Measuring Social Change: Performance and Accountability in a Complex World

Curated on Posted on by Stefaan Verhulst

Book by Alnoor Ebrahim: “The social sector is undergoing a major transformation. We are witnessing an explosion in efforts to deliver social change, a burgeoning impact investing industry, and an unprecedented intergenerational transfer of wealth. Yet we live in a world of rapidly rising inequality, where social sector services are unable to keep up with societal need, and governments are stretched beyond their means.

Alnoor Ebrahim addresses one of the fundamental dilemmas facing leaders as they navigate this uncertain terrain: performance measurement. How can they track performance towards worthy goals such as reducing poverty, improving public health, or advancing human rights? What results can they reasonably measure and legitimately take credit for? This book tackles three core challenges of performance faced by social enterprises and nonprofit organizations alike: what to measure, what kinds of performance systems to build, and how to align multiple demands for accountability. It lays out four different types of strategies for managers to consider—niche, integrated, emergent, and ecosystem—and details the types of performance measurement and accountability systems best suited to each. Finally, this book examines the roles of funders such as impact investors, philanthropic foundations, and international aid agencies, laying out how they can best enable meaningful performance measurement….(More)”.

Data as oil, infrastructure or asset? Three metaphors of data as economic value

Curated on Posted on by Stefaan Verhulst

Jan Michael Nolin at the Journal of Information, Communication and Ethics in Society: “Principled discussions on the economic value of data are frequently pursued through metaphors. This study aims to explore three influential metaphors for talking about the economic value of data: data are the new oil, data as infrastructure and data as an asset.

With the help of conceptual metaphor theory, various meanings surrounding the three metaphors are explored. Meanings clarified or hidden through various metaphors are identified. Specific emphasis is placed on the economic value of ownership of data.

In discussions on data as economic resource, the three different metaphors are used for separate purposes. The most used metaphor, data are the new oil, communicates that ownership of data could lead to great wealth. However, with data as infrastructure data have no intrinsic value. Therefore, profits generated from data resources belong to those processing the data, not those owning it. The data as an asset metaphor can be used to convince organizational leadership that they own data of great value….(More)”.

Government at a Glance 2019

Curated on Posted on by Stefaan Verhulst

OECD Report: “Government at a Glance provides reliable, internationally comparative data on government activities and their results in OECD countries. Where possible, it also reports data for Brazil, China, Colombia, Costa Rica, India, Indonesia, the Russian Federation and South Africa. In many public governance areas, it is the only available source of data. It includes input, process, output and outcome indicators as well as contextual information for each country.

The 2019 edition includes input indicators on public finance and employment; while processes include data on institutions, budgeting practices and procedures, human resources management, regulatory government, public procurement and digital government and open data. Outcomes cover core government results (e.g. trust, inequality reduction) and indicators on access, responsiveness, quality and citizen satisfaction for the education, health and justice sectors.

Governance indicators are especially useful for monitoring and benchmarking governments’ progress in their public sector reforms.Each indicator in the publication is presented in a user-friendly format, consisting of graphs and/or charts illustrating variations across countries and over time, brief descriptive analyses highlighting the major findings conveyed by the data, and a methodological section on the definition of the indicator and any limitations in data comparability….(More)”.

Big Data, Big Impact? Towards Gender-Sensitive Data Systems

Curated on Posted on by Stefaan Verhulst

Report by Data2X: “How can insights drawn from big data sources improve understanding about the lives of women and girls?

This question has underpinned Data2X’s groundbreaking work at the intersection of big data and gender — work that funded ten research projects that examined the potential of big data to fill the global gender data gap.

Big Data, Big Impact? Towards Gender-Sensitive Data Systems summarizes the findings and potential policy implications of the Big Data for Gender pilot projects funded by Data2X, and lays out five cross-cutting messages that emerge from this body of work:

  1. Big data offers unique insights on women and girls.
  2. Gender-sensitive big data is ready to scale and integrate with traditional data.
  3. Identify and correct bias in big datasets.
  4. Protect the privacy of women and girls.
  5. Women and girls must be central to data governance.

This report argues that the time for pilot projects has passed. Data privacy concerns must be addressed; investment in scale up is needed. Big data offers great potential for women and girls, and indeed for all people….(More)”.

Public value creation in digital government

Curated on Posted on by Stefaan Verhulst

Introduction to Special Issue by Panos Panagiotopoulos, BramKlievink, and AntonioCordella: “Public value theory offers innovative ways to plan, design, and implement digital government initiatives. The theory has gained the attention of researchers due to its powerful proposition that shifts the focus of public sector management from internal efficiency to value creation processes that occur outside the organization.

While public value creation has become the expectation that digital government initiatives have to fulfil, there is lack of theoretical clarity on what public value means and on how digital technologies can contribute to its creation. The special issue presents a collection of six papers that provide new insights on how digital technologies support public value creation. Building on their contributions, the editorial note conceptualizes the realm of public value creation by highlighting: (1) the integrated nature of public value creation supported by digital government implementations rather than enhancing the values provided by individual technologies or innovations, (2) how the outcome of public value creation is reflected in the combined consumption of the various services enabled by technologies and (3) how public value creation is enabled by organizational capabilities and configurations….(More)”.

Digital human rights are next frontier for fund groups

Curated on Posted on by Stefaan Verhulst

Siobhan Riding at the Financial Times: “Politicians publicly grilling technology chiefs such as Facebook’s Mark Zuckerberg is all too familiar for investors. “There isn’t a day that goes by where you don’t see one of the tech companies talking to Congress or being highlighted for some kind of controversy,” says Lauren Compere, director of shareholder engagement at Boston Common Asset Management, a $2.4bn fund group that invests heavily in tech stocks.

Fallout from the Cambridge Analytica scandal that engulfed Facebook was a wake-up call for investors such as Boston Common, underlining the damaging social effects of digital technology if left unchecked. “These are the red flags coming up for us again and again,” says Ms Compere.

Digital human rights are fast becoming the latest front in the debate around fund managers’ ethical investments efforts. Fund managers have come under pressure in recent years to divest from companies that can harm human rights — from gun manufacturers or retailers to operators of private prisons. The focus is now switching to the less tangible but equally serious human rights risks lurking in fund managers’ technology holdings. Attention on technology groups began with concerns around data privacy, but emerging focal points are targeted advertising and how companies deal with online extremism.

Following a terrorist attack in New Zealand this year where the shooter posted video footage of the incident online, investors managing assets of more than NZ$90bn (US$57bn) urged Facebook, Twitter and Alphabet, Google’s parent company, to take more action in dealing with violent or extremist content published on their platforms. The Investor Alliance for Human Rights is currently co-ordinating a global engagement effort with Alphabet over the governance of its artificial intelligence technology, data privacy and online extremism.

Investor engagement on the topic of digital human rights is in its infancy. One roadblock for investors has been the difficulty they face in detecting and measuring what the actual risks are. “Most investors do not have a very good understanding of the implications of all of the issues in the digital space and don’t have sufficient research and tools to properly assess them — and that goes for companies too,” said Ms Compere.

One rare resource available is the Ranking Digital Rights Corporate Accountability Index, established in 2015, which rates tech companies based on a range of metrics. The development of such tools gives investors more information on the risk associated with technological advancements, enabling them to hold companies to account when they identify risks and questionable ethics….(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)”.

We are finally getting better at predicting organized conflict

Curated on Posted on by Stefaan Verhulst

Tate Ryan-Mosley at MIT Technology Review: “People have been trying to predict conflict for hundreds, if not thousands, of years. But it’s hard, largely because scientists can’t agree on its nature or how it arises. The critical factor could be something as apparently innocuous as a booming population or a bad year for crops. Other times a spark ignites a powder keg, as with the assassination of Archduke Franz Ferdinand of Austria in the run-up to World War I.

Political scientists and mathematicians have come up with a slew of different methods for forecasting the next outbreak of violence—but no single model properly captures how conflict behaves. A study published in 2011 by the Peace Research Institute Oslo used a single model to run global conflict forecasts from 2010 to 2050. It estimated a less than .05% chance of violence in Syria. Humanitarian organizations, which could have been better prepared had the predictions been more accurate, were caught flat-footed by the outbreak of Syria’s civil war in March 2011. It has since displaced some 13 million people.

Bundling individual models to maximize their strengths and weed out weakness has resulted in big improvements. The first public ensemble model, the Early Warning Project, launched in 2013 to forecast new instances of mass killing. Run by researchers at the US Holocaust Museum and Dartmouth College, it claims 80% accuracy in its predictions.

Improvements in data gathering, translation, and machine learning have further advanced the field. A newer model called ViEWS, built by researchers at Uppsala University, provides a huge boost in granularity. Focusing on conflict in Africa, it offers monthly predictive readouts on multiple regions within a given state. Its threshold for violence is a single death.

Some researchers say there are private—and in some cases, classified—predictive models that are likely far better than anything public. Worries that making predictions public could undermine diplomacy or change the outcome of world events are not unfounded. But that is precisely the point. Public models are good enough to help direct aid to where it is needed and alert those most vulnerable to seek safety. Properly used, they could change things for the better, and save lives in the process….(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)”.

Geolocation Data for Pattern of Life Analysis in Lower-Income Countries

Curated on Posted on by Stefaan Verhulst

Report by Eduardo Laguna-Muggenburg, Shreyan Sen and Eric Lewandowski: “Urbanization processes in the developing world are often associated with the creation of informal settlements. These areas frequently have few or no public services exacerbating inequality even in the context of substantial economic growth.

In the past, the high costs of gathering data through traditional surveying methods made it challenging to study how these under-served areas evolve through time and in relation to the metropolitan area to which they belong. However, the advent of mobile phones and smartphones in particular presents an opportunity to generate new insights on these old questions.

In June 2019, Orbital Insight and the United Nations Development Programme (UNDP) Arab States Human Development Report team launched a collaborative pilot program assessing the feasibility of using geolocation data to understand patterns of life among the urban poor in Cairo, Egypt.

The objectives of this collaboration were to assess feasibility (and conditionally pursue preliminary analysis) of geolocation data to create near-real time population density maps, understand where residents of informal settlements tend to work during the day, and to classify universities by percentage of students living in informal settlements.

The report is organized as follows. In Section 2 we describe the data and its limitations. In Section 3 we briefly explain the methodological background. Section 4 summarizes the insights derived from the data for the Egyptian context. Section 5 concludes….(More)”.