Stefaan Verhulst
Article by Michelle Cho, Joshua Schoop, Timothy Murphy: “What are the biggest challenges facing government? Bureaucracy? Gridlock? A shrinking pool of resources?
Chances are compliance—when people act in accordance with preset rules, policies, and/or expectations—doesn’t top the list for many. Yet maybe it should. Compliance touches nearly every aspect of public policy implementation. Over the past 10 years, US government spending on compliance reached US$7.5 billion.
Even the most sophisticated and well-planned policies often require cooperation and input from real humans to be successful. From voluntary tax filing at the Internal Revenue Service (IRS) to reducing greenhouse emissions at the Environmental Protection Agency (EPA), to achieving the public policy outcomes decision-makers intend, compliance is fundamental.
Consider these examples of noncompliance and their costs:
- Taxes. By law, the IRS requires all income-earning, eligible constituents to file and pay their owed taxes. Tax evasion—the illegal nonpayment or underpayment of tax—cost the federal government an average of US$458 billion per year between 2008 and 2010.3 The IRS believes it will recover just 11 percent of the amount lost in that time frame.
- The environment. The incorrect disposal of recyclable materials has cost more than US$744 million in the state of Washington since 2009.4 The city audit in San Diego found that 76 percent of materials disposed of citywide are recyclable and estimates that those recyclables could power 181,000 households for a year or conserve 3.4 million barrels of oil.5
Those who fail to comply with these rules could face direct and indirect consequences, including penalties and even jail time. Yet a significant subset of the population still behaves in a noncompliant manner. Why?
Behavioral sciences offer some clues. Through the combination of psychology, economics, and neuroscience, behavioral sciences demonstrate that people do not always do what is asked of them, even when it seems in their best interest to do so. Often, people choose a noncompliant path because of one of these reasons: They are unaware of their improper behavior, they find the “right” choice is too complex to decipher, or they simply are not intrinsically motivated to make the compliant choice.
For any of these reasons, when a cognitive hurdle emerges, some people resort to noncompliant behavior. But these hurdles can be overcome. Policymakers can use these same behavioral insights to understand why noncompliance occurs and alternatively, employ behavioral-inspired tools to encourage compliant behavior in a more agile and resource-efficient fashion.
In this spirit, leaders can take a more human-centered approach to program design by using behavioral science lessons to develop policies and programs in a manner that can make compliance easier and more appealing. In our article, we discuss three common reasons behind noncompliance and how better, more human-centered design can help policymakers achieve more positive results….(More)”.
Chapter by Ali Abbas, Max Senges and Ronald A. Howard in “Next Generation Ethics: Engineering a Better Society” (2018): “…presents an ethical creed, which we refer to as the Hippocratic Oath for Technologists. The creed is built on three fundamental pillars: proactively understanding the ethical implications of technology for all stakeholders, telling the truth about the capabilities, advantages, and disadvantages of a technology, and acting responsibly in situations you find morally challenging.
The oath may be taken by students at Universities after understanding its basic definitions and implications, and it may also be discussed with technology firms and human resources departments to provide the necessary support and understanding for their employees who wish to abide by the norms of this oath. This work lays the foundations for the arguments and requirements of a unified movement, as well as a forum for signing up for the oath to enable its wide-spread dissemination….(More)”.
Paper by Michael P. Cañares: “The record of countries in the region in terms of transparency and accountability is dismal. In the latest Corruption Perceptions Index released by Transparency International, more than half of the country in the region scored below 50, with at least a quarter of these are countries considered with systemic corruption problems. Nevertheless, there have been significant attempts of several countries to install transparency measures and project a commitment towards greater openness. At least a dozen
The Open Government Partnership (OGP) is a multilateral initiative that aims to secure concrete commitments from governments to promote transparency, empower citizens, fight corruption, and harness new technologies to strengthen governance. OGP’s vision is that more governments become more transparent, more accountable, and more responsive to their own citizens, with the goal of improving the quality of governance, as well as the quality of services that citizens receive. Since its inception in 2011, OGP today brings together 75 countries and 15 subnational governments with over 2,500 commitments to make their governments more open and accountable. In Asia, only the governments of Indonesia, the Philippines, and South Korea are participating countries along with two subnational pilots, Seoul and Bojonegoro. These governments have launched initiatives to involve citizens in the planning and budgeting processes, proactively disclose budget and other public financial information, and engage citizens in
Report from the Congressional Research Service: “Quantum information science (QIS) combines elements of mathematics, computer science, engineering, and physical sciences, and has the potential to provide capabilities far beyond what is possible with the most advanced technologies available today.
Although much of the press coverage of QIS has been devoted to quantum computing, there is more to QIS. Many experts divide QIS technologies into three application areas:
- Sensing and metrology,
- Communications, and
- Computing and simulation.
… Today, QIS is a component of the National Strategic Computing Initiative (Presidential Executive Order 13702), which was established in 2015. Most recently, in September 2018, the National Science and Technology Council issued the National Strategic Overview for Quantum Information Science. The policy opportunities identified in this strategic overview include:
- choosing a science-first approach to QIS,
- creating a “quantum-smart” workforce,
- deepening engagement with the quantum industry,
- providing critical infrastructure,
- maintaining national security and economic growth, and
- advancing international cooperation.
This report provides an overview of QIS technologies: sensing and metrology, communications, and computing and simulation. It also includes examples of existing and potential future applications; brief summaries of funding and selected R&D initiatives in the United States and elsewhere around the world; a description of U.S. congressional activity; and a discussion of related policy considerations….(More)”.
Jenni Lloyd and Alice Casey at Nesta: “Today, we’re pleased to welcome you to ShareTown. Our fictional town and its cast of characters
In this future, government plays a plurality of roles, working closely with local people to understand their needs, how these can best be met and by whom. Provided with new opportunities to connect and collaborate with others, individuals and households are free to navigate, combine and contribute to different services as they see fit
…the ShareLab team wanted to find a route by which we could explore how people’s needs can be put at the
Futures Cone from Nesta’s report ‘Don’t Stop Thinking About Tomorrow: A modest defence of futurology’
ShareTown is not intended as a prediction, but a source of inspiration – and provocation. If, as theatre-maker Annette Mees says, the future is fictional and the fictions created about it help us set our direction of travel, then the making of stories about the future we want should be something we can all be involved in – not just the media, politicians, or brands…. (More)”.
Paper by Morgan E. Currie and Joan M. Donovan: “The purpose of this paper is to expand on emergent data activism literature to draw distinctions between different types of data management practices undertaken by groups of data activists.
The authors offer three case studies that illuminate the data management strategies of these groups. Each group discussed in the case studies is devoted to representing a contentious political issue through data, but their data management practices differ in meaningful ways. The project Making Sense produces their own data on pollution in Kosovo. Fatal Encounters collects “missing data” on police homicides in the USA. The Environmental Data Governance Initiative hopes to keep vulnerable US data on climate change and environmental injustices in the public domain.
In
Book by Yanni Alexander Loukissas: “In our data-driven society, it is too easy to assume the transparency of data. Instead, Yanni Loukissas argues in All Data Are Local, we should approach data sets with an awareness that data are created by humans and their dutiful machines, at a time, in a place, with the instruments at hand, for audiences that are conditioned to receive them. All data are local. The term data set implies something discrete, complete, and portable, but it is none of those things. Examining a series of data sources important for understanding the state of public life in the United States—Harvard’s Arnold Arboretum, the Digital Public Library of America, UCLA’s Television News Archive, and the real estate marketplace Zillow—Loukissas shows us how to analyze data settings rather than data sets.
Loukissas sets out six principles: all data are local; data have complex attachments to place; data are collected from heterogeneous sources; data and algorithms are inextricably entangled; interfaces recontextualize data; and data are indexes to local knowledge. He then provides a set of practical guidelines to follow. To make his argument, Loukissas employs a combination of qualitative research on data cultures and exploratory data visualizations. Rebutting the “myth of digital universalism,” Loukissas reminds us of the meaning-making power of the local….(More)”.
/ˌmɛkəˈnɪstɪk ˈɛvədəns/
Evidence about either the existence or the nature of a causal mechanism connecting the two; in other words, about the entities and activities mediating the XY relationship (Marchionni and Samuli Reijula, 2018).
There has been mounting pressure on policymakers to adopt and expand the concept of evidence-based policy making (EBP).
In 2017, the U.S. Commission on Evidence-Based Policymaking issued a report calling for a future in which “rigorous evidence is created efficiently, as a routine part of government operations, and used to construct effective public policy.” The report asserts that modern technology and statistical methods, “combined with transparency and a strong legal framework, create the opportunity to use data for evidence building in ways that were not possible in the past.”
Similarly, the European Commission’s 2015 report on Strengthening Evidence Based Policy Making through Scientific Advice states that policymaking “requires robust evidence, impact assessment and adequate monitoring and evaluation,” emphasizing the notion that “sound scientific evidence is a key element of the policy-making process, and therefore science advice should be embedded at all levels of the European policymaking process.” That same year, the Commission’s Data4Policy program launched a call for contributions to support its research:
“If policy-making is ‘whatever government chooses to do or not to do’ (Th. Dye), then how do governments actually decide? Evidence-based policy-making is not a new answer to this question, but it is constantly challenging both policy-makers and scientists to sharpen their thinking, their tools and their responsiveness.”
Yet, while the importance and value of EBP are well established, the question of how to establish evidence is often answered by referring to randomized controlled trials (RCTs), cohort studies, or case reports. According to Caterina Marchionni and Samuli Reijula these answers overlook the important concept of mechanistic evidence.
Their paper takes a deeper dive into the differences between statistical and mechanistic evidence:
“It has recently been argued that successful evidence-based policy should rely on two kinds of evidence: statistical and mechanistic. The former is held to be evidence that a policy brings about the desired outcome, and the latter concerns how it does so.”
The paper further argues that in order to make effective decisions, policymakers must take both statistical and mechanistic evidence into account:
“… whereas statistical studies provide evidence that the policy variable, X, makes a difference to the policy outcome, Y, mechanistic evidence gives information about either the existence or the nature of a causal mechanism connecting the two; in other words, about the entities and activities mediating the XY relationship. Both types of evidence, it is argued, are required to establish causal claims, to design and interpret statistical trials, and to extrapolate experimental findings.”
Ultimately Marchionni and Reijula take a closer look at why introducing research methods that beyond RCTs is crucial for evidence-based policymaking:
“The evidence-based policy (EBP) movement urges policymakers to select policies on the basis of the best available evidence that they work. EBP utilizes evidence-ranking schemes to evaluate the quality of evidence in support of a given policy, which typically prioritize meta-analyses and randomized controlled trials (henceforth RCTs) over other evidence-generating methods.”
They go on to explain that mechanistic evidence has been placed “at the bottom of the evidence hierarchies,” while RCTs have been considered the “gold standard.”
However, the paper argues, mechanistic evidence is in fact as important as statistical evidence:
“… evidence-based policy nearly always involves predictions about the effectiveness of an intervention in populations other than those in which it has been tested. Such extrapolative inferences, it is argued, cannot be based exclusively on the statistical evidence produced by methods higher up in the hierarchies.”
Sources and Further Readings:
- Clarke, Brendan, Gillies, Donald, Illari, Phyllis, Federica Russo, and Jon Williamson. “Mechanisms and the Evidence Hierarchy.” Topoi 33 (2014): 339–360.
- “Evidence-Based Policymaking: What is it? How does it work? What relevance for developing countries?” Overseas Development Institute, 2015.
- Grüne-Yanoff, Till. “Why Behavioural Policy Needs Mechanistic Evidence.” Economics and Philosophy 32 no. 3 (2016).
National Academies: “Scientific research that involves nonscientists contributing to research processes – also known as ‘citizen science’ – supports participants’ learning, engages the public in science, contributes to community scientific literacy, and can serve as a valuable tool to facilitate larger scale research, says a new report from the National Academies of Sciences, Engineering, and Medicine. If one of the goals of a citizen science project is to advance learning, designers should plan for it by defining intended learning outcomes and using evidence-based strategies to reach those outcomes.
“This report affirms that citizen science projects can help participants learn scientific practices and content, but most likely only if the projects are designed to support learning,” says Rajul Pandya, chair of the committee that wrote the report and director, Thriving Earth Exchange, AGU.
The term “citizen science” can be applied to a wide variety of projects that invite nonscientists to engage in doing science with the intended goal of advancing scientific knowledge or application. For example, a citizen science project might engage community members in collecting data to monitor the health of a local stream. As another example, among the oldest continuous organized datasets in the United States are records kept by farmers and agricultural organizations that document the timing of important events, such as sowing, harvests, and pest outbreaks.
Citizen science can support science learning in several ways, the report says. It offers people the opportunity to participate in authentic scientific endeavors, encourages learning through projects conducted in real-world contexts, supports rich social interaction that deepens learning, and engages participants with real data. Citizen science also includes projects that grow out of a community’s desire to address an inequity or advance a priority. For example, the West-Oakland Indicators Project, a community group in Oakland, Calif., self-organizes to collect and analyze air quality data and uses that data to address trucking in and around schools to reduce local children’s exposure to air pollution. When communities can work alongside scientists to advance their priorities, enhanced community science literacy is one possible outcome
In order to maximize learning outcomes, the report recommends that designers and practitioners of citizen science projects should intentionally build them for learning. This involves knowing the audience; intentionally designing for diversity; engaging stakeholders in the design; supporting multiple kinds of participant engagement; encouraging social interaction; building learning supports into the project; and iteratively improving projects through evaluation and refinement. Engaging stakeholders and participants in design and implementation results in more learning for all participants, which can support other project goals.
The report also lays out a research agenda that can help to build the field of citizen science by filling gaps in the current understanding of how citizen science can support science learning and enhance science education. Researchers should consider three important factors: citizen science extends beyond academia and therefore, evidence for practices that advance learning can be found outside of peer-reviewed literature; research should include attention to practice and link theory to application; and attention must be given to diversity in all research, including ensuring broad participation in the design and implementation of the research. Pursuing new lines of inquiry can help add value to the existing research, make future research more productive, and provide support for effective project implementation….(More)”.
Article by John McKenna: “We’ve all heard about donating blood, but how about donating data?
Chronic non-communicable diseases (NCDs) like diabetes, heart disease and epilepsy are predicted by the World Health Organization to account for 57% of all disease by 2020.
This has led some experts to call NCDs the “greatest challenge to global health”.
Could data provide the answer?
Today over 600,000 patients from around the world share data on more than 2,800 chronic diseases to improve research and treatment of their conditions.
People who join the PatientsLikeMe online community share information on everything from their medication and treatment plans to their emotional struggles.
Many of the participants say that it is hugely beneficial just to know there is someone else out there going through similar experiences.
But through its use of data, the platform also has the potential for far more wide-ranging benefits to help improve the quality of life for patients with chronic conditions.
Give data, get data
PatientsLikeMe is one of a swathe of emerging data platforms in the healthcare sector helping provide a range of tech solutions to health problems, including speeding up the process of clinical trials using Real Time Data Analysis or using blockchain to enable the secure sharing of patient data.
Its philosophy is “give data, get data”. In