in 2022 by the Discovery Institute.  The Musk quote is from https://www.cnbc.com/2021/08/24/elon-musk-warned-of-ai-apocalypsenow-hes-building-a-tesla-robot.html, the Gates quote is from https://futurism.com/bill-gates-artificial-intelligence-nuclear-weapons, and a story about AI used for sentencing guidelines is at https://www.technologyreview.com/2019/01/21/137783/algorithms-criminal-justice-ai/.  I also referred to Wikipedia for biographical information on Marks. 

Living—and Dying—By Algorithms

The National Health Service (NHS) in England is one of the oldest government health-care systems in the world, founded in 1948 when the Labor Party was in power.  Despite consuming some 30% of the public service budget, by many accounts it is underfunded, especially when it comes to capital equipment such as IT systems.  This may be a factor in a scandal involving a wayward algorithm that prevented some half-million Englishwomen from receiving mammograms for the last nine years.  Estimates vary as to how serious a problem this is, but it's likely that at least a few women have lost their lives due to breast cancer that was caught too late as a result of this computer error.

A report carried in the IEEE's "Risk Factor" blog describes how in 2009, an algorithm designed to schedule older women for breast cancer screening was set up incorrectly.  As a result, over the next nine years almost 500,000 women aged 68 to 71 were not allowed to have mammograms that they otherwise would have been scheduled for.  When the error was caught, the news media had a field day with headlines like "Condemned to Death . . . by an NHS Computer."  Depending on who's making the statistical estimate, the consequences are either tragic or possibly beneficial.

The NHS's own Health Minister had his statisticians run the numbers, and they came up with a range of 135 to 270 women who may have died as a result of this error.  But others claim that as many as 800 women may be better off because of not having to go through surgical and other procedures based on the false positives that inevitably result from a large number of mammograms. 

While the actual consequences of this problem are ambivalent, it raises a larger issue:  what should we do when computer-generated algorithms that affect the fates of thousands go awry? 

As a practical matter, computer algorithms are part of the fabric of modern industrial society now.  If you want to borrow money, the bank uses algorithms to decide whether you're a good credit risk.  If you look for something online, sophisticated algorithms take note of it and decide what other kinds of ads you see.  And if you're in England or another country where health care is allocated by a central computerized authority, a computer is going to tell you when you can get certain kinds of preventive health care and if you're ill, it may even tell you when you can get treated—if at all. 

From a utilitarian engineering perspective, computer algorithms are the ideal solution for large-scale resource-allocation problems.  Health care these days is very complicated.  Each person has a unique combination of health history, genetic makeup, and needs, and the arsenal of treatments is constantly changing too.  If you are working in an environment of centralized fixed resources (as NHS is), then you will naturally turn to computers as a way of implementing policies that can be shown mathematically to treat everyone equally.  Unless they don't, of course, as happened with the older women who were left out of mammogram screenings by the badly programmed algorithm. 

There's an old saying, "To err is human, but to screw up royally requires a computer."  The NHS flap is a good example of how one mistake can affect thousands or millions when multiplied by the power of a large system. 

The U. S., with its much more hodge-podge mixture of private, commercial, and government health care systems, is still not immune from such errors, but because the federal government doesn't run the whole show, its mistakes are somewhat limited in extent.  There are also numerous outside agents keeping tabs on things, so that an egregious error by, say Medicare, comparable to what happened with the NHS algorithm in England, would probably be caught by private insurers before it got too far.  Just as a power grid with a number of small distributed generating stations is more robust than one that relies exclusively on one giant power plant, the U. S. health care system, even with all its flaws, is less likely to be felled by a single coding mistake. 

Instead, we have widely distributed minor errors that cause more inconvenience than tragedy.  But precisely because the system is so kludged together, it doesn't take much to cause a problem.

Here's a simple example:  my wife is scheduled the day I am writing this for a routine well-person exam that requires her general practitioner (GP) to write a referral for it.  Dutiful organized person that she is, several weeks ago she went by her doctor's office and asked them to do the referral so she could schedule the appointment, and the staff at the office said they'd take care of it.  Yesterday (the day before the procedure), she got a call from the office that was going to do the procedure, saying they hadn't gotten the referral yet and if they didn't get it they were going to cancel the procedure or make us pay cash for it.

So ensued a half-hour or so of near panic, during which time we ran down to her doctor's office and discovered that the lady who was supposed to send the referral out had quit the previous day.  And that was one of the things she left undone. 

When the GP's office staff figured out what had happened, they were very nice about it—they faxed the referral to the proper office, handed us a copy which we carried over by hand to the office needing it, and everything is fine now.  But until all medical offices are staffed by robots and all paperwork is untouched by human hands, people will always be involved in medical care, and people sometimes make mistakes. 

Personally, I much prefer a system in which I can drive over to the office where the mistake was made and talk to the people responsible.  If we had something like the NHS here, the mistake might have been made in Crystal City, Virginia by an anonymous person whom it would take the FBI to discover, and my wife would have been out of luck.   

Sources:  IEEE Spectrum website's Risk Factor blog carried the report of the NHS computer error at https://spectrum.ieee.org/riskfactor/computing/it/450000-woman-missed-breast-cancer-screening-exams-in-uk-due-to-algorithm-failure.  I also referred to the Wikipedia article "National Health Service (England)."
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