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New Report: “Towards a European AI & Society Ecosystem”

By Peter Bihr
In AI, policy, work
5 Min read
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I’m happy to share that a new report I had the joy and privilege to co-author with Leonie Beining and Stefan Heumann (both of Stiftung Neue Verantwortung) just came out. It’s titled:

“Towards a European AI & Society Ecosystem”

I’m including the executive summary below, you can find the full report here. The report is co-produced by Stiftung Neue Verantwortung and ThingsCon.

Here’s the executive summary:

Artificial Intelligence (AI) has emerged as a key technology that has gripped the attention of governments around the globe. The European Commission has made AI leadership a top priority. While seeking to strengthen research and commercial deployment of AI, Europe has also embraced the role of a global regulator of technology, and is currently the only region where a regulatory agenda on AI rooted in democratic values – as opposed than purely market or strategic terms – can be credibly formulated. And given the size of the EU’s internal market, this can be done with a reasonable potential for global impact. However, there is a gap between Europe’s lofty ambitions and its actual institutional capacity for research, analysis and policy development to define and shape the European way on AI guided by societal values and the public interest. Currently the debate is mostly driven by industry, where most resources and capacity for technical research are located. European civil society organizations that study and address the social, political and ethical challenges of AI are not sufficiently consulted and struggle to have an impact on the policy debate. Thus, the EU’s regulatory ambition faces a serious problem: If Europe puts societal interests and values at the center of its approach towards AI, it requires robust engagement and relationships between governments and many diverse actors from civil society. Otherwise any claims regarding human-centric and trustworthy AI would come to nothing.

Therefore, EU policy-making capacity must be supported by a broader ecosystem of stakeholders and experts especially from civil society. This AI & Society Ecosystem, a subset of a broader AI Ecosystem that also includes industry actors, is essential in informing policy-making on AI, as well as holding the government to its self-proclaimed standard of promoting AI in the interest of society at large. We propose the ecosystem perspective, originating from biology and already applied in management and innovation studies (also with regard to AI). It captures the need for diversity of actors and expertise, directs the attention to synergies and connections, and puts the focus on the capacity to produce good outcomes over time. We argue that such a holistic perspective is urgently needed if the EU wants to fulfil its ambitions regarding trustworthy AI. The report aims to draw attention to the role of government actors and foundations in strengthening the AI & Society Ecosystem.

The report identifies ten core functions, or areas of expertise, that an AI & Society Ecosystem needs to be able to perform – ten areas of expertise where the ecosystem can contribute meaningfully to the policy debate: Policy, technology, investigation, and watchdog expertise; Expertise in strategic litigation, and in building public interest use cases of AI; Campaign and outreach, and research expertise; Expertise in promoting AI literacy and education; and sector-specific expertise. In a fully flourishing ecosystem these functions need to be connected in order to complement each other and benefit from each other.

The core ingredients needed for a strong AI & Society Ecosystem already exist: Europe can build on strengths like a strong tradition of civil society expertise and advocacy, and has a diverse field of digital rights organizations that are building AI expertise. It has strong public research institutions and academia, and a diverse media system that can engage a wider public in a debate around AI. Furthermore, policy-makers have started to acknowledge the role of civil society for the development of AI, and we see new funding opportunities from foundations and governments that prioritize the intersection of AI and society.

There are also clear weaknesses and challenges that the Ecosystem has to overcome: Many organizations lack the resources to build the necessary capacity, and there is little access to independent funding. Fragmentation across Europe lowers the visibility and impact of individual actors. We see a lack of coordination between civil society organizations weakening the the AI & Society Ecosystem as a whole. In policy-making there is a lack of real multi-stakeholder engagement and civil society actors often do not have sufficient access to the relevant processes. Furthermore, the lack of transparency on where and how AI systems are being used put additional burden on civil society actors engaging in independent research, policy and advocacy work.

Governments and foundations play a strong role for the development of a strong and impactful AI & Society Ecosystem in Europe. They provide not only important sources of funding on which AI & Society organizations depend. They are also themselves important actors within that ecosystem, and hence have other types of non-monetary support to offer. Policy-makers can, for example, lower barriers to participation and engagement for civil society. They can also create new resources for civil society, e.g. by encouraging NGOs to participate in government funded research or by designing grants especially with small organizations in mind. Foundations shape the ecosystem through broader support including aspects such as providing training and professional development. Furthermore, foundations are in the position to act as convener and to build bridges between different actors that are necessary in a healthy ecosystem. They are also needed to fill funding gaps for functions within the ecosystem, especially where government funding is hard or impossible to obtain. Overall, in order to strengthen the ecosystem, two approaches come into focus: managing relationships and managing resources.

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New Report: “Smart Cities: A Key to a Progressive Europe”

By Peter Bihr
In digital rights, IoT, policy, Smart Cities
1 Min read
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I’m happy to share that a report is out today that I had the honor and pleasure to co-author. It’s published jointly by the Foundation for European Progressive Studies (FEPS) and the Cooperation Committee of the Nordic Labour Movement (SAMAK).

The report is called “A Progressive Approach to Digital Tech — Taking Charge of Europe’s Digital Future.”

In FEPS’s words:

This report tries to answer the question how progressives should look at digital technology, at a time when it permeates every aspect of our lives, societies and democracies. (…)
The main message: Europe can achieve a digital transition that is both just and sustainable, but this requires a positive vision and collective action.

At its heart, it’s an attempt to outline a progressive digital agenda for Europe. Not a defensive one, but one that outlines a constructive, desirable approach.

My focus was on smart cities and how a progressive smart city policy could look like. My contribution specifically comes in the form of a stand-alone attachment titled:

“Smart Cities: A Key to a Progressive Europe”

I’d love to hear what you think. For now, enjoy the report!

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Cost-benefit analysis, Data-Driven Infrastructure edition

By Peter Bihr
In digital rights, IoT, policy, Smart Cities
3 Min read
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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 20in20:04.

It’s a common approach for making (business, policy…) decision by performing a cost-benefit analysis of some sort. Sometimes this is done via a rigorous process, sometimes it’s ballparked — and depending on the context, that’s OK.

One thing is pretty constant: In a cost-benefit analysis you traditionally work on the basis of reasonably expected costs and reasonably expected benefits. If the benefits outweigh the costs, green light.

Now, I’d argue that for data-driven infrastructure(-ish) projects, we need to set a higher bar.

By data-driven infrastructure I mean infrastructure(ish) things like digital platforms, smart city projects, etc. that collect data, process data, feed into or serve as AI or algorithmic decision-making (ADM) systems, etc. This may increasingly include what’s traditionally included under the umbrella of critical infrastructure but extends well beyond.

For this type of data-driven infrastructure (DDI), we need a different balance. Or, maybe even better, we need a more thorough understanding of what can be reasonably expected.

I argue that for DDI, guaranteed improvement must outweigh the worst case scenario risks.

If the last decade has shown us anything, it’s that data-driven infrastructure will be abused to its full potential.

From criminals to commercial and governmental actors, from legitimate and rogue, if there is valuable data then we’ll see strong interests in this honey pot of data. Hence, we need to assume at least some of those actors will get access to it. So whatever could happen when they do — which would differ dramatically depending on which types or which combination of types of actors does, obviously — is what we have to factor in. Also, the opportunity cost and expertise drain and newly introduced dependencies that come with vendor lock-in.

All of this — that level of failure — should be the new “reasonable” expectation on the cost side.

But in order to make semantic capture of the term “reasonable” a little bit harder, I’m proposing to be very explicit about what we mean by this:

So instead of “Let’s compare what happens if things go kinda-sorta OK on the benefit side and only go kinda-sorta wrong on the cost side”, let’s say “the absolutely guaranteed improvements on the benefit side must significantly outweigh the worst case failure modes on the costs side.”

For DDI, let’s work with aggressive-pessimistic scenarios for the costs/risk side, and conservative scenarios for the benefit side. The more critical the infrastructure, the more thorough we need to be.

That should make for a much more interesting debate, and certainly for more insightful scenario planning.

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Just enough City

By Peter Bihr
In IoT, policy, Smart Cities
8 Min read
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In this piece, I’m advocating for a Smart City model based on restraint, and focused first and foremost on citizen needs and rights.

A little while ago, the ever-brilliant and eloquent Rachel Coldicutt wrote a piece on the role of public service internet, and why it should be a model of restraint. It’s titled Just enough Internet, and it resonated deeply with me. It was her article that inspired not just this piece’s title but also its theme: Thank you, Rachel!

Rachel argues that public service internet (broadcasters, government services) shouldn’t compete with commercial competitors by commercial metrics, but rather use approaches better suited to their mandate: Not engagement and more data, but providing the important basics while collecting as little as possible. (This summary doesn’t do Rachel’s text justice, she makes more, and more nuanced points there, so please read her piece, it’s time well spent.)

I’ll argue that Smart Cities, too, should use an approach better suited to their mandate—an approach based on (data) restraint, and on citizens’ needs & rights.

This restraint and reframing is important because it prevents mission creep; it also alleviates the carbon footprint of all those services.

Enter the Smart City

Wherever we look on the globe, we see so-called Smart City projects popping up. Some are incremental, and add just some sensors. Others are blank slate, building whole connected cities or neighborhoods from scratch. What they have in commons is that they mostly are built around a logic of data-driven management and optimization. You can’t manage what you can’t measure, management consultant Peter Drucker famously said, and so Smart Cities tend to measure… everything. Or so they try.

Of course, sensors only measure so many things, like physical movement (of people, or goods, or vehicles) through space, or the consumption and creation of energy. But thriving urban life is made up of many more things, and many of those cannot be measured as easily: Try measuring opportunity or intention or quality of life, and most Smart City management dashboards will throw an error: File not found.

The narrative of the Smart City is based fundamentally that of optimizing a machine to run as efficiently as possible. It’s neoliberal market thinking in its purest form. (Greenfield and Townsend and Morozov and many other Smart City critics have made those points much more eloquently before.) But that doesn’t reflect urban life. The human side of it is missing, a glaring hole right in the center of that particular vision.

Instead of putting citizens in that spot in the center, the “traditional” Smart City model aims to build better (meaning: more efficient, lower cost) services to citizens by collecting, collating, analyzing data. It’s the logic of global supply chains and predictive maintenance and telecommunications networks and data analytics applied to the public space. (It’s no coincidence of the large tech vendors in that space come from either one of those backgrounds.)

The city, however, is no machine to be run at maximum efficiency. It’s a messy agora, with competing and often conflicting interests, and it needs slack in the system: Slack and friction all increase resilience in the face of larger challenges, as do empowered citizens and municipal administrations. The last thing any city needs is to be fully algorithmically managed at maximum efficiency just to come to a grinding halt when — not if! — the first technical glitch happens, or some company ceases their business.

Most importantly, I’m convinced that depending on context, collecting data in public space can be a fundamental risk to a free society—and that it’s made even worse if the data collection regime is outside of the public’s control.

The option of anonymity plays a crucial role for the freedom of assembly, of organizing, of expressing thoughts and political speech. If sensitive data is collected in public space (even if it’s not necessarily personably identifiable information!) then the trust in the collecting entity needs to be absolute. But as we know from political science, the good king is just another straw man, and that given the circumstance even the best government can turn bad quickly. History has taught us the crucial importance of checks & balances, and of data avoidance.

We need a Smart City model of restraint

Discussing publicly owned media, Rachel argues:

It’s time to renegotiate the tacit agreement between the people, the market and the state to take account of the ways that data and technology have nudged behaviours and norms and changed the underlying infrastructure of everyday life.

This holds true for the (Smart) City, too: The tacit agreement between the people, the market and the state is that, roughly stated, the government provides essential services to its citizens, often with the help of the market, and with the citizens’ interest at the core. However, when we see technology companies lobby governments to green-light data-collecting pilot projects with little accountability in public space, that tacit agreement is violated. Not the citizens’ interests but those multinationals’ business models move into the center of these considerations.

There is no opt-out in public space. So when collecting meaningful consent to the collection of data about citizens is hard or impossible, that data must not be collected, period. Surveillance in public space is more often detrimental to free societies than not. You know this! We all know this!

Less data collected, and more options of anonymity in public space, make for a more resilient public sphere. And what data is collected should be made available to the public at little or no cost, and to commercial interests only within a framework of ethical use (and probably for a fee).

What are better metrics for living in a (Smart) City?

In order to get to better Smart Cities, we need to think about better, more complete metrics than efficiency & cost savings, and we need to determine those (and all other big decisions about public space) through a strong commitment to participation: From external experts to citizens panels to digital participation platforms, there are many tools at our disposal to make better, more democratically legitimized decisions.

In that sense I cannot offer a final set of metrics to use. However, I can offer some potential starting points for a debate. I believe that every Smart City projects should be evaluated against the following aspects:

  • Would this substantially improve sustainability as laid out in the UN’s Sustainable Development Goals (SGD) framework?
  • Is meaningful participation built into the process at every step from framing to early feedback to planning to governance? Are the implications clear, and laid out in an accessible, non-jargony way?
  • Are there safeguards in place to prevent things from getting worse than before if something doesn’t work as planed?
  • Will it solve a real issue and improve the life of citizens? If in doubt, cut it out.
  • Will participation, accountability, resilience, trust and security (P.A.R.T.S.) all improve through this project?

Obviously those can only be starting points.

The point I’m making is this: In the Smart City, less is more.

City administrations should optimize for thriving urban live and democracy; for citizens and digital rights — which also happen to be human rights; for resilience and opportunity rather than efficiency. That way we can create a canvas to be painted by citizens, administration and — yes! — the market, too.

We can only manage what we can measure? Not necessarily. Neither the population or the urban organism need to be managed; just given a robust framework to thrive within. We don’t always need real time data for every decision — we can also make good decision based on values and trust in democratic processes, and by giving a voice to all impacted communities. We have a vast body of knowledge from decades of research around urban planning and sociology, and many other areas: Often enough we know the best decisions and it’s only politics that keeps us from enacting them.

We can change that, and build the best public space we know to build. Our cities will be better off for it.

About the author

Just for completeness’ sake so you can see where I’m coming from, I’m basing this on years of working at least occasionally on Smart City projects. My thinking is informed by work around emerging tech and its impact on society, and a strong focus on responsible technology that puts people first. Among other things I’ve co-founded ThingsCon, a non-profit community that promotes responsible tech, and led the development of the Trustable Technology Mark. I was a Mozilla Fellow in 2018-19 and am an Edgeryders Fellow in 2019-20. You can find my bio here.

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The Tragedy of Future Commons

By Peter Bihr
In commons, policy, Smart Cities
3 Min read
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I can’t help but thinking that so many of today’s debates – from climate change to smart city governance and AI ethics – are so much more connected than we give them credit for. I might be projecting, but in my mind they’re just variations of one simple theme:

Do we narrow or broaden the future options space? In others words, will we leave the next generation, the public sector, or the other people around us more options or less options? Do we give them agency or take it away? And how can it ever be ok to act in a way that takes away future generations’ options? That strips governments of their chances to deliver services to their citizens?

It’s essentially the Tragedy of the Commons as applied to the time axis: The Tragedy of Future Commons. And we can choose very deliberately to strengthen the commons (now and for the future), to strengthen future generations in the face of climate change (where we might have hit another tipping point), to strengthen city governments in their ability to govern and deliver services by not hollowing them out, etc. etc. etc..

What actions that requires of us depends heavily on context of course: AI to be made with more participation and civil society involved so as to mitigate risks. Smart cities to prioritize public ownership and accountability so the city doesn’t lose its influence to the private sector. Climate change to be at the top of all our priority lists in order to give our future selves and future generations more and better options to shape their world and thrive in it.

Too often we’re stuck in debates that are based, essentially, in yesterday’s world. We need to realize the situation we’re in so as to avoid false choices. It’s not “climate or business”, it’s “climate or no business”. It’s not “climate or civil rights”, but “climate or no civil rights”. Radical changes are coming our way, and I’d rather shape them with intention and some buffer to spare rather than see them imposed on us like gravity imposed on Newton’s fabled apple.

So let’s aim for the opposite of the Tragedy of the Commons, whatever that might be called. The Thriving of the Commons?

And if you need a framework that’s decidedly not made for this purpose but has been holding up nicely for me, look to the Vision for a Shared Digital Europe (SDE) for inspiration. It lays out 4 pillars that I find pretty appealing: Cultivate the Commons; Decentralize Infrastructure; Enable Self-Determination; Empower Public Institutions. The authors drafted it with the EU’s digital agenda in mind (I was a very minor contributor, joining at a later stage). But I think it can apply meaningfully to smart cities just as much as it does to AI development and climate change and other areas. (Feel free to hit up the team to see how they might apply to your context, or reach out to me and I’ll be happy to put you in touch.) Those are good principles!

Note: This piece is cross-posted from my weekly newsletter Connection Problem, to which you can sign up here.

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

By Peter Bihr
In connected world, digital rights, IoT, policy, Smart Cities
1 Min read
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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.

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The Waving Cat