Addressing the Challenges of Drafting Contracts for Data Collaboration

Curated on Posted on by Stefaan Verhulst

Blog post by Andrew Young, Andrew J. Zahuranec, Stephen Burley Tubman, William Hoffman, and Stefaan Verhulst at Data & Society: “To deal with complex public challenges, organizations increasingly seek to leverage data across sectors in new and innovative ways — from establishing prize-backed challenges around the use of diverse datasets to creating cross-sector federated data systems. These and other forms of data collaboratives are part of a new paradigm in data-driven innovation in which participants from different sectors provide access to data for the creation of public value. It provides an essential new problem-solving approach for our increasingly datafied society. However, the operational challenges associated with creating such partnerships often prevent the transformative potential of data collaboration from being achieved.

One such operational challenge relates to developing data sharing agreements — through contracts and other legal documentation. The current practice suffers from large inefficiencies and transaction costs resulting from (i) the lack of a common understanding of what the core issues are with data exchange; (ii) lack of common language or models; (iii) large heterogeneity in agreements used; (iv) lack of familiarity among lawyers of the technologies involved and (v) a sense that every initiative needs to (re)invent the wheel. Removing these barriers may enable collaborators to partner more systematically and responsibly around the re-use of data assets. Contracts for Data Collaboration (C4DC) is a new initiative seeking to address these barriers to data collaboration…

In the longer term, participants focused on three major themes that, if addressed, could steer contracting for data collaboration toward greater effectiveness and legitimacy.

Data Stewardship and Responsibility: First, much of the discussion centered on the need to promote responsible data practices through data stewardship. Though part of this work involves creating teams and individuals empowered to share, it also means empowering them to operationalize ethical principles.

By developing international standards and moving beyond the bare minimum legal obligation, these actors can build trust between parties, a quality that has often been difficult to foster. Such relationships are key in engaging intermediaries or building complex contractual agreements between multiple organizations. It is also essential to come to an agreement about which practices are legitimate and illegitimate.

Incorporation of the Citizen Perspective: Trust is also needed between the actors in a data collaborative and the general public. In light of many recent stories about the misuse of data, many people are suspicious, if not outright hostile, to data partnerships. Many data subjects don’t understand why organizations want their data or how the information can be valuable in advancing public good.

In data-sharing arrangements, all actors need to explain intended uses and outcomes to data subjects. Attendees spoke about the need to explain the data’s utility in clear and accessible terms. They also noted data collaborative contracts are more legitimate if they incorporate citizen perspectives, especially those of marginalized groups. To take this work a step further, the public could be brought into the contract writing process by creating mechanisms capable of soliciting their views and concerns.

Improving Internal and External Collaboration: Lastly, participants discussed the need for actors across the data ecosystem to strengthen relationships inside and outside their organizations. Part of this work entails securing internal buy-in for data collaboration, ensuring that the different components of an organization understand what assets are being shared and why.

It also entails engaging with intermediaries to fill gaps. Each actor has limitations to their capacities and expertise and, by engaging with start-ups, funders, NGOs, and others, organizations can improve the odds of a successful collaboration. Together, organizations can create norms and shared languages that allow for more effective data flows.

One such operational challenge relates to developing data sharing agreements — through contracts and other legal documentation. The current practice suffers from large inefficiencies and transaction costs resulting from (i) the lack of a common understanding of what the core issues are with data exchange; (ii) lack of common language or models; (iii) large heterogeneity in agreements used; (iv) lack of familiarity among lawyers of the technologies involved and (v) a sense that every initiative needs to (re)invent the wheel. Removing these barriers may enable collaborators to partner more systematically and responsibly around the re-use of data assets. Contracts for Data Collaboration (C4DC) is a new initiative seeking to address these barriers to data collaboration…(More)”.

Rethinking Encryption

Curated on Posted on by Stefaan Verhulst

Jim Baker at Lawfare: “…Public safety officials should continue to highlight instances where they find that encryption hinders their ability to effectively and efficiently protect society so that the public and lawmakers understand the trade-offs they are allowing. To do this, the Justice Department should, for example, file an annual public report describing, as best it can, the continuing nature and scope of the going dark problem. If necessary, it can also file a classified annual report with the appropriate congressional committees.

But, for the reasons discussed above, public safety officials should also become among the strongest supporters of widely available strong encryption.

I know full well that this approach will be a bitter pill for some in law enforcement and other public safety fields to swallow, and many people will reject it outright. It may make some of my former colleagues angry at me. I expect that some will say that I’m simply joining others who have left the government and switched sides on encryption to curry favor with the tech sector in order to get a job. That is wrong. My dim views about cybersecurity risks, China and Huawei are essentially the same as those that I held while in government. I also think that my overall approach on encryption today—as well as my frustration with Congress—is generally consistent with the approach I had while I was in government.

I have long said—as I do here—that encryption poses real challenges for public safety officials; that any proposed technical solution must properly balance all of the competing equities; and that (absent an unlikely definitive judicial ruling as a result of litigation) Congress must change the law to resolve the issue. What has changed is my acceptance of, or perhaps resignation to, the fact that Congress is unlikely to act, as well as my assessment that the relevant cybersecurity risks to society have grown disproportionately over the years when compared with other risks….(More)”.

Becoming a data steward

Curated on Posted on by Stefaan Verhulst

Shalini Kurapati at the LSE Impact Blog: “In the context of higher education, data stewards are the first point of reference for all data related questions. In my role as a data steward at TU Delft, I was able to advise, support and train researchers on various aspects of data management throughout the life cycle of a research project, from initial planning to post-publication. This included storing, managing and sharing research outputs such as data, images, models and code.

Data stewards also advise researchers on the ethical, policy and legal considerations during data collection, processing and dissemination. In a way, they are general practitioners for research data management and can usually solve most problems faced by academics. In cases that require specialist intervention, they also serve as a key point for referral (eg: IT, patent, legal experts).

Data stewardship is often organised centrally through the university library. (Subject) Data librarians, research data consultants and research data officers, usually perform similar roles to data stewards. However, TU Delft operates a decentralised model, where data stewards are placed within faculties as disciplinary experts with research experience. This allows data stewards to provide discipline specific support to researchers, which is particularly beneficial, as the concept of what data is itself varies across disciplines….(More)”.

Civic Duty Days: One Way Employers Can Strengthen Democracy

Curated on Posted on by Stefaan Verhulst

Blog by Erin Barnes: “As an employer, I’m always looking for structural ways to support my team in their health and wellbeing. We know that individual health is so often tied to community health: strong communities mean, among other things, better health outcomes, reduced crime, and better education for our children, so making space for my team to be able to be active participants in their neighborhoods gives them and their families better health outcomes. So, from my perspective, allowing time to give back to the community is just as important as providing sick days.

When my cofounder Brandon Whitney and I started ioby — a nonprofit focused on building civic leadership in our neighborhoods — we wanted our internal organizational values to reflect our mission. For example, we’ve always given Election Day off, and Brandon created ioby’s Whole Person Policy inspired by the work of Parker Palmer. And a few years ago, after a series of high-profile killings of people of color by police made it difficult for many of our staff to feel fully present at work while also showing up for those in their community who were struggling with pain and grief, we decided to add an additional 5 days of Paid Time Off (PTO) for civic duty.

At ioby, a Civic Duty Day is not the same as jury duty. Civic Duty Days are designed to give ioby staff the time to do what we need to do to be active participants involved in everyday democracy. Activities can include neighborhood volunteering, get-out-the-vote volunteering, fundraising, self-care and community-care to respond to local and national emergencies, writing letters, meeting with local elected officials, making calls, going to a healing workshop, and personal health to recover from civic duty activities that fall on weekends.

A couple weeks ago, at a retreat with other nonprofit leaders, we were discussing structural ways to increase civic participation in the United States. Given that nearly 15% of Americans cite lack of time as their reason for not voting, and 75% of Americans cite it as their reason for not volunteering, employers can make a big difference in how Americans show up in public life.

I asked my team what sorts of things they’ve used Civic Duty Days for. In addition to the typical answers about park cleanups, phone banking, door knocking and canvassing, postcard writing, attending demonstrations like the Women’s March and the Climate Strike, I heard some interesting stories.

  • One ioby staff person used her Civic Duty Days to attend Reverse Ride Alongs where she acts as a guide with cadets for the entire day. This program allows cadets to see the community they will be serving and for the community to have a voice in how they see policing and what ways best to be approached by new police officers.
  • An ioby staff person used Civic Duty Days to attend trial for an activist who was arrested for protesting; this would have been impossible to attend otherwise since trials are often during the day.
  • Another ioby staff person used his days to stay home with his kids while his wife attended demonstrations….(More)”

How to ensure that your data science is inclusive

Curated on Posted on by Stefaan Verhulst

Blog by Samhir Vasdev: “As a new generation of data scientists emerges in Africa, they will encounter relatively little trusted, accurate, and accessible data upon which to apply their skills. It’s time to acknowledge the limitations of the data sources upon which data science relies, particularly in lower-income countries.

The potential of data science to support, measure, and amplify sustainable development is undeniable. As public, private, and civic institutions around the world recognize the role that data science can play in advancing their growth, an increasingly robust array of efforts has emerged to foster data science in lower-income countries.

This phenomenon is particularly salient in Sub-Saharan Africa. There, foundations are investing millions into building data literacy and data science skills across the continent. Multilaterals and national governments are pioneering new investments into data science, artificial intelligence, and smart cities. Private and public donors are building data science centers to build cohorts of local, indigenous data science talent. Local universities are launching graduate-level data science courses.

Despite this progress, among the hype surrounding data science rests an unpopular and inconvenient truth: As a new generation of data scientists emerges in Africa, they will encounter relatively little trusted, accurate, and accessible data that they can use for data science.

We hear promises of how data science can help teachers tailor curricula according to students’ performances, but many school systems don’t collect or track that performance data with enough accuracy and timeliness to perform those data science–enabled tweaks. We believe that data science can help us catch disease outbreaks early, but health care facilities often lack the specific data, like patient origin or digitized information, that is needed to discern those insights.

These fundamental data gaps invite the question: Precisely what data would we perform data science on to achieve sustainable development?…(More)”.

Timing Technology

Curated on Posted on by Stefaan Verhulst

Blog by Gwern Branwen: “Technological forecasts are often surprisingly prescient in terms of predicting that something was possible & desirable and what they predict eventually happens; but they are far less successful at predicting the timing, and almost always fail, with the success (and riches) going to another.

Why is their knowledge so useless? The right moment cannot be known exactly in advance, so attempts to forecast will typically be off by years or worse. For many claims, there is no way to invest in an idea except by going all in and launching a company, resulting in extreme variance in outcomes, even when the idea is good and the forecasts correct about the (eventual) outcome.

Progress can happen and can be foreseen long before, but the details and exact timing due to bottlenecks are too difficult to get right. Launching too early means failure, but being conservative & launching later is just as bad because regardless of forecasting, a good idea will draw overly-optimistic researchers or entrepreneurs to it like moths to a flame: all get immolated but the one with the dumb luck to kiss the flame at the perfect instant, who then wins everything, at which point everyone can see that the optimal time is past. All major success stories overshadow their long list of predecessors who did the same thing, but got unlucky. So, ideas can be divided into the overly-optimistic & likely doomed, or the fait accompli. On an individual level, ideas are worthless because so many others have them too—‘multiple invention’ is the rule, and not the exception.

This overall problem falls under the reinforcement learning paradigm, and successful approaches are analogous to Thompson sampling/posterior sampling: even an informed strategy can’t reliably beat random exploration which gradually shifts towards successful areas while continuing to take occasional long shots. Since people tend to systematically over-exploit, how is this implemented? Apparently by individuals acting suboptimally on the personal level, but optimally on societal level by serving as random exploration.

A major benefit of R&D, then, is in laying fallow until the ‘ripe time’ when they can be immediately exploited in previously-unpredictable ways; applied R&D or VC strategies should focus on maintaining diversity of investments, while continuing to flexibly revisit previous failures which forecasts indicate may have reached ‘ripe time’. This balances overall exploitation & exploration to progress as fast as possible, showing the usefulness of technological forecasting on a global level despite its uselessness to individuals….(More)”.

Ethical guidelines issued by engineers’ organization fail to gain traction

Curated on Posted on by Stefaan Verhulst

Blogpost by Nicolas Kayser-Bril: “In early 2016, the Institute of Electrical and Electronics Engineers, a professional association known as IEEE, launched a “global initiative to advance ethics in technology.” After almost three years of work and multiple rounds of exchange with experts on the topic, it released last April the first edition of Ethically Aligned Design, a 300-page treatise on the ethics of automated systems.

The general principles issued in the report focus on transparency, human rights and accountability, among other topics. As such, they are not very different from the 83 other ethical guidelines that researchers from the Health Ethics and Policy Lab of the Swiss Federal Institute of Technology in Zurich reviewed in an article published in Nature Machine Intelligence in September. However, one key aspect makes IEEE different from other think-tanks. With over 420,000 members, it is the world’s largest engineers’ association with roots reaching deep into Silicon Valley. Vint Cerf, one of Google’s Vice Presidents, is an IEEE “life fellow.”

Because the purpose of the IEEE principles is to serve as a “key reference for the work of technologists”, and because many technologists contributed to their conception, we wanted to know how three technology companies, Facebook, Google and Twitter, were planning to implement them.

Transparency and accountability

Principle number 5, for instance, requires that the basis of a particular automated decision be “discoverable”. On Facebook and Instagram, the reasons why a particular item is shown on a user’s feed are all but discoverable. Facebook’s “Why You’re Seeing This Post” feature explains that “many factors” are involved in the decision to show a specific item. The help page designed to clarify the matter fails to do so: many sentences there use opaque wording (users are told that “some things influence ranking”, for instance) and the basis of the decisions governing their newsfeeds are impossible to find.

Principle number 6 states that any autonomous system shall “provide an unambiguous rationale for all decisions made.” Google’s advertising systems do not provide an unambiguous rationale when explaining why a particular advert was shown to a user. A click on “Why This Ad” states that an “ad may be based on general factors … [and] information collected by the publisher” (our emphasis). Such vagueness is antithetical to the requirement for explicitness.

AlgorithmWatch sent detailed letters (which you can read below this article) with these examples and more, asking Google, Facebook and Twitter how they planned to implement the IEEE guidelines. This was in June. After a great many emails, phone calls and personal meetings, only Twitter answered. Google gave a vague comment and Facebook promised an answer which never came…(More)”

The weather data gap: How can mobile technology make smallholder farmers climate resilient?

Curated on Posted on by Stefaan Verhulst

Rishi Raithatha at GSMA: “In the new GSMA AgriTech report, Mobile Technology for Climate Resilience: The role of mobile operators in bridging the data gap, we explore how mobile network operators (MNOs) can play a bigger role in developing and delivering services to strengthen the climate resilience of smallholder farmers. By harnessing their own assets and data, MNOs can improve a broad suite of weather products that are especially relevant for farming communities. These include a variety of weather forecasts (daily, weekly, sub-seasonal and seasonal) and nowcasts, as real-time monitoring and one- to two-hour predictions are often used for Early Warning Systems (EWS) to prevent weather-related disasters. MNOs can also help strengthen the value proposition of other climate products, such as weather index insurance and decision agriculture.

Why do we need more weather data?

Agriculture is highly dependent on regional climates, especially in developing countries where farming is largely rain-fed. Smallholder farmers, who are responsible for the bulk of agricultural production in developing countries, are particularly vulnerable to changing weather patterns – especially given their reliance on natural resources and exclusion from social protection schemes. However, the use of climate adaptation approaches, such as localised weather forecasts and weather index insurance, can enhance smallholder farmers’ ability to withstand the risks posed by climate change and maintain agricultural productivity.

Ground-level measurements are an essential component of climate resilience products; the creation of weather forecasts and nowcasts starts with the analysis of ground, spatial and aerial observations. This involves the use of algorithms, weather models and current and historical observational weather data. Observational instruments, such as radar, weather stations and satellites, are necessary in measuring ground-level weather. However, National Hydrological and Meteorological Services (NHMSs) in developing countries often lack the capacity to generate accurate ground-level measurements beyond a few areas, resulting in gaps in local weather data.

While satellite offers better quality resolution than before, and is more affordable and available to NHMSs, there is a need to complement this data with ground-level measurements. This is especially true in tropical and sub-tropical regions where most smallholder farmers live, where variable local weather patterns can lead to skewed averages from satellite data….(More).”

Why policy networks don’t work (the way we think they do)

Curated on Posted on by Stefaan Verhulst

Blog by James Georgalakis: “Is it who you know or what you know? The literature on evidence uptake and the role of communities of experts mobilised at times of crisis convinced me that a useful approach would be to map the social network that emerged around the UK-led mission to Sierra Leone so it could be quantitatively analysed. Despite the well-deserved plaudits for my colleagues at IDS and their partners in the London School of Hygiene and Tropical Medicine, the UK Department for International Development (DFID), the Wellcome Trust and elsewhere, I was curious to know why they had still met real resistance to some of their policy advice. This included the provision of home care kits for victims of the virus who could not access government or NGO run Ebola Treatment Units (ETUs).

It seemed unlikely these challenges were related to poor communications. The timely provision of accessible research knowledge by the Ebola Response Anthropology Platform has been one of the most celebrated aspects of the mobilisation of anthropological expertise. This approach is now being replicated in the current Ebola response in the Democratic Republic of Congo (DRC).  Perhaps the answer was in the network itself. This was certainly indicated by some of the accounts of the crisis by those directly involved.

Social network analysis

I started by identifying the most important looking policy interactions that took place between March 2014, prior to the UK assuming leadership of the Sierra Leone international response and mid-2016, when West Africa was finally declared Ebola free. They had to be central to the efforts to coordinate the UK response and harness the use of evidence. I then looked for documents related to these events, a mixture of committee minutes, reports and correspondence , that could confirm who was an active participant in each. This analysis of secondary sources related to eight separate policy processes and produced a list of 129 individuals. However, I later removed a large UK conference that took place in early 2016 at which learning from the crisis was shared.  It appeared that most delegates had no significant involvement in giving policy advice during the crisis. This reduced the network to 77….(More)”.

Three Big Things: The Most Important Forces Shaping the World

Curated on Posted on by Stefaan Verhulst

Essay by Morgan Housel: “An irony of studying history is that we often know exactly how a story ends, but have no idea where it began…

Nothing is as influential as World War II has been. But there are a few other Big Things worth paying attention to, because they’re the root influencer of so many other topics.

The three big ones that stick out are demographics, inequality, and access to information.

There are hundreds of forces shaping the world not mentioned here. But I’d argue that many, even most, are derivatives of those three.

Each of these Big Things will have a profound impact on the coming decades because they’re both transformational and ubiquitous. They impact nearly everyone, albeit in different ways. With that comes the reality that we don’t know exactly how their influence will unfold. No one in 1945 knew exactly how World War II would go on to shape the world, only that it would in extreme ways. But we can guess some of the likeliest changes.

Essay by Morgan Housel: “An irony of studying history is that we often know exactly how a story ends, but have no idea where it began…

3. Access to information closes gaps that used to create a social shield of ignorance.

Carole Cole disappeared in 1970 after running away from a juvenile detention center in Texas. She was 17.

A year later an unidentified murdered body was found in Louisiana. It was Carole, but Louisiana police had no idea. They couldn’t identify her. Carole’s disappearance went cold, as did the unidentified body.

Thirty-four years later Carole’s sister posted messages on Craigslist asking for clues into her sister’s disappearance. At nearly the same time, a sheriff’s department in Louisiana made a Facebook page asking for help identifying the Jane Doe body found 34 years before.

Six days later, someone connected the dots between the two posts.

What stumped detectives for almost four decades was solved by Facebook and Craigslist in less than a week.

This kind of stuff didn’t happen even 10 years ago. And we probably haven’t awoken to its full potential – good and bad.

The greatest innovation of the last generation has been the destruction of information barriers that used to keep strangers isolated from one another…(More)”