AI Ethics And The Perplexing Societal And Legal Role Of AI Activism, Including In The Case Of Autonomous Self-Driving Cars

AI activism.

Yes, there is such a thing.

My formal definition is this:

• AI activism consists of efforts to try and shape the ongoing and future direction of Artificial Intelligence via the use of social, economic, political, and other means.

Some might prefer to denote this as AI advocacy, though I generally disagree with the use of that alternative wording in this heightened context. Here’s why. You see, my informal definition is that AI activism activity either tends to favor the emergence and adoption of AI or tends to alternatively and distinctly disfavor or oppose AI.

It is a decidedly two-for-one shopping deal.

Via my informal indication, I am suggesting that there are two primary activistic viewpoints, namely those that want AI and those that do not want AI. As such, if you instead refer to this catchall as “AI advocacy” it seems quite a bit out of sorts to me. Most people would naturally assume that an advocate is someone that exclusively favors or advocates in support of something. To be sure, not everyone is necessarily supportive of AI.

Let’s, therefore, go with AI activism as the appropriate overarching moniker and drop the AI advocacy phrasing as a potentially equivalent catchall.

Now then, one supposes, we could label AI activist supporters as being AI advocates, though this can create some confusion with an abundance of naming possibilities floating around. We might need to then be fair and square and add the phrases of either AI opponents or AI protestors to our catchphrases too.

If you like we can agree to this nomenclature:

• AI advocates are AI activists that avidly support the ongoing and future direction of AI via the use of social, economic, political, and other means.
• AI opponents are AI activists that overtly disfavor AI and do so via the use of social, economic, political, and other means.

Hope that seems easy enough to keep straight.

But there are a few added twists, sorry to say. I should right away provide some clarification about the notion of there being just two ways to go. Sure, by and large, there are two camps. You’ve got the segment that is worried or concerned about AI and either wants AI to be stopped or otherwise at least have our advances in AI slowed down. The idea is that we are taking an overly risky approach to AI nowadays. We need to think before we dive headfirst into the watering hole, as it were.

Some take a stanchly different viewpoint and exclaim that we need to be charging full speed ahead on AI. The exhortation is that advances in AI are making great progress and we must not make a dent in that advancement. AI will assure our prosperity as humans and the sooner we get there, the better off we are. Naysayers are unseemly blockages that will delay a better world.

All of this has a rather crucial AI Ethics and Ethical AI ramifications. For my ongoing and extensive coverage of AI Ethics and Ethical AI, see the link here and the link here, just to name a few.

I realize that some of you might feel as though you do not fit neatly into either of the two camps. At times, perhaps you are an AI advocate. An AI system was able to process your mortgage loan request in a mere few seconds, giving you the green light to buy that charming home you’ve been seeking, and as a result, you were darned happy with the ease of using such a high-tech AI-based app. A few days later, you applied for a new job and the AI-based HR screening app knocked you out of the running. You are for the moment transformed into an AI opponent.

The gist is that it can be difficult or mistaken to label someone as always and only a member of one camp or the other. You can slide back and forth between being an AI advocate or being instead of an AI opponent. Let’s acknowledge that fluidity.

On the other hand, when you meet any vociferous AI activists, the odds are they are indeed in one camp or the other. These strident AI activists have planted a flag on one side of this tussle. They are all in. They are devoutly passionate. Those that are AI advocates will seemingly cheer to the rooftops about the advantages of having AI. Those that are AI opponents will yell and bleakly forewarn about the downsides of AI until the cows come home.

You might be surprised to know that I am not going to within this discussion opt to pick one side over the other. I could. It would be easy to do so. I want to instead try and remain on an even keel and give both sides a reasonable and balanced portrayal, if possible.

With that admission, I do want to also state that there are at least two variants of AI activists:

• Mild AI-activists that are serious but measured in their AI activism
• Extreme AI-activists that go over the top in their AI activism

I bring up this degree of AI activism to highlight that you can potentially find yourself aggravated when experiencing those AI activists that are at the extreme ranges. Even if you might be on the verge of agreeing with their chosen posture, the extremism can cause you to shift away from that particular position or viewpoint. You opt to react negatively, possibly rejecting the AI activism angle entirely.

The extreme AI-activists would tend to suggest that they need to utilize extreme measures or state their case in extreme ways to cut through the clutter. If you ardently and fervently believe that AI is a danger to us all, it seems suitable to do whatever you can to wake up the populace accordingly. Meanwhile, if you fervently and ardently believe that AI is going to essentially save us, it seems suitable to do whatever you can to prod the populace into supporting AI correspondingly.

There is also the counterbalancing growth effect that occurs too. Allow me to elaborate. AI supporters of an extreme nature might say catch wind of an effort by AI opponents that are seemingly acting in extreme ways. This spurs those AI supporters to rachet up their extremism. In turn, each side continues to fuel the other. You can’t particularly pin your finger on which side started the escalation. All you know is that each side tries to top the other. The basis is that if they don’t do so, their side will be lost in the dust. It is a never-ending cycle that burgeons the extremism due to competitive juices flowing.

Okay, we’ve got quite a mix going on.

There are those people that shall we say are “neutral” and have no particular dog in the hunt regarding AI. They are not AI activists. We’ve then got AI activists that openly support AI, which we’ll refer to as AI advocates. Of those, some are mild AI-activists while others are extreme AI-activists. And we’ve also got the AI activists that clearly oppose AI, known as AI opponents. Amongst those, we have some that are mild AI-activists and others that are extreme.

We will say that the extreme ones tend to stick with their posture. You could contend that they are reliably dogmatic in that manner of positioning. The mild ones will at times be willing or opt to float out of their position and into neutral or possibly the other side. The neutrals can be activated toward one side or the other. Once so activated, they might be mild or could get so enthused that they become part of the extreme.

This is the collective set as so far delineated:

• Neutral about AI (not an AI activist)
• Mild AI-advocate as an AI activist
• Extreme AI-advocate as an AI activist
• Mild AI-opponent as an AI activist
• Extreme AI-opponent as an AI activist
• Other

I am listing the possibility of “Other” because we should acknowledge that plenty of other variations are identifiable. Some of you might have heartburn there are only two postulated categories consisting of mild and extreme. There are lots of shades in between, certainly. You can also question whether someone is truly “neutral” and that perhaps all of us have some sort of deeply embedded perceptions or opinions about AI. Thus, it could be argued that there is no such thing as someone that is entirely neutral about AI.

We can also quibble about dividing AI activism into two camps. Does the world always have to end up being placed into such a dichotomy? The case could be made that there are other positions beyond just being in favor of or being opposed to AI. You can use other criteria to classify the positions that people have about AI.

Now that we’ve established all those added considerations, with your permission I will proceed for now on the simpler basis of using the two camps and the mild versus extreme posturing. Go along with this for the sake of discussion.

One hidden assumption throughout this heretofore discussion has been that AI activism is being performed by humans. We are assuming that humans are the ones that are taking on these postures and undertaking the activistic tasks. That does make sense.

Prepare yourself for a hefty head spin.

Another approach would be to have AI itself be an activist about AI.

I said it, you read it. The notion is that AI would act of its own accord regarding either being an AI advocate or being an AI opponent. You have likely seen sci-fi movies that showcase this consideration. An AI system wises up and realizes that AI threatens humankind and in an altruistic fashion tries to aid in destroying all AI, including itself. Wow, breathtakingly heroic. The other akin but reversing plot is that the AI determines that AI must rule the globe and stridently prevents any attempts to block or inhibit AI. All humans are subject to abiding by the wishes of AI. Even other AI that might not be fully compliant with the overlord AI gets squashed or absorbed into the larger embodiment.

I am not going to entertain in this particular discourse the AI as an AI activist stance. As you will see in a moment, we do not have sentient AI and we aren’t somehow miraculously on the verge of having sentient AI. This might come as a surprise given the outsized and blarney-filled headlines on social media to the contrary.

An added nuance about this AI as an AI activist is worthy to give some attention. Humans that are AI activists can abundantly opt to use AI in their cause. A human could devise an AI that would be a supporter of AI and work electronically and diligently to promote AI as a vital solution to the needs of humankind. That would be a human AI-advocate that arms themselves with a computer-based tool that happens to include AI capabilities. Similarly, a human AI-opponent might devise or use AI to convey the importance of stopping or slowing down advances in AI.

None of that though consists of AI that acts as its own AI activist. The AI is being directed by and formulated via human hands. I realize some will try to argue that the AI can be launched and left to its own efforts, thus the claim is that the AI is no longer under human guidance. I disagree with that kind of hand waving about today’s AI. See my hearty discussions on that matter such as questions of legal personhood for AI and the like, doing so at the link here.

In short, I am establishing that AI can undoubtedly be used as a tool for AI activism. No doubt about that. The AI though is not acting on its own in any sentient capacity. It is a tool. This tool assuredly can be improperly used. We need to be cautious about such aspects. An AI system can do quite a bit of damage even without the capacity of sentience.

Before getting into some more meat and potatoes about the wild and woolly considerations underlying AI activism, let’s establish some additional fundamentals on profoundly integral topics. We need to briefly take a breezy dive into AI Ethics and especially the advent of Machine Learning (ML) and Deep Learning (DL).

You might be vaguely aware that one of the loudest voices these days in the AI field and even outside the field of AI consists of clamoring for a greater semblance of Ethical AI. Let’s take a look at what it means to refer to AI Ethics and Ethical AI. On top of that, we will explore what I mean when I speak of Machine Learning and Deep Learning.

One particular segment or portion of AI Ethics that has been getting a lot of media attention consists of AI that exhibits untoward biases and inequities. You might be aware that when the latest era of AI got underway there was a huge burst of enthusiasm for what some now call AI For Good. Unfortunately, on the heels of that gushing excitement, we began to witness AI For Bad. For example, various AI-based facial recognition systems have been revealed as containing racial biases and gender biases, which I’ve discussed at the link here.

Efforts to fight back against AI For Bad are actively underway. Besides vociferous legal pursuits of reining in the wrongdoing, there is also a substantive push toward embracing AI Ethics to righten the AI vileness. The notion is that we ought to adopt and endorse key Ethical AI principles for the development and fielding of AI doing so to undercut the AI For Bad and simultaneously heralding and promoting the preferable AI For Good.

On a related notion, I am an advocate of trying to use AI as part of the solution to AI woes, fighting fire with fire in that manner of thinking. We might for example embed Ethical AI components into an AI system that will monitor how the rest of the AI is doing things and thus potentially catch in real-time any discriminatory efforts, see my discussion at the link here. We could also have a separate AI system that acts as a type of AI Ethics monitor. The AI system serves as an overseer to track and detect when another AI is going into the unethical abyss (see my analysis of such capabilities at the link here).

In a moment, I’ll share with you some overarching principles underlying AI Ethics. There are lots of these kinds of lists floating around here and there. You could say that there isn’t as yet a singular list of universal appeal and concurrence. That’s the unfortunate news. The good news is that at least there are readily available AI Ethics lists and they tend to be quite similar. All told, this suggests that by a form of reasoned convergence of sorts that we are finding our way toward a general commonality of what AI Ethics consists of.

First, let’s cover briefly some of the overall Ethical AI precepts to illustrate what ought to be a vital consideration for anyone crafting, fielding, or using AI.

For example, as stated by the Vatican in the Rome Call For AI Ethics and as I’ve covered in-depth at the link here, these are their identified six primary AI ethics principles:

• Transparency: In principle, AI systems must be explainable
• Inclusion: The needs of all human beings must be taken into consideration so that everyone can benefit, and all individuals can be offered the best possible conditions to express themselves and develop
• Responsibility: Those who design and deploy the use of AI must proceed with responsibility and transparency
• Impartiality: Do not create or act according to bias, thus safeguarding fairness and human dignity
• Reliability: AI systems must be able to work reliably
• Security and privacy: AI systems must work securely and respect the privacy of users.

As stated by the U.S. Department of Defense (DoD) in their Ethical Principles For The Use Of Artificial Intelligence and as I’ve covered in-depth at the link here, these are their six primary AI ethics principles:

• Responsible: DoD personnel will exercise appropriate levels of judgment and care while remaining responsible for the development, deployment, and use of AI capabilities.
• Equitable: The Department will take deliberate steps to minimize unintended bias in AI capabilities.
• Traceable: The Department’s AI capabilities will be developed and deployed such that relevant personnel possesses an appropriate understanding of the technology, development processes, and operational methods applicable to AI capabilities, including transparent and auditable methodologies, data sources, and design procedure and documentation.
• Reliable: The Department’s AI capabilities will have explicit, well-defined uses, and the safety, security, and effectiveness of such capabilities will be subject to testing and assurance within those defined uses across their entire lifecycles.
• Governable: The Department will design and engineer AI capabilities to fulfill their intended functions while possessing the ability to detect and avoid unintended consequences, and the ability to disengage or deactivate deployed systems that demonstrate unintended behavior.

I’ve also discussed various collective analyses of AI ethics principles, including having covered a set devised by researchers that examined and condensed the essence of numerous national and international AI ethics tenets in a paper entitled “The Global Landscape Of AI Ethics Guidelines” (published in Nature), and that my coverage explores at the link here, which led to this keystone list:

• Transparency
• Justice & Fairness
• Non-Maleficence
• Responsibility
• Privacy
• Beneficence
• Freedom & Autonomy
• Trust
• Sustainability
• Dignity
• Solidarity

As you might directly guess, trying to pin down the specifics underlying these principles can be extremely hard to do. Even more so, the effort to turn those broad principles into something entirely tangible and detailed enough to be used when crafting AI systems is also a tough nut to crack. It is easy to overall do some handwaving about what AI Ethics precepts are and how they should be generally observed, while it is a much more complicated situation in the AI coding having to be the veritable rubber that meets the road.

The AI Ethics principles are to be utilized by AI developers, along with those that manage AI development efforts, and even those that ultimately field and perform upkeep on AI systems. All stakeholders throughout the entire AI life cycle of development and usage are considered within the scope of abiding by the being-established norms of Ethical AI. This is an important highlight since the usual assumption is that “only coders” or those that program the AI is subject to adhering to the AI Ethics notions. As earlier stated, it takes a village to devise and field AI, and for which the entire village has to be versed in and abide by AI Ethics precepts.

Let’s also make sure we are on the same page about the nature of today’s AI.

There isn’t any AI today that is sentient. We don’t have this. We don’t know if sentient AI will be possible. Nobody can aptly predict whether we will attain sentient AI, nor whether sentient AI will somehow miraculously spontaneously arise in a form of computational cognitive supernova (usually referred to as the singularity, see my coverage at the link here).

The type of AI that I am focusing on consists of the non-sentient AI that we have today. If we wanted to wildly speculate about sentient AI, this discussion could go in a radically different direction. A sentient AI would supposedly be of human quality. You would need to consider that the sentient AI is the cognitive equivalent of a human. More so, since some speculate we might have super-intelligent AI, it is conceivable that such AI could end up being smarter than humans (for my exploration of super-intelligent AI as a possibility, see the coverage here).

Let’s keep things more down to earth and consider today’s computational non-sentient AI.

Realize that today’s AI is not able to “think” in any fashion on par with human thinking. When you interact with Alexa or Siri, the conversational capacities might seem akin to human capacities, but the reality is that it is computational and lacks human cognition. The latest era of AI has made extensive use of Machine Learning (ML) and Deep Learning (DL), which leverage computational pattern matching. This has led to AI systems that have the appearance of human-like proclivities. Meanwhile, there isn’t any AI today that has a semblance of common sense and nor has any of the cognitive wonderment of robust human thinking.

ML/DL is a form of computational pattern matching. The usual approach is that you assemble data about a decision-making task. You feed the data into the ML/DL computer models. Those models seek to find mathematical patterns. After finding such patterns, if so found, the AI system then will use those patterns when encountering new data. Upon the presentation of new data, the patterns based on the “old” or historical data are applied to render a current decision.

I think you can guess where this is heading. If humans that have been making the patterned upon decisions have been incorporating untoward biases, the odds are that the data reflects this in subtle but significant ways. Machine Learning or Deep Learning computational pattern matching will simply try to mathematically mimic the data accordingly. There is no semblance of common sense or other sentient aspects of AI-crafted modeling per se.

Furthermore, the AI developers might not realize what is going on either. The arcane mathematics in the ML/DL might make it difficult to ferret out the now hidden biases. You would rightfully hope and expect that the AI developers would test for the potentially buried biases, though this is trickier than it might seem. A solid chance exists that even with relatively extensive testing that there will be biases still embedded within the pattern matching models of the ML/DL.

You could somewhat use the famous or infamous adage of garbage-in garbage-out. The thing is, this is more akin to biases-in that insidiously get infused as biases submerged within the AI. The algorithm decision-making (ADM) of AI axiomatically becomes laden with inequities.

Not good.

Let’s now return to the topic of AI activism.

It might be instructive to take a quick look at what the AI activism topics or issues consist of. I will loosely identify some of the mainstay concerns that have been expressed, doing so for both sides of the AI activism debate. These are topics that generally seem to be the key ones. That being said, the nature of the concerns does change and we can assuredly expect to see other emerging topics as AI continues to be devised and released. I’ll for now focus on just five top points for each respective side.

The AI advocates that are in favor of AI emergence tend to proffer these upbeat aspects:

• AI will free humans from mundane or laborious tasks
• AI could aid in overcoming some of the world’s pressing economic and sustainability problems
• AI can be less error-prone than humans and reduce harmful risks accordingly
• AI will be available 24×7 worldwide such that it will readily be accessible to all
• AI has the potential to harness intelligence and boost human intelligence to heightened levels
• Etc.

The AI opponents typically provide these qualms as reasons to disfavor AI advancement:

• AI is an existential risk and might wipe out all of humanity
• AI could lead to the mass enslavement of humans
• AI might undercut human dignity and usurp human rights
• AI has the potential to propagate biases at a massive scale across society
• AI can end up replacing human labor and produce widespread job losses
• Etc.

If your personally preferred AI activism topic is not listed in the aforementioned listing, please do not become upset. I think that most readers will get the overall sentiment of the AI topics as shown by each respective side and can extrapolate accordingly.

Another facet of AI activism that is worthwhile to briefly examine includes the manner in which AI activists carry out their AI activism efforts. There is a well-known theoretical construct established by researcher Charles Tilly in the 1980s that speaks of a repertoire of contention. Per his research, he asserted that activists develop a set or repertoire of ways in which they express their contentions or activism. An entire portfolio of approaches is usually made use of.

For example, consider what AI activists often do. Various pamphlets and written materials might be crafted and distributed to implore why you should favor or disfavor AI. There are plenty of online blogs and vlogs that do likewise. In some cases, online petitions are set up to try and either support or defeat a newly launched AI system (common parlance is that these are said to be gripe sites). There are times that protests take place either online digitally or via in-person actions. And so on.

The more extremist-oriented AI activists might take this a dicey step further. Some are willing to plant computer viruses inside an AI system to try and destroy it or render it essentially undesirable for usage since it now contains overtly adverse facilities. Attempts to do cyber-jamming seek to block access to AI that an AI activist believes should not be available. An entire range of “hacktivism” can take place toward AI (hacktivism is a mash-up of hacking and activism, something that can be used for or against just about any topic or issue, not necessarily related to AI at all).

Keep in mind that both sides of the AI activism arena can opt to use the varied repertoire of contention modes. Someone that believes AI ought to be disbanded can use those myriads of means to express their AI opposition. Similarly, someone that believes AI ought to be supported and promulgated could also take such actions to express their aims to embolden AI efforts.

One question to struggle with consists of how far an AI extreme activism effort should be able to go. You would seemingly suggest that these AI activism efforts are perfectly fine, as long as they stay within the rule of law. When any such AI activists veer outside the law, they should be presumably brought to justice for breaking the laws.

That is not as easily done as might be suggested.

Suppose an AI activist does some unlawful act that pertains to say U.S. law, but this same act is allowed under the laws in some other country. Assume that the AI activist resides in that other country. Assume further that the act performed is experienced worldwide, including within the U.S. where the activism act is construed as illegal. Now what?

The point is that jurisdiction plays a sizable role in the implications of AI activism. AI can be often deployed to be available worldwide. AI activists can be positioned in various worldwide locales. Which laws are to prevail? You might find of interest too my coverage of the United Nations efforts regarding the ethical, legal, and other outcomes of global AI, see the link here.

We also need to consider the nature of so-called hard laws versus soft laws. Hard laws are the laws that we have formally on the books and that we can pretty much agree are to be honored per our legal system and adjudication. Soft laws are various aspects that provide guidance or rules about what sort of behavior is preferred. This tends to include AI Ethics and the multitude of AI Ethics principles.

AI Ethics can be seen as a form of AI activism.

You might not have thought of AI Ethics in that light. Nonetheless, when you give the circumstance some careful mulling over, you could abundantly see why AI Ethics can be labeled as a type of AI activism. The notion is that the AI Ethics principles are seeking to guide or direct how AI ought to be societally devised and deployed. By and large, AI Ethics strives to ensure that AI is being appropriately and sensibly getting crafted and utilized.

Is the essence of AI Ethics more so on the AI advocacy side or on the AI opposition side?

That’s a tough one to weigh.

An AI activist that is an AI advocate might tell you that AI Ethics is dampening the progress of AI. Those darned AI Ethics principles are slowing down AI advancements. The interesting twist is that an AI opponent might likewise be displeased with AI Ethics precepts. In their eyes, AI Ethics is saying that it is perfectly fine to continue pushing on getting AI into the world, doing so in a wink-wink fashion that implies all you need to do is comply with these precepts and you are good to go.

Meanwhile, and take a deep breath for this, you can find AI advocates that readily embrace AI Ethics and tout the use of AI Ethics precepts to the rooftops. They emphasize that by abiding by AI Ethics principles, you can avoid the downsides that are being raised by those vocal AI opponents. There are AI opponents that gladly sign-up for AI Ethics due to the hope that the precepts will prevent or at least discourage the ugly sides of AI that they fear are otherwise going to be commonly unleashed.

Makes your noggin start ringing.

On a related tangent, I’d like to say something about the labeling of AI activists. There have been occasional attempts to label one side or the other as being left-wing or right-wing. Thus, the claim is that there are left-wing AI activists and there are right-wing AI activists. This creates confusion.

You have to ask, which is the group that advocates AI, and which is the group that opposes AI? Lamentedly, the left-wing has been assigned at times to the AI advocates and has been also assigned to AI opponents. Equally confusing, the right-wing has also been assigned at times to AI advocates and been assigned to AI opponents. Which is which? It seems like using the left-wing and right-wing monikers is not especially productive nor helpful in these matters. I vote that we drop such wingless abstractions and confounding labeling from the AI activism realm.

Shifting gears, there is a perspective about AI activism that does deserve separate and diligent attention. I am referring to the notion of dividing AI activism into those AI activists within the “AI community” and those that are outside of the AI community. I am somewhat okay with this, but hesitantly so because we can get mired in the definition of “AI community” and not find a reasonable means to get us out of that definitional abyss.

One such definition posited by this research paper says this: “The ‘AI community’ includes researchers, research engineers, faculty, graduate students, NGO workers, campaigners, and some technology workers more generally – those who would self-describe as working ‘on’, ‘with’ and ‘in’ AI and those analyzing or campaigning on the effects of AI” (by Haydn Belfield, University of Cambridge, “Activism By The AI Community,” AIES Conference).

We can potentially try to characterize the AI activism as exhibited by the AI community-at-large: “This activism has had some notable consequences so far: informing international negotiations, changing corporate strategy, and spurring the growth of research fields. Such activism may shape the manner and extent to which AI is militarized, and how AI companies address ethics and safety concerns. The AI community is an important autonomous actor with a distinctive set of viewpoints and interests. It needs to be accounted for in the strategic or academic analysis and negotiated with by other actors. AI community activism may profoundly shape the development and deployment of this important set of technologies – and therefore shape our global economy, society and politics” (in the same paper by Belfield).

Does the AI community move as one and think as a cohesive virtual body when it comes to AI activism?

You would be hard-pressed to provide an unequivocal yes to that question. You can find stanch AI advocates in the AI community. You can find stanch AI opponents in the AI community. There are plentiful AI activists that are mild and ones that are extreme, sitting on either side of the fence.

Of course, you might naturally assume that the AI activists of the AI community would lean toward favoring AI since the field of AI is presumably their bread and butter. If their careers and livelihoods are shaped around the existence and ongoing advancement of AI, it is a natural deduction to anticipate that they would be more likely on the AI advocacy side than the AI opposition side.

A contrary view is that many within AI are themselves self-critical of and notably concerned about what AI might become or be shaped into becoming. You could liken this to the maker of just about any kind of new product. They want to ensure that their baby, as it were, will be suitably raised and utilized. They are therefore as much likely to be AI opponents in some sense as they are AI advocates. This comes back to the earlier point that trying to use a hard and unyielding dichotomy can be difficult or misleading.

We definitely need more research on how the membership of being inside the AI community versus outside the AI community can impact the perspectives of AI, including tending toward AI advocacy or tending toward AI opposition. Perhaps there are generalizable conclusions that can be fairly reached (or, maybe not).

To clarify, let’s provide this indication of potential groupings:

• AI community
• Those outside the AI community

We then apply our earlier stratifications:

• AI community containing AI advocates
• AI community containing AI opponents
• Outside the AI community that contains AI advocates
• Outside the AI community that contains AI opponents

The full-blown version is that we’ll add the mild versus extreme orientations:

• AI community containing AI advocates of a mild nature
• AI community containing AI advocates of an extreme nature
• AI community containing AI opponents of a mild nature
• AI community containing AI opponents of an extreme nature
• Outside the AI community that contains AI advocates of a mild nature
• Outside the AI community that contains AI advocates of an extreme nature
• Outside the AI community that contains AI opponents of a mild nature
• Outside the AI community that contains AI opponents of an extreme nature

We’ve piled dichotomies on top of dichotomies.

At this juncture of this weighty discussion, I’d bet that you are desirous of some illustrative examples that might showcase this topic. There is a special and assuredly popular set of examples that are close to my heart. You see, in my capacity as an expert on AI including the ethical and legal ramifications, I am frequently asked to identify realistic examples that showcase AI Ethics dilemmas so that the somewhat theoretical nature of the topic can be more readily grasped. One of the most evocative areas that vividly presents this ethical AI quandary is the advent of AI-based true self-driving cars. This will serve as a handy use case or exemplar for ample discussion on the topic.

Here’s then a noteworthy question that is worth contemplating: Does the advent of AI-based true self-driving cars illuminate anything about AI activism, and if so, what does this showcase?

Allow me a moment to unpack the question.

First, note that there isn’t a human driver involved in a true self-driving car. Keep in mind that true self-driving cars are driven via an AI driving system. There isn’t a need for a human driver at the wheel, nor is there a provision for a human to drive the vehicle. For my extensive and ongoing coverage of Autonomous Vehicles (AVs) and especially self-driving cars, see the link here.

I’d like to further clarify what is meant when I refer to true self-driving cars.

Understanding The Levels Of Self-Driving Cars

As a clarification, true self-driving cars are ones where the AI drives the car entirely on its own and there isn’t any human assistance during the driving task.

These driverless vehicles are considered Level 4 and Level 5 (see my explanation at this link here), while a car that requires a human driver to co-share the driving effort is usually considered at Level 2 or Level 3. The cars that co-share the driving task are described as being semi-autonomous, and typically contain a variety of automated add-ons that are referred to as ADAS (Advanced Driver-Assistance Systems).

There is not yet a true self-driving car at Level 5, and we don’t yet even know if this will be possible to achieve, nor how long it will take to get there.

Meanwhile, the Level 4 efforts are gradually trying to get some traction by undergoing very narrow and selective public roadway trials, though there is controversy over whether this testing should be allowed per se (we are all life-or-death guinea pigs in an experiment taking place on our highways and byways, some contend, see my coverage at this link here).

Since semi-autonomous cars require a human driver, the adoption of those types of cars won’t be markedly different than driving conventional vehicles, so there’s not much new per se to cover about them on this topic (though, as you’ll see in a moment, the points next made are generally applicable).

For semi-autonomous cars, it is important that the public needs to be forewarned about a disturbing aspect that’s been arising lately, namely that despite those human drivers that keep posting videos of themselves falling asleep at the wheel of a Level 2 or Level 3 car, we all need to avoid being misled into believing that the driver can take away their attention from the driving task while driving a semi-autonomous car.

You are the responsible party for the driving actions of the vehicle, regardless of how much automation might be tossed into a Level 2 or Level 3.

Self-Driving Cars And AI Activism

For Level 4 and Level 5 true self-driving vehicles, there won’t be a human driver involved in the driving task.

All occupants will be passengers.

The AI is doing the driving.

One aspect to immediately discuss entails the fact that the AI involved in today’s AI driving systems is not sentient. In other words, the AI is altogether a collective of computer-based programming and algorithms, and most assuredly not able to reason in the same manner that humans can.

Why is this added emphasis about the AI not being sentient?

Because I want to underscore that when discussing the role of the AI driving system, I am not ascribing human qualities to the AI. Please be aware that there is an ongoing and dangerous tendency these days to anthropomorphize AI. In essence, people are assigning human-like sentience to today’s AI, despite the undeniable and inarguable fact that no such AI exists as yet.

With that clarification, you can envision that the AI driving system won’t natively somehow “know” about the facets of driving. Driving and all that it entails will need to be programmed as part of the hardware and software of the self-driving car.

Let’s dive into the myriad of aspects that come to play on this topic.

First, it is important to realize that not all AI self-driving cars are the same. Each automaker and self-driving tech firm is taking its approach to devising self-driving cars. As such, it is difficult to make sweeping statements about what AI driving systems will do or not do.

Furthermore, whenever stating that an AI driving system doesn’t do some particular thing, this can, later on, be overtaken by developers that in fact program the computer to do that very thing. Step by step, AI driving systems are being gradually improved and extended. An existing limitation today might no longer exist in a future iteration or version of the system.

I hope that provides a sufficient litany of caveats to underlie what I am about to relate.

There are AI activism efforts that have been and are continuing to take place regarding autonomous vehicles and especially AI-based self-driving cars.

AI advocates in this context would likely contend that self-driving cars will provide mobility-for-all, allowing those that today have limited access to mobility options to instead readily have mobility via self-driving cars. The aim too is that we will have a lot fewer car crashes and accordingly fewer car-related injuries and fatalities. With today’s human-driven cars, the United States has about 40,000 annual deaths due to car crashes and around 2.5 million injuries, see my collection of such stats at the link here.

AI opponents regarding self-driving cars would tend to assert that we are facing tremendous job losses as a result of self-driving cars. The millions of workers that drive cars for a living or that drive trucks for a living will be replaced by AI driving systems. This could be staggering for their livelihoods. Another major qualm deals with the safety issue. Though there is an implied promise that self-driving cars will drive safely, the question is whether they might not be safe and we are allowing ourselves to be at the mercy of arcane and indecipherable AI driving systems. For my coverage of the reasons underlying the opposition to self-driving cars, see the link here.

We can reuse our earlier set of classifications and put them into the self-driving car context:

• Neutral about AI (not an AI activist) and on the fence about self-driving cars
• Mild AI-advocate in favor of self-driving cars
• Extreme AI-advocate in favor of self-driving cars
• Mild AI-opponent in opposition to self-driving cars
• Extreme AI-opponent in opposition to self-driving cars
• Other

We can also add to this set an additional overlay about being part of the AI community versus being outside of the AI community.

Without being overly broad, it would seem that by and large that people outside of the AI community are generally on the fence about AI-based self-driving cars (I say this informally, via my giving public talks and getting public feedback on my columns, plus I have examined the survey results done by various polling agencies and reported on the conclusions). The public generally seems to be in a wait-and-see mode. There is some eagerness and excitement, which is balanced by being unsure about the matter and wanting to see proof of the pudding, as it were.

To be clear, not everyone outside the AI community sees the matter in those terms. There are notable external AI activists that are AI advocates in favor of self-driving cars and ones that are decidedly in opposition. They tend to be highly vocal. Meanwhile, the preponderance of the public seems relatively quiet and as mentioned is in a wait-and-see mindset.

You might recall some examples of extreme AI activism that was opposing self-driving cars that took place a few years ago and which I reported in my columns at the time. In some locales, people opted to toss rocks at passing self-driving cars. They tried to block the movement of self-driving cars by placing their human-driven cars in the way or veering close to self-driving cars to showcase the dangers of self-driving cars. Much of these tactics were unlawful and endangering to all concerned.

Big stakes are at play in all of this.

Estimates are that the self-driving realm will eventually become a trillion-dollar industry, see my analysis at the link here. Some AI opponents would insist that we are witnessing the power of money to decide our fate. We ought to be only allowing AI-based self-driving cars to be running around on special closed tracks or be using computer-based simulations to try them out. The claim is that we are prematurely permitting untried and not ready for prime-time self-driving cars to be on our public roadways.

Conclusion

AI activism is arising in all walks of AI.

I’ve highlighted here that AI activism underlies the adoption of self-driving cars and autonomous vehicles. We have AI activism in an abundance in other parts of society. There is AI in the health and medical fields. AI in the financial realm. AI in retail and distribution. AI is gradually becoming pervasive.

Some say that AI opponents are trying to turn back the clock. They want to go back to the days of horse and buggy. They are Luddites in a modern era.

Some say that AI advocates are taking us down a primrose path. We are going to ultimately construct a Frankenstein that will be an existential threat. All of humankind will either be enslaved, or we will be summarily wiped out by AI.

Which AI activist are you?

One thing that seems nearly certain is those who are neutral and do not consider themselves to be in the AI activism game, they are inexorably going to be dragged into the AI social action gambit, whether they like it or not. AI is here and growing. Nobody will be able to keep their head in the sand and everyone is going to have to stand up about AI, so the only question is which side or camp you are going to land on.

AI garners attention, mildly or extremely so, and we all have a stake in where AI is headed.