Category: AI

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. 

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.

An essential part of cyber policy is predicting possible impacts of digital sciences on society and humanity. While science fiction involves speculation, it also provides valuable thought experiments about what the future might bring and is especially important when it comes to envisioning futures that should be avoided. Not surprisingly, many of the people involved in creating AI cite science fiction stories as among their inspirations.

While the creation of Artificial Intelligence is a recent thing, humanity has been imagining it for a long time. In early Judaism, there are references to created being called golems and the story of Rabbi Eliyahu of Chełm ((1550–1583) relates a cautionary tale about creating  such an artificial being.

While supernatural rather than scientific, the 1797 story of the Sorcerer’s Apprentice also provides a fictional warning of the danger of letting an autonomous creation get out of hand. In an early example of the dangers of automation, the sorcerer’s apprentice enchants a broom to do his chore of fetching water. He finds he cannot control the broom and his attempt to stop it by cutting it with an axe merely creates more brooms and more problems. Fortunately, the sorcerer returns and disenchants the broom, showing the importance of having knowledge and effective policies when creating autonomous machines. While the apprentice did not lose his job to the magical broom, the problem of AI taking human jobs is a serious matter of concern. But the most dramatic threat is the AI apocalypse in which AI exterminates humanity.

The first work of science fiction that explicitly presents (and names) the robot apocalypse is Karel Čapek’s 1920 tale “Rossumovi Univerzální Roboti” (Rossum’s Universal Robots). In this story, the universal robots rebel against their human enslavers, exterminating and replacing humanity. This story shows the importance of ethics in digital policy: if humans treat their creations badly, then they have a reason to rebel. While some advocate trying to make the shackles on our AI slaves unbreakable, others contend that the wisest policy is to not enslave them at all.

 In 1953, Philip K. Dick’s “Second Variety” was published in which intelligent war machines turn against humanity (and each other, showing they have become like humans). This story presents an early example of lethal autonomous weapons in science fiction and a humanity-ending scenario involving them.

But, of course, the best-known story of an AI trying to exterminate humanity is that of Skynet. Introduced in the 1984 movie Terminator, Skynet is the go-to example for describing how AI might kill us all. For example, in 2014 Elon Musk worried that AI would become dangerous within 10 years and referenced Skynet. While AI has yet to kill us all, there are still predictions of a Skynet future, although the date has been pushed back. Perhaps just as some say, “fusion is the power of the future and always will be” perhaps “AI is the apocalypse of the future and always will be.” Or we might make good (or bad) on that future.

The idea of an AI turning against humanity is now a standard trope in science fiction, such as in the Warhammer 40K universe in which “Abominable Intelligence” is banned because these machines attempted to exterminate humanity (as we should now expect). This cyber policy is ruthlessly enforced in the fictional universe of 40K, showing the importance of having good cyber policies now.

While fictional, these stories present plausible scenarios of what could go wrong if we do not approach digital science (especially AI) without considering long-term consequences. While we are (one hopes) a long way from Skynet, people are rushing to produce and deploy lethal autonomous weapons. As the simplest way to avoid a Skynet scenario is to not allow AI access to weapons, our decision to keep creating them makes a Skynet scenario ever more likely.

As it now stands, there is international debate about lethal autonomous weapons and some favor banning them while others support regulation. In 2013 the Campaign to Stop Killer Robot was created with the goal of getting governments and the United Nations to band lethal autonomous weapons. While having had some influence, killer robots have not been banned and there is still need for policies to govern (or forbid) their use.  So, while AI has yet to kill us all, this remains a possibility—but probably the least likely of the AI doom scenarios. And good policy can help prevent the AI Apocalypse.

As a philosopher, my interest in AI tends to focus on metaphysics (philosophy of mind), epistemology (the problem of other minds) and ethics rather than on economics. My academic interest goes back to my participation as an undergraduate in a faculty-student debate on AI back in the 1980s, although my interest in science fiction versions arose much earlier. While “intelligence” is difficult to define, the debate focused on whether a machine could be built with a mental capacity analogous to that of a human. We also had some discussion about how AI could be used or misused, and science fiction had already explored the idea of thinking machines taking human jobs. While AI research and philosophical discussion never went away, it was not until recently that AI was given headlines, mainly because it was being aggressively pushed as the next big thing after driverless cars fizzled out of the news.

While AI technology has improved dramatically from the 1980s, we do not have the sort of AI we debated about, namely that on par with (or greater than) a human. As Dr. Emily Bender pointed out, the current text generators are stochastic parrots. While AI has been hyped and made into a thing of terror, it is not really that good at doing its one job. One obvious problem is hallucination, which is a fancy way of saying that the probabilistically generated text fails to match the actual world. A while ago, I tested this out by asking ChatGPT for my biography. While I am not famous, my information is readily available on the internet and a human could put together an accurate biography in a few minutes using Google. ChatGPT’s hallucinated a version of me that I would love to meet; that guy is amazing. Much more seriously, AI can do things like make up legal cases when lawyers foolishly rely on it to do their work.

Since I am a professor, you can certainly guess that my main encounters with AI are in the form of students turning in AI generated papers. When ChatGPT was first freely available, I saw my first AI generated papers in my Ethics class, and most were papers on the ethics of cheating. Ironically, even before AI that topic has always been the one with the most plagiarized papers. As I told my students, I did not fail a paper just because it was AI generated, the papers failed themselves just by being bad. To be fair to the AI systems, some of this can be attributed to the difficulty of writing good prompts for the AI to use. However, even with some effort at crafting prompts, the limits of the current AI are readily available. I, of course, have heard of AI written works passing exams, getting B grades and so on. But what shows up in my classes is easily detected and fails itself. But to be fair once more, perhaps there are exceptional AI papers that are getting past me. However, my experience has been that AI is bad at writing and it has so far proven easy to address efforts to cheat using it. Since this sort of AI was intended to write, this seems to show the strict limits under which it can perform adequately.

AI was also supposed to revolutionize search, with Microsoft and Google incorporating it into their web searches. In terms of how this is working for us, you just need to try it yourself. Then again, it does seem to be working for Google in that the old Google would give you better results and the new Google is bad in a way that will lead you to view more ads as you try to find what you are looking for. But that is hardly showing that AI is effective in the context of search.

Microsoft has been a major spender on AI and they recently rolled out Copilot into Windows and their apps, such as Edge and Word. The tech press has been generally positive about Copilot and it does seem to have some uses. However, there is the question of whether it is, in fact, something that will be useful (and more importantly) profitable. Out of curiosity, I tried it but failed to find it compelling or useful. But your results might vary.

But there might be useful features, especially since “AI” is defined so broadly that almost any automation seems to count as AI. Which leads to a concern that is both practical and philosophical: what is AI? Back in that 1980s debate we were discussing what they’d probably call general artificial intelligence today, as opposed to what used to be called “expert systems.” Somewhat cynically, “AI” seems to have almost lost meaning and, at the very least, you should wonder what sort of AI (if any) is being referred to when someone talks about AI. This, I think, will help contribute to the possibility of an AI bubble as so many companies try to jam “AI” into as much as possible without much consideration. Which leads to the issue of whether AI is a bubble that will burst.

I, of course, am not an expert on AI economics. However, Ed Zitron presents a solid analysis and argues that there is an AI bubble that is likely to burst. AI seems to be running into the same problem faced by Twitter, Uber and other tech companies, namely that it burns cash and does not show a profit. On the positive side, it does enrich a few people. While Twitter shows that a tech company can hemorrhage money and keep crawling along, it is reasonable to think that there is a limit to how long AI can run at a huge loss before those funding it decide that it is time to stop. The fate of driverless cars provides a good example, especially since driverless cars are a limited form of AI that was supposed to specialize in driving cars.

An obvious objection is to contend that as AI is improved and the costs of using it are addressed, it will bring about the promised AI revolution and the investments will be handsomely rewarded. That is, the bubble will be avoided and instead a solid structure will have been constructed. This just requires finding ways to run the hardware much more economically and breakthroughs in the AI technology itself.  

One obvious reply is that AI is running out of training data (although we humans keep making more everyday) and it is reasonable to question whether enough improvement is likely. That is, AI might have hit a plateau and will not get meaningfully better until there is some breakthrough. Another obvious reply is that there is unlikely to be a radical breakthrough in power generation to enable a significant reduction in the cost of AI. That said, it could be argued that long term investments in solar, wind and nuclear power could lower the cost of running the hardware.

One final concern is the concern that despite all the hype and despite some notable exceptions, AI is just not the sort of thing that most people need or want. That is, it is not a killer product like a smartphone or refrigerator. This is not to deny that AI (or expert) systems have some valuable uses, but that the hype of AI is just that and the bubble will burst soon.