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)”.
State Capacities and Wicked Problems of Public Policy: Addressing Vulnerabilities that Affect Human Development
Report by Mosqueira, Edgardo; and Alessandro, Martín: “There is a growing mismatch between the types of public problems that governments face and the capabilities of the public administrations that design and implement policies to address them. Traditional administrative processes, the division of labor into ministries and agencies with clearly defined mandates, and even results-based management tools (such as logical frameworks or project management methodologies) are useful to address problems with relatively linear and predictable cause-effect relationships, in which success depends on the reliable execution of a predefined plan. In contrast, when dealing with wicked problems, multiple factors and actors are involved, often pushing in opposite directions and generating impacts across different sectors. Therefore, it is difficult to both align incentives and predict the effect of interventions. Such complex systems require a different approach, one that promotes collaboration among diverse actors, experimentation and learning to understand what works, and the ability to make rapid adjustments to interventions. This report illustrates the characteristics of wicked problems in two crucial development areas for Latin American and Caribbean countries: inequality and climate change. For each, it proposes institutional and managerial reforms that would expand the intervention capacities of LAC governments and analyzes the most relevant contexts for each option…(More)”.
The Adoption and Implementation of Artificial Intelligence Chatbots in Public Organizations: Evidence from U.S. State Governments
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
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
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
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
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)”.
Promoting Sustainable Data Use in State Programs
Toolkit by Chapin Hall:”…helps public sector agencies build the culture and infrastructure to apply data analysis routinely, effectively, and accurately—what we call “sustainable data use.” It is meant to serve as a hands-on resource, containing strategies and tools for agencies seeking to grow their analytic capacity.
Administrative data can be a rich source of information for human services agencies seeking to improve programs. But too often, data use in state agencies is temporary, dependent on funds and training from short-term resources such as pilot projects and grants. How can agencies instead move from data to knowledge to action routinely, creating a reinforcing cycle of evidence-building and program improvement?
Chapin Hall experts and experts at partner organizations set out to determine who achieves sustainable data use and how they go about doing so. Building on previous work and the results of a literature review, we identified domains that can significantly influence an agency’s ability to establish sustainable data practices. We then focused on eight state TANF agencies and three partner organizations with demonstrated successes in one or more of these domains, and we interviewed staff who work directly with data to learn more about what strategies they used to achieve success. We focused on what worked rather than what didn’t. From those interviews, we identified common themes, developed case studies, and generated tools to help agencies develop sustainable data practices…(More)”.
Unleashing possibilities, ignoring risks: Why we need tools to manage AI’s impact on jobs
Article by Katya Klinova and Anton Korinek: “…Predicting the effects of a new technology on labor demand is difficult and involves significant uncertainty. Some would argue that, given the uncertainty, we should let the “invisible hand” of the market decide our technological destiny. But we believe that the difficulty of answering the question “Who is going to benefit and who is going to lose out?” should not serve as an excuse for never posing the question in the first place. As we emphasized, the incentives for cutting labor costs are artificially inflated. Moreover, the invisible hand theorem does not hold for technological change. Therefore, a failure to investigate the distribution of benefits and costs of AI risks invites a future with too many “so-so” uses of AI—uses that concentrate gains while distributing the costs. Although predictions about the downstream impacts of AI systems will always involve some uncertainty, they are nonetheless useful to spot applications of AI that pose the greatest risks to labor early on and to channel the potential of AI where society needs it the most.
In today’s society, the labor market serves as a primary mechanism for distributing income as well as for providing people with a sense of meaning, community, and purpose. It has been documented that job loss can lead to regional decline, a rise in “deaths of despair,” addiction and mental health problems. The path that we lay out aims to prevent abrupt job losses or declines in job quality on the national and global scale, providing an additional tool for managing the pace and shape of AI-driven labor market transformation.
Nonetheless, we do not want to rule out the possibility that humanity may eventually be much happier in a world where machines do a lot more economically valuable work. Even despite our best efforts to manage the pace and shape of AI labor market disruption through regulation and worker-centric practices, we may still face a future with significantly reduced human labor demand. Should the demand for human labor decrease permanently with the advancement of AI, timely policy responses will be needed to address both the lost incomes as well as the lost sense of meaning and purpose. In the absence of significant efforts to distribute the gains from advanced AI more broadly, the possible devaluation of human labor would deeply impact income distribution and democratic institutions’ sustainability. While a jobless future is not guaranteed, its mere possibility and the resulting potential societal repercussions demand serious consideration. One promising proposal to consider is to create an insurance policy against a dramatic decrease in the demand for human labor that automatically kicks in if the share of income received by workers declines, for example a “seed” Universal Basic Income that starts at a very small level and remains unchanged if workers continue to prosper but automatically rises if there is large scale worker displacement…(More)”.
Reimagining Our High-Tech World
Essay by Mike Kubzansky: “…Channeling the power of technology for the good of society requires a shared vision of an ideal society. Despite the country’s increasing polarization, most Americans agree on the principles of a representative democracy and embrace the three quintessential rights inscribed in the Declaration of Independence—life, liberty, and the pursuit of happiness. Freedom and individual liberty, including freedom of speech, religion, and assembly and the right to privacy, are fundamental to most people’s expectations for this country, as are equality for all citizens, a just legal system, and a strong economy. Widespread consensus also exists around giving children a strong start in life; ensuring access to basic necessities like health care, food, and housing; and taking care of the planet.
By deliberately building a digital tech system guided by these values, society has an opportunity to advance its interests and future-proof the digital tech system for better outcomes.
Such collective action requires a broad conversation about what kind of society Americans want and how digital technology fits into that vision. To initiate this discussion, I suggest five questions philanthropists, technologists, entrepreneurs, policy makers, academics, advocates, movement leaders, students, consumers, investors, and everyone else who has a stake in the nation’s future need to start asking—now….(More)”.