Emerging Rise Of “AI Localism” Is Getting Bigger, Bolder, And Badder Says AI Ethics And AI Law

They say that all politics is local.

You’ve undoubtedly heard or seen that snazzy catchphrase many times.

It gets used relatively frequently, especially around the time that elections take place. The general idea is that politicians tend to win or lose their election aspirations based on whatever is happening in their local jurisdiction. Sometimes an overt effort to pander to a local constituency occurs. A classic example entails so-called pork barrel spending that an incumbent politician brings to their hometown in hopes that this will bolster their chances of getting reelected.

U.S. House Speaker Thomas “Tip” O’Neill, Jr. extensively used the slogan in 1935. Doing so seemed to have demonstrably aided his reelection. The die was cast and the motto became well-known and oft-used thereafter. Though Tip O’Neill managed to get the adage underway, some scholars emphasize that it was newspaper writer Bryon Price that initially coined the handy-dandy contrivance. If you take a look at Price’s columns of February 1932 and July 1932, you will see the maxim and several variants showcased including “all politics is local in the last analysis,” “politics is local,” and “all politics is local politics” (whether this was the first instance is arguable, but it definitely preceded Tip O’Neill’s usage).

The word “all” tends to give a disquieting pause for some that aren’t convinced of the saying all told.

There are politics at a variety of levels, skeptics assert stridently. Local politics is absolutely important. No doubt about it. On the other hand, trying to lay at the feet of all political actions the solitary bedrock of a local dimension is perhaps an overstatement and misleading. Furthermore, this particular smidgin of wisdom might be befitting in the United States due to its political structure, meanwhile, other countries often differ in their political milieu, and thus the saying there is likely less pertinent.

It is all debatable.

I think that we can all agree on one very important consideration, namely that whatever you do, do not ignore or overlook the local facets of politics. I say this because our lives are generally bombarded by news about political antics and actions occurring at the broader or larger levels of our existence. We hear or read about federal actions. We hear or read about state actions. Local aspects can be overtaken by the constant drumbeat of what is taking place at the state and federal levels.

Local matters are apt to get buried beneath the big-time maneuvering and machinations at heightened levels of our society.

Here’s something that might surprise you. There is one particular area of today’s whooping and hollering that seems to always be taking place at the macro levels and doesn’t get much attention at the local levels.

Are you ready?

Artificial Intelligence (AI).

Yes, the wrangling and consternation about AI seems to pretty much be dominated by efforts at the state and federal levels, plus at the multinational and international levels too. For example, I’ve previously discussed that there is an ongoing and at times aggressive AI Race going on between nations as to which nation will have the best or most advanced AI over all the others – see “AI Ethics And The Geopolitical Wrestling Match Over Who Will Win The Race To Attain True AI” at the link here (Lance Eliot, Forbes, August 15, 2022).

In addition, I’ve pointed out that there is a lot of potential political power that can arise in a nation as a result of its holding onto or hoarding the latest in AI advances – see “AI Ethics And The Looming Political Potency Of AI As A Maker Or Breaker Of Which Nations Are Geopolitical Powerhouses” at the link here (Lance Eliot, Forbes, August 22, 2022). You might also find of interest that nations are seeking to use AI as a type of bargaining chip. A nation that has made impressive advances in AI might attempt to use the latest AI in negotiations for favored nation status when trading goods or other amenities — see “Nations Trading Their AI As Geopolitical Bargaining Chips Raise Angst For AI Ethics And AI Law” at the link here (Lance Eliot, Forbes, December 9, 2022).

The same focus of attention is generally occurring within the realm of AI Ethics and AI Law. We want AI to abide by various Ethical AI precepts or “soft laws” as to how AI is composed and used. Meanwhile, slowly but surely, on-the-books laws and regulations about AI are being debated and put into place. AI Law is going to be a tremendous tool in trying to deal with AI and where we as a society go with AI. For my ongoing and extensive coverage of AI Ethics and AI Law, see the link here and the link here, just to name a few.

Most of the aspects of AI Ethics and AI Law are customarily at the state, federal, or international levels. Not so much at the local levels. I’ll be saying more about this in a moment.

Let’s first lay out the lay of the land for AI Ethics as:

• International AI Ethics: AI Ethics proclamations and establishment at the international level
• National AI Ethics: AI Ethics proclamations and establishment at the national or federal level
• State AI Ethics: AI Ethics proclamations and establishment at the state or province level
• Local AI Ethics: AI Ethics proclamations and establishment at the local city or town level

The same can be said for AI Law:

• International AI Laws: AI legal-oriented laws and regulations at the international level
• National AI Laws: AI legal-oriented laws and regulations at the nationwide or federal level
• State AI Laws: AI legal-oriented laws and regulations at the state or province level
• Local AI Laws: AI legal-oriented laws and regulations at the local city or town level

That’s a whole bunch of potentially disparate angles and cross-eyed perspectives about AI Ethics and AI Law.

Consider the complexities involved. If here in the U.S. we pass laws about AI at the federal level or enact regulations, you ought to be wondering whether those comport with AI laws in other countries or at a multinational capacity such as the United Nations. Meanwhile, states within the U.S. have to be eyeing what the federal AI laws allow and disallow. This can impact the state-crafted and enacted AI laws.

At the teeny tiny bottom of this long ladder of AI legal concoctions come the local AI laws. You might be wondering whether there is any AI Ethics and AI Law action taking place at the local levels. Are localities pushing into the enactment of AI Ethics precepts and the establishment of AI Laws?

Yes, abundantly so.

For example, take a look at my coverage of the New York City (NYC) law about AI that entails getting businesses in NYC to perform AI-focused audits when they are making use of AI for certain aspects of hiring and firing human workers (see the link here). Some believe that this law is fantastic and we ought to do the same at the state and federal levels. In addition, various cities across the country are watching how this law goes (it starts January 2023), and might decide to do something similar in their local areas.

Others aren’t so sure about embracing such an AI Law. Complications are aplenty. The desire to keep AI in reign is often lauded, but the devil is in the details. The cost to comply is a worrisome concern. Lawsuits are going to indubitably be flying back and forth. Perhaps this particular AI Law is premature and needs more care and feeding before it starts impacting on a widespread basis.

Anyway, the gist here is that local AI is increasingly getting noticed. Slowly, gradually, perhaps excruciatingly so, and regrettably belatedly (the horse might already be out of the darn).

Here’s the deal. If you are willing to concede that all politics is local, a corollary might be that all AI is local. People will feel the impact of AI at their local levels. They are bound to want to have some say in how AI is being used within their local communities. All of the noise about AI at the state level, national federal level, and international level is drowning out the need and actions at the local level.

A rallying cry is being spurred. Speak up about AI concerns and considerations at the local level. Make sure that your local politicians are up to date about AI and how it is affecting the constituents in their local jurisdiction. Alas, many local leaders are bound to be utterly unaware of what AI is. They might not realize that AI is sneakily coming into their domain or local area. Wake up!

Some refer to this overall as AI localism.

We’ll have to wait and see if this somewhat newly minted-phrase will catch hold. For now, just the fact that there is an effort afoot to knock on doors and get local awareness up-to-speed is said to be demonstrably helpful and hopeful. You see, once AI gets rooted into local efforts, it might be too late to try and make needed corrections or put in place appropriate Ethical AI practices and AI Laws. Don’t let the trojan horse be drawn past the local gates. Be prepared. Get ahead of the AI curve.

Before diving deeply into the topic, I’d like to first lay some essential foundation about AI and particularly AI Ethics and AI Law, doing so to make sure that the discussion will be contextually sensible.

The Rising Awareness Of Ethical AI And Also AI Law

The recent era of AI was initially viewed as being AI For Good, meaning that we could use AI for the betterment of humanity. On the heels of AI For Good came the realization that we are also immersed in AI For Bad. This includes AI that is devised or self-altered into being discriminatory and makes computational choices imbuing undue biases. Sometimes the AI is built that way, while in other instances it veers into that untoward territory.

I want to make abundantly sure that 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).

I’d strongly suggest that we keep things 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.

Be very careful of anthropomorphizing today’s AI.

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.

All of this has notably significant AI Ethics implications and offers a handy window into lessons learned (even before all the lessons happen) when it comes to trying to legislate AI.

Besides employing AI Ethics precepts in general, there is a corresponding question of whether we should have laws to govern various uses of AI. New laws are being bandied around at the federal, state, and local levels that concern the range and nature of how AI should be devised. The effort to draft and enact such laws is a gradual one. AI Ethics serves as a considered stopgap, at the very least, and will almost certainly to some degree be directly incorporated into those new laws.

Be aware that some adamantly argue that we do not need new laws that cover AI and that our existing laws are sufficient. They forewarn that if we do enact some of these AI laws, we will be killing the golden goose by clamping down on advances in AI that proffer immense societal advantages.

In prior columns, I’ve covered the various national and international efforts to craft and enact laws regulating AI, see the link here, for example. I have also covered the various AI Ethics principles and guidelines that various nations have identified and adopted, including for example the United Nations effort such as the UNESCO set of AI Ethics that nearly 200 countries adopted, see the link here.

Here’s a helpful keystone list of Ethical AI criteria or characteristics regarding AI systems that I’ve previously closely explored:

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

Those AI Ethics principles are earnestly supposed 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 prior emphasized herein, 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.

I also recently examined the AI Bill of Rights which is the official title of the U.S. government official document entitled “Blueprint for an AI Bill of Rights: Making Automated Systems Work for the American People” that was the result of a year-long effort by the Office of Science and Technology Policy (OSTP). The OSTP is a federal entity that serves to advise the American President and the US Executive Office on various technological, scientific, and engineering aspects of national importance. In that sense, you can say that this AI Bill of Rights is a document approved by and endorsed by the existing U.S. White House.

In the AI Bill of Rights, there are five keystone categories:

• Safe and effective systems
• Algorithmic discrimination protections
• Data privacy
• Notice and explanation
• Human alternatives, consideration, and fallback

I’ve carefully reviewed those precepts, see the link here.

Now that I’ve laid a helpful foundation on these related AI Ethics and AI Law topics, we are ready to jump into the heady topic of AI Localism.

Eyeing AI Locally Is An Eye-Opening Consideration

Let’s unpack the local AI conundrum.

In a research paper entitled “AI Localism In Practice: Examining How Cities Govern AI” by Sara Marcucci, Uma Kalkar, and Stefaan Verhulst, The GovLab), the authors indicate that AI localism “refers to the actions taken by local decision-makers to address the governance of AI within a city or community. Numerous types of ‘localisms’ exist to address specific, local needs that national policy is not always fit to address, or to fill policy gaps in communities overlooked by national governments.”

I’ve previously discussed AI localism extensively in a white paper that I did with Harvard on the advent of autonomous vehicles and self-driving cars, see the link here. We examined closely how cities and towns in the U.S. have been coping with the introduction and emergence of self-driving vehicles. Should local politicians such as mayors and city councils openly embrace self-driving vehicles or should they be cautious in doing so? What types of local ordinances should be enacted? Etc.

As I mentioned earlier herein, AI enters into the local domain in a wide variety of ways. Sometimes the AI is comparatively hidden, such as the AI being used to drive autonomous vehicles. Another hidden use of AI has to do with facial recognition. I’ve covered how localities such as San Francisco have grappled with placing local controls over AI that powers facial recognition, see my analysis at the link here. Concerns arise about this kind of AI exhibiting undue biases and acting in discriminatory ways.

Action at all levels of government is happening when it comes to corralling and guiding AI. Some of it is useful, and some of it is disgraceful. There are those with the best intentions that are astutely proceeding. There are those with confused or muddled intentions that are oddly proceeding. It is a mixed bag.

Which level of government is doing a better job at envisioning and instilling AI Ethics and AI Laws in the gallant pursuit of trying to govern AI?

Your choices are at the international level, national or federal level, state level, or local level.

Scholars are debating which level is doing the best on this evolving topic. A viewpoint expressed in the research paper on AI localism says this: “However, our research finds that cities and states are leading the charge of developing governance frameworks and implementing policies at a quicker, more direct, and more impactful level than their national counterparts. A number of cities have indeed proposed innovative smart urbanism visions that move away from a techno-centric approach and toward a more human-centric one” (ibid).

Whether you concur with their assessment or not, the idea that local efforts might be more on-target and quicker to be responsive does intuitively seem to make sense. Usually, actions at a national or federal level can be slow and glacial to take effect. Plus, often there are bona fide criticisms that the all-encompassing widespread pronouncements don’t take into account the nuances and tweaks required at local levels.

The researchers have identified seven key themes of what they characterize as the AI localism canvas (I am quoting here per their research study):

• “Principles and Rights: Non-binding agreements local agencies may develop and use, sometimes in collaboration with other agencies or city partners, to ensure the responsible use of AI at a local level;
• Procurement: Innovations regarding the acquisition of AI by a public institution from third party private vendors;
• Engagement: Novel ways to engage publics into conversations and decisions regarding AI-related concerns, such as the collection and use of urban data;
• Laws and Policies: Efforts to regulate government use of AI as well as how certain AI applications can be used in certain sectors, such as public education or urban mobility;
• Accountability and Oversight: Initiatives on a local level that are aimed at enforcing accountability mechanisms about the use of AI systems;
• Transparency: Local efforts to develop and encourage transparency about the acquisition and application of AI systems across governmental agencies and domains; and
• Literacy: Avenues to educate citizens, residents, policymakers and the public as a whole about the development and use of AI, its functionings and social impacts.”

You can readily use such a framework to take a close look at your own local AI-related infusion. Are your local agencies aware of AI and considering the ramifications of using AI at the local level? Who in the local jurisdiction is supposed to be watching for these AI issues? To what degree is the local constituency being informed about how AI is being adopted locally? And so on.

Some especially strong-willed proponents of AI localism have been calling for local jurisdictions to establish a Chief AI Adviser (or similar title) that would be available to aid local authorities as they figure out what to do about AI. This person would be versed in AI sufficiently to advise and consult with mayors, city councils, local boards, and committees, and would also be sought to give presentations about how AI is being adopted at the local levels. They might lead the charge toward putting in place AI Ethics provisions and local AI-related laws.

Keep in mind too that all of this local AI can range from AI For Good to AI For Bad.

Local leaders should be wary of AI that either at the get-go is AI For Bad or that has the endangering possibility of veering into any undesirably nefarious territory. Local politicians should not be accepting AI For Good at face value. They need to ask pointedly whether there are proper controls in place to keep AI For Good in the AI For Good camp. That’s something local leaders should be dealing with, though they might not realize it is on their shoulders to contend with.

Local leaders are certainly vulnerable to making mistakes regarding AI.

They can overcorrect on AI and put the kibosh on local AI innovations. They can undercorrect and allow adverse AI to permeate their local area. As stated by the researchers: “It is necessary to note, however, how AI Localism does not necessarily equal ‘good governance’ of AI at the local level. Indeed, there have been several instances where local efforts to regulate and employ AI have encroached on public freedoms and impaired the public good” (ibid).

You should anticipate that a potential conflict is going to emerge between AI provisions at the local levels versus at the state, federal and national levels. Do not assume that everyone agrees about how AI is to be governed. Differing views exist. AI Laws are not all the same. Even AI Ethics precepts have differences.

We will have states that sue or seek court action to stop local jurisdictions from putting in place or imposing various local AI laws. Local jurisdictions will almost certainly be suing or seeking court action to prevent states from countermanding their local AI provisions. The same will occur at the federal level. Feds going after states and going after localities.

A brouhaha is coming.

Conclusion

The ideal dream would be that AI Ethics and AI Law are completely in sync across all levels. We might look to the national or federal level to first establish AI cornerstones. In turn, the states would leverage those AI cornerstones and tailor the provisions to their state-specific needs. Then, further, in turn, the local jurisdictions would leverage the respective state provisions and tailor them according to their local AI needs.

A nice happy family of well-aligned AI Ethics and AI Laws.

An added benefit is that there is no reinventing of the wheel. Whereas today a local jurisdiction might have to invent anew some AI Ethics or AI Laws that otherwise aren’t around or haven’t been vetted, instead the idea is that the local realm would merely pick and choose from the level above them.

Sounds wonderful.

Hang onto that smiley face thought.

Unfortunately, reality upends that dream.

There will be all manner of local AI provisions that are helter-skelter. Those provisions will be in direct conflict with and potentially violate state and federal-level AI provisions. It is going to be a gigantic mess.

Do not though assume that this is due to AI localism gone wild.

There are equal chances that the federal level will concoct AI provisions that are non-sensical or not livable at local levels. States are bound to do something of a similar crazed nature. They might not care about what happens at the local level. They might care but hadn’t anticipated what occurs once their AI provisions get handed down to the local realms.

A free-for-all about AI governance.

We don’t want a free-for-all.

Some efforts are underway at the federal level to try and garner local input about how the national AI provisions should best be devised and put into use, see my analysis at the link here. Some states are doing the same. We have a fighting chance to try and align AI governance. It won’t be easy.

Thomas Jefferson famously stated that government is the strongest of which every person feels a part. AI is going to be ubiquitous. AI will ultimately be as much a concern at the local level as at the broader levels. Make sure that AI localism is alive and well in your local jurisdiction, otherwise, you might not have any say in how AI will be impacting your human life on your local day-to-day basis.

AI localism is coming to your town, sooner or later.

Aim to make it sooner, rather than later.