I have been thinking a lot lately about the increasing importance of the “public data layer” — meaning, data that we will need (“we” applied broadly, meaning the general public, NGOs, government, scientists, journalists) to make sense of what’s going on in and increasingly busy, but increasingly quantifiable world.

First, some of the drivers here. In general, there is more data being generated than ever before, so much of which has a bearing on “public” issues. A few of the specific drivers include:

• Increasing role of “platforms” in regulated spaces (transportation, health, finance, education, etc) — these are enormous generators of data with direct and indirect bearing on public issues.
• Sensors & IoT (publicly and privately owned) — same as above.
• Abundance of media — as we have seen with the recent US election, the rise of social & independent media is democratizing but also problematic.
• Personal health data — the cost of gene sequencing is dropping like a rock, which will lead to an explosion of health data. This data will provide personal value but can also provide enormous societal value.

Why this will be important? Because all of these data have the potential to increase collective intelligence and societal knowledge. And more specifically, we have the potential to redesign the way we make policy and handle regulation given these inputs. If we do this right, we can get smarter at policymaking, and design regulatory systems that have both greater effectiveness and lower costs of implementation and compliance.

So, what infrastructure will we need to handle and process all of this public data? This seems to be forming into a few broad categories:

• Data pooling & analysis platforms — tools and APIs that make sense of these data — generic/foundational tools like Composable Analytics and Stae, and more specific, vertically-oriented projects & tools, like OpenTraffic and Aerostate.
• “Regulation 2.0” platforms — specifically designed to facilitate a data-driven policymaking and regulatory process — for example, MeWe, Airmap, SeamlessGov.
• Foundational and application-layer blockchains — on the pure tech side, this is the most interesting area of development. Blockchains give us both public data access and data integrity in a way that’s not been possible before. Much of the focus is still on “foundational” blockchains like Bitcoin, Ethereum, Tezos and Zcash, but eventually this technology will reach the application layer and we’ll have more explicitly “public” applications. I also expect that Blockchains and Regulation 2.0 platforms will get ever closer and ultimately merge.
• Mechanisms for identifying and amplifying truth — this is a tough, but important one. We have two problems, in parallel: First, how to we discern truth from untruth? And second: how do we give truth the attention it needs to “win”? The big platforms like Facebook are experimenting with this now, and we’ll likely see more tools and services that help with this.

That’s the vision — where it seems clear that we are heading, and where we need to head. So, the more important question is, how will we actually get there? A bunch of questions/thoughts on my mind are:

• Broad vs narrow? Strikes me that we will see the most traction in narrow applications first — the thin edge of the wedge, that solves a concrete problem. Also, the “personal data layer” hasn’t arrived in one broad platform either.
• Open standards + distribution magnets: dating back to my work around open transit data, a key learning was that open standards need distribution magnets. The thing that got transit agencies to publish data in the open GTFS format was Google Maps.
• Portal access vs. real access — the natural tendency of data owners is to offer access via siloes and portals (e.g., Uber Movement). This is something, but’s not the real thing — the more important question is how to get actual data moving.
• Government isn’t the only audience: public data is of course useful for policymaking and regulation, but it’s equally important for scientific research and journalism. These areas could end up being the initial leaders.

That’s it for now. More to come. For some more context on my thinking here, see Regulating with Data and Alternative Compliance.

People often ask me how I ended up working in venture capital, and more specifically in a role that deals with policy issues (“policy” broadly speaking, including public policy, legal, “trust & safety”, content & community policy, etc.). Coming from a background as a hacker / entrepreneur with an urban planning degree, how I ended up here can be a little bit puzzling.

The way I like to describe it is this:

From the beginning, I’ve been fascinated with the “experience” of things — the way things feel. Things meaning products, places, experiences etc. I’ve always been super attuned to the details that make something “feel great”, and I’d say the overriding theme through everything I’ve done is the pursuit of the root cause of “great experiences”.

From there, I naturally have been drawn to design: the physical construction of things. I love to make and hack, and I geek out over the minor design details of lots of things, whether that’s the seam placement on a car’s body panels, or the design of a crosswalk, or the entrance to a building, or the buttery UI of an app. Design is the place where people meet experience.

But over time, I came to realize something else: what we design and how we design it is not an island unto itself. It’s shaped — and enabled, and often constrained — by the rules and policies that underly the design fabric. That’s true for cars, parks, buildings, cities, websites, apps, social networks, and the internet. The underlying policy is the infrastructure upon which everything is built.

This first really hit me, right after college (16 years ago now), when I was reading Cities Back from the Edge: New Life for Downtown, a book chronicling the revitalization of many smaller downtowns across America, written by my old friend Norman Mintz. Before I started the book, my main thinking was: “I want to be an architect, because architects design places”. Norman had told me “you don’t want to be an architect.” But I didn’t believe him. But I distinctly remember, about halfway through the book, having an a-ha moment, where I scrawled in the margin: “I don’t want to be an architect! I want to do this!”. Where this was engaging in the planning and community engagement process that ultimately shaped the design. It hit me that this is where the really transformative decisions happened.

I spent the next three years at Project for Public Spaces, working on the design of public spaces across the US (including Times Square and Washington Square Park in NYC), with an emphasis on the community process that shaped the policies, that would shape the design, that would determine the experience. The goal was all about experience, but the guiding philosophy at PPS was that you got to great experience by engaging at the people/community/policy level, and letting the design grow from there.

Being a hacker and builder, I’ve always been drawn to computers and the internet. During my 6 years leading the “labs” group at OpenPlans, a now-shuttered incubator for software and media businesses at the intersection of cities, data, and policy, I made a similar journey — from experience, to design, to policy — but this time focused on tech & data policy and the underpinnings of that other world we inhabit: the Internet. I started out building product — head in the code, focused on the details — and emerged focusing on issues like open data policy, open standards, and how we achieve an open, accessible, permissionless environment for innovation. The most satisfying achievement at OpenPlans was working with NYC’s MTA (which operates the buses and subways) to overhaul their data access policies, and then helping to build the cities first real-time transit API.

So the common thread is: great places (physical AND virtual) are a joy and a pleasure to inhabit. Creating them and cultivating them is an art, more than a science, and is a result of the Experience ↔ Design ↔ Policy dynamic.

To apply this idea a little further to the web/tech world: I think of the “policy” layer as including public policy issues (like copyright law or telecom policy) which affect the entire ecosystem, but also — and often, more importantly — internal policy issues, like a company’s mission/values, community policies, data/privacy policies, API policies, relationship to adjacent open source communities, etc. These are the foundation upon which a company (or community, in the case of a cryptocurrency) are built, and the more thoughtfully and purposefully designed these are, the easier time the company/community will have in making hard decisions down the road.

So if you think of companies like Kickstarter, or Etsy, or DuckDuckGo (all USV portfolio companies), they’ve invested considerable effort into their policy foundations.

But it’s not just “feel good” or “fuzzy bunny”, mission-driven companies that this applies to. USV portfolio company Cloudflare announced yesterday that they’ve been fighting a National Security Letter from the FBI, under gag order, since 2013, in order to protect their users’ data, reinforcing their longstanding commitment to their users. This **very hard** decision was borne directly from the hard work they did at the founding of the company, to ground their activities (and the subsequent design of their product, and the experience they provide to their users) in foundational policy decisions.

Or look at all the trouble that Twitter has been having recently combating the abuse problem. Or Facebook with the fake news problem. Policy in the spotlight, with a huge impact on product, design and experience.

Or look at the internal turmoil with the Bitcoin and Ethereum communities over the past 12 months as they’ve dealt with very difficult technical / political decisions. Lucky for us, there is so much innovation in this space, and every new cryptocurrency that launches is learning from these examples — take Tezos, an emerging cryptocurrency that explicitly ships with mechanisms to handle future governance issues (democracy, coded).

So I guess the purpose of this post is to draw that through line, from Experience, to Design, to Policy, and show how it actually shapes nearly everything we encounter every day. What a profound and exciting challenge.

I’ve been struck recently by the power and surprise of unintended consequences.

For example, a recent Slate article digs into flip side of the life-saving potential of automated vehicles: our reliance on car crash deaths for organ donors:

“An estimated 94 percent of motor-vehicle accidents involve some kind of a driver error. As the number of vehicles with human operators falls, so too will the preventable fatalities. In June, Christopher A. Hart, the chairman of the National Transportation Safety Board, said, “Driverless cars could save many if not most of the 32,000 lives that are lost every year on our streets and highways.” Even if self-driving cars only realize a fraction of their projected safety benefits, a decline in the number of available organs could begin as soon as the first wave of autonomous and semiautonomous vehicles hits the road—threatening to compound our nation’s already serious shortages.” [#]

Or, with gene editing, what if we are successful at eradicating illness and preserving life forever? What new challenges will that present? How will we eat? How will we not consume all of earth’s natural resources? Or perhaps the life-saving potential will ultimately be canceled out by the life-harming potential — it’s clearly just as possible to use gene editing to weaponize mosquitos as it is to sterilize them.

Or, with the democratization of media — on the one hand radically increasing freedom of expression, but also laying the foundation for the “fake news” problem. I don’t think anyone who believed in the power of social networks to enable free speech and political organizing online really saw that coming, and it’s a real, hard problem.

Or, with artificial intelligence — how do we avoid being blinded by the shiny newness of helpful automation while ignoring potential existential threats? Bill Gates on that subject:

“I am in the camp that is concerned about super intelligence,” Gates wrote. “First the machines will do a lot of jobs for us and not be super intelligent. That should be positive if we manage it well. A few decades after that though the intelligence is strong enough to be a concern. I agree with Elon Musk and some others on this and don’t understand why some people are not concerned.” [#]

All of these consequences are made more serious by the fact that in a connected world, change can take place very very quickly, and it can be hard, or impossible to manage or roll back. A single person in a single place now has more power to impact the world (the whole world!) than ever before. As Kevin Esvelt, the geneticist who is the subject of the New Yorker article linked above said: “as a single scientist, I can alter an organism in a laboratory that will have more of an effect on all your lives than anything the legislature across the river can do.” [#]

So what to do? These kinds of changes are coming (seemingly) faster than ever. I like Esvelt’s suggestion that, in the case of gene editing, we should be building “undo” functionality into anything we deploy:

“With CRISPR and gene-drive technology, it might be possible for just one engineered mosquito, or fly, or any other animal or seed, to eventually change the fundamental genetics of an entire species. As Esvelt puts it, “A release anywhere could be a release everywhere.” Recognizing the possibility of an irreversible error, however, he and Church, in their earliest experiments, began to build drives capable of restoring any DNA that had been removed. Both say that if an edit cannot be corrected it should not be attempted. They also suggest retaining, in its original form, some part of any population that has been edited—a kind of molecular Noah’s Ark.” [#]

That’s one approach that seems reasonably and will hopefully be effective, at least in some cases. But for most of what we’re doing there is no natural “undo” function, so we must think about other ways to manage, or at the very least, quantify and understand, the consequences of what we’re making.

I’m in SF this week with the USV team – once a year we all come out here together, do a bunch of meetings and social events w our portfolio.

Yesterday struck me — and it’s amazing how much of a surprise this is to me, after doing this nearly 5 years — with just how exciting it is to be around people who are executing hard against a big vision. Four meetings yesterday, with four companies at different stages of development, but the common theme: founders who are going after it. Big problem, big opportunity, big fix. Man, it’s exciting.

The week before last, my in-laws were hit by a truck while crossing the street after dinner.

The time since has been a disorienting whirlwind of sadness, fear, hope and thankfulness. My mother-in-law suffered a very serious brain injury, and while she has cleared the first hurdle of basic survival, the outlook won’t be clear for quite some time. It’s been enormously trying on the whole family, and will continue to be for a long time; maybe forever.

The issue I want to reflect on here is how, in the face of previously unimaginable circumstances, we seem to have the ability to quickly reset to the new normal. Two weeks ago it was unthinkable that this would have happened and she’d be in this condition, and now, that’s just how things are — that’s where we’re starting from and it’s what we have to work with.

I find that encouraging, and also a little bit scary. On the one hand, it shows how adaptable humans are, how we can handle more than we might think. On the other hand, it shows how fragile any current environment or situation can be. I’m inspired by our ability to take things in stride, and also a little bit terrified by the reality of how quickly things can change.

For instance, lots of the talk this election cycle has been drawing parallels between now and the WWII era, in particular looking at what people did or didn’t do to stop the rise of Hitler. As with Trump today, Germans of the 1930s didn’t take Hitler seriously, and I’m sure couldn’t believe that such a radical change in national character could happen so quickly. Whether or not you find that comparison fair, the point is that things can change quickly (or seemingly quickly).

Given that, I’m thinking about two things:

First, man you gotta appreciate what you have when you have it. Looking back at photos from two weeks ago, or thinking about the last time we saw each other a day before the accident — that’s a lifetime ago now. And it’s cliche, but realizing how quickly things can change really helps you motivate to appreciate what you have. Whether that’s family, friends, democracy, or the environment (however imperfect each may be). For the past week, every time I’ve been snuggled up with my kids & my wife, or enjoying a moment with a friend, or tackling an interesting work-related issue, I’ve been hyper aware of how awesome is to be alive and doing that.

Second, maybe change isn’t so scary after all. Someone once explained this to me as pain x resistance = suffering. We burn a lot of effort and energy worrying about what might happen and what it might mean, resisting any exposure to pain. But this is ineffective and counterproductive, and in fact only increases our suffering. When bad things actually do happen, we face the pain and move through it, and only then are then able to build up. This is hard to internalize, especially with smaller things on a day-to-day basis, but I think there’s something there to grab onto.

To sum up, I just want to say thank you to everyone that has been supporting us through this time, and also thank you to everyone out there putting one foot in front of the other to get through every day, no matter what issues are dogging you.