Covid-19: Lessons from and for Government Digital Service Groups

This article was written by David Eaves, lecturer at the Harvard Kennedy School, Tom Loosemore, Partner at Public Digital, with Tommaso Cariati and Blanka Soulava, students at the Harvard Kennedy School. It first appeared in Apolitical.

Government digital services have proven critical to the pandemic response. As a result, the operational pace of launching new services has been intense: standing up new services to provide emergency funds, helping people stay healthy by making critical information accessible online, reducing the strain on hospitals with web and mobile based self-assessment tools and laying the groundwork for a gradual reopening of society by developing contact tracing solutions.

To share best practices and discuss emerging challenges Public Digital and the Harvard Kennedy School co-hosted a gathering of over 60 individuals from digital teams from over 20 national and regional governments. On the agenda were two mini-case studies: an example of collaboration and code-sharing across Canadian governments and the privacy and interoperability challenges involved in launching contract tracing apps.

We were cautious about convening teams involved in critical work, as we’re aware of how much depends on them. However, due to the positive feedback and engaging learnings from this session we plan additional meetings for the coming weeks. These will lead up to the annual Harvard / Public Digital virtual convening of global digital services taking place this June. (If you are part of a national or regional government digital service team and interested in learning more please contact us here.)

Case 1: sharing code for rapid response

In early March as the Covid-19 crisis gained steam across Canada, the province of Alberta’s non-emergency healthcare information service became overwhelmed with phone calls.

Some calls came from individuals with Covid-19 like symptoms or people who had been exposed to someone who had tested positive. But many calls also came from individuals who wanted to know whether it was prudent to go outside, who were anxious, or had symptoms unrelated to Covid-19 but were unaware of which symptoms to look out for. As the call center became overwhelmed it impeded their ability to help those most at risk.

Enter the Innovation and Digital Solutions from Alberta Health Services, led by Kass Rafih and Ammneh Azeim. In two days, they interviewed medical professionals, built a prototype self-assessment tool and conducted user-testing. On the third day, exhausted but cautiously confident, they launched the province of Alberta’s Covid-19 Self Assessment tool. With a ministerial announcement and a lucky dose of Twitter virality, they had 300k hits in the first 24h, rising to more than 3 million today. This is in a province with a total population of 4.3 million residents.

But the transformative story begins five days later, when the Ontario Digital Service called and asked if the team from Alberta would share their code. In a move filled with Canadian reasonableness, Alberta was happy to oblige and uploaded their code to GitHub.

Armed with Alberta’s code, the Ontario team also moved quickly, launching a localised version of the self-assessment tool in three days on Anticipating high demand, a few days later they stood up and migrated it to a new domain — — which has since evolved into a comprehensive information source for citizens, hosting information such as advice on social distancing or explanations about how the virus works with easy to understand answers.

The evolution of the Ontario Covid-19 portal information page, revised for ease of understanding and use

The Ontario team, led in part by Spencer Daniels, quickly iterated on the site, leveraging usage data and user feedback to almost entirely rewrite the government’s Covid-19 advice in simpler and accessible language. This helped reduce unwarranted calls to the province’s help lines.

Our feeling is that governments should share code more often. This case is a wonderful example of the benefits it can create. We’ve mostly focused on how code sharing allowed Ontario to move more quickly. But posting the code publicly also resulted in helpful feedback from the developer community and wider adoption. In addition, several large private sector organisations have repurpose that code to create similar applications for their employees and numerous governments on our call expressed interest in localising it in their jurisdiction. Sharing can radically increase the impact of a public good.

The key lesson. Sharing code allows:

  • Good practices and tools to be adopted more widely — in days, not weeks
  • Leveraging existing code allows a government team to focus on user experience, deploying and scaling
  • The crisis is a good opportunity to overcome policy inertia around sharing or adopting open source solutions
  • Both digital services still have their code on GitHub (Ontario’s can be found here and Alberta’s here).

The amazing outcome of this case is also a result of the usual recommendations for digital services that both Alberta and Ontario executed so well: user-centered design, agile working and thinking, working in cross-functional teams, embedding security and privacy by design and using simple language.

Case 2: Contact tracing and data interoperability

Many countries hit hard by the coronavirus are arriving at the end of the beginning.

The original surge of patients is beginning to wane. And then begins a complicated next phase. A growing number of politicians will be turning to digital teams (or vendors) hoping that contact tracing apps will help re-open societies sooner. Government digital teams need to understand the key issues to ensure these apps are deployed in ways that are effective, or to push back against decision makers if these apps will compromise citizens’ trust and safety.

To explore the challenges contact tracing apps might create, the team from Safe Paths, an open source, privacy by design contact tracing app built by an MIT led team of epidemiologists, engineers, data scientists and researchers, shared some early lessons. On our call, the Safe Paths team outlined two core thoughts behind their work on the app: privacy and interoperability between applications.

The first challenge is the issue of data interoperability. For large countries like the United States, or regions like Europe where borders are porous, contact tracing will be difficult if data cannot be scaled or made interoperable. Presently, many governments are exploring developing their own contact tracing apps. If each has a unique approach to collecting and structuring data it will be difficult to do contact tracing effectively, particularly as societies re-open.

Apple and Google’s recent announcement on a common Bluetooth standard to enable interoperability may give governments and a false sense of security that this issue will resolve itself. This is not the case. While helpful, this standard will not solve the problem of data portability so that a user could choose to share their data with multiple organisations. Governments will need to come together and use their collective weight to drive vendors and their internal development teams towards a smaller set of standards quickly.

The second issue is privacy. Poor choices around privacy and data ownership — enabled by the crisis of a pandemic — will have unintended consequences both in the short and long term. In the short term, if the most vulnerable users, such as migrants, do not trust a contact app they will not use it or worse, attempt to fool it, degrading data collection and undermining the health goals. Over the long term, decisions made today could normalise privacy standards that run counter to the values and norms of free liberal societies, undermining freedoms and the public’s long term trust in government. This is already of growing concern to civil liberties groups.

One way Safepaths has tried to address the privacy issue is by storing users data on their device and giving the user control over how and when data is shared in a de-identified manner. There are significant design and policy challenges in contact apps. This discussion is hardly exhaustive, but they need to start happening now, as decisions about how to implement these tools are already starting to be made.

Finally, the Safepaths team noted that governments have a responsibility in ensuring access to contact tracing infrastructure. For example, they struck agreements to zero-rate — e.g. make the mobile data needed to download and run the app free of charge — in a partner Caribbean country to minimise any potential cost to the users. Without such agreements, some of the most vulnerable won’t have access to these tools.

Conclusions and takeaways

This virtual conversation was the first in a series that will be held between now and the annual June Harvard / Public Digital convening of global digital services. We’ll be hosting more in the coming weeks and months.


  • The importance of collaboration and sharing code within and between countries. This was exemplified by code sharing between the Canadian provinces and by the hope that this can become an international effort.
  • Importance of maintaining user-centered focus despite of the time pressure and fast-changing environment that requires quick implementation and iteration. Another resource here is California’s recently published crisis digital standard.
  • Privacy and security must be central to solutions that help countries deal with Covid-19. The technology exists to make private and secure self-assessment forms and contact tracing apps. The challenge is setting those standards early and driving global adoption of them.
  • Interoperability of contact tracing solutions will be pivotal to tackle a pandemic that doesn’t borders, cultures, or nationality. As the SafePaths team highlighted, this is a global standard-setting challenge.

Harvard and Public Digital are planning to host another event on this series on the digital response to Covid-19, sign up here if you’d like to participate in future gatherings! — David Eaves and Tom Loosemore with Tommaso Cariati and Blanka Soulava

This piece was originally published on Apolitical.

Lecturing and Teaching Remotely — My Setup and Approach

I just ran a workshop/facilitate this morning for a number of the Chief Digital Officers from several European capital cities to help them share best practices and shared challenges in their respond to COVID19. I very much enjoyed the session and my set up has me excited about how remote teaching can approximate the intimacy and interaction of in person teaching.

This, combined with some wise words from Ron Heifetz - who shared in an online lecture yesterday how leadership is often just doing what needs to be done - has me writing this post. My present job is to teach, provide students some stability and help prepare them for a rapidly evolving and uncertain world. So… this is me both trying to exercise leadership and, to be truthful, engage in some writing therapy, trying to share something small but hopefully useful for my colleagues and extended community.

Context - We’re all Remote Teachers Now
Last week Harvard announced that all classes for the rest of the semester would be taught remotely, and that includes me. I miss our students already, and they have so much uncertainty to deal with. And, this is the right move. Students and faculty should absolutely be practicing social distancing.

So suddenly, many of us need to teach remotely. I’ve strong preference about my teaching environment so I can express myself effectively, maintain energy and ensure the type of engagement with students I think is necessary to enable learning. Here I’ll share what my guiding criteria were and then how I cobbled together some equipment I (or my partner) had around the house to set up my teaching environment. Hoping others may find this helpful.
Oh, and sidebar, I’d also encourage you to take a look at Teddy Svoronos website which is filled with great tips around tech and teaching, I’m a huge fan of Teddy and Dan Levy who are the kings of pedagogy here at the Harvard Kennedy School.

My Criteria for a Good Environment
I’ve been running meetings via zoom with up to 35 people for a couple of years now now. Teaching is different but there is a lot of overlap. In addition, I’ve been lucky to experience a fair amount of remote teaching. This includes courses for mayors and chiefs of staff in the Bloomberg Harvard City Leadership Initiative using the HBX Live Platform. That was a huge luxury as HBX is ridiculous. It’s effectively a studio with multiple cameras and a cameraperson following you around as you teach to 60+ people each on three foot high screens (see photo below). Not replicable at home, but it opened my eyes to how being mobile - even remotely - matters.

Image of HBX Live Studio

HBX Live Studio - it’s amazing, but doesn’t scale to my guest room

I’ve also taught over zoom from my office such as this mornings session mentioned above, or a month or two ago, teaching my Aadhaar case study to a group of journalists in Africa. That experience highlighted why getting the audio right, and being able to flip from slides to discussion quickly is important.

So my main criteria in setting up my environment included:

Spend little or no money
Listen, as amazing as HBX Live is, we’re not going to be recreating it in our homes. And who knows how long this will go on for. I’m sure most faculty aren’t keen to spend a lot of money for something they may only need for 2–6 months.

See the whites of my students eyes
Teaching in an empty room is hard. Teaching to a zoom call with nothing but grey phone icons feels just as hard. We get so much feedback from people’s faces, expressions and posture, I wanted my solution to maximize this feedback.

Facilitate multitasking between students, slides and comments
Obviously one needs to see and be able to advance slides, but this is secondary to seeing and engaging with students (I already know the content of my slides). Critically, I don’t want my own screen dominated by slides and limit to showing a handful of students (say, no more than just 4–5 which is what zoom will default to when you are sharing a presentation).

Be more than a floating head on a screen
When I teach I like to roam the room and am fairly expressive with my body language. Teaching an hour and 15 minute class while sitting down doesn’t enable me to engage or maintain the level of energy I’ve come to expect of myself. I also think students benefit form seeing more than just a talking head.

Have great sound quality
And that means… not letting my kids yelling in the room next door interfere with the class. I’m obviously expecting a full on BBC talking head kid intervention will occur at some point this semester, but I want to keep out the sound from the rest of the house.

So here is my set up:

Photo of my ad hoc, at home, teaching studio

Thank you to some of my students helping me calibrate my set up

The Setup
The key was figuring out I could hijack our virtually unused television. I list more details on the equipment below, but here is how it works.

I log into zoom on my iPhone which I attach to the top of my TV. My iPhone is used to capture video of me and to share any slides I might have (I’ve moved to Google Slides). I can easily advance slides by swiping, I can also switch to chat to see any student comments fairly easily.

I then log in again on my laptop. I mute the laptop speakers, mic and video. I move the zoom app to the TV where I display all the participants (and effectively hide the slides by shrinking them to be as small as possible). This semester I’m teaching a required course - API-501 Policy Design and Delivery- which has about 60 students, and I can see almost 50 of them at on this screen, and they are decently sized so I can see the whites of their eyes.

One could just use the audio from the phone or the laptop, but I happen to have a plantronics wireless headset (this is the one investment I’d probably encourage you to make as they don’t pick up ANY sound from more than a few inches from your mouth - it is incredible). This ensures that no sounds from outside or elsewhere in the house interfere with the class. It connects via bluetooth to either my phone or computer depending which one I want to use.

This arrangement allows students to see anywhere from 1/3rd to my whole body depending on where I stand. This allows me to pace and use body language more effectively. It also means I’m pretty much compelled to stand (which I like - I find it keeps the energy level up). I could bring in a high chair from another room, but won’t for now.

The Norms
I’ve a handful of simple norms I use as well. These include:

  • Everyone must use video. A classroom is a community. That community functions a lot better if people can see one another.
  • Ask all participants to fill out their name in zoom, and then set zoom to always display names. At HKS we have name placards students bring to every class - this strikes me as a virtual version.
  • Faculty and/or course assistants should log in 5–10 minutes early to ensure the room is ready when people show up.
  • Use the raise hand feature in zoom. It is much harder to read the queues about when to jump in and interrupt a lecture. When someone does raise a hand - I try to get to the questions ASAP, ideally within 15–30 seconds if not immediately, to encourage people to raise hands and engage.
  • Everyone stays on mute unless they are talking

The Equipment & Software

  • Zoom. I won’t go into this since basically everyone is getting a crash course in using it right now. In my case, the university provides this.
  • Whatsapp (or Slack). I use this to backchannel with the course assistants. Mostly for them to yell at me if I missed something or someone. My course assistants and I have been coordinating on Whatsapp before all these changes.
  • JOBY GorillaPod, basically a crazy tripod that you can use to afix or stabilize your phone to anything. My partner had one I was able to snag.
  • Plantronics wireless headset, I’ve already sung the praises of these. They really are crazy good for phone calls as they block out background noise in an amazing way.
  • Mobile Phone, you’ve probably got one.
  • Laptop, you could use a desktop computer as well.
  • Big Screen TV, I happen to have underused one (I haven’t had cable in almost a decade, so… these just don’t get used).
  • Not shown - but I occasionally have a music stand in front of me with an iPad on it which I use to monitor the in class chat.
  • Rockband drum set, this is not actually part of the setup, but I suspect some of you noticed it. We found this old used one, and I’ve been thinking of setting up to the kids and I can play…

Hope this is helpful. Mostly nice to just write something. Hope you are all self-isolating, staying safe and reaching out to loved ones.

“They’ll Just Make It Illegal”

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.

The End of the Beginning of Digital Service Units

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 PlaybookCollege 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.


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.

Teaching Policy People to Code at the Harvard Kennedy School

Part 1: hypothesis & goals


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.

Teaching Digital at the Kennedy School of Government: Part 6: Bringing it Together

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:

Core foundational topics for understanding digital

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

An illustrative list of possible concepts to teach at a Policy School around digital

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

Starting to put it all together here.

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 securityJim 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:

Teaching Digital at the Kennedy School of Government: Part 5: Foundational Topics

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.


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:

here at Digital@HKS or on my blog.

Teaching Digital at the Kennedy School of Government: Part 4: The Trap — Teaching Tech and Concepts

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 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:

Teaching Digital at the Kennedy School of Government: Part 3 – Our Users and What They Need

Focusing on the User: Who Policy Schools Teach

While students from Schools of Policy and Government go on to do a variety of work, whether in the private, nonprofit or for profit sector, most will take a role in one of three functional areas: Politics, Administration/Operations and Public Policy.

Like with much in life, there isn’t always a clear dividing line between types. In addition, over the course of their career many students will occupy jobs in all three and some roles will blend responsibilities. However, as a heuristic to help organize a policy school’s thinking around what it should teach, these are helpful definitions.

This felt further validated while reading Craig Lambert’s interesting case study on the founding of the Harvard Kennedy School (sent via co-conspirator Nicco Mele). In it, Edith Stokey, one of the school’s founding mothers, had a similar view when describing how the school’s curriculum emerged.

“Another new invention was the KSG curriculum which, from the start, emphasized policy analysis and systems analysis to improve decision-making. “That grows out of the [Robert] McNamara and the ‘whiz kids,’ ” says Edith Stokey, referring to the coterie the helped McNamara transform Ford Motor Company when he headed it in the 1950s. “But then came the discovery that good policy isn’t any use if it isn’t implemented at the street level, so we began to worry about implementation and management. Thirdly, with Neudstadt the moving force, there was growing emphasis on politics, including persuasion, legitimacy, and how get the power to get things done.”

Stokey’s three curriculum areas, roughly mapped to the roles I outlined.

A Framework for Organizing our Users

Having established these roles as the “product” that schools of policy and government produce, I’ve fleshed out personas for each. Below are illustrative examples of what a school of policy and government should focus on, from a digital perspective, to equip students with the judgment, knowledge and experience to be successful in each role:

First, I expect people may disagree as to what is most important for each role to learn. I’m okay with that. The point is that fleshing out the framework will prove useful to anyone seeking to engage in education in this space. The goal is to focus on user needs (the students) to help schools determine where to target resources and/or how to structure courses by type (and would love feedback). This is my best effort and is one way by which to structure courses (I have a second framework I do as well that I’ll be sharing in the next post or two).

In addition to understanding what type of product you are trying to create, my hope is that this chart will prevent people from creating courses that lump all the roles into a single course. There are ways that can work, but it is hard, and if you don’t structure it correctly there are real risks you’ll end up making everyone unhappy.

Second, this framework helps me because it identifies key common traits about the key roles students will have in a student body that is both:

a) insanely diverse: I mean this both in the students’ backgrounds (students range in age from 23–50+, come from over 80 countries and span the range of race, gender, sexual orientation, religion, and socio-economic class); and

b) in terms of career focus and interest: The types of jobs people had when they arrive and when they graduate is also exceedingly diverse.

You may not suffer from problem (a) or (b) which is lucky. But most governments’ educational programs and many policy schools do, so the framework provides some structure despite this heterogeneity.

Third, our students come to us with varying degrees of knowledge and skills when it comes to digital issues and technologies. Some are software engineers and data scientists, others have never had a gmail account. Maybe in 20 years’ time the baseline level of knowledge will normalize, but I doubt it, and well, that’s so deep into my career arc it isn’t worth thinking about. Yes, I want to prepare people for careers in public service who will go on to be CIOs… AND I need to prepare that overwhelming majority who won’t and for whom digital will be just a part of their job, not all of their job. This chart gives me some lane ways to organize them and a way to begin thinking about what knowledge, in which domains, I need them to know in order to feel like the school is preparing them appropriately for each of the roles outlined.

And of course even if you don’t suffer from the challenges above, I think it still serves as a useful starting point if your students are yelling “we want more technology courses” (which they were here). This may provide a little of a map to discern what kind of digital courses, the types of case studies and possible topics for events or guest speakers, that will be useful to them.

The Goal: Digital Leaders and Partners

I’m not going to go into details about what skills, knowledge and capabilities I think students need to have (yet). But I do have two other categories of students, those who will be technology leaders and those who need to be effective partners.

I don’t expect (nor do I have the skills) to have all 110 students in my main course on technology and government — DPI-662: Digital Government — to magically emerge as Todd Park clones (although that would be amazing).

Rather, I have two goals.

The first relates to those who come to me with a strong digital background. Here the goal is to equip them with language, frameworks and tools that set them on a path where, with hard work, experience and luck, some could emerge as Todd Parks one day in the future. I take great care to attract students with digital backgrounds. It isn’t easy. But it also isn’t impossible. Policy schools need to attract students with strong digital background. It is, to put it bluntly, much easier to turn a software engineer into a policy wonk than a policy wonk into an software engineer. As a result, any school interested in focusing on digital issues will need to actively pursue and accept students with technical backgrounds. Contrary to popular belief that software engineers are impossible to hire and recruit, USDS, 18F, Code for America and numerous other programs demonstrate that many software engineers, designers, product managers, and data scientists are deeply interested in foregoing salaries to serve the public good. Cultivating this small group into the next generation of IT leaders who can help support and ultimately lead the digital transformation of governments and other important institutions at the enterprise level is a major goal of mine, and Digital@HKS.

The second group is the larger group and those who come to the school without a strong digital background. The goal here is not to magically turn them into digital experts (although some can leave HKS as effective product managers and data scientists). Rather the goal is to enable them to:

a) at a minimum: equip them with sufficient knowledge to have solid BS detecting skills to ascertain when direct reports, vendors or even executives try to push initiatives that will fail or not work from a digital perspective. (This is akin to what we try to do in statistics with many students — some arrive skilled and leave as deep experts, but most arrive with less skills. We don’t turn them into statisticians, but we enable them to spot good from bad practices.)

b) ideally: have sufficient skills to help the departments in which they work or oversee be able to adapt its work to a digital world; and

c) preferably: know how to be effective partners to CIOs, vendors and digital types so they can help support digital transformation at the agency or enterprise level when appropriate and push back when ideas are poorly conceived or technology-centric with no clear purpose.

Having now worked with several hundred students here, what is nice is that I can clearly lump them in to both buckets. I have those with clearer digital skills looking for CIO or say product management jobs and I have those that are returning to a policy area (such as housing or eduction) as an analyst or manager who have a clearer idea of what questions they should be asking before anyone starts trying to engage in technology initiatives.

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 or at the Digital@HKS blog. You can also read part one here and part two here.

Teaching Digital at the Kennedy School of Government: Part 2 – Defining Digital

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 You can also read part one.