Dylan Walsh at MIT Sloan: “In May of 2018, the EU adopted the General Data Protection Regulation, referred to by The New York Timesas “the world’s toughest rules to protect people’s online data.” Among its many safeguards, the GDPR gave individuals ownership of their personal data and thereby restricted its collection and use by businesses.
“That’s a good first start,” said Alex Pentland, a co-creator of the MIT Media Lab who played a foundational role in the development of the GDPR. “But ownership isn’t enough. Simply having the rights to your data doesn’t allow you to do much with it.” In response to this shortcoming, Pentland and his team have proposed the establishment of data cooperatives.
The idea is conceptually straightforward: Individuals would pool their personal data in a single institution — just as they pool money in banks — and that institution would both protect the data and put it to use. Pentland and his team suggest credit unions as one type of organization that could fill this role. And while companies would need to request permission to use consumer data, consumers themselves could request analytic insights from the cooperative. Lyft drivers, for instance, might compare their respective incomes across routes, and ride-share passengers could compare how much they pay relative to other cooperative members….
Several states have now asked credit unions to look into the idea of data cooperatives, but the model has yet to gain a foothold. “Credit unions are conservative,” Pentland said. But assuming the idea gains traction, the infrastructure won’t be difficult to build. Technology exists to automatically record and organize all the data that we give to companies; and credit unions, which have 100 million members nationwide, possess charters readymade to take on data management….(More)”.
Moses John Bockarie at The Conversation: “Global collaboration and sharing data on public health emergencies is important to fight the spread of infectious diseases. If scientists and health workers can openly share their data across regions and organisations, countries can be better prepared and respond faster to disease outbreaks.
This was the case in with the 2014 Ebola outbreak in West Africa. Close to 100 scientists, clinicians, health workers and data analysts from around the world worked together to help contain the spread of the disease.
But there’s a lack of trust when it comes to sharing data in north-south collaborations. African researchers are suspicious that their northern partners could publish data without acknowledging the input from the less resourced southern institutions where the data was first generated. Until recently, the authorship of key scientific publications, based on collaborative work in Africa, was dominated by scientists from outside Africa.
The Global Research Collaboration for Infectious Disease Preparedness, an international network of major research funding organisations, recently published a roadmap to data sharing. This may go some way to address the data sharing challenges. Members of the network are expected to encourage their grantees to be inclusive and publish their results in open access journals. The network includes major funders of research in Africa like the European Commission, Bill & Melinda Gates Foundation and Wellcome Trust.
The roadmap provides a guide on how funders can accelerate research data sharing by the scientists they fund. It recommends that research funding institutions make real-time, external data sharing a requirement. And that research needs to be part of a multi-disciplinary disease network to advance public health emergencies responses.
In addition, funding should focus on strengthening institutions’ capacity on a number of fronts. This includes data management, improving data policies, building trust and aligning tools for data sharing.
Allowing researchers to freely access data generated by global academic counterparts is critical for rapidly informing disease control strategies in public health emergencies….(More)”.
Paper by David Osimo and Francesco Mureddu: “Co-creation” and “design thinking” are trendy themes – the topic of innumerable conferences and a growing number of academic papers. But how do we turn co-creation into a reality for Europe’s 508 million citizens? In Co-Creation of Public Services: Why and How, Co-VAL’s new Policy Brief, co-authors Francesco Mureddu and David Osimo propose a ten-step roadmap for delivering genuinely user-centric digital government. The authors argue that it is time to put co-creation at the core of government functioning.
According to the authors, “today, co-creation is a mature subject. There is an extended theoretical and applied research effort underway, led in many places by members of the Co-VAL consortium, whose research informed the new policy brief. And there is a solid professional community, ready to deliver, and staffed by people with clearly identified job profiles, such as “user researcher” and “service designer.” There are even success stories of entire countries that scaled up design thinking at national level, such as Italy’s Government Commissioner and Digital Transformation Team and the United Kingdom’s legendary Government Digital Services.”…(More)”.
Article by John B. Morris Jr. and Cameron F. Kerry: “It’s my data.” It’s an idea often expressed about information privacy.
Indeed, in congressional hearings last year, Mark Zuckerberg said multiple times that “people own all of their own content” on Facebook. A survey by Insights Network earlier this year found that 79% of consumers said they want compensation when their data is shared. Musician and tech entrepreneur will.i.am took to the website of The Economist to argue that payment for data is a way to “redress the balance” between individuals and “data monarchs.”
Some policymakers are taking such thinking to heart. Senator John Kennedy (R-LA) introduced a three-page bill, the “Own Your Own Data Act of 2019,” which declares that “each individual owns and has an exclusive property right in the data that individual generates on the internet” and requires that social media companies obtain licenses to use this data. Senators Mark Warner (D-VA) and Josh Hawley (R-MO) are filing legislation to require Facebook, Google, and other large collectors of data to disclose the value of personal data they collect, although the bill would not require payments. In California, Governor Gavin Newsome wants to pursue a “data dividend” designed to “share in the wealth that is created from [people’s] data.”
Treating our data as our property has understandable appeal. It touches what the foundational privacy thinker Alan Westin identified as an essential aspect of privacy, a right “to control, edit, manage, and delete information about [individuals] and decide when, how, and to what extent information is communicated to others.” It expresses the unfairness people feel about an asymmetrical marketplace in which we know little about the data we share but the companies that receive the data can profit by extracting marketable information.
The trouble is, it’s not your data; it’s not their data either. Treating data like it is property fails to recognize either the value that varieties of personal information serve or the abiding interest that individuals have in their personal information even if they choose to “sell” it. Data is not a commodity. It is information. Any system of information rights—whether patents, copyrights, and other intellectual property, or privacy rights—presents some tension with strong interest in the free flow of information that is reflected by the First Amendment. Our personal information is in demand precisely because it has value to others and to society across a myriad of uses.
Treating personal information as property to be licensed or sold may induce people to trade away their privacy rights for very little value while injecting enormous friction into free flow of information. The better way to strengthen privacy is to ensure that individual privacy interests are respected as personal information flows to desirable uses, not to reduce personal data to a commodity….(More)”.
Matt Harder at Beyond Voting: “….Below, we’ll explore three websites that allow citizens to communicate better with their governing systems.
Countable.us makes it easier to know what your representatives are voting on, and to tell them how you think they should vote. For each upcoming bill, you can suggest a yea or nay to your representative via email or can even send video messages. Each bill also has a lively debate section so the yeas and nays can share, upvote their opinions and learn from each other. The result is seeing more informed and better arguments in favor of your preferences, and perhaps more importantly, against.
IssueVoter.us is similar to Countable in that you give your opinions to your representatives. But IssueVoter puts a different spin on it by giving you a “scorecard” highlighting how closely your representatives votes align to your preferences. The site is still new, so the functionality is not as great as it could be, but the concept is worth note.
Bang the Table focuses on engagement at a local level. They create civic engagement dashboards for cities that allow residents to stay informed and share opinions about city projects. They offer several levels of engagement, from simply dispensing information for the city to engaging citizens in collective discussions and decision making. Fayetteville, AR used them to make the engagement page Speak Up Fayetteville, which informed citizens about projects such as the Cultural Arts Corridor.
While none of these are driving massive change just yet, it’s easy to imagine how they could be enormously impactful if embraced at scale. First, they will all have to figure out how to design websites which are appealing enough to bring the masses, yet meaningful enough to benefit decision-makers. We’re stuck in the in-between phase where the internet is the most powerful communication medium, but we haven’t learned to utilize it for productive democratic purposes….(More)”.
Blog by Jim Nelson: “The idea is that web sites will verify you much as a bartender checks your ID before pouring a drink. The bar doesn’t store a copy of your card and the bartender doesn’t look at your name or address; only your age is pertinent to receive service. The next time you enter the bar the bartender once again asks for proof of age, which you may or may not relinquish. That’s the promise of self-sovereign identity.
At the Decentralized Web Summit, questions and solutions were bounced around in the hopes of solving this fundamental problem. Developers spearheading the next web hashed out the criteria for decentralized identity, including:
secure: to prevent fraud, maintain privacy, and ensure trust between all parties
self-sovereign: individual ownership of private information
consent: fine-tuned control over what information third-parties are privy to
directed identity: manage multiple identities for different contexts (for example, your doctor can access certain aspects while your insurance company accesses others)
and, of course, decentralized: no central authority or governing body holds private keys or generates identifiers
One problem with decentralized identity is that these problems often compete, pulling in polar directions.
Courtesy of Jolocom
For example, while security seems like a no-brainer, with self-sovereign identity the end-user is in control (and not Facebook, Google, or Twitter). It’s incumbent on them to secure their information. This raises questions of key management, data storage practices, and so on. Facebook, Google, and Twitter pay full-time engineers to do this job; handing that responsibility to end-users shifts the burden to someone who may not be so technically savvy. The inconvenience of key management and such also creates more hurdles for widespread adoption of the decentralized web.
The good news is, there are many working proposals today attempting to solve the above problems. One of the more promising is DID (Decentralized Identifier).
A DID is simply a URI, a familiar piece of text to most people nowadays. Each DID references a record stored in a blockchain. DIDs are not tied to any particular blockchain, and so they’re interoperable with existing and future technologies. DIDs are cryptographically secure as well.
DIDs require no central authority to produce or validate. If you want a DID, you can generate one yourself, or as many was you want. In fact, you should generate lots of them. Each unique DID gives the user fine-grained control over what personal information is revealed when interacting with a myriad of services and people.
Wolfgang Münchau at the Financial Times: “…Where the conflation of the expert and the policymaker did real damage was not to policy but to expertdom itself. It compromised the experts’ most prized asset — their independence.
When economics blogging started to become fashionable, I sat on a podium with an academic blogger who predicted that people like him would usurp the role of the economics newspaper columnist within a period of 10 years. That was a decade ago. His argument was that trained economists were just smarter. What he did not reckon with is that it is hard to speak truth to power when you have to beg that power to fund your think-tank or institute. E
ven less so once you are politically attached or appointed. Independence matters. A good example of a current issue where lack of independence gets in the way is the debate on cryptocurrencies. I agree that governments should not lightly concede the money monopoly of the state, which is at the heart of our economic system. But I sometimes wonder whether those who hyperventilate about crypto do so because they find the whole concept offensive. Cryptocurrencies embody a denial of economics. There are no monetary policy committees. Cryptocurrencies may, or may not, damage the economy. But they surely damage the economist.
Even the best arguments lose power when they get mixed up with personal interests. If you want to be treated as an independent authority, do not join a policy committee, or become a minister or central banker. As soon as you do, you have changed camps. You may think of yourself as an expert. The rest of the world does not. The minimum needed to maintain or regain credibility is to state conflicts of interests openly. The only option in such cases is to be transparent. This is also why financial journalists have to declare the shares they own. The experts I listen to are those who are independent, and who do not follow a political agenda. The ones I avoid are the zealots and those who wander off their reservation and make pronouncements without inhibition. An economist may have strong views on the benefits of vaccination, for example, but is still no expert on the subject. And I often cringe when I hear a doctor trying to prove a point by using statistics. The world will continue to need policymakers and the experts who advise them. But more than that, it needs them to be independent….(More)”.
Luke Stark & Anna Lauren Hoffmann at Quartz: “Data is, apparently, everything.
It’s the “new oil” that fuels online business. It comes in floods or tsunamis. We access it via “streams” or “fire hoses.” We scrape it, mine it, bank it, and clean it. (Or, if you prefer your buzzphrases with a dash of ageism and implicit misogyny, big data is like “teenage sex,” while working with it is “the sexiest job” of the century.)
These data metaphors can seem like empty cliches, but at their core they’re efforts to come to grips with the continuing onslaught of connected devices and the huge amounts of data they generate.
In a recent article, we—an algorithmic-fairness researcher at Microsoft and a data-ethics scholar at the University of Washington—push this connection one step further. More than simply helping us wrap our collective heads around data-fueled technological change, we set out to learn what these metaphors can teach us about the real-life ethics of collecting and handling data today.
Instead of only drawing from the norms and commitments of computer science, information science, and statistics, what if we looked at the ethics of the professions evoked by our data metaphors instead?…(More)”.
Beth Noveck at apolitical: “So how do we develop these better ways of working in government? How do we create a more effective public service?
Governments, universities and philanthropies are beginning to invest in training those inside and outside of government in new kinds of public entrepreneurial skills. They are also innovating in how they teach.
Canada has created a new Digital Academy to teach digital literacy to all 250,000 public servants. Among other approaches, they have created a 15 minute podcast series called bus rides to enable public servants to learn on their commute.
The better programs, like Canada’s, combine online and face-to-face methods. This is what Israel does in its Digital Leaders program. This nine-month program alternates between web- and live meetings as well as connecting learners to a global, online network of digital innovators.
Many countries have started to teach human-centred design to public servants, instructing officials in how to design services with, not simply for the public, as WeGov does in Brazil. in Chile, the UAI University has just begun teaching quantitative skills, offering three day intensives in data science for public servants.
To ensure that learning translates into practice, Australia’s BizLab Academy, turns students into teachers by using alumni of their human-centred design training as mentors for new students.
The Cities of Orlando and Sao Paulo go beyond training public servants. Orlando includes members of the public in its training program for city officials. Because they are learning to redesign services with citizens, the public participates in the training.
The Sao Paulo Abierta program uses citizens as trainers for the city’s public servants. Over 23,000 of them have studied with these lay trainers, who possess the innovation skills that are in short supply in government. In fact, public officials are prohibited from teaching in the program altogether.
Image from the ten recommendations for training public entrepreneurs. Read all the recommendations here.
Recognising that it is not enough to train only a lone innovator or data scientist in a unit, governments are scaling their programs across the public sector.
Argentina’s LabGob has already trained 30,000 people since 2016 in its Design Academy for Public Policy with plans to expand. For every class taken, a public servant earns points, which are a prerequisite for promotions and pay raises in the Argentinian civil service.
Rather than going broad, some training programs are going deep by teaching sector-specific innovation skills. The NHS Digital Academy done in collaboration with Imperial College is a series of six online and four live sessions designed to produce leaders in health innovation.
Innovating in a bureaucracy
In my own work at the GovLab at New York University, we are helping public entrepreneurs take their public interest projects from idea to implementation using coaching, rather than training.
Training classes may be wonderful but leave people feeling abandoned when they return to their desks to face the challenge of innovating within a bureaucracy.
With hands-on mentoring from global leaders and peer-to-peer support, the GovLab Academycoaching programs try to ensure that public servants are getting the help they need to advance innovative projects.
About: “Whether we work within schools or as part of the broader ecosystem of parent-teacher associations, and philanthropic, nonprofit, and volunteer organizations, we need data to guide decisions about investing our time and resources.
This data is typically expensive to gather, often unvalidated (e.g. self-reported), and commonly available only to those who collect or report it. It can even be hard to ask for data when it’s not clear what’s available. At the same time, information – in the form of discrete research, report-card style PDFs, or static websites – is everywhere. The result is that many already resource-thin organizations that could be collaborating around strategies to help kids advance, spend a lot of time in isolation collecting and searching for data.
In the past decade, we’ve seen solid progress in addressing part of the problem: the emergence of connected longitudinal data systems (LDS). These warehouses and linked databases contain data that can help us understand how students progress over time. No personally identifiable information (or PII) is shared, yet the data can reveal where interventions are most needed. Because these systems are typically designed for researchers and policy professionals, they are rarely accessible to the educators, parents, and partners – arts, sports, academic enrichment (e.g. STEM), mentoring, and family support programs – that play such important roles in helping young people learn and succeed…
“We need open tools for the ecosystem – parents, volunteers, non-profit organizations and the foundations and agencies that support them. These partners can realize significant benefit from the same kind of data policy makers and education leaders hold in their LDS.
That’s why we’re launching the Education Data Collaborative. Working together, we can build tools that help us use data to improve the design, efficacy, and impact of programs and interventions and find new way to work with public education systems to achieve great things for kids. …Data collaboratives, data trusts, and other kinds of multi-sector data partnerships are among the most important civic innovations to emerge in the past decade….(More)”
