Cryptocurrencies, Public Goods & the State

Late last year, I and a colleague from HKS were meeting with a VC I’d gotten to know in San Francisco. As an opening salvo in the conversation, the VC asked us “aren’t you worried about a cryptocurrency making the US dollar obsolete?”

I replied that if that such a threat became likely, the federal government might simply make cryptocurrencies illegal. So no, I wasn’t that worried.

The entrepreneur was incredulous — how could the government possibly stand in the way of something so broad and valuable? And, logistically, how could they actually stop anyone? My colleague, who has a few years on me and has served in senior government roles, chuckled. He remarked that the private ownership of gold bullion had been illegal in his lifetime.

My colleague’s point highlights a blind spot for the larger cryptocurrency (and possibly, the broader blockchain) community. In the excitement surrounding the rapid rise of cryptocurrencies and other blockchain technologies, the focus on decentralization, disintermediation and private benefit has come at the expense of a conversation about the enormous “public goods” the present financial system offers and the power of the state — on behalf of citizens — to protect the provision of said goods.

If cryptocurrencies are going to become important, the community backing them needs to spend time thinking about what systems need emerge around the technology that will provide at least some of the critical public goods created by the status quo. This is not a defense of the current financial and banking system. The status quo comes at great cost — high rents paid to financial intermediary institutions along with other various and protected oligarchies. However, it also provides benefits in the form of public goods. It generates and sustains core functions of the broader state and economy such as tools to capture tax revenues, prevent money laundering and terrorism financing, capacity to control the money supply, protect consumers and investors, and ensure market integrity and even (a degree of) financial stability.

In a world of cryptocurrencies, who will provide these public goods? This question arose in a conversation with Gary Gensler, the former Chair of the Commodity Futures Trading Commission in the Obama administration and current Senior Lecturer at MIT during a talk he gave at digital HKS here at the Harvard Kennedy School. Gensler identified some of the key features, challenges, and potential priorities for blockchain governance, and in one part of the discussion, he zoomed in on issue areas where public policy makers have urgent questions for cryptocurrency’s role:

• complying with the tax code;
• preventing money laundering;
• providing stability and market integrity;
• protecting consumers and investors.

There’s another way to read this list — as a catalogue of those public goods which, through hundreds of years of government, business, and democratic processes, we’ve agreed are priorities and values our finance and currency systems should reflect. But it is not clear if the current iterations of cryptocurrencies can provide the kind of integrity, laundering prevention, and tax compliance we’ve come to expect. Indeed, many of cryptocurrencies’ biggest advocates celebrate the fact that they will not.

When I talk to cryptocurrency and blockchain advocates, they usually tell me that the decentralized ledger will prevent excessive intrusion by government by making transactions anonymous and prevent excessive rents from going to financial institutions by dis-intermediating transactions. My counter is that people might like the concept of anonymity, and they may even hate their bank, but they like a functioning society and (relatively) stable financial markets a lot more. In fact, we’re usually willing to sacrifice some anonymity, or create governance systems (warrants) that impinge on them in exchange for public goods like law and order. Anonymity may be a concern for high net-worth individuals and money launderers, but I’ve yet to see evidence that the vast majority of the world’s citizens feel that absolute anonymity is an urgent issue to address. It’s true that the current financial system involves high rents paid to intermediary institutions — but one big reason is that society benefits from the market integrity, protection against laundering, and tax compliance that system provides. As consumers and citizens, at least some part of the rents we’re paying to the financial sector (and the decision to regulate that sector) reflect how much we value those public goods. I agree that the current system is imperfect (and the rents possibly too high), but if you dismantle the system to remove those costs, you are also dismantle the benefits.

When I talk to cryptocurrency advocates, they typically argue about privatebenefits but I want to hear more about the public benefits, either being created or sacrificed. That’s the conversation we need to focus on — because if we don’t, and cryptocurrencies take off, there is a real risk that national governments will respond in a way that’s both aggressive and counterproductive for all parties.

So far, governments have been relatively hands-off, and there aren’t signs of major legislative action on cryptocurrencies in the next few years. But part of that complacency has been tied to cryptocurrencies not yet threatening the status quo, and the growth trajectory we’re on could change that soon. If we can’t figure out how to ensure that cryptocurrencies create the public goods we expect of a financial and currency system, there’s a very real chance that governments won’t wait around; they’ll move to prohibition. Let me be very clear — I think this would be a terrible outcome for everyone involved. When government proscribes things that people like and find useful, it distorts behavior, can serve as an excuse to violate democratic norms in other areas, and wastes resources — and we’ve learned this through Prohibition and the War on Drugs. But unfettered financial markets without any consumer safety, investor protection, or integrity aren’t pretty either — and we should be very concerned about the equity implications of a new free-for-all.

I’m not calling for a cryptocurrency ban or suggesting it’s guaranteed to happen. Cryptocurrencies have incredible potential to transform not only the financial sector, but vast regions of life and public policy. But the blockchain community’s trumpeting of features they love without attention to the public goods that citizens actually value is dangerous for the future of this technology. We need to think critically about how to protect consumers in case these technologies become mainstream, so that we don’t have the same kinds of crises that have happened for taxi drivers that invested in medallions. We need to think about how cryptocurrencies will support the public funding and spending that benefits all of us, so that we aren’t just using collective dislike of the banking system to dismantle a system that provides us with important goods. Today, Gary Gensler is arguing that many cryptocurrencies are noncompliant securities and will be taken off the market, suggesting that the slumbering beast of government is finally awakening to police this space. We need to work hard to ensure that the beast focuses its work in the right direction: to use the advantages and efficiencies of blockchain technology to strengthen and protect the public goods that matter to all of us.

This piece was written by David Eaves, Lecturer in Public Policy at HKS and Ben McGuire, an HKS student.

Balancing Users, Platforms, and Buy-in Strategies for National Digital Teams

This week, digital HKS is partnering with Public Digital to convene digital services units from around the world. We will talk about what is and, more importantly, what is not working, with their work. Our intention is to make this an annual gathering where digital service groups can exchange learnings, explore shared challenges, converge around common language and frameworks and identify research questions.

Now this is not the end. It is not even the beginning of the end. But it is, perhaps, the end of the beginning.

We are at an interesting time for digital service units. One the one hand, the novelty and newness of these teams has worn off; on the other hand, there is growing acceptance by many governments that these teams are useful tool in driving new practices, particularly agile development processes and user centric design. Less clear, but still a possibility, is the key question of whether these units can enable the deeper digital transformation that will prompt a fundamental rethink in how technology could re-shape governments for the 21st century.

At the project level we’ve seen some very promising successes. While at the enterprise level — trying to answer the key question about deeper digital transformation— there are few dramatic results. So, on the whole, no unqualified successes, but given the magnitude of the task and the size of the governments this is a tall ask. And, to counter, few failures and lots of tactical wins.

Equally important, a lot has been learned. So much so that we now stand at the end of the beginning for digital services units. The end of the beginning, because a rough consensus around a “north star” and general tactics has emerged. And not the end, as we are both far from the end of the journey and have earned ample license to carry on.

Some Background

Since the founding of the UK Government Digital Service in 2011, the number of digital service groups — teams of digital experts, often drawn from the commercial tech industry and combined with in house government talent, and tasked with “digitizing” government — has exploded. Today Peru, Argentina, United States, Mexico, Canada, Italy and Australia are just a few of the countries with such units, joining the ranks of long-evolving government technology programs in pioneers like Estonia, Israel and Singapore. In addition, a growing number of sub-national actors, such California, Ontario and Georgia also boast these teams. In the US, the United States Digital Service (USDS) has led projects across federal bureaucracies and produced public resources like the Digital Services Playbook, College Scorecard, and TechFAR Handbook. It is now training a new generation of digitally oriented procurement officers on technology procurement practices.

Where we are today

In short, as a form of both organizations and a theory of driving change, digital service groups are a relatively mature. Maybe not a mature practice, but certainly a mature experiment by this time.

We’re no longer in a development phase when digital services has to prove its need to exist in the first place; in most jurisdictions political awareness of the need to improve the delivery of online services is real. And in some (but hardly all) jurisdictions, public servants see the value in improved technology infrastructure and access. The model of digital service units has, for both good and ill, earned enough political capital to be given some runway and to continue the work that they do.

Equally important, two key pieces of the puzzle seem to have become clear. The first is a “North Star” to guide digital service teams on their journey. Specifically, whether they can build them today or not, creating or acquiring a core government platform (e.g., single sign on, payments, identity) is the end game most digital teams know they need to get to. Some digital service groups are able to work on these already. Others are too busy with specific projects, putting out fires, and or building credibility or capacity to engage in this work. However, creating common platforms to power governments services is key to digital transformation over the long term. If groups cannot work on it today, there is an emerging consensus that they should create the political capital and conditions, to enable them to steer towards this outcome.

The second piece of the puzzle has been validation that using an agile process to start with, and focus on, users is the among the most effective tactics for achieving short term success. Whether it is rolling out a new digital application for health care at Veterans Affairs or making it easier to assign power of attorney in the UK, user-centered projects yield real and tangible benefits for users and huge political value for elected officials. Focusing on users also serves as a way to cleave through bureaucracy and force divergent interests to adhere to a common goal.

This emerging consensus — steer towards building common platforms tools while using the focus on user needs to power you through projects on the way there — is helpful. It gives people a shared roadmap and common language and frameworks that transcend jurisdictions.

Challenges

While confirming that such a consensus exists will be one helpful goal of the convening, so to will be understanding shared challenges.

Interestingly, these two trends mentioned above can be in competition. Focusing on the user’s satisfaction against all other goals can turn digital services groups into web design shops that roll out functional and pretty websites — but accomplish little in the way of deeper transformation, particularly in underlying legacy systems. On the opposite end of the spectrum, focusing exclusively on building platform services can be hard to pull off without real needs and users to validate against. More importantly, not working on complete services cause units to not demonstrate short-term tangible benefits to citizens (and therefore their elected officials).

Plotting digital services on this matrix could help identify shared theories of change and approaches

The other common challenge among many digital units we talk to is in how they negotiate for buy-in within their own bureaucratic context. Some have been granted (or grabbed) as much power and authority as possible to control digital projects across government. In some cases, this paid off. It can enforce standards and practices and prevent large, poorly designed projects that confuse and frustrate users, and prevent digital services from getting off the ground in the first place. It also often creates major political challenges. Those whose projects are killed or whose practices must adapt can become competitors and even opponents within the government.

Other teams focus on gently cajoling government partners and organizations to go along; they upsell the potential savings of a website redesign, trumpet the happiness of core users when they interact with new tools, and home in on how shared services allow more differentiated value. Building consensus can be great, but it can also take time, and without enforcement mechanisms may ultimately prove to weak to prompt an enterprise wide shift.

And of course, while digital service groups may be mature experiments, surviving transitions in government is always a critical challenge. Ensuring there is multi-party support and that there is continuity even as administrations change — like the work of most public servants — is essential.

If This is the End of the Beginning, What’s Next?

The exciting part about being at the end of the beginning is that the model of digital service units has been sufficiently validated that more and more governments will likely experiment with them over the coming 5 years. In addition, these new groups will benefit from a clearer roadmap and lessons learned from those who came before.

In addition, I suspect that expectations have been more appropriately calibrated. For better or for worse, political masters now expect incremental wins on a project by project basis — not enterprise transformation.

So what’s next? In the short term the north star and tactics outlined above answer that question. Continue to deliver value on projects, drive agile methodologies and user focused approaches while nudging towards platform services. The key is to maintain or build political capital —or what my colleague Mark Moore refers to as capacity for authority — to prepare for the next phase.

Because, as hard as it is to believe, today is likely the easiest part of the journey. Behind us is the hard part of starting up. Today is about building capital and capacity. What’s next in the mid term…? Along slow battle over what the structure and shape of government will look like. And making progress on that I fear will be infinitely more difficult and painful than improving services on a project by project basis.

This piece was written by David Eaves, Lecturer in Public Policy at HKS and Ben McGuire, an HKS student.

Part 1: hypothesis & goals

Context

This summer, digital HKS is excited to launch an experimental pilot that will help MPP and MPA students at the Harvard Kennedy School of Government (HKS) learn Python.

Over the next two to three months, we’ll share more details about this experiment: why we are running it, how we are going about doing it, what we hope will happen, what actually did happen. We’ll also share how this effort dovetails with some of our thoughts about the future of technology and technologists in the public sector.

In this first post we will talk about why we’ve chosen to provide resources to teaching students to code, and why we think tackling this challenge over the summer is the right approach.

Measuring and Satisfying Demand

One thing which hasn’t been clear to many faculty at HKS is the appetite among students to learn how to code. Most assumed that a small minority cared: we suspected the number was significant. Our first step was to simply create a Google Form to solicit interest to see if the experiment was even worth considering. This form was our Minimum Viable Product. If after sharing it with students, no one filled it out, we could pack everything up and move on to the next thing.

However, after emailing all incoming and a large minority of returning students, about 245 HKS students expressed an interest in participating (representing about 27 percent of all policy and administration students next year — we did not offer the course to mid-career students as they are pre-occupied with an existing summer program). To be clear, we don’t expect every one of these students to participate or complete the course (although we are hoping to get as many as possible), but this outcome still stands as a significant signal of interest.

Focusing in On Data Fundamentals:

A Huge Opportunity for Data and the Public Interest

The power of data in public policy analysis and development has always been at the core of how the HKS enables its students to engage in transformative public-sector management. This isn’t the only value proposition of the school; there’s a constant and healthy tension between those who focus in quantitative methods and those who believe in the power of narrative, adaptive leadership, and negotiation to drive policy. Yet today more than ever before, data exists within the public sector and on the internet that, if unlocked, could create significant public goods and help solve public problems. When HKS was founded, datasets tended to be limited in number and scope. They were expensive to produce, relatively high quality, and created for statistical analysis by agencies and economists. Today, almost the reverse is true. Public servants live in a world awash in data–but it’s messy, unstructured, and it takes a special set of skills to find value within it. The fundamental skillsets and ways of thinking necessary to successfully leverage this new world of data are different from the skillsets demanded in the past. Equipping policy students for today’s data rich, but messy world, is part of the goal of this experiment.

Teaching A Large, Popular, and Growing Language popular with Data Scientists

One question we occasionally get is ‘Why Python?’ For us, Python occupies a sweet spot. The narrow goal of the summer camp is to enable HKS students to take CS109 — the introduction to data science. However, beyond that, dedicated graduates of this summer camp could to skill “up” into software development more generally or data science more specifically. At the same time, participants could also easily skill “down” and learn R for data analysis and statistics.

An additional reason is there is a lot of demand for Python skills in the labor market. In 2017, labor market analytics firm Burning Glass Technologiesfound that across industries, demand for Python-related skills grew by 182%in the last two years–and average advertised salary for jobs that required Python knowledge was $101,903. Increasingly, this includes jobs in the public or non-profit sector. Simply visiting Code for America’s job board gives a sample of some jobs for which coding in python is important.

Making Use of the Summer:

High Opportunity Cost for Fall and Spring Introductory Computer Science

I actively discourage MPP or MPA students from taking basic coding courses while at Harvard and believe the Kennedy School’s decision to let students register for them was, and is, a terrible idea. The opportunity cost of taking such a course is enormous. There are many free or low-cost courses for learning to code; why would you pay a Harvard tuition to do what is essentially free??? Worse, time spent in a coding class is time students won’t spend taking courses that are truly unique, with incredible faculty students can only find here. Marshall Ganz is respected and beloved the world over for his scholarship and practice of building self-reliant and strong communities–students can spend a semester getting his advice and training on a real-life organizing project within their own communities. Former UN Ambassador Samantha Power has fought for human rights and democracy in some of the toughest diplomatic environments on earth — and she’s here on campus to share that experience. Khalil Muhammad is one of the nation’s leading scholars on race and inequality; his courses push our students to understand the critical role of history and institutions in today’s policies, and how to move forward. These courses are, for many, once in a lifetime opportunities.

We know that students want to add coding or data science skills to their resume, and taking this summer pilot course is not a way to avoid taking computer science courses. Rather, it’s our goal to make sure students can take value-add courses in machine learning and advanced topics, while still making time for the incredible professors we have here in the building.

Keeping you up to date

All of us at digital HKS look forward to seeing how the students build their skills during the summer, and the kinds of academic and professional doors that opens for them in the coming year. Keep an eye out for future posts from us — and as always, don’t hesitate to reach out to us with questions.

This piece was written by David Eaves, Lecturer in Public Policy at HKS and Ben McGuire, an HKS student who is, by chance, participating in the Python Pilot.

Okay, so to recap, here at the Kennedy School of Government I’m interested in the social, economic and policy changes brought about by the way digital technologies expand or threaten how we can solve problems, relate to one another, and reimagine institutions and the world.

We have a range of students who fall into three broad camps:

To whom we are focused on teaching a culture of learning as well as a number of key foundational topics and skills:

To help them grasp a wide range of concepts, processes and tools made possible by digital technology:

I combine those to provide a more general framework for how I think about teaching digital at a policy school that looks like this.

One element I like about this chart is that it identifies some shared learning areas of which students should have a solid understanding. This enables one to concentrate resources in one or more core courses that provide students with basic building blocks of knowledge that can be used to learn and be critical about a range of concepts and ideas.

It also allows us to create a set of courses that each dive deeper into each of the foundational topics and related concepts secure in the knowledge that such courses will be useful to a broad range of students. Examples of these courses include Bruce Schneier’s class on security, Jim Waldo’s class on privacy and Dana Chisnell’s class on design thinking.

This approach also allows for flexibility. As I mentioned in an earlier post, depending on their career paths students may invest more heavily in some foundational topics. A regulator may be more concerned with privacy, design and data while a cyber security expert may be more interested in security and data. Thus students can opt to dive deeper into areas they think will be critical to their career. Nonetheless, my sense is that regardless of role, a basic understanding of each of the above foundational topics (as well as the underlying culture and norms of iteration and learning) will serve them well in any role and so getting an overview of each is critical.

With more students having been exposed to a range of the foundational topics I also feel more comfortable offering courses that focus on some of the concepts. Again it is worth noting that the “concepts” part of the chart encapsulates thousands of possible issues. Not only are there far more than can be taught, but they are in constant flux. Some fall out of favor or become obsolete while new ones are constantly emerging. That said, some are likely essential to everyone (for example, I teach all my students about the concept of a platform) and others are likely to be important to specific roles, indeed part of the function of a school and a teacher is to figure out which of these concepts — for a given role — are essential versus merely good to know versus unnecessary. A great example of this type of course includes Nicco Mele’s course on technology and the media and his course on technology and political campaigns.

I’ll talk more about how we map out classes in a subsequent post.

The Big Questions

Part of the goal for a policy school is to educate and train students, equipping them with the skills and knowledge they need to be successful in creating public value and engage public organizations in digital transformation.

But as a school of public policy and, frankly one that has a global reach, we have a responsibility to also ask bigger questions. One hope I have is to push the school to understand how some of the questions that are asked in the “digital” sphere are in reality Big Questions that affect society at large, the fabric of democracy and governance, the nature of human rights, etc… and need the engagement of the school at large focused on them. This is not to say that these questions are the only questions that matter. Climate change, massive inequality, and managing the US-China relationship probably represent the great challenges, if not in some cases, the existential threats of our time, and deserve much attention. But there are questions created by issues in the digital sphere that are similar in nature.

These include:

• Have we become a surveillance society? With both the state and companies tracking our every move, what does this mean for freedom? For dissent? For citizenship?
• If the 20th century was about harnessing the power of the state to reshape the distribution of wealth under capitalism from a power law into a bell curve, how will we do the same in the internet age?
• What does an API-driven government look like? What will be the checks and balances around power, surveillance, and privacy in such an institution?
• Will artificial intelligence and the second machine age leave (almost) everyone unemployed? And if they do, what then?

I see these and other questions like them as core to the role and purpose of a policy school. They may not be the questions that all, or even most of our students are required to ask day to day in the jobs they take up, but they are the questions that we all, as citizens, need to start wrestling with as we think about what we want the future of our world to look like.

Okay, I’ll stop there. More to come soon.

This is the sixth in a series of pieces about how I’m wrestling with how to teach about digital technologies at policy schools. If you’re interested you can read:

• part one: Why Digital Matters
• part two: Defining Digital
• part three: Our Users and What They Need
• part four: The Trap — Teaching Tech and Concepts
• part five: Foundational Topics
• part six: Bringing it Together (this post)

One challenge I’ve observed about how digital technologies are taught at most schools of policy or government is it takes a relatively ad hoc approach. It is a mix of courses that emerge due to either student demand or faculty interest. To be fair, this is often better than nothing, but it offers little in terms of methodology or structure for thinking about digital. Students are left to themselves to draw connections between subjects, or the underlying principles and challenges that span across them.

My goal is to educate students around the social, economic and policy changes brought about by the way digital technologies expand or threaten how we can solve problems, relate to one another, and reimagine institutions and the world.

Achieving this requires a structured approach, to bring clarity to the core issues and ensure students leave with a solid foundation of knowledge.

The intent is to enable students to understand how digital challenges rules, norms and structures — for good and ill. It is also about getting them to manage learning organizations that can absorb and leverage the fast feedback digital systems create.

Prerequisites

As a brief aside, in my classroom I assume students come to me with some basic knowledge. At the Harvard Kennedy School, students in the MPP program have a set of “core” classes required in the first year. This include some economics, stats, and most importantly, ethics. So I assume many of my students come into my class with some background in these subjects.

Foundational Topics

My bias in all this is around how digital will impact the provision of public services (I’m happy to own this bias and recognize it, meaning I make choices others might not) but I have attempted to design a structure for my students I believe works across a broad range of policy and governance challenges.

Here at HKS I’ve tried to lay out six foundational topics of which a basic understanding is essential. It is not that other skills or domains of knowledge don’t matter, (such as economics or leadership — these should be taught as well, but are likely already covered in a leading schools) but it is that these are most likely not to be taught, particularly in the context of digital.

The first starts with some culture shock. Getting students to understand how technology is challenging the speed and way public goods could be built and delivered.

A part of this is teaching agile, not just as a project management skill but also as form of organizational culture. It is about having students understand how digital technologies alter how quickly organizations can learn.

To be clear, the point is not to worship at the alter of agile, but to think critically about where agile can work to increase speed and learning in policy development and the delivery of public services, as well as where it makes less sense as an approach. Should 100% of government work adopt an agile approach? Definitely not. But more than 0% should. And this is particularly true when it comes adopting digital approaches to organizing work within government and delivering services. Enabling students to see a universe beyond multi year inflexible plans and to provide them with language and frameworks for an adaptive and agile approach is an essential foundation for both thinking about digital in government and frankly, for a great deal of other work that has little to do with digital.

Once this foundation is laid, students then look at the topics of User Needs, Design Thinking*, Data, Privacy and Security**. These five topics are a useful way to talk about the politics, tradeoffs and challenges in digital sphere.

A basic analytical framework in each of the above areas provides students with a foundation for asking critical and important questions when confronting a new policy question or mobilizing assets to deliver services digitally. Each of these foundational topics are packed with both practical operational questions as well as significant political and ethical questions:

• Who are our users? (this is a deeply political and practical question that should be answered at multiple levels).
• Are we capable of designing for our end users and the administrators who must serve them and the broader public interest?
• What data do we collect? Are we using it to learn? Is collecting it necessary? How might this data be mis-used?
• Does this service, process, or product protect users’ privacy? Should it? What is the benefit? What is the cost?
• What threats should we protect governments systems from? Economic systems? Broader democratic and social systems? Who is responsible for this protection?

These issues are also listed in priority. While all are critical, each one must be understood and informs one’s understanding of the next one. And while all are essential, they may be weighted based on the learning and career objective of a student. A student interested in service delivery will need to know more about user needs, design and data than, say, an information cybersecurity expert who will have a stronger focus on security and data.

I use this framework in two ways. First, in my DPI-662 Digital Government course, I seek to transform students into foxes, by giving them some basic introduction to each of these concepts. My assumption is that, when confronted with a online service to regulate, a vendor trying to sell the government software or trying to deploy an government service online, asking a question on any of the above 6 topics will probably serve them well. Thus, learning to think critically about each of them will provide a crucial foundation for learning about any new technology or concept.

The second way I use this framework at the Harvard Kennedy School is as an organizing structure for other classes. The intent is to give students the opportunity to become “hedgehogs” and receive further instruction on each of these foundational topics. As a result we offer multiple deeper courses on each of these topics so that depending on the career a student will have — either as a politico, administrator or regulator — they can do a deeper dive in a manner that will serve their interests. More on how we do this in a subsequent post.

* Note: Some readers may wonder why User Needs and Design Thinking are listed separately. It is true that these would traditionally be merged. I’ve separated them for two reasons. First, there are a set of questions about who the users are that are deeply political that should be answered separately from the issue of how we would design for services, policies and regulations to serve them. The second is, I’ve found governments are frequently not great at a) identifying and understanding users and b) engaging in design thinking, so separating them out is another way to emphasize the need to invest in these these capacities.

** Note: Security and Privacy are also deeply related topics. I’ve purposely listed them separately. Security and privacy interests can clash, particularly when discussing the interests of an organization versus those of an individual. My experience, in the government context, is that when privacy and security are lumped together, privacy has a funny way of taking a back seat in the discussion. This risk is particularly real in schools of policy and government, where organizational interests — usually those of the government — are front and center. Separating them out hopefully ensures they remain on a equal footing.

This is the fifth in a series of pieces about how I’m wrestling with how to teach about digital technologies at policy schools. If you’re interested you can read:

• part one: Why Digital Matters
• part two: Defining Digital
• part three: Our Users and What They Need
• part four: The Trap — Teaching Tech and Concepts
• part five: Foundational Topics (this post)

here at Digital@HKS or on my blog.

Before talking about the framework for thinking about digital at the Harvard Kennedy School, I want to discuss what we aren’t doing. I do this because I frequently get asked by students and others to respond to needs that I think are poorly articulated. I believe we should listen to users (students) but that doesn’t always mean they know how to articulate what they want perfectly.

Sample of Technologies and Concepts

One risk is that a policy school ends up focusing on either what is easy or sexy (or both). This is compounded by the fact that professional degree students (as well as exec-ed students) who feel real pressure to skill up for the job market may gravitate to courses that focus on tactics or tools. This includes subjects like how to use a technology of the day, such as Twitter, Slack, or Bitcoins, or perhaps a specific skill, such as learning to code in rails or python.

Courses on these topics appeal for many reasons. They are practical: one learns how to “use” a technology or leaves with a greater awareness of it. They are bounded: by focusing on a specific technology or application, they are narrow in scope. This creates nice boundaries for the student, and it also makes teaching them easier (but not necessarily effective). The more tactical the course, the cheaper they are likely to run: finding people willing to teach a course on how to program or how to use social media in a campaign is probably easy and cost-effective. But even when the course is around a broader concept rather than a narrow tool, there are still drawbacks. There are so many important issues that are shared across technology, like issues of privacy or security, that students risk re-learning core concepts over and over again as they go from course to course about each new concept or technology.

This is not to say policy schools should teach no courses that meet the above criteria. It is just the wrong place to start. Why?

First, technologies evolve and change over time — sometimes quickly — so learning how to use a specific technology may simply set a student up to become rapidly deskilled. Second, learning how to use tools, while at a policy school, has a huge opportunity cost. Third, policy schools (and universities in general) are ill equipped to teach these skills cheaply and quickly. Here at the Harvard Kennedy School students have access to Lynda.com which teaches many of these technologies quickly and cheaply. But finally and most importantly, this work is generally tactical. For a policy school a set of technologies cannot make up an organizing principle around which a curriculum can be structured. This isn’t to say that a specific technology isn’t sometimes important, but it is not the point of departure. I’m not interested in teaching specific technologies. I’m interested in how all digital technologies may impact systems, organizations and the delivery of public goods. Insofar as is possible, I’m much more interested in policy schools providing students tools to assess all digital technologies than a specific one.

I mean, each of these are really interesting and you could (and maybe even should) legitimately do a course on each one.

Any serious policy school should focus on how these digital technologies are changing governance, the provision of public services, social norms and/or the economy. This requires that students have some shared sense of critical questions they should be asking about any digital technology and how it may or may not benefit government or society.

As for “tool learning” this should — where possible — be a byproduct of assignments, but it should not be the lesson in of itself. As a result I encourage my colleagues here at HKS to build assignments that involve tools: for example I make all students submit all assignments via blogs, so that they learn how blogging tools work, but learning how to blog is never the assignment in of itself.

Sidebar: The second point from above is why I advise students not to take the popular CS50 course. If students want to learn to code, they shouldn’t do it while at school of policy. It is possibly the singularly most expensive way I could imagine to learn to code. Encourage students to do it via Code Academy or some other resource the summer before students arrive. They’ll learn more than they would in CS50, it will cost a fraction of the amount, they’ll be able to apply what they learned in classes immediately and, it will free up time to take courses they they’ll never be able to take outside of the policy school environment.

Next up, let’s talk about what foundational knowledge students should learn at a policy school that will make it both easier to learn the tools and concepts outlined above as well as position students to be more critical and thoughtful while engaged in that learning.

This is the fourth in a series of pieces about how I’m wrestling with how to teach about digital technologies at policy schools. If you’re interested you can read:

• part one: Why Digital Matters
• part two: Defining Digital
• part three: Our Users and What They Need
• part four: The Trap — Teaching Tech and Concepts (this post)
  

Why Digital?

For the purposes of our thinking we will use “digital” an umbrella term to describe the set of challenges, opportunities and issues that arise from a combination of information and telecommunications technologies.

Why digital? For one, “technology” is too broad a term. At HKS — and I suspect schools of policy and government in general — technology refers to not only information technology but all technologies and what I think many in the public would think of as areas of science like nuclear energy, biotech and climate change. This is clearly outside the purview of digital (and/or what I’m personally focused on). Words matter. If you run around using technology synonymously with information technology, some very smart and generally supportive people doing important and good work will rightfully be offended. Let’s not fight academic battles with allies — we have more important ones to engage in (privacy, user centric approaches, security, surveillance, regulation, etc..).

On the opposite end, “information technology” feels too narrow. Yes digital is about things like software, the internet, big data, and innovations like smartphones and artificial intelligence. But it must also be more than that. I’ve always loved how Clay Shirky wrestled with this in Here Comes Everybody:

“The tools that a society uses to create and maintain itself are as central to human life as a hive is to bee life. Though the hive is not part of any individual bee, it is part of the colony, both shaped by and shaping the lives of its inhabitants.”

Here at Digital@HKS we are as much, if not more, interested in the social, economic and policy changes brought about by the way digital technologies expand or threaten how we can solve problems, relate to one another, and reimagine institutions and the world. Information technology risks focusing us on the technology. The intent of using “digital” (while admittedly imperfect) is to try to be broader, to allow us to acknowledge the foundational role information technology plays, but focus on how we as individuals and society think about digital, interact with, use and are shaped by it.

This is the second in a series of pieces about how I’m wrestling with how to teach about digital technologies at policy schools. If you’re interested follow me here on eaves.ca. You can also read part one.