Accountability in modern government: what are the issues?

Curated on Posted on by Stefaan Verhulst

Discussion Paper by Benoit Guerin, Julian McCrae and Marcus Shepheard: “…Accountability lies at the heart of democratic government. It enables people to know how the Government is doing and how to gain redress when things go wrong. It ensures ministers and civil servants are acting in the interests of the people they serve.

Accountability is a part of good governance and it can increase the trustworthiness and legitimacy of the state in the eyes of the public. Every day, 5.4 million public sector workers deliver services ranging from health care to schools to national defence.1 A host of bodies hold them to account – whether the National Audit Office undertaking around 60 value for money inquiries a year,2 Ofsted inspecting more than 5,000 schools per year, or the main Government ombudsman services dealing with nearly 80,000 complaints from the public in 2016/17 alone. More than 21,000 elected officials, ranging from MPs to local councillors, scrutinise these services on behalf of citizens.

When that accountability works properly, it helps the UK’s government to be among the best in the world. For example, public spending is authorised by Parliament and routinely stays within the limits set. The accountability that surrounds this – provided through oversight by the Treasury, audit by the National Audit Office and scrutiny by the Public Accounts Committee – is strong and dates back to the 19th century. However, in areas where that accountability is weak, the risk of failure – whether financial mismanagement, the collapse of services or chronic underperformance – increases. …

There are three factors underpinning the weak accountability that is perpetuating failure. They are: fundamental gaps in accountability in Whitehall; a failure of accountability beyond Whitehall to keep pace with an increasingly complex public sector landscape; and a pervading culture of blame….

This paper suggests potential options for strengthening accountability, based on our analysis. These involve changes to structures, increased transparency and moves to improve the culture. These options are meant to elicit discussion rather than to set the Institute for Government’s position at this stage….(More)”

What Is Human-Centric Design?

Curated on Posted on by Stefaan Verhulst

Zack Quaintance at GovTech: “…Government services, like all services, have historically used some form of design to deploy user-facing components. The design portion of this equation is nothing new. What Olesund says is new, however, is the human-centric component.

“In the past, government services were often designed from the perspective and need of the government institution, not necessarily with the needs or desires of residents or constituents in mind,” said Olesund. “This might lead, for example, to an accumulation of stats and requirements for residents, or utilization of outdated technology because the government institution is locked into a contract.”

Basically, government has never set out to design its services to be clunky or hard to use. These qualities have, however, grown out of the legally complex frameworks that governments must adhere to, which can subsequently result in a failure to prioritize the needs of the people using the services rather than the institution.

Change, however, is underway. Human-centric design is one of the main priorities of the U.S. Digital Service (USDS) and 18F, a pair of organizations created under the Obama administration with missions that largely involve making government services more accessible to the citizenry through efficient use of tech.

Although the needs of state and municipal governments are more localized, the gov tech work done at the federal level by the USDS and 18F has at times served as a benchmark or guidepost for smaller government agencies.

“They both redesign services to make them digital and user-friendly,” Olesund said. “But they also do a lot of work creating frameworks and best practices for other government agencies to adopt in order to achieve some of the broader systemic change.”

One of the most tangible examples of human-centered design at the state or local level can be found at Michigan’s Department of Health and Human Services, which recently worked with the Detroit-based design studio Civillato reduce its paper services application from 40 pages, 18,000-some words and 1,000 questions, down to 18 pages, 3,904 words and 213 questions. Currently, Civilla is working with the nonprofit civic tech group Code for America to help bring the same massive level of human-centered design progress to the state’s digital services.

Other work is underway in San Francisco’s City Hall and within the state of California. A number of cities also have iTeams funded through Bloomberg Philanthropies, and their missions are to innovate in ways that solve ongoing municipal problems, a mission that often requires use of human-centric design….(More)”.

How Artificial Intelligence Could Increase the Risk of Nuclear War

Curated on Posted on by Stefaan Verhulst

Rand Corporation: “The fear that computers, by mistake or malice, might lead humanity to the brink of nuclear annihilation has haunted imaginations since the earliest days of the Cold War.

The danger might soon be more science than fiction. Stunning advances in AI have created machines that can learn and think, provoking a new arms race among the world’s major nuclear powers. It’s not the killer robots of Hollywood blockbusters that we need to worry about; it’s how computers might challenge the basic rules of nuclear deterrence and lead humans into making devastating decisions.

That’s the premise behind a new paper from RAND Corporation, How Might Artificial Intelligence Affect the Risk of Nuclear War? It’s part of a special project within RAND, known as Security 2040, to look over the horizon and anticipate coming threats.

“This isn’t just a movie scenario,” said Andrew Lohn, an engineer at RAND who coauthored the paper and whose experience with AI includes using it to route drones, identify whale calls, and predict the outcomes of NBA games. “Things that are relatively simple can raise tensions and lead us to some dangerous places if we are not careful.”…(More)”.

How artificial intelligence is transforming the world

Curated on Posted on by Stefaan Verhulst

Report by Darrell West and John Allen at Brookings: “Most people are not very familiar with the concept of artificial intelligence (AI). As an illustration, when 1,500 senior business leaders in the United States in 2017 were asked about AI, only 17 percent said they were familiar with it. A number of them were not sure what it was or how it would affect their particular companies. They understood there was considerable potential for altering business processes, but were not clear how AI could be deployed within their own organizations.

Despite its widespread lack of familiarity, AI is a technology that is transforming every walk of life. It is a wide-ranging tool that enables people to rethink how we integrate information, analyze data, and use the resulting insights to improve decisionmaking. Our hope through this comprehensive overview is to explain AI to an audience of policymakers, opinion leaders, and interested observers, and demonstrate how AI already is altering the world and raising important questions for society, the economy, and governance.

In this paper, we discuss novel applications in finance, national security, health care, criminal justice, transportation, and smart cities, and address issues such as data access problems, algorithmic bias, AI ethics and transparency, and legal liability for AI decisions. We contrast the regulatory approaches of the U.S. and European Union, and close by making a number of recommendations for getting the most out of AI while still protecting important human values.

In order to maximize AI benefits, we recommend nine steps for going forward:

  • Encourage greater data access for researchers without compromising users’ personal privacy,
  • invest more government funding in unclassified AI research,
  • promote new models of digital education and AI workforce development so employees have the skills needed in the 21st-century economy,
  • create a federal AI advisory committee to make policy recommendations,
  • engage with state and local officials so they enact effective policies,
  • regulate broad AI principles rather than specific algorithms,
  • take bias complaints seriously so AI does not replicate historic injustice, unfairness, or discrimination in data or algorithms,
  • maintain mechanisms for human oversight and control, and
  • penalize malicious AI behavior and promote cybersecurity….(More)

Table of Contents
I. Qualities of artificial intelligence
II. Applications in diverse sectors
III. Policy, regulatory, and ethical issues
IV. Recommendations
V. Conclusion

A survey of incentive engineering for crowdsourcing

Curated on Posted on by Stefaan Verhulst

Conor Muldoon, Michael J. O’Grady and Gregory M. P. O’Hare in the Knowledge Engineering Review: “With the growth of the Internet, crowdsourcing has become a popular way to perform intelligence tasks that hitherto would be either performed internally within an organization or not undertaken due to prohibitive costs and the lack of an appropriate communications infrastructure.

In crowdsourcing systems, whereby multiple agents are not under the direct control of a system designer, it cannot be assumed that agents will act in a manner that is consistent with the objectives of the system designer or principal agent. In situations whereby agents’ goals are to maximize their return in crowdsourcing systems that offer financial or other rewards, strategies will be adopted by agents to game the system if appropriate mitigating measures are not put in place.

The motivational and incentivization research space is quite large; it incorporates diverse techniques from a variety of different disciplines including behavioural economics, incentive theory, and game theory. This paper specifically focusses on game theoretic approaches to the problem in the crowdsourcing domain and places it in the context of the wider research landscape. It provides a survey of incentive engineering techniques that enable the creation of apt incentive structures in a range of different scenarios….(More)”.

A Race to the Top? The Aid Transparency Index and the Social Power of Global Performance Indicators

Curated on Posted on by Stefaan Verhulst

Paper by Dan Honig and Catherine Weaver: “Recent studies on global performance indicators (GPIs) reveal the distinct power that non-state actors can accrue and exercise in world politics. How and when does this happen? Using a mixed-methods approach, we examine the impact of the Aid Transparency Index (ATI), an annual rating and rankings index produced by the small UK-based NGO Publish What You Fund.

The ATI seeks to shape development aid donors’ behavior with respect to their transparency – the quality and kind of information they publicly disclose. To investigate the ATI’s effect, we construct an original panel dataset of donor transparency performance before and after ATI inclusion (2006-2013) to test whether, and which, donors alter their behavior in response to inclusion in the ATI. To further probe the causal mechanisms that explain variations in donor behavior we use qualitative research, including over 150 key informant interviews conducted between 2010-2017.

Our analysis uncovers the conditions under which the ATI influences powerful aid donors. Moreover, our mixed methods evidence reveals how this happens. Consistent with Kelley & Simmons’ central argument that GPIs exercise influence via social pressure, we find that the ATI shapes donor behavior primarily via direct effects on elites: the diffusion of professional norms, organizational learning, and peer pressure….(More)”.

Austin is piloting blockchain to improve homeless services

Curated on Posted on by Stefaan Verhulst

Danny Crichton at TechCrunch: “While the vagaries of the cryptocurrency markets are keeping crypto traders glued to their CoinDesk graphs, the real potential of blockchain is its capability to solve real human challenges in a decentralized, private, and secure way. Government officials have increasingly investigated how blockchain might solve critical problems, but now one city intends to move forward with an actual implementation.

The city of Austin is piloting a new blockchain platform to improve identity services for its homeless population, as part of a competitive grant awarded by the Mayor’s Challenge program sponsored by Bloomberg Philanthropies. Austin was one of 35 cities to be awarded pilot grants, and the top city from that group will ultimately be awarded $5 million….

The city wanted to improve the ability of its patchwork of government and private homeless service providers to offer integrated and comprehensive aid. There are a number of separate challenges here: verifying the identity of a person seeking help, knowing what care that individual has previously received, and empowering the individual to “own” their own records, and ultimately, their destiny.

The goal of the city’s blockchain pilot program is to consolidate the identity and vital records of each homeless person in a safe and confidential way while providing a means for service providers to access that information. Adler explained that “there are all kinds of confidentiality issues that arise when you try to do that, so the thought was that blockchain would allow us to bridge that need.”

By using blockchain, the hope is that the city could replace paper records, which are hard to manage, with electronic encrypted records that would be more reliable and secure. In addition, the blockchain platform could create a decentralized authentication mechanism to verify a particular person’s identity. For instance, a homeless services worker operating in the field could potentially use their mobile device to verify a person live, without having to bring someone back to an office for processing.

More importantly, vital records on the blockchain could build over time, so different providers would know what services a person had used previously. Majid provided the example of health care, where it is crucially important to know the history of an individual. The idea is that, when a homeless person walks into a clinic, the blockchain would provide the entire patient history of that individual to the provider. “Here was your medical records from your last clinic visits, and we can build off the care that you were given last time,” he said. Austin is partnering with the Dell Medical School at the University of Texas to work out how best to implement the blockchain for medical professionals….(More)”.

Literature review on collective intelligence: a crowd science perspective

Curated on Posted on by Stefaan Verhulst

Chao Yu in the International Journal of Crowd Science: “A group can be of more power and better wisdom than the sum of the individuals. Foreign scholars have noticed that for a long time and called it collective intelligence. It has emerged from the communication, collaboration, competition and brain storming, etc. Collective intelligence appears in many fields such as public decisions, voting activities, social networks and crowdsourcing.

Crowd science mainly focuses on the basic principles and laws of the intelligent activities of groups under the new interconnection model. It explores how to give full play to the intelligence agents and groups, dig their potential to solve the problems that are difficult for a single agent.

In this paper, we present a literature review on collective intelligence in a crowd science perspective. We focus on researchers’ related work, especially that under which circumstance can group show their wisdom, how to measure it, how to optimize it and its modern or future applications in the digital world. That is exactly what the crowd science pays close attention to….(More)”.

Friends with Academic Benefits

Curated on Posted on by Stefaan Verhulst
Paper by Janice McCabe at Contexts: “Sometimes it’s a good thing to be like your friends, and sometimes it isn’t. . . . If they’re getting all As, of course I want to be like them,” said Valerie, an 18-year-old college student during her first year at “MU,” a large, public, four-year university in the Midwestern United States. Like Valerie, many college students use their friends as academic motivation, finding support among a close-knit group surrounding them. Other students view only certain groups of friends as academically helpful. Betsy explained that the friends on her dorm floor constantly help each other with schoolwork, but her friends from home do not. Still others desired more support and encouragement than they received from friends. Steve told me, “I’m doing it myself… I want [help], but at the same time I don’t really need it.” All three students graduated from MU within four years, yet reflect some of the wide array of experiences students have with their friend networks.

The new or interesting story isn’t just that Valerie, Betsy, and Steve’s friends had different social and academic impacts, but that they had various types of friendship networks. My research points to the importance of network structure—that is, the relationships among their friends—for college students’ success. Different network structures result from students’ experiences—such as race- and class-based marginalization on this predominantly White campus—and shape students’ experiences by helping or hindering them academically and socially.

I used social network techniques to analyze the friendship networks of 67 MU students and found they clumped into three distinctive types—tight-knitters, compartmentalizers, and samplers. Tight-knitters have one densely woven friendship group in which nearly all their friends are friends with one another. Compartmentalizers’ friends form two to four clusters, where friends know each other within clusters but rarely across them. And samplers make a friend or two from a variety of places, but the friends remain unconnected to each other. As shown in the figures, tight-knitters’ networks resemble a ball of yarn, compartmentalizers’ a bow-tie, and samplers’ a daisy. In these network maps, the person I interviewed is at the center and every other dot represents a friend, with lines representing connections among friends (that is, whether the person I interviewed believed that the two people knew each other). During the interviews, participants defined what friendship meant to them and listed as many friends as they liked (ranging from three to 45).

The students’ friendship network types influenced how friends matter for their academic and social successes and failures. Like Valerie, most Black and Latina/o students were tight-knitters. Their dense friendship networks provided a sense of home as a minority on a predominantly White campus. Tight-knit networks could provide academic support and motivation (as they did for Valerie) or pull students down academically if their friends lacked academic skills and motivation. Most White students were compartmentalizers like Betsy, and they succeeded with moderate levels of social support from friends and with social support and academic support from different clusters. Samplers came from a range of class and race backgrounds. Like Steve, samplers typically succeeded academically without relying on their friends. Friends were fun people who neither help nor hurt them academically. Socially, however, samplers reported feeling lonely and lacking social support….(More)”.

The Scientific Paper Is Obsolete

Curated on Posted on by Stefaan Verhulst

James Somers in The Atlantic: “The scientific paper—the actual form of it—was one of the enabling inventions of modernity. Before it was developed in the 1600s, results were communicated privately in letters, ephemerally in lectures, or all at once in books. There was no public forum for incremental advances. By making room for reports of single experiments or minor technical advances, journals made the chaos of science accretive. Scientists from that point forward became like the social insects: They made their progress steadily, as a buzzing mass.

The earliest papers were in some ways more readable than papers are today. They were less specialized, more direct, shorter, and far less formal. Calculus had only just been invented. Entire data sets could fit in a table on a single page. What little “computation” contributed to the results was done by hand and could be verified in the same way.

The more sophisticated science becomes, the harder it is to communicate results. Papers today are longer than ever and full of jargon and symbols. They depend on chains of computer programs that generate data, and clean up data, and plot data, and run statistical models on data. These programs tend to be both so sloppily written and so central to the results that it’s contributed to a replication crisis, or put another way, a failure of the paper to perform its most basic task: to report what you’ve actually discovered, clearly enough that someone else can discover it for themselves.

Perhaps the paper itself is to blame. Scientific methods evolve now at the speed of software; the skill most in demand among physicists, biologists, chemists, geologists, even anthropologists and research psychologists, is facility with programming languages and “data science” packages. And yet the basic means of communicating scientific results hasn’t changed for 400 years. Papers may be posted online, but they’re still text and pictures on a page.

What would you get if you designed the scientific paper from scratch today?…(More).