Tagdigital rights

Smart Cities & Human Rights

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This article is part of 20in20, a series of 20 blog posts in 20 days to kick off the blogging year 2020. This is 20in20:02.

If you’ve followed this blog or my work at all, you’ll know that I’ve been doing a fair bit of work around Smart Cities and what they mean from a citizens and rights perspective, and how you can analyze Smart City projects through a lens of responsible technology (which of course has also been the main mission of our non-profit org, ThingsCon).

For years, I’ve argued that we need to not use tech goggles to look at how we can and should connect public space but rather a rights-based perspective. It’s not about what we can do but what we should do, after all.

But while I’m convinced that’s the right approach, it’s been non-trivial to figure out what to base the argument on: What’s the most appropriate foundation to build a “Smart City Rights” perspective on?

A recent conversation led me to sketch out this rough outline which I believe points in the right direction:

Image: A sketch for a basis for a Smart City and Human Rights analytical framework

There are adjacent initiatives and frameworks that can complement and flank anything based on these three (like the Vision for a Shared Digital Europe and its commons-focused approach), and of course this also goes well with the EU’s Horizon 2020 City Mission for Climate-neutral and smart cities. So this is something I’m confident can be fleshed out into something solid.

Are there any other key documents I’m missing that absolutely should be incorporated here?

Category Error: Tracking Ads Are Not a Funding Mechanism

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This article is part of 20in20, a series of 20 blog posts in 20 days to kick off the blogging year 2020. This is 20in20:01.

A note to put this in perspective: This blog post doesn’t pull any punches, and there will be legitimate exceptions to the broad strokes I’ll be painting here. But I believe that this category error is real and has disastrous negative effects. So let’s get right to it.

I’ve been thinking a lot about category errors: The error of thinking of an issue as being in a certain category of problems even though it is primarily in another. Meaning that all analysis and debate will by necessity miss the intended goals until we shift this debate into a more appropriate category.

I increasingly believe that it is a category error to think of online advertising as a means to fund the creation of content. It’s not that online advertising doesn’t fund the creation of content, but this is almost a side effect, and that function is dwarfed by the negative unintended consequences it enables.

When we discuss ads online, it’s usually in the framing of funding. Like this: Ads pay for free news. Or: We want to pay our writers, and ads is how we can do that.

To be clear, these are solid arguments. Because you want to keep news and other types of journalism as accessible to as many people as possible (and it doesn’t get more accessible than “free”). And you do want to pay writers, editors and all the others involved in creating media products.

However.

Those sentences make sense if we consider them in their original context (newspaper ads) as well as the original digital context (banner ads on websites).

There, the social contract was essentially this: I give my attention to a company’s advertisement, and that company gives the media outlet money. It wasn’t a terribly elegant trade in that there are still (at least) three parties involved, but it was pretty straightforward.

Fast forward a few years, and tracking of success of individual ads gets introduced, which happens in steps: First, how many times is this ad displayed to readers? Then, how many readers click it? Then, how many readers click it and then follow through with a purchase? There’s a little more to it, but that’s the basic outline of what was going on.

Fast forward a few years again, and now we have a very different picture. Now, ads place cookies on readers’ devices, and track not just how often they’re been displayed or clicked or how often they convert to a purchase.

Contemporary tracking ads and their various cookies also do things like these: Track if a reader moves the cursor over the ad. Tracks from which website a reader comes to the current website and where they head after. Track the whole journey of any user through the web. Track the software and hardware of any reader’s devices and create unique fingerprints to match with other profiles. Match movement through the web with social media profiles and activities and likes and shares and faves. Track movement of the reader in the physical world. Build profiles of readers combined from all of this and then sell those in aggregate or individually to third parties. Allow extremely granular targeting of advertisements to any reader, down to the level of an ad personalized for just one person. And so on.

This is nothing like the social contract laid out above, even though the language we use is still the same. Here, the implied social contract is more like this: I get to look a little at a website without paying money, and that website and its owner and everyone the owner chooses to make deals with gets to take an in-depth look at all my online behaviors and a significant chunk of my offline behaviors, too, all without a way for me to see what’s going on, or of opting out of it.

And that’s not just a mouthful, it’s also of course not the social contract anyone has signed up for. It’s completely opaque, and there’s no real alternative when you move through the web, unless you really know about operational security in a way that no normal person should ever have to, just in order to read the news.

This micro-targeting is also at the core of what might (possibly, even though we won’t have reliable data on it until it would be too late, if confirmed) undermines and seriously threatens our political discourse. It allows anti-democratic actors of all stripes to spread disinformation (aka “to lie”) without oversight and it’s been shown to be a driver of radicalization by matching supply with demand at a whole new scale.

Even if you don’t want to go all the way to this doomsday scenario, the behavior tracking and nudging that is supposed to streamline readers into just buying more stuff all the time (you probably know how it feels to be chased around the web by an ad for a thing you looked up online once) without a reasonable chance to stop it is, at best, nasty. At worst, illegal under at least GDPR, as a recent study demonstrated. It also creates a surprising — and entirely avoidable! — carbon footprint.

So, to sum up, negative externalities of tracking ads include:

  • micro-targeting used to undermine the democratic process through disinformation and other means;
  • breaches of privacy and data rights;
  • manipulation of user behavior, and negatively impacting user agency;
  • and an insane carbon footprint.

Of course, the major tracking players benefit a great deal financially: Facebook, who make a point of not fact-checking any political ads, i.e. they willingly embrace those anti-democratic activities. Google, who are one of the biggest provider of online ad tracking and also own the biggest browser and the biggest mobile phone operating system, i.e. they collect data in more places than anyone else. And all the data brokers, the shadiest of all shadow industries.

Let me be clear, none of this is acceptable, and it is beyond me that at least parts of it are even legal.

So, where does that lead us?

I argue we need to stop talking about tracking ads as if they were part of our social contract for access to journalism. Instead, we need to name and frame this in the right category:

Tracking ads are not a funding method for online content. Tracking ads are the infrastructure for surveillance & manipulation, and a massive attack vector for undermining society and its institutions.

Funding of online content is a small side-effect. And I’d argue that while we need to fund that content, we can’t keep doing it this way no matter what. Give me dumb (i.e. privacy friendly, non-tracking) ads any day to pay for content. Or, if it helps keep the content free (both financially as well as free of tracking) for others then I think we should also consider paying for more news if we’re in any financial position to do so.

(What we shouldn’t do is just pay for our own privacy and let the rest still be spied on, that’s not really a desirable option. But even that doesn’t currently exist: If you pay for a subscription you’ll still be tracked just like everyone else, only with some other values in your profile, like “has demonstrated willingness to spend money on online content”.)

So, let’s recognize this category error for what it is. We should never repeat these statement again that ads pay for content; they do not. (Digital ad spend goes up and up but over the last 15 years or so newspaper revenue through digital ads have stayed pretty flat, and print collapsed.) Ads online today are almost completely tracking ads, and those are just surveillance infrastructure, period. 

It’s surveillance with a lot of negative impact and some positive side effects. That’s not good enough. So let’s start from there, and build on that, and figure out better models.

What type of smart city do we want to live in?

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Warning: Trick question! The right questions should of course be: What type of city do we want to live in? What parts of our cities do we want to be smart, and in what ways?

That said, this is the talk of my talk for NEXT Conference 2019 in which I explore some basic principles for making sure that if we add so-called smart city technology to our public spaces, we’ll end up with desirable results.

Developing better urban metrics for Smart Cities

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When we embed connected technologies — sensors, networks, etc. — into the public space*, we create connected public space. In industry parlance, this is called a Smart City. (I prefer “connected city”, but let’s put the terminology discussion on the back burner for now.) And data networks change the way we live.

* Note: Increasingly, the term “public space” has itself come under attack. In many cities, formerly public (as in publicly owned & governed) has been privatized, even if it’s still accessibly by the public, more or less. Think of a shopping mall, or the plazas that are sometimes attached to a shopping mall: You can walk in, but a mall cop might enforce some house rules that were written not by citizens but the corporation that owns the land. I find this not just highly problematic, I also recommend flat out rejecting that logic as a good way forward. Urban space — anything outside closed buildings, really — should, for the most part, be owned by the public, and even where for historical reasons it can’t be owned, it should at least be governed by the public. This means the rules should be the same in a park, a shopping mall-adjacent plaza, and the street; they should be enforced by (publicly employed) police rather than (privately employed) mall cops. Otherwise there’s no meaningful recourse for mistreatment, there’s no ownership, citizens are relegated from stakeholders to props/consumers.

Networks and data tend not to ease but to reinforce power dynamics, so we need to think hard about what type of Smart City we want to live in:

  • Do we want to allow people to get faster service for a fee (“Skip the line for $5”), or prefer everyone to enjoy the same level of service, independent of their income?
  • Do we want to increase the efficiency for 90% of the population through highly centralized services even if it means making the life of the other 10% much harder, or do we plan for a more resilient service delivery for all, even if it means the overall service delivery is a tad slower?
  • Do we want to cut short-term spending through privatization even if it means giving up control over infrastructure, or do we prioritize key infrastructure in our budgeting process so that the government can ensure quality control and service delivery in the long term, even if it costs more in the short term?

These are blunt examples, but I reckon you can tell where I’m going with this: I think democratic life requires public space and urban infrastructure to be available to all citizens and stakeholders, and to work well for all citizens. Pay for play should only apply for added non-essential services.

“Don’t confuse the data you can capture with the things you need to know!

In order to shape policies in this space meaningfully, we need to think about what the things are that we prioritize. Here, a brief warning is in place: the old management adage “you can’t manage what you don’t measure” is problematic to say the least. All too often we see organizations act on the things they can measure, even if these things are not necessarily meaningful but just easy to measure. Don’t confuse the data you can capture with the things you need to know!

What do we want to prioritize, and maybe even measure?

That said, what are the things we want to prioritize? And might it even be possible to measure them?

Here I don’t have final answers, just some pointers that I hope might lead us into the right direction. These are angles to be explored whenever we consider a new smart city project, at any scale — even, and maybe especially, for pilot projects! Let’s consider them promising starting points:

Participation
Has there been meaningful participation in the early feedback, framing, planning, governance processes? If feedback has been very limited and slow, what might the reasons be? Is it really lack of interest, or maybe the barrier to engagement was just too high? Were the documents to long, too full of jargon, to hard to access? (See Bianca Wylie’s thread on Sidewalk Labs’ 1.500+ page development plan.) Were the implications, the pros and cons, not laid out in an accessible way? For example, in Switzerland there’s a system in place that makes sure that in a referendum both sides have to agree on the language that explains pros and cons, so as to make sure both sides’ ideas are represented fairly and accessibly.

Sustainability
Would these changes significantly improve sustainability? The UN’s Sustainable Development Goals (SGD) framework might offer a robust starting point, even though we should probably aim higher given the political (and real!) climate.

Will it solve a real issue, improve the life for citizens?
Is this initiative going to solve a real issue and improve lives meaningfully? This is often going to be tricky to answer, but if there’s no really good reason to believe it’s going to make a meaningful positive impact then it’s probably not a good idea to pursue. The old editors’ mantra might come in handy: If in doubt, cut it out. There are obvious edge cases here: Sometimes, a pilot project is necessary to explore something truly new; in those cases, there must be a plausible, credible, convincing hypothesis in place that can be tested.

Are there safeguards in place to prevent things from getting worse than before if something doesn’t work as planned?
Unintended consequences are unavoidable in complex systems. But there are ways to mitigate risks, and to make sure that the fallback for a failed systems are not worse then the original status. If any project would be better while working perfectly but worse while failing, then that deserves some extra thought. If it works better for some groups but not for others, that’s usually a red flag, too.

When these basic goals are met, and only then, should we move on to more traditional measurements, the type that dominates the discourse today, like:

  • Will this save taxpayers’ money, and lead to more cost-effective service delivery?
  • Will this lead to more efficient service delivery?
  • Will this make urban management easier or more efficient for the administration?
  • Will this pave the way for future innovation?

These success factors / analytical lenses are not grand, impressive ideas: They are the bare minimum we should secure before engaging in anything more ambitious. Think of them as the plumbing infrastructure of the city: Largely unnoticed while everything works, but if it ever has hiccups, it’s really bad.

We should stick to basic procedural and impact driven questions first. We should incorporate the huge body of research findings from urban planners, sociologists, and political scientists rather than reinvent the wheel. And we should never, ever be just blinded by a shiny new technological solution to a complex social or societal issue.

Let’s learn to walk before we try to run.

Which type of Smart City do we want to live in?

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Connectivity changes the nature of things. It quite literally changes what a thing is.

By adding connectivity to, say, the proverbial internet fridge it stops being just an appliance that chills food. It becomes a device that senses; captures, processes and shares information; acts on this processed information. The thing-formerly-known-as-fridge becomes an extension of the network. It makes the boundaries of the apartment more permeable.

So connectivity changes the fridge. It adds features and capabilities. It adds vulnerabilities. At the same time, it also adds a whole new layer of politics to the fridge.

Power dynamics

Why do I keep rambling on about fridges? Because once we add connectivity — or rather: data-driven decision making of any kind — we need to consider power dynamics.

If you’ve seen me speak at any time throughout the last year, chances are you’ve encountered this slide that I use to illustrate this point:

The connected home and the smart city are two areas where the changing power dynamics of IoT (in the larger sense) and data-driven decision making manifest most clearly: The connected home, because it challenges our notions of privacy (in the last 150 years, in the global West). And the smart city, because there is no opting out of public space. Any sensor, any algorithm involved in governing public space impacts all citizens.

That’s what connects the fridge (or home) and the city: Both change fundamentally by adding a data layer. Both acquire a new kind of agenda.

3 potential cities of 2030

So as a thought experiment, let’s project three potential cities in the year 2030 — just over a decade from now. Which of these would you like to live in, which would you like to prevent?

In CITY A, a pedestrian crossing a red light is captured by facial recognition cameras and publicly shamed. Their CitizenRank is downgraded to IRRESPONSIBLE, their health insurance price goes up, they lose the permission to travel abroad.

In CITY B, wait times at the subway lines are enormous. Luckily, your Amazon Prime membership has expended to cover priority access to this formerly public infrastructure, and now includes dedicated quick access lines to the subway. With Amazon Prime, you are guaranteed Same Minute Access.

In CITY C, most government services are coordinated through a centralized government database that identifies all citizens by their fingerprints. This isn’t restricted to digital government services, but also covers credit card applications or buying a SIM card. However, the official fingerprint scanners often fail to scan manual laborers’ fingerprints correctly. The backup system (iris scans) don’t work on too well on those with eye conditions like cataract. Whenever these ID scans don’t work, the government service requests are denied.

Now, as you may have recognized, this is of course a trick question. (Apologies.) Two of these cities more or less exist today:

  • CITY A represents the Chinese smart city model based on surveillance and control, as piloted in Shenzhen or Beijing.
  • CITY C is based on India’s centralized government identification database, Aadhaar.
  • Only CITY B is truly, fully fictional (for now).

What model of Smart City to optimize for?

We need to decide what characteristics of a Smart City we’d like to optimize for. Do we want to optimize for efficiency, resource control, and data-driven management? Or do we want to optimize for participation & opportunity, digital citizens rights, equality and sustainability?

There are no right or wrong answers (even though I’d clearly prefer a focus on the second set of characteristics), but it’s a decision we should make deliberately. One leads to favoring monolithic centralized control structures, black box algorithms and top-down governance. The other leads to decentralized and participatory structures, openness and transparency, and more bottom-up governance built in.

Whichever we build, these are the kinds of dependencies we should keep in mind. I’d rather have an intense, participatory deliberation process that involves all stakeholders than just quickly throwing a bunch of Smart City tech into the urban fabric.

After all, this isn’t just about technology choices: It’s the question what kind of society we want to live in.

An easy guide to applying the #IOTmanifesto

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The #IOTmanifesto is a great set of guidelines for designing connected products and services. (Read more about it on iotmanifesto.com.)

Trying to make it more actionable (rather than just aspirational), the IOTmanifesto team created this cheatsheet that gives a bit of support in how to best apply the manifesto in everyday life, like say in a client meeting.

IoT Manifesto at Mozfest 2015

You’ll notice the color coding of the different phases of product design that the 10 guidelines of the manifesto. To make it a little easier to skim and read, here’s the list broken down into these phases (concept/design/implementation) and rearranged.

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