Proceedings from the National Academies of Sciences: “Artificial intelligence (AI), facial recognition, and other advanced computational and statistical techniques are accelerating advancements in the life sciences and many other fields. However, these technologies and the scientific developments they enable also hold the potential for unintended harm and malicious exploitation. To examine these issues and to discuss practices for anticipating and preventing the misuse of advanced data analytics and biological data in a global context, the National Academies of Sciences, Engineering, and Medicine convened two virtual workshops on November 15, 2022, and February 9, 2023. The workshops engaged scientists from the United States, South Asia, and Southeast Asia through a series of presentations and scenario-based exercises to explore emerging applications and areas of research, their potential benefits, and the ethical issues and security risks that arise when AI applications are used in conjunction with biological data. This publication highlights the presentations and discussions of the workshops…(More)”.
Building the Democracy We Need for the Twenty-First Century
Toolkit by Hollie Russon Gilman, Grace Levin, and Jessica Tang: “This toolkit situates collaborative governance, also known as “co-governance,” within a framework for building community that sees civic education, relationship building, and leadership development as essential first steps toward an effective and sustained participatory process. It offers key takeaways and best practices from effective, ongoing collaborative governance projects between communities and decision makers. The best of these projects shift decision-making power to the hands of communities to make room for more deliberation, consensus, and lasting change. Building on the lessons of successful case studies from across the United States, including Georgia, Kentucky, New York, and Washington, this toolkit aims to support local leaders inside and outside government as they navigate and execute co-governance models in their communities…(More)”.
Shifting the Culture of Public Procurement Can Help Improve Digital Public Services
Article by Sarah Forland: “Advancing digital public infrastructure (DPI) that strengthens the delivery of public services requires shifting the culture around how governments design, develop, and implement digital solutions. At the foundation of this work, is public procurement—a unique and often overlooked avenue for improving digital public services…
To reconceptualize public procurement, stakeholders need to collaborate to improve shared accountability, build mutual trust, and create better outcomes for public service delivery. In October 2022, DIGI worked with experts across the field to identify five core opportunity areas for change and highlighted personal narratives with advice on how to get there, including insight from some of the panelist organizations and experts…
1. View procurement as part of the innovation process.
Rather than focusing primarily on risk-avoidance and compliance, public servants should integrate procurement into the innovation process. jurisdictions can adopt goal-oriented, modular contracting practices or performance-based contracts by fostering collaboration among various stakeholders. This approach allows for agile, iterative, and flexible solution development, placing emphasis on outcome-based solutions.
2. Start with the goal, then work toward the most effective solution, rather than prescribing a solution.
Jurisdictions can create an environment that encourages vendors to propose a variety of innovative solutions through request for proposals (RFP) that explicitly outlines objectives, success indicators, and potential failure points. This process can serve as a design exercise for vendors, enabling jurisdictions to select the proposal that most effectively aligns with their identified goals.
3. Center diversity, equity, inclusion, and access (DEIA) throughout procurement.
Delivering people-centered outcomes through civic solutions requires intentional DEIA practices. On the backend, this can include increasing RFP availability and access to new vendors—especially women- and minority-owned businesses. In addition, requiring human-centered design and community input can help ensure that those who will interact with a digital solution can do so effectively, easily, and safely…(More)”.
How to Regulate AI? Start With the Data
Article by Susan Ariel Aaronson: “We live in an era of data dichotomy. On one hand, AI developers rely on large data sets to “train” their systems about the world and respond to user questions. These data troves have become increasingly valuable and visible. On the other hand, despite the import of data, U.S. policy makers don’t view data governance as a vehicle to regulate AI.
U.S. policy makers should reconsider that perspective. As an example, the European Union, and more than 30 other countries, provide their citizens with a right not to be subject to automated decision making without explicit consent. Data governance is clearly an effective way to regulate AI.
Many AI developers treat data as an afterthought, but how AI firms collect and use data can tell you a lot about the quality of the AI services they produce. Firms and researchers struggle to collect, classify, and label data sets that are large enough to reflect the real world, but then don’t adequately clean (remove anomalies or problematic data) and check their data. Also, few AI developers and deployers divulge information about the data they use to train AI systems. As a result, we don’t know if the data that underlies many prominent AI systems is complete, consistent, or accurate. We also don’t know where that data comes from (its provenance). Without such information, users don’t know if they should trust the results they obtain from AI.
The Washington Post set out to document this problem. It collaborated with the Allen Institute for AI to examine Google’s C4 data set, a widely used and large learning model built on data scraped by bots from 15 million websites. Google then filters the data, but it understandably can’t filter the entire data set.
Hence, this data set provides sufficient training data, but it also presents major risks for those firms or researchers who rely on it. Web scraping is generally legal in most countries as long as the scraped data isn’t used to cause harm to society, a firm, or an individual. But the Post found that the data set contained swaths of data from sites that sell pirated or counterfeit data, which the Federal Trade Commission views as harmful. Moreover, to be legal, the scraped data should not include personal data obtained without user consent or proprietary data obtained without firm permission. Yet the Post found large amounts of personal data in the data sets as well as some 200 million instances of copyrighted data denoted with the copyright symbol.
Reliance on scraped data sets presents other risks. Without careful examination of the data sets, the firms relying on that data and their clients cannot know if it contains incomplete or inaccurate data, which in turn could lead to problems of bias, propaganda, and misinformation. But researchers cannot check data accuracy without information about data provenance. Consequently, the firms that rely on such unverified data are creating some of the AI risks regulators hope to avoid.
It makes sense for Congress to start with data as it seeks to govern AI. There are several steps Congress could take…(More)”.
Destination? Care Blocks!
Blog by Natalia González Alarcón, Hannah Chafetz, Diana Rodríguez Franco, Uma Kalkar, Bapu Vaitla, & Stefaan G. Verhulst: “Time poverty” caused by unpaid care work overload, such as washing, cleaning, cooking, and caring for their care-receivers is a structural consequence of gender inequality. In the City of Bogotá, 1.2 million women — 30% of their total women’s population — carry out unpaid care work full-time. If such work was compensated, it would represent 13% of Bogotá’s GDP and 20% of the country’s GDP. Moreover, the care burden falls disproportionately on women’s shoulder and prevents them from furthering their education, achieving financial autonomy, participating in their community, and tending to their personal wellbeing.
To address the care burden and its spillover consequences on women’s economic autonomy, well-being and political participation, in October 2020, Bogotá Mayor Claudia López launched the Care Block Initiative. Care Blocks, or Manzanas del cuidado, are centralized areas for women’s economic, social, medical, educational, and personal well-being and advancement. They provide services simultaneously for caregivers and care-receivers.
As the program expands from 19 existing Care Blocks to 45 Care Blocks by the end of 2035, decision-makers face another issue: mobility is a critical and often limiting factor for women when accessing Care Blocks in Bogotá.
On May 19th, 2023, The GovLab, Data2X, and the Secretariat for Women’s Affairs, in the City Government of Bogotá co-hosted a studio that aimed to scope a purposeful and gender-conscious data collaborative that addresses mobility-related issues affecting the access of Care Blocks in Bogotá. Convening experts across the gender, mobility, policy, and data ecosystems, the studio focused on (1) prioritizing the critical questions as it relates to mobility and access to Care Blocks and (2) identifying the data sources and actors that could be tapped into to set up a new data collaborative…(More)”.
Artificial Intelligence, Big Data, Algorithmic Management, and Labor Law
Chapter by Pauline Kim: “Employers are increasingly relying on algorithms and AI to manage their workforces, using automated systems to recruit, screen, select, supervise, discipline, and even terminate employees. This chapter explores the effects of these systems on the rights of workers in standard work relationships, who are presumptively protected by labor laws. It examines how these new technological tools affect fundamental worker interests and how existing law applies, focusing primarily as examples on two particular concerns—nondiscrimination and privacy. Although current law provides some protections, legal doctrine has largely developed with human managers in mind, and as a result, fails to fully apprehend the risks posed by algorithmic tools. Thus, while anti-discrimination law prohibits discrimination by workplace algorithms, the existing framework has a number of gaps and uncertainties when applied to these systems. Similarly, traditional protections for employee privacy are ill-equipped to address the sheer volume and granularity of worker data that can now be collected, and the ability of computational techniques to extract new insights and infer sensitive information from that data. More generally, the expansion of algorithmic management affects other fundamental worker interests because it tends to increase employer power vis à vis labor. This chapter concludes by briefly considering the role that data protection laws might play in addressing the risks of algorithmic management…(More)”.
How Leaders in Higher Education Can Embed Behavioral Science in Their Institutions
Essay by Ross E. O’Hara: “…Once we view student success through a behavioral science lens and see the complex systems underlying student decision making, it becomes clear that behavioral scientists work best not as mechanics who repair broken systems, but as engineers who design better systems. Higher education, therefore, needs to diffuse those engineers throughout the organization.
To that end, Hallsworth recommends that organizations change their view of behavioral science “from projects to processes, from commissions to culture.” Only when behavioral science expertise is diffused across units and incorporated into all key organizational functions can a college become behaviorally enabled. So how might higher education go about this transformation?
1. Leverage the faculty
Leaders with deep expertise in behavioral science are likely already employed in social and behavioral sciences departments. Consider ways to focus their energy inward to tackle institutional challenges, perhaps using their own classrooms or departments as testing grounds. As they find promising solutions, build the infrastructure to disseminate and implement those ideas college and system wide. Unlike higher education’s normal approach—giving faculty additional unpaid and underappreciated committee work—provide funding and recognition that incentivizes faculty to make higher education policy an important piece of their academic portfolio.
2. Practice cross-functional training
I have spent the past several years providing colleges with behavioral science professional development, but too often this work is focused on a single functional unit, like academic advisors or faculty. Instead, create trainings that include representatives from across campus (e.g., enrollment; financial aid; registrar; student affairs). Not only will this diffuse behavioral science knowledge across the institution, but it will bring together the key players that impact student experience and make it easier for them to see the adaptive system that determines whether a student graduates or withdraws.
3. Let behavioral scientists be engineers
Whether you look for faculty or outside consultants, bring behavioral science experts into conversations early. From redesigning college-to-career pathways to building a new cafeteria, behavioral scientists can help gather and interpret student voices, foresee and circumvent behavioral challenges, and identify measurable and meaningful evaluation metrics. The impact of their expertise will be even greater when they work in an environment with a diffuse knowledge of behavioral science already in place…(More)”
Gamifying medical data labeling to advance AI
Article by Zach Winn: “…Duhaime began exploring ways to leverage collective intelligence to improve medical diagnoses. In one experiment, he trained groups of lay people and medical school students that he describes as “semiexperts” to classify skin conditions, finding that by combining the opinions of the highest performers he could outperform professional dermatologists. He also found that by combining algorithms trained to detect skin cancer with the opinions of experts, he could outperform either method on its own….The DiagnosUs app, which Duhaime developed with Centaur co-founders Zach Rausnitz and Tom Gellatly, is designed to help users test and improve their skills. Duhaime says about half of users are medical school students and the other half are mostly doctors, nurses, and other medical professionals…
The approach stands in sharp contrast to traditional data labeling and AI content moderation, which are typically outsourced to low-resource countries.
Centaur’s approach produces accurate results, too. In a paper with researchers from Brigham and Women’s Hospital, Massachusetts General Hospital (MGH), and Eindhoven University of Technology, Centaur showed its crowdsourced opinions labeled lung ultrasounds as reliably as experts did…
Centaur has found that the best performers come from surprising places. In 2021, to collect expert opinions on EEG patterns, researchers held a contest through the DiagnosUs app at a conference featuring about 50 epileptologists, each with more than 10 years of experience. The organizers made a custom shirt to give to the contest’s winner, who they assumed would be in attendance at the conference.
But when the results came in, a pair of medical students in Ghana, Jeffery Danquah and Andrews Gyabaah, had beaten everyone in attendance. The highest-ranked conference attendee had come in ninth…(More)”
“How Democracy Should Work” Lesson in Learning, Building Cohesion and Community
Case study by Marjan Horst Ehsassi: “Something special happened in a small community just north of San Francisco during the summer of 2022. The city of Petaluma decided to do democracy a bit differently. To figure out what to do about a seemingly-intractable local issue, the city of 60,000 decided policymakers and “experts” shouldn’t be the only ones at the decision-making table—residents of Petaluma also ought to have a voice. They would do this by instituting a Citizens’ Assembly—the first of its kind in California.
Citizens’ Assemblies and sortition are not new ideas; in fact, they’ve helped citizens engage in decision-making since Ancient Greece. Yet only recently did they resurge as a possible antidote to a representative democracy that no longer reflects citizens’ preferences and pervasive citizen disengagement from political institutions. Also referred to as lottery-selected panels or citizens’ panels, this deliberative platform has gained popularity in Western Europe but is only just beginning to make inroads in the United States. The Petaluma City Council’s decision to invite Healthy Democracy (healthydemocracy.org), a leading U.S. organization dedicated to designing and implementing deliberative democracy programs, to convene a citizens’ assembly on the future of a large plot of public land, demonstrates unique political vision and will. This decision contributes to a roadmap for innovative ways to engage with citizens.
This case study examines this novel moment of democratic experimentation in California, which became known as the Petaluma Fairgrounds Advisory Panel (PFAP). It begins with a description of the context, a summary of the PFAP’s design, composition, and process, and a discussion of the role of the government-lead or sponsor, the Petaluma City Council. An analysis of the impact of participation on the Panelist using a methodology developed by the author in several other case studies follows. Finally, the last section provides several recommendations to enhance the impact of such processes as well as thoughts on the future of deliberative platforms…(More)”.
How data helped Mexico City reduce high-impact crime by more than 50%
Article by Alfredo Molina Ledesma: “When Claudia Sheimbaum Pardo became Mayor of Mexico City 2018, she wanted a new approach to tackling the city’s most pressing problems. Crime was at the very top of the agenda – only 7% of the city’s inhabitants considered it a safe place. New policies were needed to turn this around.
Data became a central part of the city’s new strategy. The Digital Agency for Public Innovation was created in 2019 – tasked with using data to help transform the city. To put this into action, the city administration immediately implemented an open data policy and launched their official data platform, Portal de Datos Abiertos. The policy and platform aimed to make data that Mexico City collects accessible to anyone: municipal agencies, businesses, academics, and ordinary people.
“The main objective of the open data strategy of Mexico City is to enable more people to make use of the data generated by the government in a simple and interactive manner,” said Jose Merino, Head of the Digital Agency for Public Innovation. “In other words, what we aim for is to democratize the access and use of information.” To achieve this goal a new tool for interactive data visualization called Sistema Ajolote was developed in open source and integrated into the Open Data Portal…
Information that had never been made public before, such as street-level crime from the Attorney General’s Office, is now accessible to everyone. Academics, businesses and civil society organizations can access the data to create solutions and innovations that complement the city’s new policies. One example is the successful “Hoyo de Crimen” app, which proposes safe travel routes based on the latest street-level crime data, enabling people to avoid crime hotspots as they walk or cycle through the city.
Since the introduction of the open data policy – which has contributed to a comprehensive crime reduction and social support strategy – high-impact crime in the city has decreased by 53%, and 43% of Mexico City residents now consider the city to be a safe place…(More)”.