Grok Hits the Fan with Pornified Deepfakes

  

The word Grok, which Elon Musk adopted for the name of his generative chatbot integrated with the social-media platform X, formerly known as Twitter, was coined by sci-fi writer Robert A. Heinlein.  In a 1961 story, Heinlein used it to mean something like "intuitive sympathetic understanding."  Heinlein must be spinning in his grave right now, because nothing could be further from intuitive sympathetic understanding than discovering that a chatbot has taken your image and turned it into, pardon the expression, masturbation fodder.

 

A nonprofit called the Center for Countering Digital Hate announced on Jan. 22 that the Grok chatbot had produced an estimated three million sexualized images in an 11-day period in December and early January.  An estimated 23,000 of these were of children under 18.  These estimates come from a sample of 20,000 images analyzed by the center and sorted by means of AI, with the ones suspected of showing children subject to manual inspection.

 

This revelation and similar discoveries have created a firestorm of legal actions.  Thirty-five state attorneys general have sent a letter to Musk threatening investigations and prosecutions for violating various laws against dissemination of child sexual abuse material.  A class-action suit involving over 100 plaintiffs has been filed in California, alleging that thousands of women "have been digitally stripped and forced into sexual situations that they never consented to."  Once such images appear in public, they can create false impressions of a person's behavior for years.

 

For his part, Musk has claimed that the feature enabling these deepfakes would be limited to paid subscribers.  He displayed the results of what happened when he asked Grok to generate a photo of himself in a bikini.  He has even gone so far as to deny any of this was happening.  Despite his responses, Grok and its parent organizations are now facing threats of legal action both in the U. S. and in the European Community, which has much stricter laws than many U. S. states about sexualized deepfakes.

 

The phrase "hitting the fan" really is appropriate here.  When deepfakes are created by a system intrinsically linked to one of the world's most popular social mediums, of course the stuff is going to fly everywhere.  Reportedly, the process was made easier by the availability of a "spicy" option.  So it's not like users had to go to a lot of trouble and contortions to force Grok to do something it was reluctant to do.  Somebody designed this type of operation to be easy, and there are plenty of guys out there who will stand in line to hand their favorite images over to be sexualized. 

 

Ethically speaking, there are so many things going wrong here that it's hard to focus on the worst ones.  I think this perfect storm of ethical lapses arises from a combination of (a) a moral blindness or lack of moral imagination which Musk perfectly exemplifies and (b) the unprecedented power to realize his profit-making and technologically effective ideas in a regulatory environment that he treats like a vacuum. 

 

The moral blindness arises from an adolescent macho attitude which treats women as objects, and sees nothing wrong with this attitude.  It is clear that Musk and those who worked for him in creating this fiasco literally can't imagine (or won't imagine) what it's like to be a woman whose face has been plastered onto a body doing something obscene. 

           

It's one thing if the guy doing the plastering is sneaking around in a back alley behind a porn shop because he can't afford to buy what he wants, and is going through the shop's trash barrel to put something together for his evil desires.  But it's quite another when the exact same attitude toward women is held by the world's richest man, whose power to do either good or harm is historically unprecedented. 

 

What is to be done?  And more realistically, what is going to happen in this situation?

 

In an ideal world, Grok would be shut down—100%—and a thorough investigation and hearing from anyone with a claim to have been injured by its doings would be conducted.  A reparation fund cut from a sizable chunk of Musk's billions would be established, and an impartial tribunal would attempt to compensate the injured parties and do a thorough web-cleaning, assisted by Musk's AI genius engineers, to put things back to where they were before the women were digitally assaulted.  And Musk would be put on notice that if anything like this happens again, he will be tied to his Starship rocket and launched on a one-way trip to Mars, alone, where he really wants to live anyway. 

 

What will probably happen instead is that the state attorneys general will file suits against Grok, xAI, and any other well-heeled target in sight.  The California civil suit will proceed at a pace slowed by the best lawyers Musk's money can buy.  As noted by Derek Johnson, writing in an article in Cyberscoop, the U. S. federal legal system has been notably silent, which may be due to Musk's favored status in the Trump administration, despite the debacle called DOGE last year. 

 

If we are looking for evidence that out-of-control AI is going to cause great harm, look no farther.  No, nobody has died physically from this particular disaster.  It doesn't fit the mold of the typical sci-fi AI apocalypse in which evil disembodied voices emerge from everybody's smartphone as the power goes out and the supply chains fall idle.  But ask any one of those women who have been undressed and worse by Grok about how they feel about what they've been through.  For them, it's been worse than 9/11, the 2008 market crash, and COVID rolled into one.  The fact that it's "only" a few thousand children being exploited isn't important. 

 

In The Brothers Karamazov, Dostoevsky writes of a conversation between Ivan, a cynical man of the world, and Alyosha, his brother who was a believer in God.  In Chapter 4, Ivan brings up the subject of the way some children are tormented by their own parents, even parents who are "most worthy and respectable people, of good education and breeding."  Then Ivan says something that we all need to be reminded of:  "In every man, of course, a demon lies hidden—the demon of rage, the demon of lustful heat at the screams of the tortured victim, the demon of lawlessness let off the chain. . . ." 

 

Every human being is capable of doing despicable things to children.  I am, you are, everybody is.  But civilization is made possible by each person's exertion of self-control to restrain that and other evil desires.  It is corrosive to civilization to provide a means by which evil desires may flourish at the expense of the innocent.  And in allowing Grok to be exploited in such a way, Musk and his underlings are polluting the spiritual lives of millions, and will answer to a higher court than even Musk can send lawyers to.

 

Sources:  I referred to an article in the Jan. 29 edition of the Austin American-Statesmen entitled "Grok made 3M explicit images in 11 days" by Andrea Guzmán, the Center for Countering Digital Hate's posting at https://counterhate.com/research/grok-floods-x-with-sexualized-images/, the website https://cyberscoop.com/grok-undressed-victims-file-class-action-lawsuit-against-xai-elon-musk/, and Wikipedia articles on Grok (chatbot) and Grok (the word).  The Brothers Karamazov quotes are from the Constance Garnett translation.

Should Chatbots Replace Government-Worker Phone Banks?

 

The recent slashes in federal-government staffing and funding have drawn the attention of the Distributed AI Research Institute (DAIR), and two of the Institute's members warn of impending disaster if the Department of Governmental Efficiency (DOGE) carries through its stated intention to replace hordes of government workers with AI chatbots.  In the July/August issue of Scientific American, DAIR founder Timnit Gebru, joined by staffer Asmelash Teka Hadgu, decry the current method of applying general-purpose large-language-model AI to the specific task of speech recognition, which would be necessary if one wants to replace the human-staffed phone banks that are at the other end of the telephone numbers for Social Security and the IRS with machines. 

 

The DAIR people give vivid examples of the kinds of things that can go wrong.  They focused on Whisper, which is a speech-recognition feature of OpenAI, and the results of studies by four universities of how well Whisper converted audio files of a person talking into transcribed text.

 

The process of machine transcription has come a long way since the very early days of computers in the 1970s, when I heard Bell Labs' former head of research John R. Pierce say that he doubted speech recognition would ever be computerized.  But anyone who phones a large organization today is likely to deal with some form of automated speech recognition, as well as anyone who has a Siri or other voice-controlled device in the home.  Just last week I was on vacation, and the TV in the room had to be controlled with voice commands.  Simple operations like asking for music or a TV channel are fairly well performed by these systems, but that's not what the DAIR people are worried about.

 

With more complex language, Whisper was shown not only to misunderstand things, but to make up stuff as well that was not in the original audio file at all.  For example, the phrase "two other girls and one lady" in the audio file became after Whisper transcribed it, "two other girls and one lady, um, which were Black." 

 

This is an example of what is charitably called "hallucinating" by AI proponents.  If a human being did something like this, we'd just call it lying, but to lie requires a will and an intellect that chooses a lie rather than the truth.  Not many AI experts want to attribute will and intellect to AI systems, so they default to calling untruths hallucinations.

 

This problem arises, the authors claim, when companies try to develop AI systems that can do everything and train them on huge unedited swaths of the Internet, rather than tailoring the design and training to a specific task, which of course costs more in terms of human input and guidance.  They paint a picture of a dystopian future in which somebody who calls Social Security can't ever talk to a human being, but just gets shunted around among chatbots which misinterpret, misinform, and simply lie about what the speaker said.

 

Both government-staffed interfaces with the public and speech-recognition systems vary greatly in quality.  Most people have encountered at least one or two government workers who are memorable for their surliness and aggressively unhelpful demeanor.  But there are also many such people who go out of their way to pay personal attention to the needs of their clients, and these are the kinds of employees we would miss if they got replaced by chatbots.

 

Elon Musk's brief tenure as head of DOGE is profiled in the June 23 issue of The New Yorker magazine, and the picture that emerges is that of a techie dude roaming around in organizations he and his tech bros didn't understand, causing havoc and basically throwing monkey wrenches into finely-adjusted clock mechanisms.  The only thing that is likely to happen in such cases is that the clock will stop working.  Improvements are not in the picture, not even cost savings in many cases.  As an IRS staffer pointed out, many IRS employees end up bringing in many times their salary's worth of added tax revenue by catching tax evaders.  Firing those people may look like an immediate short-term economy, but in the long term it will cost billions.

 

Now that Musk has left DOGE, the threat of massive-scale replacement of federal customer-service people by chatbots is less than it was.  But we would be remiss in ignoring DAIR's warning that AI systems can be misused or abused by large organizations in a mistaken attempt to save money.

 

In the private sector, there are limits to what harm can be done.  If a business depends on answering phone calls accurately and helpfully, and they install a chatbot that offends every caller, pretty soon that business will not have any more business and will go out of business.  But in the U. S. there's only one Social Security Administration and one Internal Revenue Service, and competition isn't part of that picture. 

 

The Trump administration does seem to want to do some revolutionary things to the way government operates.  But at some level, they are also aware that if they do anything that adversely affects millions of citizens, they will be blamed for it. 

 

So I'm not too concerned that all the local Social Security offices scattered around the country will be shuttered, and one's only alternative will be to call a chatbot which hallucinates by concluding the caller is dead and cuts off his Social Security check.  Along with almost every other politician in the country, Trump recognizes Social Security is a third rail that he touches at his peril. 

 

But that still leaves plenty of room for future abuse of AI by trying to make it do things that people really still do better, and maybe even more economically than computers.  While the immediate threat may have passed from the scene with Musk's departure from DOGE, the tendency is still there.  Let's hope that sensible mid-level managers will prevail against the lightning strikes of DOGE and its ilk, and the needed work of government will go on.

 

Sources:  The article "A Chatbot Dystopian Nightmare" by Asmelash Teka Hadgu and Timnit Gebru appeared in the July/August 2025 Scientific American on pp. 89-90.  I also referred to the article "Move Fast and Break Things" by Benjamin Wallace-Wells on pp. 24-35 of the June 23, 2025 issue of The New Yorker.

Will AI End Civilization?

 

Notice I didn't say, "Will AI (artificial intelligence) End Civilization As We Know It?"  Because it will.  It already has.  Civilization as we knew it as recently as five years ago is considerably different from what we have now—better in some ways, worse in others—and a good part of those changes have been due to widespread adoption of AI.  But the speakers in a Mar. 9, 2023 talk put on YouTube by the Center for Humane Technology raises a more fundamental question:  what are the chances that humans as a species will "go extinct" because we lose control of AI?

 

Based on internal evidence, these speakers–Tristan Harris, a co-founder of the Center, and Aza Raskin—are worth listening to.  The Center is in the heart of Silicon Valley and seems to be very well connected with Big Tech insiders, as attested by the fact that they were introduced before their talk by Steve Wozniak, co-founder of Apple.  And in numerous references during the talk, they emphasized that things are happening very fast, so fast that they have to revise the content of their talk almost weekly to keep up with the explosion of AI progress.

 

I'd like to concentrate here on a list that Harris and Raskin showed when they examined the potential downside of the way AI is currently being deployed as a competitive edge by corporations such as Microsoft and Google.  This list appeared after they cited a chilling statistic from a survey of leading AI experts.  738 experts were asked, "What probability do you put on human inability to control future advanced AI systems causing human extinction or similarly permanent and severe disempowerment of the human species?"  About half of the researchers think there is a greater than 10% chance of this disaster happening.  To put this result in perspective, Harris and Raskin then showed the burned-out hulk of a crashed airliner and asked in effect, "If 50% of the engineers who designed an airplane thought there was a 10% chance of it crashing, would you get on it?"  Yet we are all being taken down the AI road at breakneck speed by the corporations that see it as a business necessity.

 

OpenAI, a formerly non-profit AI behemoth that was recently turned into a profit-making enterprise, has famously offered its ChatGPT software to the public.  Simply turning powerful AI systems loose on the populace can lead to a number of dire consequences, many of which Raskin and Harris listed and showed examples of.  I'll focus on just a few of these that I think are near-term most likely.

 

"Trust collapse"—One of the leading features of modern economies is the mutual extension of trust.  If you fundamentally do not trust the person you're dealing with, you will spend most of your time and effort trying to avoid getting cheated, and won't have much energy left to do actual productive business.  In some countries, people with even moderate wealth by U. S. standards feel compelled to erect high masonry walls topped with broken glass around their dwellings, simply because if they don't, they will be robbed as a matter of course.  If messages or communications get so easy to fake that bad actors mimic your most close and trusted colleagues, it's hard to see how we could trust anybody anymore unless they are in the room with us. 

 

"Exponential scams [and] blackmail"—The AI experts seem to be most concerned that eventually, AI will develop a kind of super-con-artist ability that will fool even the cleverest and most sophisticated human being into doing stupid and harmful things.  In an interview on Fox News recently, Elon Musk worried that super-intelligent AI would be so persuasive that it could get us to do the civilizational equivalent of walking off a cliff.  It's hard to imagine a scenario that would make that credible, but I will have more to say about that below.

 

"Automated exploitation of code"—Computerized hacking, in other words.  Harris and Raskin showed an example of just such an activity they had carried out with ChatGPT after they told it in essence, "Hack this code." 

 

"Automated fake religions" and "Synthetic relationships"—I was a little surprised to see religion mentioned, but I put these two consequences together because religion involves the worship of something, or someone, and a synthetic relationship means a human would begin to treat a synthesized AI "person" as real.  Already there have been experiments in which disabled individuals (dementia patients, etc.) have gotten to know AI robots as "caregivers," and it is far from clear whether the patients understood that their new companion was only a pile of wires.  From a utilitarian point of view, there seems to be nothing wrong with this—after all, if we don't have enough real caregivers, why not make robots do the job?  But this approach puts superficial happiness above truth and reality, which is always a mistake.

 

For most of these dire things to happen, some human beings with either evil intent or with a short-sighted eagerness to profit ahead of the competition have to implement AI in a way that corrodes the social contract and pits ordinary human beings against a giant automated system that makes them putty in the hands of the robot.  As C. S. Lewis said long ago in The Abolition of Man, humanity's power over Nature, which has enabled it to produce the amazing advances in AI we see today, is really just the power of some small group of people (call them the controllers) over the rest of humanity—the controlled.  The tendency of all too many AI forecasters—including Harris and Raskin—is to treat AI as a wholly autonomous entity beyond the ability of anyone to control. 

 

While that is not a logical impossibility, the far more likely case is one in which bad actors take control of super-AI and use it for malevolent purposes—purposes which may not seem malevolent at the time, but which turn out to be that way long after we have become dependent on the systems that embody them.  This is a real and present danger, and I hope the scary scenarios portrayed by Harris and Raskin in their talk motivate the major players to stop driving us toward the AI cliff before it's too late—whenever that might be.

 

Sources:  A blog on the Salvo website by Robin Phillips on May 17, 2023 at https://salvomag.com/post/sam-altmans-greatest-fear had a link to the Center for Humane Technology talk by Tristan Harris and Aza Raskin at https://www.youtube.com/watch?v=xoVJKj8lcNQ, and that is how I found out about the talk.  It's over an hour long, but anyone concerned about the current dangers of AI should watch it. 

Would You Buy a Used Tesla from Elon Musk?

 

My father was a loan officer who specialized in auto loans.  In that position, he had to be a good judge of character.  I seem to remember one day he was talking about a fellow he knew, and said something like the following:  "He's stayed out of jail, but I wouldn't buy a used car from him."

 

More and more used-car buyers are going to face something like the headline's question as used electric vehicles (EVs), predominantly but not exclusively Teslas, hit the used-car market.  A recent article by Jamie L. LaReau of the Detroit Free Press, and republished by papers in the USA Today network, describes the challenges consumers face in buying a used EV.

 

As you probably know, the single most expensive component in an EV is the battery.  A complete replacement of the entire battery can cost about half the price of the car (e. g. $15,000 for a $30,000 used car).  The difficulty in buying a used EV is to figure out the condition of the battery—what its current range is and how long it will be before it has to be replaced.  Currently, there is no good way to do this.

 

LaReau recommends taking the prospective purchase for a long test drive, preferably a couple of  days, and running it on the kind of commuting route you expect to use it for.  If the battery runs precariously low in such a situation, the car may not be for you.  Some types of EVs allow the owner to replace individual faulty cells in the battery, thus avoiding an expensive replacement of the entire battery.  I would imagine that the diagnostics for such a replacement might not be straightforward, and only dealers for that particular model could do such a check.  Other types of

EVs make their batteries as a unitary packaged structure that has to be replaced all at once.  So when the battery's performance falls below what is required, there's really no other option but to replace the whole thing. 

 

Dave Sargent, whose title is Vice President of Connected Vehicles at the consumer-analytics  organization J. D. Power, is quoted as saying that mileage as reported by the odometer is not a good guide to battery condition.  More important is the way the car was driven—highway versus city streets—what the average temperature of its surroundings were (Phoenix or Bangor is bad, Atlanta is good) and how it was charged.  Fast charging, for example, is harder on batteries than the slower overnight charging that most consumers are able to do in their garages.  Also, if the battery was frequently allowed to discharge lower than 20% capacity, that tends to age it faster than otherwise.

 

In principle, all this data could be (and maybe is) stored somewhere, either on the car's computer or the manufacturer's remotely gathered database on the vehicle.  If somebody hasn't done this already, it shouldn't be hard to write software that can take such data and make an educated guess as to the overall condition of the battery at the time of sale.  At this time, however, such software doesn't seem to be generally available.

 

Some dealers will test the battery for a fee of about $150, but that only tells you what condition it is in now, not what it's going to do in the future.  A Federal government mandate to guarantee the battery in a new EV for eight years or 100,000 miles is worth something, but it is not clear if that warranty is always transferable to a used-car buyer.  On the lender CapitalOne's website, an article warns that some manufacturers won't replace a battery under the federal warranty until it is totally non-functional.  So even if the car would just get out of your driveway and then die, you'd be stuck with it until it wouldn't even do that.  And sometimes the warranty won't transfer to subsequent owners.

 

All in all, anyone buying a used EV is taking a chance that the battery will not do what they want in a time sooner than they'd like.  Of course, used cars in general are a somewhat risky purchase, but as a purchaser of used cars most of my life (I'm driving the first new car I ever bought, and that was only three years ago), there are ways to tell if you're getting a lemon or not, and state-mandated "lemon laws" allow consumers to return vehicles that were sold under clearly fraudulent conditions. 

 

But the lack of expertise on the ground who can make a reliable prediction as to when an EV's battery will degrade below an acceptable level of performance is a novelty that most buyers would rather not deal with. 

 

On the other hand, the reasons why people buy electric cars are not your usual reasons.  Currently, none of the EVs available, used or new, sell for prices that would attract what you might call the typical buyer.  LaReau cites statistics that say the current average price of a new EV is about $58,000 and for a used EV, you'll pay an average of $41,000.  So we are talking high-end if not luxury vehicles, and buyers for whom price is not the main consideration. 

 

I think one of the main motivations for people who buy EVs is a politico-esthetic one:  they think they are helping to avert global warming.  Whether buying and using an EV really does this, considering all the manufacturing steps, the mining of lithium and other metals under less-than-ideal circumstances, and the source of electric power used to charge the thing, is a question for another time.  Whether or not one really does affect global warming with an EV purchase, lots of people feel like they do, and that's what counts in marketing.

 

As with any used-car purchase, the old Latin motto caveat emptor ("let the buyer beware") applies in spades to buying a used EV.  If the car's battery performance turns out to be a disappointment, maybe the purchaser can just look upon it as one more sacrifice made in the cause of fighting global warming.  But your typical car buyer is likely to be unmoved by such sentiments, and so things will have to become a lot more transparent before used EVs become just as easy to sell as conventional gas guzzlers.

 

Sources:  The article "The future of car buying" by Jamie L. LaReau appeared in the business section of the online Austin American-Statesman for May 14, 2023.  I also referred to the article on the CapitalOne website https://www.capitalone.com/cars/learn/getting-a-good-deal/how-do-ev-battery-warranties-work/1960 regarding battery warranties for used EVs.

 

Is Twitter a Wholly Owned Subsidiary of the FBI?

 

When Elon Musk took over Twitter last October, he made available to reporters a large number of internal company emails relating to content moderation, deplatforming, and other interventions that the firm has done at the request of, or under the influence of, the U. S. government.  Like most people, I was dimly aware of these revelations, but the news coverage of them was intermittent and depended greatly on the political orientation of the media outlet reporting it.  And I'm sure that remains the case today.

 

But recently I came across one report that summarizes the facts in a chilling and alarming way.  If what this report says is true, we indeed have a major problem that involves not only electronic social media, but the government and fundamental constitutional issues. 

 

In all such cases, one should consider the source.  The source of this report is John Daniel Davidson, a senior editor at The Federalist, a conservative website which Wikipedia says has carried false and misleading information at times.  The particular report I refer to did not appear in that website, but in a newsletter called Imprimis issued by Hillsdale College, a private college that is one of the few serious colleges in the U. S. that refuses to take federal funds on principle.  Adapted from a talk Davidson gave at the college, the report is entitled "The Twitter Files Reveal an Existential Threat."

 

Davidson details three examples of how the FBI, working both on its own behalf and as a liaison between a number of other federal agencies and Twitter, directed the firm to flag, suppress, or suspend numerous accounts such as those of the New York Post, whose offense was to break the news of the Hunter Biden laptop; President Trump, whose suspension after the January 6, 2021 Capitol riot was sui generis in its disregard for internal suspension policies; and during the COVID-19 epidemic, in which Twitter was asked to, and did, squelch information that did not follow the official line on the pandemic that prevailed at the time.

 

The main point of Davidson's article is summed up in these words toward the end of the piece:  ". . . the entire concept of 'content moderation' is a euphemism for censorship by social media companies that falsely claim to be neutral and unbiased."  Davidson presents evidence that in 2017, Twitter publicly announced that all content moderation took place "at [Twitter's] sole discretion," but internally, they would censor anything that "U. S. intelligence identified as a state-sponsored entity conducting cyber-operations," whether the intelligence community was right or not.  As later events proved, the suspected Russian influence on U. S. elections was largely a smokescreen for allowing the federal government to suppress a wide variety of actors, most of which were not sponsored by any state, in direct violation of the First Amendment.

 

Currently, the U. S. Supreme Court is considering two cases that involve Section 230 of the Communications Decency Act.  The basic thrust of the section is to allow social-media companies to claim immunity from prosecution regarding material posted on their sites by third parties—namely, anybody but the company itself.  It also exempts the companies from lawsuits involving content moderation as long as the company can show such moderation was a good-faith effort to remove "objectionable" material. 

 

This law was passed in the very early days of social media, when it was not at all clear that internet-based systems such as Facebook and Twitter would ever make money.  Those days are long gone, and the pipsqueak upstarts of the 1990s have become the 900-pound gorillas of the 2020s. 

 

Far from being a minor sideshow in the ways the public learns what their elected officials and the rest of the government are up to, Twitter is arguably the primary source of breaking news from officialdom, equivalent to the Associated Press wire service of the long-ago day when news really traveled mainly over copper wires to teletype machines.  As publishers, the newspapers, radio, and TV outlets of yore (yore being anytime before about 1980) knew that they were legally responsible for what they printed or broadcast, and made careful distinctions between what was news and what was analysis or opinion.  They had the freedom to print what they wanted to print, courtesy of the First Amendment, which prohibits the federal government from "abridging the freedom of speech, or of the press."  But they also had the responsibility of standing behind what they printed as facts, and so they stressed fact-checking and accuracy, plus an effort to present all the significant news and suppress none of it, no matter how far it strayed from the newspaper's own political position.

 

Granted, this was an ideal that was only approached in practice.  But if you transpose what Twitter has done in the last few years to the register of how news was produced in, say, 1970, the results can be shocking.

 

Suppose the 1970s Watergate break-in, Deep Throat's revelations, and the secretly recorded Nixon White House tapes had been systematically expunged from all newspaper, radio, and TV coverage through the intervention of the FBI, saying that it was all a plot by the Russians?  After Nixon told the news media that they wouldn't have him to kick around anymore following his 1962 loss to Pat Brown in the California governor's race, suppose all the networks agreed to ban him from ever appearing on radio or television again, again at the behest of the federal government? 

 

I am no fan of Richard Nixon.  But my point is that none of these acts of censorship happened back then, because the reigning media companies kept their distance from the government, no matter who was running it.

 

Needless to say, the situation is different now.  Davidson's summary of the Twitter Files is an indictment of the hand-in-glove way that the federal government, using the channel of the FBI, has succeeded in manipulating the media landscape to suit its purposes, and not the best interests of the American people at large.  It is far past time to restore a responsible distance between social media and the government, but doing that will require a well-informed public, and the media we have may not be up to the job.

 

Sources:  John Daniel Davidson's article "The Twitter Files Reveal an Existential Threat" appeared in Vol. 62, No. 1 (Jan. 2023) of Imprimis, a publication of Hillsdale College.  I also referred to a report on the Supreme Court Section 230 cases at https://www.cnbc.com/2023/02/21/supreme-court-justices-in-google-case-hesitate-to-upend-section-230.html and Wikipedia articles on The Federalist and Richard Nixon's November 1962 news conference. 

The Tesla Self-Driving-Software Recall

 

Innovators tend to disrupt established procedures and shake things up generally.  No matter how good a new idea is, there are usually lots of people who will be inconvenienced or worse if the innovation takes hold and spreads, and the innovator has to push hard just to get a hearing. 

 

The way Tesla under Elon Musk has introduced semi-autonomous cars is a great example of this principle.  Readers of this blog are familiar with numerous cases in which Tesla drivers have been injured or killed under circumstances that point to careless use of the car's self-driving feature.  But until now, the National Highway Traffic Safety Administration (NHTSA) has not taken definite far-reaching actions against the firm. 

 

That changed this week when Tesla, under pressure from the NHTSA, issued a voluntary recall of some 360,000 of its cars that have the so-called "Full Self-Driving" mode installed.  This option, which according to one report costs $15,000, reportedly does all the work necessary to move the car safely:  steering, acceleration, and braking, under the control of cameras and artificial-intelligence (AI) systems.  An Associated Press article quotes Raj Rajkumar, a computer-science professor at Carnegie-Mellon, as saying Teslas don't use radar or laser systems in addition to cameras, and thus can miss important environmental clues that such systems provide.

 

In its recall, the NHTSA refers to Tesla's self-driving system as a Level 2 SAE type.  Some years back the Society of Automotive Engineers established a five-level ranking system for autonomous-car features.  Warning-only features make a car Level 0, as the driver is still doing all the actual work.  Level 2 can control braking, acceleration, and steering, but the driver "must constantly supervise these support features; you must steer, brake or accelerate as needed to maintain safety." 

 

Technically, the software being recalled is a beta version, meaning that the user in some sense agrees to be a guinea pig and try out something that may still have bugs in it.  The bugs cited by the NHTSA in its recall notice include things like ignoring speed zones, rolling through stop signs without stopping, and going straight in a turn-only lane.  These things sound like typical careless-driver problems, but as Rajkumar points out, upgrading the software to solve these issues may not be a simple or quick fix.

 

The recall itself is peculiar, in that no hardware has to be idled or replaced.  Tesla will simply issue an over-the-air upgrade at no cost to the car owners.  Musk tweeted that calling such an upgrade a recall was "anachronistic and just flat wrong!"  He has a point, in that over-the-air software upgrades are a routine part of doing business, but are usually not mandated or pressured into execution by a federal agency.

 

This recall is not the only concern that the NHTSA has with self-driving Teslas.  The agency is investigating numerous incidents that pose serious safety concerns, such as the tendency of some autonomous-mode Teslas to crash into emergency vehicles—some 14 such crashes have been recorded, as well as the deaths of 19 people in accidents where self-driving features may have been involved. 

 

Musk claims that the safety record of self-driving Teslas is better than old-fashioned hand-driven cars, but detailed statistics to back up his claim are lacking.  The autonomous-car project has always suffered from a chicken-and-egg problem.  To develop good self-driving systems, you need to get extensive testing in all sorts of real-world situations, but fielding a system that isn't yet perfected—whatever that might mean—entails some level of risk for both the people riding in the autonomous vehicles and for everybody else around them too. 

 

Here in Central Texas, as I drive around the stretch of I-35 between Austin and San Antonio, sightings of Teslas have gone from remarkably rare—maybe one every few weeks—to almost routine, as a couple of them are now usually parked in the same lot I use at work.  I have not yet seen one rolling down the road while the driver was reading a book or kissing his girlfriend, but I'm sure that happens.  The one Tesla driver I've spoken to about the autonomous system—our piano tuner, of all people—says he only uses it on I-35 and takes over once he gets off the freeway.  So for every careless driver who ignores the instructions to "constantly supervise" the self-driving mode, there are many responsible Tesla owners who learn the limitations of the system and act accordingly.

 

As a federal agency, the NHTSA seems to have its act together a lot better than, say, the FBI.  It largely stays out of politics and sticks to its mandate to safeguard the nation's highways.  The Tesla recall could have been much more drastic, as the NHTSA has the power to order carmakers to tell car owners to stop using the vehicle in question until the recall is installed.  That would have been an unnecessary move.  While nineteen fatalities possibly involving a new technology are of course tragic, that number pales in comparison to the estimated 42,915 people who died in traffic accidents in 2021, which was a 16-year high. 

 

Ideally, autonomous cars will contribute to a decline in traffic casualties, not an increase.  Overall, the NHTSA seems to be doing its job as watchdog, not cutting off a given manufacturer at the knees, so to speak, but not ignoring problems either.  The recall mechanism indicates to me that the NHTSA thinks Tesla may be going a bit too fast and careless in their beta-testing of so-called Full Self-Driving systems, and Musk knows he is playing a game that could cripple his car business if he and his engineers are not careful.  But being too careful in an innovative industry leaves you in the lurch, so it will be interesting to see how, and whether, the industry as a whole approaches the prize of truly autonomous Level 5 driving, in which the driver neither knows nor cares what is going on around him.  But we are by no means there yet.

 

Sources:  The AP article "Tesla Recalls 'Full Self-Driving' To Fix Unsafe Actions" appeared on the AP website on Feb. 16, 2023 at https://apnews.com/article/tesla-recalls-full-self-driving-cars-875b54d4b71e97d43a17e968d7b856ae.  The NHTSA recall notice can be found at https://static.nhtsa.gov/odi/rcl/2023/RCLRPT-23V085-3451.PDF.  The SAE autonomous driving levels are listed at https://www.sae.org/blog/sae-j3016-update.  The statistic on 2021 U. S. driving fatalities was from https://www.cnbc.com/2022/05/17/us-traffic-deaths-hit-16-year-high-in-2021-dot-says.html. 

What? Twitter Neutral?

 

Back when I started this blog in 2006, the phrase "social media" was hardly used by anybody, according to Google Trends.  It began to climb above 1% of its current frequency of use around 2008, possibly in connection with the elections of that year, and has been climbing ever since. 

 

Twitter, the social-media format that has become the default medium of choice for announcements by Presidents on down, was also founded in 2006.  From an obscure techie-speak term, it has turned into a routine and near-universal medium of expression that its leadership has claimed is as neutral as they can make it.  But a recent article by political scientist Wilfred Reilly details how the medium's claim of neutrality is false. 

 

Specifically, in 2018, Twitter's CEO Jack Dorsey said, in response to accusations that the firm was silently suppressing or banning certain conservatives, that "We don’t shadow-ban conservatives — period."  Similar assertions were made by company officials testifying before Congress and in other public venues.

 

Then along comes reporter Bari Weiss, who used Elon Musk's recently released Twitter files last month to demonstrate dozens of examples in which Twitter silenced or suppressed certain accounts. 

 

Weiss found a variety of ways Twitter can cripple the reach of a given account.  One way is by making the person unsearchable, which is more effective these days than the class of untouchables maintained in some cultures.  Encumbering tweets with warnings, suppressing the sharing of certain tweets—the list of technical means goes on and on.

 

As wonky as I am about engineering details, I'd like to pull back to examine a broader question:  has Twitter behaved unethically in (a) saying they don't "shadow-ban" while clearly doing so, and (b) favoring some tweets and suppressing others?

 

We can dispense with (a) pretty quickly.  Unless Dorsey wants to play a Clintonesque definition game with the phrase "shadow-ban" ("It depends on what you mean by 'shadow-ban.'"), it's obvious that he and his corporate minions have lied repeatedly about how they treat certain accounts.  Companies lie about what they do for a variety of reasons.  Sometimes it's simple ignorance—nobody told the boss what was going on.  That seems hardly likely in this case.  Sometimes it's a deliberate strategy to avoid public embarrassment and financial loss.  That would explain Dorsey's behavior, certainly, and imagining what would have happened if he'd said, "Well, yes, we think we have a duty to the public to protect it from some opinions, and so we do shadow-ban," I can see why a lie would be appealing. 

 

Reilly makes the point that we shouldn't be surprised when we find that Twitter or any other social-media outlet shapes its content to suit its own purposes, whether those be profit, a desire to shape the political landscape, or other things perceived as of more value than telling the truth about what one is up to.  What is disappointing, if not surprising, is the ease and frequency with which Twitter lied about it, and the gullibility of much of the dominant media to believe them, and to criticize so-called conspiracy theorists for claiming that certain stories and outlets—the Hunter Biden laptop episode comes to mind—were intentionally suppressed.  Musk's revelations of internal Twitter documents basically confirm many of these claims that were so scornfully dismissed before.

 

What about (b)?  Regardless of whether they are honest about it, should Twitter mold and shape their content by hyping some tweets and squashing others?  And we shouldn't limit the scope of the question to Twitter.  Facebook, search engines such as Google, and the whole megillah of social media and the way we look for information these days should be included in this question.

 

Most people would agree on certain outer limits to stuff that people post or tweet.  Blackmail, bullying, the lowest dregs of the human imagination—these things should not be allowed into the public arena.  The problem comes when you ask about the rest of what comes into a place like Twitter for potential publication. 

 

Strictly speaking, Twitter and virtually all other social media are private companies which are, and probably should remain, in control of what they publish.  Twitter is not like a public park, paid for with taxes and therefore available to any taxpayer who follows some basic rules.  It's more like a private estate in that sense, where once you are allowed in on the owner's terms, almost anything goes that doesn't break the law.  There is no intrinsic right to express yourself on Twitter or any other private platform.

 

The practical problem is that in replacing the old-fashioned print and one-way electronic media, social media have become the default public square.  Stuff that used to be announced in press conferences before cameras and reporters now gets tweeted routinely first, and press conferences come later, if at all. 

 

The legacy media repressed things silently too.  I can't recall the details, but I remember reading about some reporters who showed up at the house of a prominent public official to ask him something.  His wife came to the door drunk as a skunk, and the code of behavior back then (this was in the early 1960s, I think) made them ignore her state and behavior, and they went away without any story at all.  These days, of course, a live video of her would go viral from the reporter's phone, likely as not.

 

So the news that Twitter shapes tweets to suit itself isn't really news in the sense of a radical new thing happening.  What needs to happen is that people who use social media—and for most of us, that means readers rather than the relatively few producers of viral tweets—need to be aware that everything is biased:  Twitter, Facebook, Google, the newspapers, and even emails from your friends. 

 

With your friends, you probably know them well enough to allow for whatever biases they bring to the table.  And with Musk's revelations about Twitter, we are effectively learning more about Twitter's personality—what things it likes and what things you aren't likely to hear from it.  The bad part of this is that if you want to says something that Twitter doesn't like, you are going to have to find another way to say it.  And that's a problem, but as Reilly pointed out at the end of his article, there's always dictionaries and encyclopedias, and I'd add snail-mail to that, too.

 

Sources:  Wilfred Reilly's article "The Conspiracy Theories Were Real, and Other Revelations" appeared on the National Review website on Dec. 30, 2022, at https://www.nationalreview.com/2022/12/the-conspiracy-theories-were-real-and-other-revelations/. 

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.