A Preliminary Analysis of Collection Technologies, Data Collection Laws, and Legislative Reform during COVID-19 by Benjamin Ballard, Amanda Cutinha, and Christopher Parsons: “…a preliminary comparative analysis of how different information technologies were mobilized in response to COVID-19 to collect data, the extent to which Canadian health or privacy or emergencies laws impeded the response to COVID-19, and ultimately, the potential consequences of reforming data protection or privacy laws to enable more expansive data collection, use, or disclosure of personal information in future health emergencies. In analyzing how data has been collected in the United States, United Kingdom, and Canada, we found that while many of the data collection methods could be mapped onto a trajectory of past collection practices, the breadth and extent of data collection in tandem with how communications networks were repurposed constituted novel technological responses to a health crisis. Similarly, while the intersection of public and private interests in providing healthcare and government services is not new, the ability for private companies such as Google and Apple to forcefully shape some of the technology-enabled pandemic responses speaks to the significant ability of private companies to guide or direct public health measures that rely on contemporary smartphone technologies. While we found that the uses of technologies were linked to historical efforts to combat the spread of disease, the nature and extent of private surveillance to enable public action was arguably unprecedented….(More)”.
The Census Mapper
Google blog: “…The U.S. Census is one of the largest data sets journalists can access. It has layers and layers of important data that can help reporters tell detailed stories about their own communities. But the challenge is sorting through that data and visualizing it in a way that helps readers understand trends and the bigger picture.
Today we’re launching a new tool to help reporters dig through all that data to find stories and embed visualizations on their sites. The Census Mapper project is an embeddable map that displays Census data at the national, state and county level, as well as census tracts. It was produced in partnership with Pitch Interactive and Big Local News, as part of the 2020 Census Co-op (supported by the Google News Initiative and in cooperation with the JSK Journalism Fellowships).
Census Mapper shows where populations have grown over time.
The Census data is pulled from the data collected and processed by The Associated Press, one of the Census Co-op partners. Census Mapper then lets local journalists easily embed maps showing population change at any level, helping them tell powerful stories in a more visual way about their communities.
With the tool, you can zoom into states and below, such as North Carolina, shown here.
As part of our investment in data journalism we’re also making improvements to our Common Knowledge Project, a data explorer and visual journalism project to allow US journalists to explore local data. Built with journalists for journalists, the new version of Common Knowledge integrates journalist feedback and new features including geographic comparisons, new charts and visuals…(More)”.
Adopting Agile in State and Local Governments
Report by Sukumar Ganapati: “Agile emerged initially as a set of values and principles for software development formalized in 2001 with the Agile Manifesto. For two decades, it helped revolutionize software development. Today, Agile approaches have been adapted to government services beyond software development, offering a new way of thinking and delivering in areas such as project management, policymaking, human resources, and procurement.
The basics of Agile and associated methods have been covered in previous IBM Center for The Business of Government reports. These reports provide a good overview of Agile principles, use of Lean, and application of user-centered design. They provide insights into the evolution of Agile adoption in public sector over the last two decades. This new report, Adopting Agile in State and Local Governments, by Sukumar Ganapati of Florida International University, examines the adoption of Agile among state and local governments. State and local governments have increasingly adopted Agile methods in the last decade, applying them across a range of applications. At the same time, they vary widely in terms of their maturity levels in the adoption and implementation.
Professor Ganapati identifies three broad phases in this lifecycle of Agile maturity among public agencies in general. The three phases are not clear cut, with distinctive breaks between where one phase ends and the next one begins. Rather, they could be conceived as a continuum, as public agencies evolve through the lifecycle of implementing Agile. The report highlights the evolution of the use of Agile methods in two states (Connecticut and California) and two local cities (New York and Austin). The cases show the rich contextual evolution of Agile and how the methods are applied for using technology to streamline enterprise processes and to address social policy problems. The four case studies show different trajectories of adopting Agile in state and local governments. The strategies for adopting and implementing Agile methods broadly differ in the three lifecycle phases of infancy, adolescence, and adulthood. The case studies offer lessons for enabling strategies to adopt Agile across these three phases…(More)”.
AI Generates Hypotheses Human Scientists Have Not Thought Of
Robin Blades in Scientific American: “Electric vehicles have the potential to substantially reduce carbon emissions, but car companies are running out of materials to make batteries. One crucial component, nickel, is projected to cause supply shortages as early as the end of this year. Scientists recently discovered four new materials that could potentially help—and what may be even more intriguing is how they found these materials: the researchers relied on artificial intelligence to pick out useful chemicals from a list of more than 300 options. And they are not the only humans turning to A.I. for scientific inspiration.
Creating hypotheses has long been a purely human domain. Now, though, scientists are beginning to ask machine learning to produce original insights. They are designing neural networks (a type of machine-learning setup with a structure inspired by the human brain) that suggest new hypotheses based on patterns the networks find in data instead of relying on human assumptions. Many fields may soon turn to the muse of machine learning in an attempt to speed up the scientific process and reduce human biases.
In the case of new battery materials, scientists pursuing such tasks have typically relied on database search tools, modeling and their own intuition about chemicals to pick out useful compounds. Instead a team at the University of Liverpool in England used machine learning to streamline the creative process. The researchers developed a neural network that ranked chemical combinations by how likely they were to result in a useful new material. Then the scientists used these rankings to guide their experiments in the laboratory. They identified four promising candidates for battery materials without having to test everything on their list, saving them months of trial and error…(More)”.
We need to talk about techie tunnel vision
Article by Gillian Tett :”Last year, the powerful US data company Palantir filed documents for an initial public offering. Included was a remarkable letter to investors from Alex Karp, the CEO, that is worth remembering now.
“Our society has effectively outsourced the building of software that makes our world possible to a small group of engineers in an isolated corner of the country,” he wrote. “The question is whether we also want to outsource the adjudication of some of the most consequential moral and philosophical questions of our time.”
Karp added, “The engineering elite in Silicon Valley may know more than most about building software. But they do not know more about how society should be organized or what justice requires.” To put it more bluntly, techies might be brilliant and clever at what they do, but that doesn’t make them qualified to organise our lives. It was a striking statement from someone who is himself an ultra techie and whose company’s extensive military and intelligence links have sparked controversy…
The good news is that people in his position are finally prepared to talk about it. The even better news is that there are experiments under way to combat techie tunnel vision. In Silicon Valley, for instance, Big Tech companies are hiring social scientists. Other innovation hubs show promising signs too. In Canberra, Genevieve Bell, a former vice-president at Intel, has launched a blended social and computer science AI institute. These initiatives aim to blend AI with what I call “anthropological intelligence” — a second type of “AI” that provides a sense of social context.
The bad news is that such initiatives remain modest, and there is still extreme information asymmetry between the engineers and everyone else. What is needed is an army of cultural translators who will fight our tendency to mentally outsource the issues to engineering elites. Maybe tech innovators such as Karp and Schmidt could use some of their vast wealth to fund this….(More)”.
Privacy Principles for Mobility Data
About: “The Principles are a set of values and priorities intended to guide the mobility ecosystem in the responsible use of data and the protection of individual privacy. They are intended to serve as a guiding “North Star” to assess technical and policy decisions that have implications for privacy when handling mobility data. The principles are designed to apply to all sectors, including public, private, research and non-profit….
Increasingly, organizations in the public, private and nonprofit sectors are faced with decisions that have data privacy implications. For organizations utilizing mobility data, these principles provide a baseline framework to both identify and address these situations. Individuals whose data is being collected, utilized and shared must be afforded proper protections and opportunities for agency in how information about them is used and handled. These principles offer guidance for how to engage in this process.
Human movement generates data in many ways: directly through the usage of GPS-enabled mobility services or devices, indirectly through phones or other devices with geolocation and even through cameras and other sensors that observe the public realm. While these principles were written with shared mobility services in mind, many of them will be applicable in other contexts in which data arising out of individual movement is collected and analyzed. We encourage any organization working with this type of data to adapt and apply these principles in their specific context.
While not all mobility data may present a privacy risk to individuals, all stakeholders managing mobility data should treat it as personal information that is sensitive, unless it can be demonstrated that it doesn’t present a privacy risk to individuals.
These principles were developed through a collaboration organized by the New Urban Mobility (NUMO) alliance, the North American Bikeshare & Scootershare Association (NABSA) and the Open Mobility Foundation (OMF) in 2020. These groups convened a diverse set of stakeholders representing cities, mobility service providers, technology companies, privacy advocates and academia. Over the course of many months, this group heard from privacy experts, discussed key topics related to data privacy and identified core ideas and common themes to serve as a basis for these Principles….(More)”.
A Climate Equity Agenda Informed by Community Brilliance
Essay by Jalonne L. White-Newsome: “Even with decades of data, state-of-the-art tools and prediction technologies, and clear signals that the impacts of climate change pose a threat to public health, there is still a major disconnect that is allowing extreme weather events to disrupt the health and well-being of low-income communities and people of color across the United States. Centering the health and well-being of these communities within cross-sector partnerships between residents, scientists, government, industry, and philanthropy can drive climate adaptation and resilience…(More)”
Falling in love with the problem, not the solution
Blog by Kyle Novak: “Fall in love with the problem, not your solution.” It’s a maxim that I first heard spoken a few years ago by USAID’s former Chief Innovation Officer Ann Mei Chang. I’ve found myself frequently reflecting on those words as I’ve been thinking about the challenges of implementing public policy. I spent the past year on Capitol Hill in Washington, D.C. working as a legislative fellow, funded through a grant to bring scientists to improve evidence-based policymaking within the federal government. I spent much of the year trying to better understand how legislation and oversight work together in context of policy and politics. To learn what makes good public policy, I wanted to understand how to better implement it. Needless to say, I took a course in Problem Driven Iterative Adaptation (PDIA), a framework to manage risk in complex policy challenges by embracing experimentation and “learning through doing.”
Congress primarily uses legislation and budget to control and implement policy initiatives through the federal agencies. Legislation is drafted and introduced by lawmakers with input from constituents, interest groups, and agencies; the Congressional budget is explicitly planned out each year based on input from the agencies; and accountability is built into the process through oversight mechanisms. Congress largely provides the planning and lock-in of “plan and control” management based on majority political party control and congruence with policy priorities of the Administration. But, it is difficult to successfully implement a plan-and-control approach when political, social, or economic situations are changing.
Take the problem of data privacy and protection. A person’s identity is becoming largely digital. Every day each of us produces almost a gigabyte of information—our location is shared by our mobile phones, our preferences and interpersonal connections are tagged on social media, our purchases analyzed, and our actions recorded on increasingly ubiquitous surveillance cameras. Monetization of this information, often bought and sold through data brokers, enables an invasive and oppressive system that affects all aspects of our lives. Algorithms mine our data to make decisions about our employment, healthcare, education, credit, and policing. Machine learning and digital redlining skirts protections that prohibit discrimination on basis of race, gender, and religion. Targeted and automated disinformation campaigns suppress fundamental rights of speech and expression. And digital technologies magnify existing inequities. While misuse of personal data has the potential to do incredible harm, responsible use of that data has the power to do incredible good. The challenge of data privacy and protection is one that impacts all of us, our civil liberties, and the foundations of a democratic society.
The success of members of Congress are often measured in the solutions they propose, not the problems that they identify….(More)”
How to Budget for Equity and Drive Lasting Change
Article by Andrew Kleine and Josh Inaba: “After George Floyd’s tragic death last year sparked calls to “defund the police,” government leaders across the country looked at all their operations under a new lens of equity. Most importantly, state and local leaders examined ways to invest in equitable services. While it is often said that government budgets are value statements, the past year has revealed that many budgets need to be revisited so that they better demonstrate the values of the people they serve.
To address misalignments between government spending and community values, leaders should focus on budgeting for equity, which has four fundamental facets: prioritizing equity, using data and evidence, budgeting for outcomes and engaging the community in new ways…
Data and evidence are important components of any efforts to address racial equity because they allow governments to pinpoint disparities, establish goals to remedy them and find solutions that work. This means that government leaders should be using data to evaluate not just “How well did we do it?” and “Is anyone better off?” but also consider the question “Is everyone better off?”
Asking “Is everyone better off”? is what led Boston officials to take a deep dive into its sidewalk repair data. Analysts found that because repairs were driven by 311 complaints instead of an objective assessment of need, the sidewalks in poorer, minority neighborhoods were in worse shape than those in wealthier parts of the city. Boston now uses a sidewalk condition index and other need-based factors to prioritize its sidewalk capital program.
Similarly, evidence can help governments address more long-standing inequities such as kindergarten readiness. In Maryland, for example, 60% of white students were ready for kindergarten in 2019 compared with 42% of Black students and 26% of Hispanic students, a readiness gap that has widened in recent years. Although Maryland has acted to expand early childhood education, the root cause of the disparity starts before childbirth, when the health and preparedness of mothers can make or break early childhood outcomes.
Evidence-based upstream interventions, such as Nurse-Family Partnership programs, help improve early childhood educational outcomes by supporting low-income, first-time mothers from pregnancy through the child’s second birthday. Initiatives like these can help to address long-standing inequities, and governments can use clearinghouses, such as Results for America’s Economic Mobility Catalog, to identify evidence-based strategies to address a wide variety of these equity-related gaps…(More)”.
A Proposal for Researcher Access to Platform Data: The Platform Transparency and Accountability Act
Paper by Nathaniel Persily: “We should not need to wait for whistleblowers to blow their whistles, however, before we can understand what is actually happening on these extremely powerful digital platforms. Congress needs to act immediately to ensure that a steady stream of rigorous research reaches the public on the most pressing issues concerning digital technology. No one trusts the representations made by the platforms themselves, though, given their conflict of interest and understandable caution in releasing information that might spook shareholders. We need to develop an unprecedented system of corporate datasharing, mandated by government for independent research in the public interest.
This is easier said than done. Not only do the details matter, they are the only thing that matters. It is all well and good to call for “transparency” or “datasharing,” as an uncountable number of academics have, but the way government might setup this unprecedented regime will determine whether it can serve the grandiose purposes techcritics hope it will….(More)”.