Is it time to challenge the power of philanthropy?

Curated on Posted on by Stefaan Verhulst

Blog post by Magdalena Kuenkel: “Over the past six months, we’ve partnered with Nesta to explore some of these questions. In the “Foundation Horizon Scan,” unveiled at an event today with sector leaders, we take the long view to explore the future of philanthropic giving. In compiling the report, we reviewed relevant literature and spoke to over 30 foundation leaders and critics internationally to understand what the challenges to foundations’ legitimacy and impact mean in practice and how foundations are responding to them today. 

We learned about new grantmaking practices that give more power to grantees and/or beneficiaries and leverage the power of digital technologies. We heard about alternative governance models to address power imbalances and saw many more collaborative efforts (big and small) to address today’s complex challenges. We spoke to funders who prioritise place-based giving in order to ensure that beneficiaries’ voices are heard.

Alongside these practical responses, we also identified eight strategic areas where foundations face difficult trade-offs:

  • Power and control
  • Diversity
  • Transparency
  • Role in public sector delivery
  • Time horizons
  • Monitoring, evaluation and learning
  • Assets
  • Collaboration 

There are no simple solutions. When devising future strategies, foundations will inevitably have to make tradeoffs between different priorities. Pursuing one path might well mean forfeiting the benefits afforded by a different approach. Near-term vs. long-term? Supporting vs. challenging government? Measuring vs. learning?

The “Foundation Horizon Scan” is an invitation to explore these issues – it is directed at foundation leaders, boards, grantees and beneficiaries. What do you think is the role of philanthropy in the future and what share of power should they hold in society?… (More)”.

Voting could be the problem with democracy

Curated on Posted on by Stefaan Verhulst

Bernd Reiter at The Conversation: “Around the globe, citizens of many democracies are worried that their governments are not doing what the people want.

When voters pick representatives to engage in democracy, they hope they are picking people who will understand and respond to constituents’ needs. U.S. representatives have, on average, more than 700,000 constituents each, making this task more and more elusive, even with the best of intentions. Less than 40% of Americans are satisfied with their federal government.

Across Europe, South America, the Middle East and China, social movements have demanded better government – but gotten few real and lasting results, even in those places where governments were forced out.

In my work as a comparative political scientist working on democracy, citizenship and race, I’ve been researching democratic innovations in the past and present. In my new book, “The Crisis of Liberal Democracy and the Path Ahead: Alternatives to Political Representation and Capitalism,” I explore the idea that the problem might actually be democratic elections themselves.

My research shows that another approach – randomly selecting citizens to take turns governing – offers the promise of reinvigorating struggling democracies. That could make them more responsive to citizen needs and preferences, and less vulnerable to outside manipulation….

For local affairs, citizens can participate directly in local decisions. In Vermont, the first Tuesday of March is Town Meeting Day, a public holiday during which residents gather at town halls to debate and discuss any issue they wish.

In some Swiss cantons, townspeople meet once a year, in what are called Landsgemeinden, to elect public officials and discuss the budget.

For more than 30 years, communities around the world have involved average citizens in decisions about how to spend public money in a process called “participatory budgeting,” which involves public meetings and the participation of neighborhood associations. As many as 7,000 towns and cities allocate at least some of their money this way.

The Governance Lab, based at New York University, has taken crowd-sourcing to cities seeking creative solutions to some of their most pressing problems in a process best called “crowd-problem solving.” Rather than leaving problems to a handful of bureaucrats and experts, all the inhabitants of a community can participate in brainstorming ideas and selecting workable possibilities.

Digital technology makes it easier for larger groups of people to inform themselves about, and participate in, potential solutions to public problems. In the Polish harbor city of Gdansk, for instance, citizens were able to help choose ways to reduce the harm caused by flooding….(More)”.

Are Randomized Poverty-Alleviation Experiments Ethical?

Curated on Posted on by Stefaan Verhulst

Peter Singer et al at Project Syndicate: “Last month, the Nobel Memorial Prize in Economic Sciences was awarded to three pioneers in using randomized controlled trials (RCTs) to fight poverty in low-income countries: Abhijit Banerjee, Esther Duflo, and Michael Kremer. In RCTs, researchers randomly choose a group of people to receive an intervention, and a control group of people who do not, and then compare the outcomes. Medical researchers use this method to test new drugs or surgical techniques, and anti-poverty researchers use it alongside other methods to discover which policies or interventions are most effective. Thanks to the work of Banerjee, Duflo, Kremer, and others, RCTs have become a powerful tool in the fight against poverty.

But the use of RCTs does raise ethical questions, because they require randomly choosing who receives a new drug or aid program, and those in the control group often receive no intervention or one that may be inferior. One could object to this on principle, following Kant’s claim that it is always wrong to use human beings as a means to an end; critics have argued that RCTs “sacrifice the well-being of study participants in order to ‘learn.’”

Rejecting all RCTs on this basis, however, would also rule out the clinical trials on which modern medicine relies to develop new treatments. In RCTs, participants in both the control and treatment groups are told what the study is about, sign up voluntarily, and can drop out at any time. To prevent people from choosing to participate in such trials would be excessively paternalistic, and a violation of their personal freedom.

A less extreme version of the criticism argues that while medical RCTs are conducted only if there are genuine doubts about a treatment’s merits, many development RCTs test interventions, such as cash transfers, that are clearly better than nothing. In this case, maybe one should just provide the treatment?

This criticism neglects two considerations. First, it is not always obvious what is better, even for seemingly stark examples like this one. For example, before RCT evidence to the contrary, it was feared that cash transfers lead to conflict and alcoholism.

Second, in many development settings, there are not enough resources to help everyone, creating a natural control group….

A third version of the ethical objection is that participants may actually be harmed by RCTs. For example, cash transfers might cause price inflation and make non-recipients poorer, or make non-recipients envious and unhappy. These effects might even affect people who never consented to be part of a study.

This is perhaps the most serious criticism, but it, too, does not make RCTs unethical in general….(More)”.

Artificial intelligence: From expert-only to everywhere

Curated on Posted on by Stefaan Verhulst

Deloitte: “…AI consists of multiple technologies. At its foundation are machine learning and its more complex offspring, deep-learning neural networks. These technologies animate AI applications such as computer vision, natural language processing, and the ability to harness huge troves of data to make accurate predictions and to unearth hidden insights (see sidebar, “The parlance of AI technologies”). The recent excitement around AI stems from advances in machine learning and deep-learning neural networks—and the myriad ways these technologies can help companies improve their operations, develop new offerings, and provide better customer service at a lower cost.

The trouble with AI, however, is that to date, many companies have lacked the expertise and resources to take full advantage of it. Machine learning and deep learning typically require teams of AI experts, access to large data sets, and specialized infrastructure and processing power. Companies that can bring these assets to bear then need to find the right use cases for applying AI, create customized solutions, and scale them throughout the company. All of this requires a level of investment and sophistication that takes time to develop, and is out of reach for many….

These tech giants are using AI to create billion-dollar services and to transform their operations. To develop their AI services, they’re following a familiar playbook: (1) find a solution to an internal challenge or opportunity; (2) perfect the solution at scale within the company; and (3) launch a service that quickly attracts mass adoption. Hence, we see Amazon, Google, Microsoft, and China’s BATs launching AI development platforms and stand-alone applications to the wider market based on their own experience using them.

Joining them are big enterprise software companies that are integrating AI capabilities into cloud-based enterprise software and bringing them to the mass market. Salesforce, for instance, integrated its AI-enabled business intelligence tool, Einstein, into its CRM software in September 2016; the company claims to deliver 1 billion predictions per day to users. SAP integrated AI into its cloud-based ERP system, S4/HANA, to support specific business processes such as sales, finance, procurement, and the supply chain. S4/HANA has around 8,000 enterprise users, and SAP is driving its adoption by announcing that the company will not support legacy SAP ERP systems past 2025.

A host of startups is also sprinting into this market with cloud-based development tools and applications. These startups include at least six AI “unicorns,” two of which are based in China. Some of these companies target a specific industry or use case. For example, Crowdstrike, a US-based AI unicorn, focuses on cybersecurity, while Benevolent.ai uses AI to improve drug discovery.

The upshot is that these innovators are making it easier for more companies to benefit from AI technology even if they lack top technical talent, access to huge data sets, and their own massive computing power. Through the cloud, they can access services that address these shortfalls—without having to make big upfront investments. In short, the cloud is democratizing access to AI by giving companies the ability to use it now….(More)”.

OMB rethinks ‘protected’ or ‘open’ data binary with upcoming Evidence Act guidance

Curated on Posted on by Stefaan Verhulst

Jory Heckman at Federal News Network: “The Foundations for Evidence-Based Policymaking Act has ordered agencies to share their datasets internally and with other government partners — unless, of course, doing so would break the law.

Nearly a year after President Donald Trump signed the bill into law, agencies still have only a murky idea of what data they can share, and with whom. But soon, they’ll have more nuanced options of ranking the sensitivity of their datasets before sharing them out to others.

Chief Statistician Nancy Potok said the Office of Management and Budget will soon release proposed guidelines for agencies to provide “tiered” access to their data, based on the sensitivity of that information….

OMB, as part of its Evidence Act rollout, will also rethink how agencies ensure protected access to data for research. Potok said agency officials expect to pilot a single application governmentwide for people seeking access to sensitive data not available to the public.

The pilot resembles plans for a National Secure Data Service envisioned by the Commission on Evidence-Based Policymaking, an advisory group whose recommendations laid the groundwork for the Evidence Act.

“As a state-of-the-art resource for improving government’s capacity to use the data it already collects, the National Secure Data Service will be able to temporarily link existing data and provide secure access to those data for exclusively statistical purposes in connection with approved projects,” the commission wrote in its 2017 final report.

In an effort to strike a balance between access and privacy, Potok said OMB has also asked agencies to provide a list of the statutes that prohibit them from sharing data amongst themselves….(More)”.

Using speculative design to explore the future of Open Justice

Curated on Posted on by Stefaan Verhulst

UK Policy Lab: “Open justice is the principle that ‘justice should not only be done, but should manifestly and undoubtedly be seen to be done’(1). It is a very well established principle within our justice system, however new digital tools and approaches are creating new opportunities and potential challenges which necessitate significant rethinking on how open justice is delivered.

In this context, HM Courts & Tribunal Service (HMCTS) wanted to consider how the principle of open justice should be delivered in the future. As well as seeking input from those who most commonly work with courtrooms, like judges, court staff and legal professionals, they also wanted to explore a range of public views. HMCTS asked us to create a methodology which could spark a wide-ranging conversation about open justice, collecting diverse and divergent perspectives….

We approached this challenge by using speculative design to explore possible and desirable futures with citizens. In this blog we will share what we did (including how you can re-use our materials and approach), what we’ve learned, and what we’ll be experimenting with from here.

What we did

We ran 4 groups of 10 to 12 participants each. We spent the first 30 minutes discussing what participants understood and thought about Open Justice in the present. We spent the next 90 minutes using provocations to immerse them in a range of fictional futures, in which the justice system is accessed through a range of digital platforms.

The provocations were designed to:

  • engage even those with no prior interest, experience or knowledge of Open Justice
  • be reusable
  • not look like ‘finished’ government policy – we wanted to find out more about desirable outcomes
  • as far as possible, provoke discussion without leading
This is an image of one of the provocation cards used in the Open Justice focus groups
Open Justice ‘provocation cards’ used with focus groups

Using provocations to help participants think about the future allowed us to distill common principles which HMCTS can use when designing specific delivery mechanisms.

We hope the conversation can continue. HMCTS have published the provocations on their website. We encourage people to reuse them, or to use them to create their own….(More)”.

Innovation Partnerships: An effective but under-used tool for buying innovation

Curated on Posted on by Stefaan Verhulst

Claire Gamage at Challenging Procurement: “…in an era where demand for public sector services increases as budgets decrease, the public sector should start to consider alternative routes to procurement. …

What is the Innovation Partnership procedure?

In a nutshell, it is essentially a procurement process combined with an R&D contract. Authorities are then able to purchase the ‘end result’ of the R&D exercise, without having to undergo a new procurement procedure. Authorities may choose to appoint a number of partners to participate in the R&D phase, but may subsequently only purchase one/some of those solutions.

Why does this procedure result in more innovative solutions?

The procedure was designed to drive innovation. Indeed, it may only be used in circumstances where a solution is not already available on the open market. Therefore, participants in the Innovation Partnership will be asked to create something which does not already exist and should be tailored towards solving a particular problem or ‘challenge’ set by the authority.

This procedure may also be particularly attractive to SMEs/start-ups, who often find it easier to innovate in comparison with their larger competitors and therefore the purchasing authority is perhaps likely to obtain a more innovative product or service.

One of the key advantages of an Innovation Partnership is that the R&D phase is separate to the subsequent purchase of the solution. In other words, the authority is not (usually) under any obligation to purchase the ‘end result’ of the R&D exercise, but has the option to do so if it wishes. Therefore, it may be easier to discourage internal stakeholders from imposing selection criteria which inadvertently exclude SMEs/start-ups (e.g. minimum turnover requirements, parent company guarantees etc.), as the authority is not committed to actually purchasing at the end of the procurement process which will select the innovation partner(s)….(More)”.

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)”.