Decision-making in the Age of the Algorithm

Curated on Posted on by Stefaan Verhulst

Paper by Thea Snow: “Frontline practitioners in the public sector – from social workers to police to custody officers – make important decisions every day about people’s lives. Operating in the context of a sector grappling with how to manage rising demand, coupled with diminishing resources, frontline practitioners are being asked to make very important decisions quickly and with limited information. To do this, public sector organisations are turning to new technologies to support decision-making, in particular, predictive analytics tools, which use machine learning algorithms to discover patterns in data and make predictions.

While many guides exist around ethical AI design, there is little guidance on how to support a productive human-machine interaction in relation to AI. This report aims to fill this gap by focusing on the issue of human-machine interaction. How people are working with tools is significant because, simply put, for predictive analytics tools to be effective, frontline practitioners need to use them well. It encourages public sector organisations to think about how people feel about predictive analytics tools – what they’re fearful of, what they’re excited about, what they don’t understand.

Based on insights drawn from an extensive literature review, interviews with frontline practitioners, and discussions with experts across a range of fields, the guide also identifies three key principles that play a significant role in supporting a constructive human-machine relationship: context, understanding, and agency….(More)”.

The fuzzy concept of collaborative governance: A systematic review of the state of the art

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Paper by Agnes Batory and Sara Svensson: “Collaborative approaches to policy-making are high on the agenda for most European governments and are key to European Commission activities with respect to the transformation of public administration in the European Union (EU) (Hammerschmid et al., 2016; European Commission, 2016). A long line of politicians has stated the need for government units to overcome organizational cleavages and reach out to citizens and stakeholders in order to address difficult policy problems and deliver public services more efficiently. Collaborative approaches to policy-making have also been advocated as a way to close the seemingly growing gap between government and citizens and thus to alleviate normative problems commonly besetting Western democracies in the last decades. Collaborative governance has received considerable attention from public administration scholars and is the subject of a burgeoning body of academic literature in policy studies, public management and democratic theory. However, the rapid uptake of collaborative governance and related concepts, such as coordination, cooperation, joined-up governance, network governance (e.g., Robinson 2006) and interactive governance (Michels, 2011), led to a rather amorphous, diffused discussion, rather than a coherent narrative. Attempts to structure the debate have so far exclusively focused on the academic literature in English. This article aims to facilitate the synthesis and consolidation of work undertaken so far in a way that is more culturally sensitive and more open to developments taking place in the world of practice.

More specifically, this article first seeks to map the current state of the art. It pinpoints key dimensions of variation in how collaborative governance is defined in the academic literature through a qualitative analysis of influential scholarly work and provides a systematic literature review of a corpus of over 700 article abstracts. The analysis shows that scholarly articles differ in their conceptualisation of collaborative governance along at least five dimensions, which concern the public-private (governmental-non-governmental) divide; agency; organisational aspects; scope and locus within the policy process; and normative assumptions. Second, the paper extends this analysis to incorporate some preliminary findings on relevant ‘grey’ literature on collaborative governance in Europe – which seems to be in closer touch with developments of high relevance for practice – in order to indicate whether and to what extent the scholarly and the practitioner-oriented literature overlap or differ in orientation and subjects covered. Finally, the paper takes stock of the national connotations of the term in different European languages, which aims to mitigate the Anglo-Saxon bias in the literature. For the second and third objectives, the paper relies on responses from teams of academic public administration experts in ten EU and European Free Trade Association (EFTA) countries. The methodological approach for each of these steps is described in the respective sections of the paper. The penultimate section provides a synthesis of the results, including recommendations for reconceptualization and future research….(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)”.

Angela Merkel urges EU to seize control of data from US tech titans

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Guy Chazan at the Financial Times: “Angela Merkel has urged Europe to seize control of its data from Silicon Valley tech giants, in an intervention that highlights the EU’s growing willingness to challenge the US dominance of the digital economy.

The German chancellor said the EU should claim “digital sovereignty” by developing its own platform to manage data and reduce its reliance on the US-based cloud services run by Amazon, Microsoft and Google. “So many companies have just outsourced all their data to US companies,” Ms Merkel told German business leaders. “I’m not saying that’s bad in and of itself — I just mean that the value-added products that come out of that, with the help of artificial intelligence, will create dependencies that I’m not sure are a good thing.”

Her speech, at an employers’ conference in Berlin, shows the extent to which the information economy is emerging as a battleground in the EU-US trading relationship. It also highlights the concern in European capitals that the EU could be weakened by the market dominance of the big US tech companies, particularly in the business of storing, processing and analysing data.

Margrethe Vestager, the EU’s powerful competition chief who is now also to oversee EU digital policy, last month told the Financial Times that she was examining whether large internet companies could be held to higher standards of proof in competition cases, as part of a tougher line on dominant companies, such as Google.

Ms Merkel was speaking just two weeks after Berlin unveiled plans for a European cloud computing initiative, dubbed Gaia-X, which it has described as a “competitive, safe and trustworthy data infrastructure for Europe”.

At the conference on Tuesday, Peter Altmaier, economy minister, said the data of companies such as Volkswagen, and that of the German interior ministry and social security system, were increasingly stored on the servers of Microsoft and Amazon. “And in this we are losing part of our sovereignty,” he added….(More)”.

Our Futures: By the people, for the people

Curated on Posted on by Stefaan Verhulst

Guide by Laurie Smith and Kathy Peach: “This is a guide to how mass involvement with shaping the future can solve complex problems.

Moving beyond citizen assemblies and traditional public engagement, participatory futures techniques help people to develop a collective image of the future they want, so that we can make better, more informed decisions.

Governments, city leaders, public institutions, funders, and civil society must be at the forefront of this approach, supporting it through funding, strategy and practice.

Our guide contains practical suggestions for how to do this. Examples include:

  • Carrying out publicly-funded, mission-orientated research that is informed by participatory futures exercises.
  • Creating new legislation that requires UK Government departments to use these approaches to inform decision-making and strategies.
  • Embedding these approaches in the Civil Service Competency Framework and equivalent frameworks for local government and charities…(More)”.

Kenya passes data protection law crucial for tech investments

Curated on Posted on by Stefaan Verhulst

George Obulutsa and Duncan Miriri at Reuters: “Kenyan President Uhuru Kenyatta on Friday approved a data protection law which complies with European Union legal standards as it looks to bolster investment in its information technology sector.

The East African nation has attracted foreign firms with innovations such as Safaricom’s M-Pesa mobile money services, but the lack of safeguards in handling personal data has held it back from its full potential, officials say.

“Kenya has joined the global community in terms of data protection standards,” Joe Mucheru, minister for information, technology and communication, told Reuters.

The new law sets out restrictions on how personally identifiable data obtained by firms and government entities can be handled, stored and shared, the government said.

Mucheru said it complies with the EU’s General Data Protection Regulation which came into effect in May 2018 and said an independent office will investigate data infringements….

A lack of data protection legislation has also hampered the government’s efforts to digitize identity records for citizens.

The registration, which the government said would boost its provision of services, suffered a setback this year when the exercise was challenged in court.

“The lack of a data privacy law has been an enormous lacuna in Kenya’s digital rights landscape,” said Nanjala Nyabola, author of a book on information technology and democracy in Kenya….(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)”.

Finland’s model in utilising forest data

Curated on Posted on by Stefaan Verhulst

Report by Matti Valonen et al: “The aim of this study is to depict the Finnish Forest Centre’s Metsään.fiwebsite’s background, objectives and implementation and to assess its needs for development and future prospects. The Metsään.fi-service included in the Metsään.fi-website is a free e-service for forest owners and corporate actors (companies, associations and service providers) in the forest sector, which aim is to support active decision-making among forest owners by offering forest resource data and maps on forest properties, by making contacts with the authorities easier through online services and to act as a platform for offering forest services, among other things.

In addition to the Metsään.fi-service, the website includes open forest data services that offer the users national forest resource data that is not linked with personal information.

Private forests are in a key position as raw material sources for traditional and new forest-based bioeconomy. In addition to wood material, the forests produce non-timber forest products (for example berries and mushrooms), opportunities for recreation and other ecosystem services.

Private forests cover roughly 60 percent of forest land, but about 80 percent of the domestic wood used by forest industry. In 2017 the value of the forest industry production was 21 billion euros, which is a fifth of the entire industry production value in Finland. The forest industry export in 2017 was worth about 12 billion euros, which covers a fifth of the entire export of goods. Therefore, the forest sector is important for Finland’s national economy…(More)”.

Big Data, Algorithms and Health Data

Curated on Posted on by Stefaan Verhulst

Paper by Julia M. Puaschunder: “The most recent decade featured a data revolution in the healthcare sector in screening, monitoring and coordination of aid. Big data analytics have revolutionarized the medical profession. The health sector relys on Artificial Intelligence (AI) and robotics as never before. The opportunities of unprecedented access to healthcare, rational precision and human resemblance but also targeted aid in decentralized aid grids are obvious innovations that will lead to most sophisticated neutral healthcare in the future. Yet big data driven medical care also bears risks of privacy infringements and ethical concerns of social stratification and discrimination. Today’s genetic human screening, constant big data information amalgamation as well as social credit scores pegged to access to healthcare also create the most pressing legal and ethical challenges of our time.Julia M. PuaschunderThe most recent decade featured a data revolution in the healthcare sector in screening, monitoring and coordination of aid. Big data analytics have revolutionarized the medical profession. The health sector relys on Artificial Intelligence (AI) and robotics as never before. The opportunities of unprecedented access to healthcare, rational precision and human resemblance but also targeted aid in decentralized aid grids are obvious innovations that will lead to most sophisticated neutral healthcare in the future. Yet big data driven medical care also bears risks of privacy infringements and ethical concerns of social stratification and discrimination. Today’s genetic human screening, constant big data information amalgamation as well as social credit scores pegged to access to healthcare also create the most pressing legal and ethical challenges of our time.

The call for developing a legal, policy and ethical framework for using AI, big data, robotics and algorithms in healthcare has therefore reached unprecedented momentum. Problematic appear compatibility glitches in the AI-human interaction as well as a natural AI preponderance outperforming humans. Only if the benefits of AI are reaped in a master-slave-like legal frame, the risks associated with these novel superior technologies can be curbed. Liability control but also big data privacy protection appear important to secure the rights of vulnerable patient populations. Big data mapping and social credit scoring must be met with clear anti-discrimination and anti-social stratification ethics. Lastly, the value of genuine human care must be stressed and precious humanness in the artifical age conserved alongside coupling the benefits of AI, robotics and big data with global common goals of sustainability and inclusive growth.

The report aims at helping a broad spectrum of stakeholders understand the impact of AI, big data, algorithms and health data based on information about key opportunities and risks but also future market challenges and policy developments for orchestrating the concerted pursuit of improving healthcare excellence. Stateshuman and diplomates are invited to consider three trends in the wake of the AI (r)evolution:

Artificial Intelligence recently gained citizenship in robots becoming citizens: With attributing quasi-human rights to AI, ethical questions arise of a stratified citizenship. Robots and algorithms may only be citizens for their protection and upholding social norms towards human-like creatures that should be considered slave-like for economic and liability purposes without gaining civil privileges such as voting, property rights and holding public offices.

Big data and computational power imply unprecedented opportunities for: crowd understanding, trends prediction and healthcare control. Risks include data breaches, privacy infringements, stigmatization and discrimination. Big data protection should be enacted through technological advancement, self-determined privacy attention fostered by e-education as well as discrimination alleviation by only releasing targeted information and regulated individual data mining capacities.

The European Union should consider establishing a fifth trade freedom of data by law and economic incentives: in order to bundle AI and big data gains large scale. Europe holds the unique potential of offering data supremacy in state-controlled universal healthcare big data wealth that is less fractionate than the US health landscape and more Western-focused than Asian healthcare. Europe could therefore lead the world on big data derived healthcare insights but should also step up to imbuing humane societal imperatives on these most cutting-edge innovations of our time….(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)”.