Disinformation and Civic Tech Research

Curated on Posted on by Stefaan Verhulst

Code for All Playbook: “”The Disinformation and Civic Tech Playbook is a tool for people who are interested in understanding how civic tech can help confront disinformation. This guide will help you successfully advocate for, and implement disinfo-fighting tools, programs, and campaigns from partners around the world.

In order to effectively fight misinformation at a societal scale, three stages of work must be completed in sequential order:

  1. Monitor or research media environment (traditional, social, and/or messaging apps) for misinformation
  2. Verify and/or debunk
  3. Reach people with the truth and counter-message falsehoods

These stages ascend from least impactful to most impactful activity.

Researching misinformation in the media environment has no effect whatsoever on its own. Verifying and debunking falsehoods have limited utility unless stage three is also achieved: successfully reaching communities with true information in a way that gets through to them, and effectively counter-messaging the misinformation that spreads so easily.

Unfortunately, the distribution of misinformation management projects to date seems to be the exact inverse of these stages. There has been an enormous amount of work to passively monitor and research media environments for misinformation. There is also a large amount of energy and resources dedicated to verifying and debunking misinformation through traditional fact-checking approaches. Whether because it’s the hardest one to solve or just third in the consecutive sequence, relatively few misinformation management projects have made it to the final stage of genuinely getting through to people and experimenting with effective counter-messaging and counter-engagement (see The Sentinel Project interview for further discussion)…(More)”.

Liar in a Crowded Theater

Curated on Posted on by Stefaan Verhulst

Book by Jeff Kosseff: “When commentators and politicians discuss misinformation, they often repeat five words: “fire in a crowded theater.” Though governments can, if they choose, attempt to ban harmful lies, propaganda, misinformation, and disinformation, how effective will their efforts really be? Can they punish someone for yelling “fire” in a crowded theater—and would those lies then have any less impact? How do governments around the world respond to the spread of misinformation, and when should the US government protect the free speech of liars?

In Liar in a Crowded Theater, law professor Jeff Kosseff addresses the pervasiveness of lies, the legal protections they enjoy, the harm they cause, and how to combat them. From the COVID-19 pandemic to the 2016 and 2020 presidential elections and the January 6, 2021, insurrection on the Capitol building, Kosseff argues that even though lies can inflict huge damage, US law should continue to protect them. Liar in a Crowded Theater explores both the history of protected falsehoods and where to go from here.

Drawing on years of research and thousands of pages of court documents in dozens of cases—from Alexander Hamilton’s enduring defense of free speech to Eminem’s victory in a lawsuit claiming that he stretched the truth in a 1999 song—Kosseff illustrates not only why courts are reluctant to be the arbiters of truth but also why they’re uniquely unsuited to that role. Rather than resorting to regulating speech and fining or jailing speakers, he proposes solutions that focus on minimizing the harms of misinformation. If we want to seriously address concerns about misinformation and other false speech, we must finally exit the crowded theater…(More)”.

Sharing Health Data: The Why, the Will, and the Way Forward.

Curated on Posted on by Stefaan Verhulst

Book edited by Grossmann C, Chua PS, Ahmed M, et al. : “Sharing health data and information1 across stakeholder groups is the bedrock of a learning health system. As data and information are increasingly combined across various sources, their generative value to transform health, health care, and health equity increases significantly. Facilitating this potential is an escalating surge of digital technologies (i.e., cloud computing, broadband and wireless solutions, digital health technologies, and application programming interfaces [APIs]) that, with each successive generation, not only enhance data sharing, but also improve in their ability to preserve privacy and identify and mitigate cybersecurity risks. These technological advances, coupled with notable policy developments, new interoperability standards (particularly the Fast Healthcare Interoperability Resources [FHIR] standard), and the launch of innovative payment models within the last decade, have resulted in a greater recognition of the value of health data sharing among patients, providers, and researchers. Consequently, a number of data sharing collaborations are emerging across the health care ecosystem.

Unquestionably, the COVID-19 pandemic has had a catalytic effect on this trend. The criticality of swift data exchange became evident at the outset of the pandemic, when the scientific community sought answers about the novel SARS-CoV-2 virus and emerging disease. Then, as the crisis intensified, data sharing graduated from a research imperative to a societal one, with a clear need to urgently share and link data across multiple sectors and industries to curb the effects of the pandemic and prevent the next one.

In spite of these evolving attitudes toward data sharing and the ubiquity of data-sharing partnerships, barriers persist. The practice of health data sharing occurs unevenly, prominent in certain stakeholder communities while absent in others. A stark contrast is observed between the volume, speed, and frequency with which health data is aggregated and linked—oftentimes with non-traditional forms of health data—for marketing purposes, and the continuing challenges patients experience in contributing data to their own health records. In addition, there are varying levels of data sharing. Not all types of data are shared in the same manner and at the same level of granularity, creating a patchwork of information. As highlighted by the gaps observed in the haphazard and often inadequate sharing of race and ethnicity data during the pandemic, the consequences can be severe—impacting the allocation of much-needed resources and attention to marginalized communities. Therefore, it is important to recognize the value of data sharing in which stakeholder participation is equitable and comprehensive— not only for achieving a future ideal state in health care, but also for redressing long-standing inequities…(More)”

The Secret Solution To Increasing Resident Trust

Curated on Posted on by Stefaan Verhulst

Report by CivicPlus: “We surveyed over 16,000 Americans to determine what factors most impacted community members in fostering feelings of trust in their local government. We found that residents in communities with digital resident self-service technology are more satisfied with their local government than residents still dependent on analog interactions to obtain government services. Residents in technology-forward communities also tend to be more engaged civic participants…(More)”.

Creating Action with Data: Using Data to Increase Equity in Urban Development

Curated on Posted on by Stefaan Verhulst

Report by Justin Kollar, Niko McGlashan, and Sarah Williams: “The use of data in urban development is controversial because of the numerous examples showing its use to reinforce inequality rather than inclusion. From the development of Home Owners Loan Corporation (HOLC) maps, which excluded many minority communities from mortgages, to zoning laws used to reinforce structural racism, data has been used by those in power to elevate some while further marginalizing others. Yet data can achieve the opposite outcome by exposing inequity, encouraging dialogue and debate, making developers and cities more accountable, and ultimately creating new digital tools to make development processes more inclusive. Using data for action requires that we build teams to ask and answer the right questions, collect the right data, analyze the data ingeniously, ground-truth the results with communities, and share the insights with broader groups so they can take informed action. This paper looks at the development of two recent approaches in New York and Seattle to measure equity in urban development. We reflect on these approaches through the lens of data action principles (Williams 2020). Such reflections can highlight the challenges and opportunities for furthering the measurement and achievement of equitable development by other groups, such as real estate developers and community organizations, who seek to create positive social impact through their activities…(More)”.

The Adoption and Implementation of Artificial Intelligence Chatbots in Public Organizations: Evidence from U.S. State Governments

Curated on Posted on by Stefaan Verhulst

Paper by Tzuhao Chen, Mila Gascó-Hernandez, and Marc Esteve: “Although the use of artificial intelligence (AI) chatbots in public organizations has increased in recent years, three crucial gaps remain unresolved. First, little empirical evidence has been produced to examine the deployment of chatbots in government contexts. Second, existing research does not distinguish clearly between the drivers of adoption and the determinants of success and, therefore, between the stages of adoption and implementation. Third, most current research does not use a multidimensional perspective to understand the adoption and implementation of AI in government organizations. Our study addresses these gaps by exploring the following question: what determinants facilitate or impede the adoption and implementation of chatbots in the public sector? We answer this question by analyzing 22 state agencies across the U.S.A. that use chatbots. Our analysis identifies ease of use and relative advantage of chatbots, leadership and innovative culture, external shock, and individual past experiences as the main drivers of the decisions to adopt chatbots. Further, it shows that different types of determinants (such as knowledge-base creation and maintenance, technology skills and system crashes, human and financial resources, cross-agency interaction and communication, confidentiality and safety rules and regulations, and citizens’ expectations, and the COVID-19 crisis) impact differently the adoption and implementation processes and, therefore, determine the success of chatbots in a different manner. Future research could focus on the interaction among different types of determinants for both adoption and implementation, as well as on the role of specific stakeholders, such as IT vendors…(More)”.

Developing Wearable Technologies to Advance Understanding of Precision Environmental Health

Curated on Posted on by Stefaan Verhulst

Report by the National Academies of Sciences, Engineering, and Medicine: “The rapid proliferation of wearable devices that gather data on physical activity and physiology has become commonplace across various sectors of society. Concurrently, the development of advanced wearables and sensors capable of detecting a multitude of compounds presents new opportunities for monitoring environmental exposure risks. Wearable technologies are additionally showing promise in disease prediction, detection, and management, thereby offering potential advancements in the interdisciplinary fields of both environmental health and biomedicine.

To gain insight into this burgeoning field, on June 1 and 2, 2023, the National Academies of Sciences, Engineering, and Medicine organized a 2-day virtual workshop titled Developing Wearable Technologies to Advance Understanding of Precision Environmental Health. Experts from government, industry, and academia convened to discuss emerging applications and the latest advances in wearable technologies. The workshop aimed to explore the potential of wearables in capturing, monitoring, and predicting environmental exposures and risks to inform precision environmental health…(More)”.

It’s Official: Cars Are the Worst Product Category We Have Ever Reviewed for Privacy

Curated on Posted on by Stefaan Verhulst

Article by the Mozilla Foundation: “Car makers have been bragging about their cars being “computers on wheels” for years to promote their advanced features. However, the conversation about what driving a computer means for its occupants’ privacy hasn’t really caught up. While we worried that our doorbells and watches that connect to the internet might be spying on us, car brands quietly entered the data business by turning their vehicles into powerful data-gobbling machines. Machines that, because of their all those brag-worthy bells and whistles, have an unmatched power to watch, listen, and collect information about what you do and where you go in your car.

All 25 car brands we researched earned our *Privacy Not Included warning label — making cars the official worst category of products for privacy that we have ever reviewed…(More)”.

Scaling deep through transformative learning in public sector innovation labs – experiences from Vancouver and Auckland

Curated on Posted on by Stefaan Verhulst

Article by Lindsay Cole & Penny Hagen: “…explores scaling deep through transformative learning in Public Sector Innovation Labs (PSI labs) as a pathway to increase the impacts of their work. Using literature review and participatory action research with two PSI labs in Vancouver and Auckland, we provide descriptions of how they enact transformative learning and scaling deep. A shared ambition for transformative innovation towards social and ecological wellbeing sparked independent moves towards scaling deep and transformative learning which, when compared, offer fruitful insights to researchers and practitioners. The article includes a PSI lab typology and six moves to practice transformative learning and scaling deep…(More)”.

Toward a 21st Century National Data Infrastructure: Enhancing Survey Programs by Using Multiple Data Sources

Curated on Posted on by Stefaan Verhulst

Report by National Academies of Sciences, Engineering, and Medicine: “Much of the statistical information currently produced by federal statistical agencies – information about economic, social, and physical well-being that is essential for the functioning of modern society – comes from sample surveys. In recent years, there has been a proliferation of data from other sources, including data collected by government agencies while administering programs, satellite and sensor data, private-sector data such as electronic health records and credit card transaction data, and massive amounts of data available on the internet. How can these data sources be used to enhance the information currently collected on surveys, and to provide new frontiers for producing information and statistics to benefit American society?…(More)”.