CategoryDigital Transformation

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.

How to plan & govern a smart city?

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Taking the publication of Sidewalk Labs’ Master Innovation and Development Plan plan for the smart city development at Toronto’s waterfront (“Toronto Tomorrow”) as an occasion to think out loud about smart cities in general, and smart city governance in particular, I took to Twitter the other day.

If you don’t want to read the whole thing there, here’s the gist: I did a close reading of a tiny (!) section of this giant data dump that is the 4 volume, 1.500+ page Sidewalk Labs plan. The section I picked was the one that John Lorinc highlighted in this excellent article — a couple of tables on page 222 of the last of these 4 volumes, in the section “Supplemental Tables”. This is the section that gets no love from the developers; it’s also the section that deals very explicitly with governance of this proposed development. So it’s pretty interesting. This, by the way, is also roughly my area of research of my Edgeryders fellowship.

On a personal note: It’s fascinating to me how prescient our speakers at Cognitive Cities Conference were back in 2011 – eight years is a long time in this space, and it feels like we invited exactly the right folks back then!

Smart cities & governance: A thorny relationship

In this close reading I focused on exactly that: What does governance mean in a so-called smart city context. What is it that’s being governed and how, and maybe most importantly, by whom?

Rather than re-hash the thread here, just a quick example to illustrate the kind of issues. Where this plan speaks of publicly accessible spaces and decision-making taking into account community input, I argue that we need public spaces and full citizens rights. Defaults matter, and in cities we need the default to be public space and citizens to wield the final decision-making power over their environment. Not even the most benign or innovative company or other non-public entity is an adequate replacement for a democratically elected administration/government, and any but the worst governments — cumbersome as a government might be in some cases — is better than the alternatives.

My arguments didn’t go unnoticed, either. Canadian newspaper The Star picked up my thread on the thorny issue of governance and put it in context of other experts critical of privatizing the urban space; the few others I know from the thread make me think I’m in good company there.

What’s a smart city, anyway?

As a quick, but worthwhile diversion I highly recommend the paper Smart cities as corporate storytelling (Ola Söderström, Till Paasche, Francisco Klauser, published in City vol. 18 (2014) issue 3). In it, the authors trace not just the origin of the term smart cities but also the deliberate framing of the term that serves mostly the vendors of technologies and services in this space, in efficient and highly predictable ways. They base their analysis on IBM’s Smarter City campaign (highlights mine):

”this story is to a large extent propelled by attempts to create an ‘obligatory passage point’ (…) in the transformation of cities into ‘smart’ ones. In other words it is conceived to channel urban development strategies through the technological solutions of IT companies.

These stories are important and powerful:

Stories are important because they provide actors involved in planning with an understanding of what the problem they have to solve is (…). More specifically, they play a central role in planning because they “can be powerful agents or aids in the service of change, as shapers of a new imagination of alternatives.” (….) stories are the very stuff of planning, which, fundamentally, is persuasive and constitutive storytelling about the future.” (…)

The underlying logic is that of a purely data-driven, almost mechanical model of urban management that is overly simplistic and neither political, nor does it require expert matters. This logic is inherently faulty. Essentially, it disposes with the messiness that humans and all their pesky complex socio-cultural issues.

In this approach, cities are no longer made of different – and to a large extent incommensurable – socio-technical worlds (education, business, safety and the like) but as data within systemic processes. (…) As a result, the analysis of these ‘urban themes’ no longer seem to require thematic experts familiar with the specifics of a ‘field’ but only data- mining, data interconnectedness and software-based analysis.

So: Governance poor, underlying logic poor. What could possibly go wrong.

A better way to approach smart city planning

In order to think better, more productively about how to approach smart cities, we need to step back and look at the bigger picture.

If you follow my tweets or my newsletter, you’ll have encountered the Vision for a Shared Digital Europe before. It’s a proposed alternative for anything digital in the EU that would, if adopted, replace the EU’s Digital Single Market (DSM). Where the EU thinks about the internet, it’s through this lens of the DSM — the lens of markets first and foremost. the Vision for a Shared Digital Europe (SDE) however proposes to replace this logic of market first through 4 alternative pillars:

  • Cultivate the Commons
  • Decentralize infrastructure
  • Enable self-determination
  • Empower public institutions

Image: Vision for a Shared Digital Europe (shared-digital.eu)

I think these 4 pillars should hold up pretty well in the smart city planning context. Please note just how different this vision is from what Sidewalk Labs (and the many other smart city vendors) propose:

  • Instead of publicly available spaces we would see true commons, including but not limited to space.
  • Instead of centralized data collection, we might see decentralization, meaning a broader, deeper ecosystem of offerings and more resilience (as opposed to just more efficiency).
  • Instead of being solicited for “community input”, citizens would actively shape and decide over their future.
  • And finally, instead of working around (or with, to a degree) public administrations, a smart city after this school of thought would double down on public institutions and give them a strong mandate, sufficient funding, an in-house capacity to match the industry’s.

It would make for a better, more democratic and more resilient city.

So I just want to put this out there. And if you’d like to explore this further together, please don’t hesitate to ping me.

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.

Thanks and Happy Holidays: That was 2017

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This is end-of-year post #10 (all prior ones here). That’s right, I’ve been writing this post every year for ten years in a row!

So what happened in 2017? Let’s have a look back: Part work, part personal. Enjoy.

Globally speaking I’d file 2017 under shitty year. So much so that I’ll try not to go into anything global or all too political here. But in terms of work it’s been quite interesting and impactful, and personally it’s been a pretty damn great year.

So, right to it!

The theme for 2017

Last year I wrote (and I’m paraphrasing to keep it short):

“(…) even in hindsight 2016 didn’t have one theme as such, but rather a few in parallel: 1) Growth & stabilization, in the business generally speaking, but also and specifically in all things related to ThingsCon. 2) Lots and lots of collaborations with close friends, which I’m grateful for. 3) Also, 2016 was a year for a bit of overload, I may have spread myself a little thin at times.”

Again, lots of collaboration with old and new friends. But this year I was a lot more focused, with lots of research that allowed me to go deep. I’d say in 2017, the theme was first and foremost impact. Impact through large partners, through policy work, through investments into research.

My work was with some large partners with big picture themes, like our work with Mozilla on trustmarks for the internet of things.

I hope to continue this high-impact work in one way or another.

Friends and family

Overall a bit of a mixed bag.

The bad: Some family members had health issues. Some friends received some nasty diagnoses.

The good: Some of the health issues were solved, we got to spend lots of time with close friends and family. Also, lots of babies were born among our friends, including one of our own. Welcome, little K! To be honest, this alone would make me love 2017. So yay, personal 2017!

Travel

For years I had been trying to cut down a little on travel to a somewhat more sustainable level. It kinda-sorta worked in 2017, at least a little bit. Still ways to go, but it’s a start.

Looking at my Tripit, this is what comes up. Tripit stats are a little fuzzy. (Did I mention I still miss Dopplr?) As far as I can reconstruct it on the quick, including vacation time I traveled to 7 countries on just 9 trips, and spent about 89 days traveling. (As opposed to 21 trips to 12 countries for a total of 152 days the year before.) So that’s great, even if it sounds like I might have missed a couple short trips.

pyrenees

Work

There was a lot going on in 2017, so I had to consult my monthnotes to refresh my memory. The focus is still, and ever more so, at the intersection of strategy, emerging technologies, and ethics/governance.

Lots of work around trustmarks and consumer trust generally speaking around the internet of things. Increasingly, artificial intelligence has also solidly established itself as part of the emerging tech canon I’ve been watching closely.

I wrote a lot. I mean, a lot. And I’ve enjoyed it tremendously. Outside my blog and some project-related newsletters and Twitter I did some long and short form writing:

If the writing is part of my overall communications landscape, then so is my website. So I relaunched that completely and restructured it for much more clarity.

I also got to work more with foundations, which is always fun. From workshops with Boell Foundation to research for Mozilla Foundation, the non-commercial, impact-driven sector is certainly an area I’d like to spend more time in.

Very Fun Side Projects

Then there are two “side projects” that have been especially fun this year: ThingsCon and Zephyr.

ThingsCon, our global community on a mission to foster the creation of a responsible & human-centric IoT, has been growing steadily. Milestones in 2017 include:

  • Another research trip to Shenzhen, the Silicon Valley of hardware.
  • We had a bunch of ThingsCon-labeled publications, including about Shenzhen and IoT trustmarks: View Source: Shenzhen, The State of Responsible IoT, A Trustmark for IoT.
  • We launched the ThingsCon Fellowship Program to recognize achievements and commitment that advance the ThingsCon mission of fostering the creation of a responsible and human-centric IoT generally, and support for the ThingsCon community specifically. Shout-out to our most excellent six initial fellows, Alexandra Deschamps-Sonsino, Ame Elliott, Dries de Roeck, Iohanna Nicenboim, Michelle Thorne and Ricardo Brito. I hope we’ll get the fellowship program into full swing in 2018!
  • New cities with salons or conferences around the world. Let me use stats from November: At that point ThingsCon events have happened in 20 cities across 12 countries, from Berlin to Brussels to Amsterdam and Milan to London and Shanghai to Austin and Copenhagen and Nairobi.

I can’t possibly tell you how awesome this is for me to watch and experience. Learn more at thingscon.com.

Zephyr Berlin, the trousers/pants project M and I launched on Kickstarter just over a year ago, continues to be a lot of fun. Just a few weeks back we produced another small batch of men’s trousers, this time with super deep pockets to make things like cycling with large phones super easy. So there’s a new batch of men’s, and a very small number of women’s available. Check out zephyrberlin.com to learn more.

Conferences

A lot less conference work this year. What I did in terms of conferences was mostly for ThingsCon. I always enjoyed conferences (both the curation and the planning, but the curation much more than the planning), but not having a conference to plan isn’t too bad either, to be honest. A lot of my other work, especially the writing, would not have been possible if I had committed to another conference.

As a directly related note, without the fantastic, lovable, smart and endlessly committed ThingsCon Amsterdam crew and their annual ThingsCon event (it just happened for the fourth time!), ThingsCon also wouldn’t be what it is today. My eternal thanks go to Iskander, Marcel & Monique and their team.

Speaking

As part of my cutting down on conference travel, I gave just a few talks in 2017. Most of them focused on IoT and consumer trust.

There were a few at ThingsCon events like in Berlin and Shenzhen, others were at Underexposed, TU Dresden, Netzpolitik conference, DevOpsCon, and Transatlantic Digital Debates. There were also a few (paid) in-house talks.

Media

It was a pretty good year for media and writing. Among others, my thoughts or projects were mentioned/quoted/referenced/etc on CNN, SPIEGEL, and WIRED. I had some interviews—the lovely conversation for Markus Andrezak’s Stories Connected Dots stands out to me.

Things started and discontinued

Started:

  • Writing more, if you’ll forgive me going so meta.

Continued:

  • Zephyr Berlin, producing pants that travel extremely well.
  • ThingsCon as an event platform, and growing it beyond that into other areas of engagement.

Discontinued:

  • My Facebook account, just now as I’m writing this. Bye bye Facebook. You feel like Old Social Media by now, not worth having around.

Books read

Read an okay, but not great amount. I think it was pretty much these: WTF, Tim O’Reilly. Control Shift, David Meyer. The Rings of Saturn, W. G. Seibald. Wiener Straße, Sven Regener. Go: Die Mitte des Himmels, Michael H. Koulen. Babyjahre, Remo H. Largo. American Gods, Neil Gaiman. Death’s End, Deep Forest, The Three-Body Problem, Cixin Liu. Goldene Unternehmerregeln, Bihr & Jahrmarkt. Schadenfreude, Rebecca Schuhman. Rapt, Winifred Gallagher. Shoe Dog, Phil Knight. The Story of My Teeth, Valeria Luiselli. Snuff, Terry Pratchett . Deep Work, Cal Newport. Bonk, Mary Roach. The Power and the Glory, Graham Greene. The Industries of the the Future, Alec Ross.

Firsts & some things I learned along the way

Firsts: Wrote a ton of long form and launched it properly. Cut an umbilical cord. Diapered a newborn. Merged photo libraries.

Learned: How to communicate my work (focus, offering, structure) better (as the website will demonstrate). To make time for writing, thinking, processing input. Some Python. Some more about tech policy. These are all qualitative upgrades in my book.

So what’s next?

It looks like 2018 might bring a fantastic opportunity to continue some of my work from this year and before in a big-impact context; if this happens, I’ll be extremely happy. (If not, I’ll continue chipping away at the same issues with all the means available to me.) I hope to continue doing lots of research and writing. I’ll take some parental leave at some point, and otherwise spend as much time as I can with the baby. (They grow up so fast, as I’m learning even now, after not even a month.) Some travel, and hopefully once more a month or two spent working from a new place.

I’m always up for discussing interesting new projects. If you’re pondering one, get in touch!

But for now, I hope you get to relax and enjoy the holidays!

Focus areas over time

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The end of the year is a good time to look back and take stock, and one of the things I’ve been looking at especially is how the focus of my work has been shifting over the years.

I’ve been using the term emerging technologies to describe where my interests and expertise are, because it describes clearly that the concrete focus is (by definition!) constantly evolving. Frequently, the patterns become obvious only in hindsight. Here’s how I would describe the areas I focused on primarily over the last decade or so:

focus areas over time Focus areas over time (Image: The Waving Cat)

Now this isn’t a super accurate depiction, but it gives a solid idea. I expect the Internet of Things to remain a priority for the coming years, but it’s also obvious that algorithmic decision-making and its impact (labeled here as artificial intelligence) is gaining importance, and quickly. The lines are blurry to begin with.

It’s worth noting that these timelines aren’t absolutes, either: I’ve done work around the implications of social media later than that, and work on algorithms and data long before. These labels indicated priorities and focus more than anything.

So anyway, hope this is helpful to understand my work. As always, if you’d like to bounce ideas feel free to ping me.

Interview with Netzpolitik.org: Regulierung und Datenschutz im Internet der Dinge

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In September I spoke at Netzpolitik’s annual conference, Das ist Netzpolitik. While I was there, Netzpolitik.org also recorded an interview with me: “Regulierung und Datenschutz im Internet der Dinge“.

A big thank you to Netzpolitik and Stefanie Talaska for the conversation!

IoT, artificial intelligence, and digital transformation are all intimately related

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Here at The Waving Cat, we’re in the business of analyzing the impact of emerging technologies and finding ways to harness their opportunities. This is why our services include both research & foresight and strategy: First we need to develop a deep understanding, then we can apply it. Analyze first, act second.

Over the last few years, my work has mostly homed in on the Internet of Things (#IoT). This is no coincidence: IoT is where a lot of emerging technologies converge. Hence, IoT has been a massive driver of digital transformation.

IoT has been a massive driver of digital transformation.

However, increasingly the lines between IoT and other emerging technologies are becoming ever-more blurry. Concretely, data-driven and algorithmic decision-making is taking on a life on its own, both within the confines of IoT and outside of them. Under the labels of machine learning (#ML), artificial intelligence (#AI), or the (now strangely old school moniker) big data we’ve seen tremendous development over the last few years.

The physical world is already suffused with data, sensors, and connected devices/systems, and we’re only at the beginning of this development. Years ago I curated a track at NEXT Conference called the Data Layer, on the premise that the physical world will be covered in a data layer. Now, 5 years or so later, this reality has absolutely come to pass.

IoT with its connected devices, smart cities, connected homes, and connected mobility is part of that global infrastructure. No matter if the data crunching happens in the cloud or at the edge (i.e. close to where the data is captured/used), more and more has to happen implicitly and autonomously. Machine learning and AI play an essential role in this.

Increasingly, artificial intelligence is becoming a driver of digital transformation

Most organizations will need to develop an approach to harnessing artificial intelligence, and so increasingly artificial intelligence is becoming a driver of digital transformation.

As of today, Internet of Things, artificial intelligence & machine learning, and digital transformation are intimately connected. You can’t really get far in one without understanding the others.

These are exciting, interesting times, and they offer lots of opportunities. We’re here to help you figure out how to harness them.