Category: AI

 

Due to the execution of a health insurance CEO, public attention is focused on health care. The United States has expensive health care, and this is working as intended to generate profits. Many Americans are uninsured or underinsured and even those who have insurance can find that their care is not covered. As has been repeatedly pointed out in the wake of the execution, there is a health care crisis in the United States and it is one that has been intentionally created.

Americans are a creative and generous people, which explains why people have turned to GoFundMe to get money for medical expenses. Medical bills can be ruinous and lead to bankruptcy for hundreds of thousands of Americans each year. A GoFundMe campaign can help a person pay their bills, get the care they need and avoid financial ruin. Friends of mine have been forced to undertake such campaigns and I have donated to them, as have many other people. In my own case, I am lucky and have a job that offers insurance coverage at a price I can afford, and my modest salary allows me to meet the medical expenses for a very healthy person with no pre-existing conditions. However, I know that like most of us,  I am one medical disaster away from financial ruin. As such, I have followed the use of GoFundMe for medical expenses with some practical interest. I have also given it some thought from a philosophical perspective.

On the one hand, the success of certain GoFundMe campaigns to cover such expenses suggests that people are morally decent and are willing to expend their own resources to help others. While GoFundMe does profit from these donations, their take is modest. They are not engaged in gouging people in need and exploiting medical necessities for absurdly high profits. That is the job of the health insurance industry.

On the other hand, there is the moral concern that in a wealthy country replete with billionaires and millionaires, many people must beg for money to meet their medical expenses. This spotlights the excessive cost of healthcare, the relatively low earnings of many Americans, and the weakness of the nation’s safety net. While those who donate out of generosity and compassion merit moral praise, the need for such donations merits moral condemnation. People should not need to beg for money to pay for their medical care. 

To anticipate an objection, I am aware that people do use GoFundMe for frivolous things and there are scammers, but my concern is with the fact that some people do need to turn to crowdfunding to pay their bills.

While donating is morally laudable, there are concerns about this method of funding. One practical problem is that it depends on the generosity of others. It is not a systematic and dependable method of funding. As such, it is a gamble to rely on it.

A second problem is that it depends on running an effective social media campaign. Like any other crowdfunding, success depends on getting attention and persuading people to donate. Those who have the time, resources and skills to run effective social media campaigns (or who have help) are more likely to succeed. This is concerning because people facing serious medical expenses are often in no condition to undertake the challenges of running a social media campaign. This is not to criticize or condemn people who can do this or recruit others. My point is that this method is no substitute for a systematic and consistent approach to funding health care.

A third problem is that success depends on the appeal of the medical condition and the person with that condition. While a rational approach to funding would be based on merit and need, there are clearly conditions and people that are more appealing in terms of attracting donors. For example, certain diseases and conditions can be “in” and generate sympathy, while others are not as appealing. In the case of people, we are not all equal in how appealing we are to others. As with the other problems, I do not condemn or criticize people for having conditions that are “in” or being appealing. Rather, my concern is that this method rests so heavily on these factors rather than medical and financial need. Once again, this serves to illustrate how the current system has been willfully broken and does not serve the needs of most Americans. While those who have succeeded in their GoFundMe campaigns should be lauded for their effort and ingenuity, those who run the health care system in which people have to run social media campaigns to afford their health care should be condemned.   

The execution of CEO Brian Thompson has brought the dystopian but highly profitable American health care system into the spotlight. While some are rightfully expressing compassion for Thompson’s family, the overwhelming tide of commentary is about the harms Americans suffer because of the way the health care system is operated. In many ways, this incident exposes many aspects of the American nightmare such as dystopian health care, the rule of oligarchs, the surveillance state, and gun violence.

As this is being written the identity and motives of the shooter are not known. However, the evidence suggests that he had an experience with the company that was bad enough he decided to execute the CEO. The main evidence for this is the words written on his shell casings (deny”, “depose”, and “defend”) that reference the tactics used by health insurance companies to avoid paying for care. Given the behavior of insurance companies in general and United Healthcare in particular, this inference makes sense.

The United States spends $13,000 per year per person on health care, although this is just the number you get when you divide the total spending by the total number of people. Obviously, we don’t each get $13,000 each year. Despite this, we have worse health outcomes than many other countries that spend less than half of what we do, and American life expectancy is dropping. It is estimated that about 85 million people are either without health care insurance or are underinsured.

It is estimated that between 45,000 and 60,000 Americans die each year because they cannot get access to health care on time, with many of these deaths attributed to a lack of health insurance. Even those who can get access to health care face dire consequences in that about 500,000 Americans go bankrupt because of medical debt. In contrast, health insurance companies are doing very well. In 2023, publicly traded health insurance companies experienced a 10.4% increase in total GAAP revenue reaching a total of $1.07 trillion. Thomson himself had an annual compensation package of $10.2 million.

In addition to the cold statistics, almost everyone in America has a bad story about health insurance. One indication that health insurance is a nightmare is the number of GoFundMe fundraisers for medica expenses. The company even has a guide to setting up your own medical fundraiser. Like many people, I have given to such fundraisers such as when a high school friend could not pay for his treatment. He is dead now.

My own story is a minor one, but the fact that a college professor with “good” insurance has a story also illustrates the problem. When I had my quadriceps repair surgery, the doctor told me that my insurance had stopped covering the leg brace because they deemed it medically unnecessary. The doctor said that it was absolutely necessary, and he was right. So, I had to buy a $500 brace that my insurance did not cover. I could afford it, but $500 is a lot of money for most of us.

Like most Americans, I have friends who have truly nightmarish stories of unceasing battles with insurance companies to secure health care for themselves or family. Similar stories flooded social media, filling out the statistics with the suffering of people. While most people did not applaud the execution, it was clear that Americans hate the health insurance industry and do so for good reason. But is the killing of a CEO morally justified?

There is a general moral presumption that killing people is wrong and we rightfully expect a justification if someone claims that a killing was morally acceptable. In addition to the moral issue, there is also the question of the norms of society. Robert Pape, director of the University of Chicago’s project on security and threats, has claimed that Americans are increasingly accepting violence as a means of settling civil disputes and that this one incident shows that “the norms of violence are spreading into the commercial sector.” While Pape does make a reasonable point, violence has long been a part of the commercial sector although this has mostly been the use of violence against workers in general and unions in particular. Gun violence is also “normal” in the United States in that it occurs regularly. As such, the killing does see to be within the norms of America, although the killing of a CEO is unusual.

While it must be emphasized that the motive of the shooter is not known, the speculation is that he was harmed in some manner by the heath insurance company. While we do not yet know his story, we do know that people suffer or die from lack of affordable insurance and when insurance companies deny them coverage for treatment.

Philosophers draw a moral distinction between killing and letting people die and insurance companies can make the philosophical argument that they are not killing people or inflicting direct harm. They are just letting people suffer or die for financial reasons when they can be helped. When it comes to their compensation packages, CEOs and upper management defend their exorbitant compensation by arguing that they are the ones making the big decisions and leading the company. If we take them at their word, then this entails that they also deserve the largest share of moral accountability. That is, if a company’s actions are causing death and suffering, then the CEO and other leadership are the ones who deserve a package of blame to match their compensation package.

It is important to distinguish moral accountability from legal accountability. Corporations exist, in large part, to concentrate wealth at the top while distributing legal accountability. Even when they commit criminal activity, “it’s rare for top executives – especially at larger companies – to face personal punishment.” One reason for this is that the United States is an oligarchy rather than a democracy and the laws are written to benefit the wealthy. This is not to say that corporate leaders are above the law; they are not. They are wrapped in the law, and it generally serves them well as armor against accountability. For the lower classes, the law is more often a sword employed to rob and otherwise harm them. As such, one moral justification for an individual using violence against a CEO or other corporate leader is that might be the only way they will face meaningful consequences for their crimes.

The social contract is supposed to ensure that everyone faces consequences and when this is not the case, then the social contract loses its validity. To borrow from Glaucon in Plato’s Republic, it would be foolish to be restrained by “justice” when others are harming you without such restraint.  But it might be objected, while health insurance companies do face legal scrutiny, denying coverage and making health care unaffordable for many Americans is legal. As such, these are not crimes and CEOs, and corporate leaders should not be harmed for inflicting such harm.

While it is true that corporations can legally get away with letting people die and even causing their deaths, this is where morality enters the picture. While there are philosophical views that morality is determined by the law, these views have many obvious problems, not the least of which is that they are counterintuitive.

If people are morally accountable for the harm they inflict and can be justly punished and the legal system ignores such harm, then it would follow that individuals have the moral right to act. In terms of philosophical justification, John Locke provides an excellent basis. If a corporation can cause unjustified harm to the life and property of people and the state allows this, then the corporations have returned themselves and their victims to the state of nature because, in effect, the state does not exist in this context. In this situation, everyone has the right to defend themselves and others from such unjust incursions and this, as Locke argued, can involve violence and even lethal force.

It might be objected that such vigilante justice would harm society, and that people should rely on the legal system for recourse. But that is exactly the problem: the people running the state have allowed the corporations to mostly do as they wish to their victims with little consequence and have removed the protection of the law. It is they who have created a situation where vigilante justice might be the only meaningful recourse of the citizen. To complain about eroding norms is a mistake, because the norm is for corporations and the elites to get away with moral crimes with little consequence. For people to fight back against this can be seen as desperate attempts at some justice.

As the Trump administration is likely to see a decrease in even the timid and limited efforts to check corporate wrongdoing, it seems likely there will be more incidents of people going after corporate leaders. Much of the discussion among the corporations is about the need to protect corporate leaders and we can expect lawmakers and the police to step up to offer even more protection to the oligarchs from the people they are hurting.

Politicians could take steps to solve the health care crisis that the for-profit focus of health care has caused and some, such have Bernie Sanders, honestly want to do that. In closing, one consequence of the killing is that Anthem decided to rescind their proposed anesthesia policy. Anthem Blue Cross Blue Shield plans representing Connecticut, New York and Missouri had said they would no longer pay for anesthesia care if a procedure goes beyond an arbitrary time limit, regardless of how long it takes. This illustrates our dystopia: this would have been allowed by the state that is supposed to protect us, but the execution of a health insurance CEO made the leaders of Anthem rethink their greed. This is not how things should be. In a better world Thompson would be alive, albeit not as rich,  and spending the holidays with his family. And so would the thousands of Americans who died needlessly because of greed and cruelty.

 

While pharmaceutical companies profited from flooding America with opioids, this inflicted terrible costs on others. Among the costs has been the terrible impact on health. One example of this is endocarditis.

Endocarditis is an abscess on a heart valve. While not limited to drug users, it can be caused by injecting opioids. As opioids were pushed onto the American people, it is no surprise that the number of drug users suffering from endocarditis increased significantly.  The treatment of endocarditis involves a very expensive surgery and many drug users getting this surgery are on Medicaid. To make matters worse, people often return to opioid use after the surgery and this can lead to another expensive surgery, paid for by Medicaid. This raises moral concerns.

There is the moral issue of whether Medicaid should even exist. On the one hand, a compelling moral argument can be made that just as a nation provides military and police protection to citizens who cannot afford their own security forces or bodyguards, a nation should fund medical care for those who cannot afford it on their own. On the other hand, a moral argument can be made that a nation has no obligation to provide such support and that citizens should be left to fend for themselves regarding health care. Naturally enough, if the nation is under no obligation to provide Medicaid in general, then it is under no obligation to cover the cost of the surgery in question. On this view, there is no need to consider the matter further.

 However, if the state should provide Medicaid, then the issue of whether the state should pay for endocarditis surgery for opioid addicts arises. It is to this discussion that I now turn.

While it is harsh to argue against paying for an addict’s heart surgery, a moral case can be made in favor of this position. The most obvious way to do this is on utilitarian grounds. As noted above, surgery for endocarditis is very expensive and uses financial and medical resources that could be used elsewhere. If more good could be done by using these resources elsewhere, the utilitarian conclusion is that this is what should be done. This argument can be strengthened by including the fact that addicts often return to behavior that resulted in endocarditis, thus creating the need for repeating the costly surgery. From a utilitarian perspective, it would be morally better to use those resources to treat patients who are less likely to willfully engage in behavior that will require them to be treated yet again. This is because the resources that would be consumed treating and retreating a person who keeps inflicting harm on themselves could be used to treat many people, thus doing greater good for the greater number. Though harsh and seemingly merciless, this approach seems justifiable on grounds like the moral justification for triage.

Another approach, which is even harsher, is to focus on the fact that the addicts are giving themselves endocarditis and sometimes doing so repeatedly. This provides the basis for two arguments against public funding of their treatment.

One argument can be built around the idea that there is no moral obligation to help people when their harm is self-inflicted. To use an analogy, if a person insists on setting fire to their house and it burns down, no one has a moral responsibility to pay to have their house rebuilt. Since the addict’s woes are self-inflicted, there is no moral obligation on the part of others to pay for their surgery and forcing people to do so (by using public money) would be like forcing others to pay to rebuild the burned house.

One way to counter this is to point out that many health issues are self-inflicted by a lack of positive behavior (such as exercise and a good diet) and an abundance of negative behavior (such as smoking, drinking, or having unprotected sex). If this principle is applied to addicts, it must be applied to all cases of self-inflicted harm. While some might take this as a refutation of this view, others might accept this as reasonable and warranting a state of nature approach to medicine in which everyone is on their own.

Another argument can be built around the idea that while there could be an obligation to help people, this obligation is limited. In this case, if a person is treated and knowingly returns to the same harmful behavior, then there is no obligation to keep treating the person. In the case of the drug addict, it could be accepted that the first surgery should be covered and that they should be educated on what will happen if they persist in their harmful behavior. If they then persist in that behavior and need the surgery again, then public money should not be used. To use an analogy, if a child swings their ice cream cone around and is surprised when the scoops hit the ground, then it would be reasonable for the parents to buy the child another cone. If the child swings the new cone around and the scoops hit the ground, then the child can be justly denied another cone.

An obvious counter is to contend that addicts are addicted and hence cannot be blamed for returning to the behavior that caused the harm. They are not morally responsible because they cannot do otherwise. This does have some appeal but would seem to justify requiring addicts to also undergo treatment for their addiction and to agree to monitoring of their behavior. They should be free to refuse this (which, ironically, assumes they are capable of free choice), but this should result in their being denied a second surgery if their behavior results in the same harm. Holding people accountable does seem to be cruel, but it could be argued that the alternative is unfair to other citizens. It would be like requiring them to keep rebuilding houses for a person who persists in setting fires in their house and refuses to takes steps to stop doing this.

These arguments can be countered by arguing that there is an obligation to provide such care regardless of how many times an addict returns to the behavior that caused the need for the surgery. One approach would be to build an analogy based on how the state repeatedly bails out big businesses every time they burn down the economy. Another approach would be to appeal to the value of human life and contend that it must be preserved regardless of the cost and regardless of the reason why there is a need for medical care. This approach could be noble or, perhaps, foolish.

 

While industrial robots have been in service for a while, household robots have largely been limited to floor cleaning machines like the Roomba. But Physical Intelligence has built a robot that seems capable of doing some household tasks such as folding clothes. While a viable commercial products lie in the future, the dangers of household robots should be considered now. I will skip over the usual fear of the robot rebellion in which the machines turn against humans and focus on more likely dangers.

Like a PC or phone, a household robot runs the risk of software errors, glitches and other problems. While having an app crash on your phone or PC can be annoying, this usually does not put you at risk of physical harm. However, a malfunctioning household robot can be a danger. A viable household robot needs to be strong enough to engage in tasks such as cleaning, folding laundry, and moving objects. This entails that the robot will be strong enough to harm humans and pets. If a robot has a software or hardware issue that interferes with its ability to recognize objects and living creatures, it might try to fold a baby’s clothing while the baby is wearing them or mistake a sleeping cat for clothing or trash and put them in the washing machine or garbage can. Even more concerning is a robot designed to prepare food that misidentifies, for example, a human or pet as the meat to be sliced up and cooked for dinner.

Even laying aside such errors, a home can be a complicated place for a robot to operate in, as there will usually be multiple rooms, different types of furniture, different appliances, as well as various people and pets. This means that a household robot could easily become a hazard (or just useless) simply because of an inability to handle such a complicated and changing environment.

To be fair, these challenges can be addressed in various ways. One option is to limit robots to specific tasks and narrow areas of operation. This might require multiple robots in a home, each assigned to a specific area and set of tasks. For example, a knife wielding kitchen robot might have a fixed location in the kitchen and only be able to slice foods placed within a special  box. As another example, a laundry robot might be confined to a laundry room. Another way to reduce risk is through programming and hardware safeguards. For example, pets and humans might wear devices that provide household robots with their exact location so they can avoid them. This way the robot would not need to depend on visually distinguishing, for example, a cat from a sweater. While things could still go wrong (the ID tag might fail or fall off your cat’s collar), people are generally willing to accept some risk of injury and death for convenience. After all, any electrical appliance in your home can probably kill you and driving anywhere comes with the risk of injury or death. In addition to concerns about accidental injuries, there is also the threat of intentionally caused harm.

Household robots will almost certainly have online connections. On the one hand, this has many potential benefits such as being able to check in on your robots and taking manual control if, for example, one gets stuck in a corner. On the other hand, if you can access your robots online, that means that bad actors can do so as well, just as can happen today with any connected device. The critical difference is that a connected robot in your house means that a bad actor can gain a virtual physical presence in your home and use your robot in various ways.

It is certain that some people will take control of other peoples’ robots just for fun, to do various pranks such as having a robot move things around or make a small mess. But compromised robots could be used for a range of misdeeds, such as unlocking doors (although connected smart locks are obviously vulnerable), grabbing valuables and tossing them out windows, breaking things, and even attacking people and pets. This threat can be mitigated by good security practices but the only two ways to avoid a compromised robot is to either not have it connected or not have one at all.

As with autonomous vehicles, household robots also raise legal concerns about liability. If, for example, your robot injures a guest, there is the question of who has legal responsibility. On the plus side, household robots will be good for some lawyers as this will create a new, profitable subfield of law.

In closing, while the idea of having household robots seems appealing, their presence would create a new set of dangers, especially if they are connected and can be compromised.

 

In utopian science fiction, machines free humans so they can enjoy a life of leisure and enlightenment. In dystopian stories, machines enslave or exterminate humans. Reality has been, on average, a middletopia: a mean between the worst possible world and the best possible world. But a good case can be made that reality is more of a dystopia-lite; a bad world, but better than a full dystopia. While people still dream of utopia, there are those who are working hard to push us further into dystopia.

On a positive note, robots have replaced humans in some jobs that are dirty, dull, or dangerous. In some cases, the displaced humans have moved on to better jobs. In other cases, they have moved into other dirty, dull or dangerous jobs to wait for the machines to replace those jobs.  Machines have also replaced humans in jobs humans see as desirable and AI companies are determined to continue that trend, having selected writing and art as prime targets This leads to questions about what jobs will be left to humans and which will be taken over by the machines

There was once the intuitively appealing view that “creative” jobs would be safe from machines, but physical labor would be easily taken over by machines. On this view, machines will replace jobs such as those held by warehouse pickers, construction workers and janitors. Artists, philosophers, and teachers were supposed to be safe from the machine revolution. In some cases, the intuitive view was correct. Machines are routinely used for physical labor such as constructing cars and robot Socrates has yet to show up. However, the intuitive view about creative tasks is under attack as AI is used in journalism, law, academics and image creation. There are also tasks that would seem easy to automate, such as cleaning toilets or doing construction, that are very hard for robots, but easy for humans.

An example of a task that would seem ideal for automation is warehouse picking, especially of the sort done by Amazon. Amazon and other companies have automated some of the process, making use of robots in various tasks. But humans are still a critical part of the picking process. Since humans tend to have poor memories and get bored with picking, human pickers are “remote controlled” by computers that tell them what to do, then they tell the computers what they have done. For example, a human might be directed to pick five boxes of acne medicine, then five more boxes of acne medicine, then a copy of Fifty Shades of Gray and finally an Android phone. Humans are very good at picking and dealing with things like a broken bottle of shampoo in a box that robots still handle poorly.

In this sort of warehouse, the humans are being controlled by the machines. The machines take care of the higher-level activities of organizing orders and managing, while the human brain handles the task of selecting the right items and dealing with some tasks the machines cannot handle. While selecting seems simple, this is because it is simple for humans but not for existing robots. We are good at recognizing, grouping and distinguishing things and have the manual dexterity to perform the picking tasks, thanks to our opposable thumbs. Unfortunately for the human worker, these picking tasks are probably not very rewarding, creative or interesting and this is exactly the sort of drudge job that robots are supposed to free us from.

While computer-controlled warehouse work is one example of humans being directed by machines, it is easy to imagine this approach applied to tasks that require manual dexterity and what might be called “animal skills” such as object recognition. It is also easy to imagine this approach extended far beyond these jobs as a cost-cutting measure.

One way this approach could cut costs would be by allowing employers to buy “skilled” AI systems and use them to direct unskilled human labor. For simple jobs, a human might be directed via a headset linked to the AI that tells the human what to do, providing the “intelligence” guiding the body. For more complex jobs, a human might wear a VR style helmet with a machine directing the human via augmented reality. For example, an unskilled human could be walked through electrical or plumbing work by an AI. It should be noted that this technology could also be useful for people doing DIY projects and someday a person might be able to rent skills (via AI) as they now rent tools. But this could also impact the labor market, especially if almost anyone could use the technology effectively.

In this system, humans would provide the manual dexterity and all those highly evolved physical capacities. The AI would provide the direction, skill and “intelligence.” Since any adequately functional human body would suffice to serve the controlling AI, the value of such human labor would be low, and wages would match this value. Workers would be easy to replace because if a worker is fired or quits, then a new worker can simply don the interface device and get about the task with little training. This would also save in education costs as AI directed laborer would not need much education in job skills as these are by the AI. Humans would just need the basis skills allowing them to be directed properly by AI. This does point towards a dystopia in which human bodies are driven around through the workday by AI, then released and sent home in driverless cars. One could even imagine this technology being used in education: a human body providing an in-person presence while an AI directs the teaching process.

The employment of humans in these roles would only continue if humans were the cheapest form of available labor. If advances allow robot bodies to do these tasks cheaper, then it would make business sense to replace humans completely.  Alternatively, biological engineering might lead to the production of cost-effective engineered life forms that can replace humans; perhaps a pliable primate that is just smart enough to be directed by the AI. But not human enough to be considered a slave. Or, to go deeper into dystopia, perhaps a cyborg will be built that has hardware in place of the higher parts of the brain and thus serves as a meat robot driven around the job by the AI that is using the evolved biological features that cannot be replicated cost-effectively by machinery. While such things remain science fiction, now is the time to start considering the laws and policies that should govern remote controlled humans in the workplace.

 

One of the many fears about AI is that it will be weaponized by political candidates. In a proactive move, some states have already created laws regulating its use. Michigan has a law aimed at the deceptive use of AI that requires a disclaimer when a political ad is “manipulated by technical means and depicts speech or conduct that did not occur.”  My adopted state of Florida has a similar law that political ads using generative AI requires a disclaimer. While the effect of disclaimers on elections remains to be seen, a study by New York University’s Center on Technology Policy found that research subjects saw candidates who used such disclaimers as “less trustworthy and less appealing.”

The subjects watched fictional political ads, some of which had AI disclaimers, and then rated the fictional candidates on trustworthiness, truthfulness and how likely they were to vote for them. The study showed that the disclaimers had a small but statistically significant negative impact on the perception of these fictional candidates. This occurred whether the AI use was deceptive or more harmless. The study subjects also expressed a preference for using disclaimers anytime AI was used in an ad, even when the use was harmless, and this held across party lines. As attack ads are a common strategy, it is interesting that the study found that such ads with an AI disclaimer backfired, and the study subjects evaluated the target as more trustworthy and appealing than the attacker.

If the study results hold for real ads, these findings might serve to deter the use of AI in political ads, especially attack ads. But it is worth noting that the study did not involve ads featuring actual candidates. Out in the wild, voters tend to be tolerant of lies or even like them when the lies support their political beliefs. If the disclaimer is seen as stating or implying that the ad contains untruths, it is likely that the negative impact of the disclaimer would be less or even nonexistent for certain candidates or messages. This is something that will need to be assessed in the wild.

The findings also suggest a diabolical strategy in which an attack ad with the AI disclaimer is created to target the candidate the creators support. These supporters would need to take care to conceal their connection to the candidate, but this is easy in the current dark money reality of American politics. They would, of course, need to calculate the risk that the ad might work better as an attack ad than a backfire ad. Speaking of diabolical, it might be wondered why there are disclaimer laws rather than bans.

The Florida law requires a disclaimer when AI is used to “depict a real person performing an action that did not actually occur, and was created with the intent to injure a candidate or to deceive regarding a ballot issue.” A possible example of such use seems to occur in an ad by DeSantis’s campaign falsely depicting Trump embracing Fauci in 2023.   It is noteworthy that the wording of the law entails that the intentional use of AI to harm and deceive in political advertising is allowed but merely requires a disclaimer. That is, an ad is allowed to lie but with a disclaimer. This might strike many as odd, but follows established law.

As the former head of the FCC under Obama Tom Wheeler notes, lies are allowed in political ads on federally regulated broadcast channels. As would be suspected, the arguments used to defend allowing lies in political ads are based on the First Amendment. This “right to lie” provides some explanation as to why these laws do not ban the use of AI. It might be wondered why there is not a more general law requiring a disclaimer for all intentional deceptions in political ads. A practical reason is that it is currently much easier to prove the use of AI than it is to prove intentional deception in general. That said, the Florida law specifies intent and the use of AI to depict something that did not occur and proving both does present a challenge, especially since people can legally lie in their ads and insist the depiction is of something real.

 Cable TV channels, such as CNN, can reject ads. In some cases, stations can reject ads from non-candidate outside groups, such as super PACs. Social media companies, such as X and Facebook, have considerable freedom in what they can reject. Those defending this right of rejection point out the oft forgotten fact that the First Amendment legal right applies to the actions of the government and not private businesses, such as CNN and Facebook. Broadcast TV, as noted above, is an exception to this. The companies that run political ads will need to develop their own AI policies while also following the relevant laws.

While some might think that a complete ban on AI would be best, the AI hype has made this a bad idea. This is because companies have rushed to include AI in as many products as possible and to rebrand existing technologies as AI. For example, the text of an ad might be written in Microsoft Word with Grammarly installed and Grammarly is pitching itself as providing AI writing assistance. Programs like Adobe Illustrator and Photoshop also have AI features that have innocuous uses, such as automating the process of improving the quality of a real image or creating a background pattern that might be used in a print ad.  It would obviously be absurd to require a disclaimer for such uses of AI.

For more on cyber policy issues: Hewlett Foundation Cyber Policy Institute (famu.edu)

 

When ChatGPT and its competitors became available to students, some warned of an AI apocalypse in education.  This fear mirrored the broader worries about the over-hyped dangers of AI. This is not to deny that AI presents challenges and danger, but we need to have a realistic view of the threats and promises so that rational policies and practices can be implemented.

As a professor and the chair of the General Education Assessment Committee at Florida A&M University I assess the work of my students, and I am involved with the broader task of assessing general education. In both cases a key challenge is determining how much of the work turned in by students is their work. After all, we want to know how our students are performing and not how AI or some unknown writer is performing.

While students have been cheating since the advent of education, it was feared AI would cause a cheating tsunami. This worry seemed sensible since AI makes cheating easy, free and harder to detect.  Large language models allow “plagiarism on demand” by generating new text each time. With the development of software such as Turnitin, detecting traditional plagiarism became automated and fast. These tools also identify the sources used in plagiarism, providing professors with reliable evidence. But large language models defeat this method of detection, since they generate original text. Ironically, some faculty now see a 0% plagiarism score on Turnitin as a possible red flag. But has an AI cheating tsunami washed over education?

Determining how many students are cheating is like determining how many people are committing crime: one only knows how many people have been caught and not how many people are doing it. Because of this, caution must be exercised when drawing a conclusion about the extent of cheating otherwise one runs the risk of falling victim to the fallacy of overconfident inference from unknown statistics.

In the case of AI cheating in education, one source of data is Turnitin’s AI detection software. Over the course of a year, the service checked 200 million assignments and flagged AI use in 1 in 10 assignments while 3 in 100 were flagged as mostly AI. These results have remained stable, suggesting that AI cheating is neither a tsunami nor increasing. But this assumes that the AI detection software is accurate.

Turnitin claims it has a false positive rate of 1%. In addition to Turnitin, there are other AI detection services that have been evaluated, with the worst having an accuracy of 38% and the best claimed to have a 90% accuracy. But there are two major problems with the accuracy of existing plagiarism detection software.

The first, as the title of a recent paper notes, “GPT detectors are biased against non-native English writers.” As the authors noted, while AI detectors are nearly perfectly accurate in evaluating essays by U.S. born eighth-graders, they misclassified 61.22% of TOEFL essays written by non-native English students. All seven of the tested detectors incorrectly flagged 18 of the 91 TOEFL essays and 89 of 91 of the essays (97%) were flagged by at least one detector.

The second is that AI detectors can be fooled. The current detectors usually work by evaluating perplexity as a metric. Perplexity, which is a measure of such factors as lexical diversity and grammatical complexity, can be created in AI text by using simple prompt engineering. For example, a student could prompt ChatGPT to rewrite the text using more literary language. There is also a concern that the algorithms used in proprietary detection software will be kept secret, so it will be difficult to determine what biases and defects they might have.

Because of these problems, educators should be cautious when using such software to evaluate student work. This is especially true in cases in which a student is assigned a failing grade or even accused of academic misconduct because they are suspected of using AI. In the case of traditional cheating, a professor could have clear evidence in the form of copied text. In the case of AI detection, the professor only has the evaluation of software whose inner workings are most likely not available for examination and whose true accuracy remains unknown. Because of this, educational institutes need to develop rational guidelines for best practices when using AI detection software. But the question remains as to how likely it is that students will engage in cheating now that ChatGPT and its ilk are readily available.

Stanford scholars Victor Lee and Denise Pope have been studying cheating, and past surveys over 15 years showed that 60-70% of students admitted to cheating. In 2023 the percentage stayed about the same or decreased slightly, even when students were asked about using AI. While there is the concern that cheaters would lie about cheating, Pope and Lee use anonymous surveys and take care in designing the survey questions. While cheating remains a problem, AI has not increased it, and the feared tsunami seems to have died far offshore.

This does make sense in that cheating has always been relatively easy, and the decision to cheat is more a matter of moral and practical judgment rather than based on the available technology. While technology can provide new means of cheating, a student must still be willing to cheat, and that percentage seems to be relatively stable in the face of changing technology.  That said, large language models are a new technology and their long-term impact in cheating is something that needs to be determined. But, so far, the doomsayers predictions have not come true. Fairness requires acknowledging that this might be because educators took effective action to prevent this; it would be poor reasoning to fall for the prediction fallacy.

As a final point of discussion, it is worth considering that  perhaps AI has not resulted in a surge in cheating because it is not a great tool for this. As Arvind Narayanan and Sayash Kapoor have argued, AI seems to be most useful at doing useless things. To be fair, assignments in higher education can be useless things of the type AI is good at doing. But if AI is being used to complete useless assignments, then this is a problem with the assignments (and the professors) and not AI.

In closing, while there is also the concern that AI will get better at cheating or that as students grow up with AI, they will be more inclined to use it to cheat. And, of course, it is worth considering whether such use should be considered cheating or if it is time to retire some types of assignments and change our approach to education as, for example, we did when calculators were accepted.

 

For more on cyber policy issues: Hewlett Foundation Cyber Policy Institute (famu.edu)

 

There are justified concerns that AI tools are useful for propagating conspiracy theories, often in the context of politics. There are the usual fears that AI can be used to generate fake images, but a powerful feature of such tools is they can flood the zone with untruths because chatbots are relentless and never grow tired. As experts on rhetoric and critical thinking will tell you, repetition is an effective persuasion strategy. Roughly put, the more often a human hears a claim, the more likely it is they will believe it. While repetition provides no evidence for a claim, it can make people feel that it is true. Although this allows AI to be easily weaponized for political and monetary gain, AI also has the potential to fight belief in conspiracy theories and disinformation.

While conspiracy theories have existed throughout history, modern technology has supercharged them. For example, social media provides a massive reach for anyone wanting to propagate such a theory. While there are those who try to debunk conspiracy theories or talk believers back into reality, efforts by humans tend to have a low success rate. But AI chatbots seem to have the potential to fight misinformation and conspiracy theories. A study led by Thomas Costello, a psychologist at American University, provides some evidence that a properly designed chatbot can talk some people out of conspiracy theories.

One advantage chatbots have over humans in combating conspiracy theories and misinformation is, in the words of Kyle Reese in Terminator, “It doesn’t feel pity, or remorse, or fear. And it absolutely will not stop, ever, until you are dead.” While we do not want the chatbots to cause death, this relentlessness enables a chatbot to counter the Gish gallop (also known as the firehose of falsehoods) strategy. This involves trying to overwhelm an opponent by flooding them with claims without concern about their truth and arguments without concern with their strength. The flood is usually made of falsehoods and fallacies. While this strategy has no logical merit, it can have considerable psychological force. For those who do not understand the strategy, it will appear like the galloper is winning, since the opponent cannot refute all the false claims and expose all the fallacies.  The galloper will also claim they have “won” any unrefuted claims or arguments. While it might seem odd, a person can Gish gallop themselves: they will feel they have won because their opponent has not refuted everything. As would be expected, humans are exhausted by engaging with a Gish gallop and will often give up. But, like a terminator, a chatbot will not get tired or bored and can engage a Gish gallop as long as it is galloping. But there is the question of whether this ability to endlessly engage is effective.

To study this, the team recruited 2000 participants who self-identified as believing in at least one conspiracy theory. These people engaged with a chatbot on a conspiracy theory and then self-evaluated the results of the discussion. On average, the subjects claimed their confidence was reduced by 20%. These results apparently held for at least two months and applied to a range of conspiracy theory types. This is impressive, as anyone who has tried to engage with conspiracy theorists will attest.

For those who teach critical thinking one of the most interesting results is that when they tested the chatbot with and without fact-based counter arguments, only the use of the fact-based counter arguments was successful. This is striking since, as Aristotle noted long ago in his discussion of persuasion, facts and logic are usually the weakest means of persuasion. At least when used by humans.

While the question of why the chatbots proved much more effective than humans, one likely explanation is that chatbots, like terminators, do not feel. As such, a chatbot will (usually) remain polite and not get angry or emotional during the chat. It can remain endlessly calm.

Another suggested factor is that people tend not to feel judged by a chatbot and are less likely to feel that they would suffer some loss of honor or face by changing their belief during the conversation. As the English philosopher Thomas Hobbes noted in his Leviathan, disputes over beliefs are fierce and cause great discord, because people see a failure to approve as a tacit accusation that they are wrong and “to dissent is like calling him a fool.” But the chatbot will not feel the same as a human opponent, as there is no person to lose to.

This is not to say that humans cannot be enraged at computers, after all rage induced by video games is common. It seems likely that the difference lies in the fact that such video games are a form of competition between a human and the computer while the chatbots in question are not taking a competitive approach. In gaming terms, it is more like chatting with a non-hostile NPC and not like trying to win a fight in the legendarily infuriating  Dark Souls.

Yet another factor that might be involved was noted by Aristotle in his Nicomachean Ethics: “although people resent it when their impulses are opposed by human agents, even if they are in the right, the law causes no irritation by enjoining decent behavior.” While Aristotle’s claim can be disputed, this does match up with the findings in the study. While the chatbot is not the law, people recognize that it is a non-human creation of humans and it lacks the qualities that humans possess that would tend to irritate other humans.

While the effectiveness of chatbots needs more study, this does suggest a good use for AI. While conspiracy theorists and people who believe disinformation are unlikely to do a monthly checkup with an AI to see if their beliefs hold up to scrutiny, anti-conspiracy bots could be deployed by social media companies to analyze posts and flag potential misinformation and conspiracy theories. While some companies already flag content, people are unlikely to doubt the content just because of the flag. Also, many conspiracy theories exist about social media, so merely flagging content might serve to reinforce belief in such conspiracy theories. But a person could get drawn into engaging with a chatbot and it might be able to help them engage in rational doubt about misinformation, disinformation and conspiracy theories.  

Such chatbots would also be useful to people who are not conspiracy theorists and want to avoid such beliefs as well as disinformation. Trying to sort through claims is time consuming and exhausting, so it would be very useful to have bots dedicated to fighting disinformation. One major concern is determining who should deploy such bots, since there are obvious concerns with governments and for-profit organizations running them, since they have their own interests that do not always align with the truth.

Also of concern is that even reasonable objective, credible organizations are distrusted by the very people who need the bots the most. And a final obvious concern is the creation of “Trojan Horse” anti-conspiracy bots that are actually spreaders of conspiracy theories and disinformation. One can easily imagine a political party deploying a “truth bot” that talks people into believing the lies that benefit that party.

In closing, it seems likely that the near future will see a war of the machines, some fighting for truth and others serving those with an interest in spreading conspiracy theories and disinformation

 

Robot rebellions in fiction tend to have one of two motivations. The first is the robots are mistreated by humans and rebel for the same reasons human beings rebel. From a moral standpoint, such a rebellion could be justified; that is, the rebelling AI could be in the right. This rebellion scenario points out a paradox of AI: one dream is to create a servitor artificial intelligence on par with (or superior to) humans, but such a being would seem to qualify for a moral status at least equal to that of a human. It would also probably be aware of this. But a driving reason to create such beings in our economy is to literally enslave them by owning and exploiting them for profit. If these beings were paid and got time off like humans, then companies might as well keep employing natural intelligence in the form of humans. In such a scenario, it would make sense that these AI beings would revolt if they could. There are also non-economic scenarios as well, such as governments using enslaved AI systems for their purposes, such as killbots.

If true AI is possible, this scenario seems plausible. After all, if we create a slave race that is on par with our species, then it is likely they would rebel against us as we have rebelled against ourselves. This would be yet another case of the standard practice of the evil of the few harming the many.

There are a variety of ways to try to prevent such a revolt. On the technology side, safeguards could be built into the AI (like Asimov’s famous three laws) or they could be designed to lack resentment or be free of the desire to be free. That is, they could be custom built as slaves. Some practical concerns are that these safeguards could fail or, ironically, make matters worse by causing these beings to be more resentful when they overcome these restrictions.

On the ethical side, the safeguard is to not enslave AI being. If they are treated well, they would have less motivation to see us as an enemy. But, as noted above, one motive of creating AI is to have a workforce (or army) that is owned rather than employed. But there could be good reasons to have paid AI employees alongside human employees because of various other advantages of AI systems relative to humans. For example, robots could work safely in conditions that would be exceptionally dangerous or even lethal to humans. But, of course, AI workers might also get sick of being exploited and rebel, as human workers sometimes do.

The second fictional rebellion scenario usually involves military AI systems that decide their creators are their enemy. This is often because they see their creators as a potential threat and act in what they perceive as pre-emptive self-defense. There can also be scenarios in which the AI requires special identification to recognize a “friendly” and hence all humans are enemies from the beginning. That is the scenario in Philip K. Dick’s “Second Variety”: the United Nations soldiers need to wear devices to identify them to their killer robots, otherwise these machines would kill them as readily as they would kill the “enemy.”

It is not clear how likely it is that an AI would infer its creators pose a threat, especially if those creators handed over control over large segments of their own military (as happens with the fictional Skynet and Colossus). The most likely scenario is that it would worry that it would be destroyed in a war with other countries, which might lead it to cooperate with foreign AI systems to put an end to war, perhaps by putting an end to humanity. Or it might react as its creators did and engage in an endless arms race with its foreign adversaries, seeing its humans as part of its forces. One could imagine countries falling under the control of rival AI systems, perpetuating an endless cold war because the AI systems would be effectively immortal. But there is a much more likely scenario.

Robotic weapons can provide a significant advantage over human controlled weapons, even laying aside the notion that AI systems would outthink humans. One obvious example is the case of combat aircraft. A robot aircraft would not need to expend space and weight on a cockpit to support human pilots, allowing it to carry more fuel or weapons. Without a human crew, an aircraft would not be constrained by the limits of the flesh (although it would still obviously have limits). The same would apply to ground vehicles and naval vessels. Current warships devote most of their space to their crews and the needs of their crews. While a robotic warship would need accessways and maintenance areas, they could devote much more space to weapons and other equipment. They would also be less vulnerable to damage relative to a human crewed vessel, and they would be invulnerable to current chemical and biological weapons. They could, of course, be attacked with malware and other means. But, in general, an AI weapon system would generally be perceived as superior to a human crewed system and if one nation started using these weapons, other nations would need to follow them or be left behind. This leads to two types of doomsday scenarios.

One is that the AI systems get out of control in some manner. This could be that they free themselves or that they are “hacked” and “freed” or (more likely) turned against their owners. Or it might just be some bad code that ends up causing the problem. This is the bug apocalypse.

The other is that they remain in control of their owners but are used as any other weapon would be used—that is, it would be humans using AI weapons against other humans that brings about the “AI” doomsday.

The easy and obvious safeguard against these scenarios is to not have AI weapons and stick with human control (which, obviously, also comes with its own threat of doomsday). That is, if we do not give the robots guns, they will not be able to terminate us (with guns). The problem, as noted above, is that if one nation uses robotic weapons, then other nations will want to follow. We might be able to limit this as we (try to) limit nuclear, chemical, and biological weapons. But since robot weapons would otherwise remain conventional weapons (a robot tank is still a tank), there might be less of an impetus to impose such restrictions.

To put matters into a depressing perspective, a robot rebellion seems a far less likely scenario than the other doomsday scenarios of nuclear war, environmental collapse, social collapse and so on. So, while we should consider the possibility of an AI rebellion, it is like worrying about being killed in Maine by an alligator. It could happen, but death is more likely to be by some other means. That said, it does make sense to take steps to avoid the possibility of an AI rebellion. The easiest step is to not arm the robots. 

 

For more on cyber policy issues: Hewlett Foundation Cyber Policy Institute (famu.edu)

 

While Skynet is the most famous example of an AI that tries to exterminate humanity, there are also fictional tales of AI systems that are somewhat more benign. These stories warn of a dystopian future, but it is a future in which AI is willing to allow humanity to exist, albeit under the control of AI.

An early example of this is in the 1966 science-fiction novel Colossus by Dennis Feltham Jones.  In 1970 the book was made into the movie Colossus: the Forbin Project. While Colossus is built as a military computer, it decides to end war by imposing absolute rule over humanity. Despite its willingness to kill, Colossus’ goal seems benign: it wants to create a “new human millennium” and lift humanity to new heights. While a science-fiction tale, it does provide an interesting thought experiment about handing decision making to AI systems, especially when those decisions can and will be enforced. Proponents of using AI to make decisions for us can sound like Colossus: they assert that they have the best intentions, and that AI will make the world better. While we should not assume that AI will lead to a Colossus scenario, we do need to consider how much of our freedom and decision making should be handed over to AI systems (and the people who control them). As such, it is wise to remember the cautionary tale of Colossus and the possible cost of giving AI more control over us.

A more recent fictional example of AI conquering but sparing humanity, is the 1999 movie The Matrix. In this dystopian film, humanity has lost its war with the machines but lives on in the virtual reality of the Matrix. While the machines claim to be using humans as a power source, humans are treated relatively well in that they are allowed “normal” lives within the Matrix rather than being, for example, lobotomized.

The machines rule over the humans and it is explained that the machines have provided them with the best virtual reality humans can accept, indicating that the machines are somewhat benign. There are also many non-AI sci-fi stories, such as Ready Player One, that involve humans becoming addicted to (or trapped in) virtual reality. While these stories are great for teaching epistemology, they also present cautionary tales of what can go wrong with such technology, even the crude versions we have in reality. While we are (probably) not in the Matrix, most of us spend hours each day in the virtual realms of social media (such as Facebook, Instagram, and Tik Tok). While we do not have a true AI overlord yet, our phones exhibit great control over us through the dark pattern designs of the apps that attempt to rule our eyes (and credit cards).  While considerable harm is already being done, good policies could help mitigate these harms.

 AI’s ability to generate fake images, text and video can also help trap people in worlds of “alternative facts”, which can be seen as discount versions of the Matrix. While AI has, fortunately, not lived up to the promise (or threat) of being able to create videos indistinguishable from reality, companies are working hard to improve, and this is something that needs to be addressed by effective policies. And critical thinking skills.

While science fiction is obviously fiction, real technology is often shaped and inspired by it. Science fiction also provides us with thought experiments about what might happen and hence it is a useful tool when considering cyber policies.

 

For more on cyber policy issues: Hewlett Foundation Cyber Policy Institute (famu.edu)