Paper by Shaleen Khanal, Hongzhou Zhang & Araz Taeihagh: “Artificial intelligence (AI) is arguably the most transformative technology of our time. While all nations would like to mobilize their resources to play an active role in AI development and utilization, only a few nations, such as the United States and China, have the resources and capacity to do so. If so, how can smaller or less resourceful countries navigate the technological terrain to emerge at the forefront of AI development? This research presents an in-depth analysis of Singapore’s journey in constructing a robust AI ecosystem amidst the prevailing global dominance of the United States and China. By examining the case of Singapore, we argue that by designing policies that address risks associated with AI development and implementation, smaller countries can create a vibrant AI ecosystem that encourages experimentation and early adoption of the technology. In addition, through Singapore’s case, we demonstrate the active role the government can play, not only as a policymaker but also as a steward to guide the rest of the economy towards the application of AI…(More)”.
The limits of state AI legislation
Article by Derek Robertson: “When it comes to regulating artificial intelligence, the action right now is in the states, not Washington.
State legislatures are often, like their counterparts in Europe, contrasted favorably with Congress — willing to take action where their politically paralyzed federal counterpart can’t, or won’t. Right now, every state except Alabama and Wyoming is considering some kind of AI legislation.
But simply acting doesn’t guarantee the best outcome. And today, two consumer advocates warn in POLITICO Magazine that most, if not all, state laws are overlooking crucial loopholes that could shield companies from liability when it comes to harm caused by AI decisions — or from simply being forced to disclose when it’s used in the first place.
Grace Gedye, an AI-focused policy analyst at Consumer Reports, and Matt Scherer, senior policy counsel at the Center for Democracy & Technology, write in an op-ed that while the use of AI systems by employers is screaming out for regulation, many of the efforts in the states are ineffectual at best.
Under the most important state laws now in consideration, they write, “Job applicants, patients, renters and consumers would still have a hard time finding out if discriminatory or error-prone AI was used to help make life-altering decisions about them.”
Transparency around how and when AI systems are deployed — whether in the public or private sector — is a key concern of the growing industry’s watchdogs. The Netherlands’ tax authority infamously immiserated tens of thousands of families by accusing them falsely of child care benefits fraud after an algorithm used to detect it went awry…
One issue: a series of jargon-filled loopholes in many bill texts that says the laws only cover systems “specifically developed” to be “controlling” or “substantial” factors in decision-making.
“Cutting through the jargon, this would mean that companies could completely evade the law simply by putting fine print at the bottom of their technical documentation or marketing materials saying that their product wasn’t designed to be the main reason for a decision and should only be used under human supervision,” they explain…(More)”
In shaping AI policy, stories about social impacts are just as important as expert information
Blog by Daniel S. Schiff and Kaylyn Jackson Schiff: “Will artificial intelligence (AI) save the world or destroy it? Will it lead to the end of manual labor and an era of leisure and luxury, or to more surveillance and job insecurity? Is it the start of a revolution in innovation that will transform the economy for the better? Or does it represent a novel threat to human rights?
Irrespective of what turns out to be the truth, what our key policymakers believe about these questions matters. It will shape how they think about the underlying problems that AI policy is aiming to address, and which solutions are appropriate to do so. …In late 2021, we ran a study to better understand the impact of policy narratives on the behavior of policymakers. We focused on US state legislators,…
In our analysis, we found something surprising. We measured whether legislators were more likely to engage with a message featuring a narrative or featuring expert information, which we assessed by seeing if they clicked on a given fact sheet/story or clicked to register for or attended the webinar.
Despite the importance attached to technical expertise in AI circles, we found that narratives were at least as persuasive as expert information. Receiving a narrative emphasizing, say, growing competition between the US and China, or the faulty arrest of Robert Williams due to facial recognition, led to a 30 percent increase in legislator engagement compared to legislators who only received basic information about the civil society organization. These narratives were just as effective as more neutral, fact-based information about AI with accompanying fact sheets…(More)”
Using Data for Good: Identifying Who Could Benefit from Simplified Tax Filing
Blog by New America: “For years, New America Chicago has been working with state agencies, national and local advocates and thought leaders, as well as community members on getting beneficial tax credits, like the Earned Income Tax Credit (EITC) and Child Tax Credit (CTC), into the hands of those who need them most. Illinois paved the way recently with its innovative simplified filing initiative which helps residents easily claim their state Earned Income Credit (EIC) by confirming their refund with a prepopulated return.
This past year we had discussions with Illinois policymakers and state agencies, like the Illinois Department of Revenue (IDoR) and the Illinois Department of Human Services (IDHS), to envision new ways for expanding the simplified filing initiative. It is currently designed to reach those who have filed a federal tax return and claimed their EITC, leaving out non-filer households who typically do not file taxes because they earn less than the federal income requirement or have other barriers.
In Illinois, over 600,000 households are enrolled in SNAP, and over 1 million households are enrolled in Medicaid. Every year thousands of families spend countless hours applying for these and other social safety net programs using IDHS’ Application for Benefits Eligibility (ABE). Unfortunately, many of these households are most in need of the federal EITC and the recently expanded state EIC but will never receive it. We posed the question, what if Illinois could save families time and money by using that already provided income and household information to streamline access to the state EIC for low-income families that don’t normally file taxes?
Our friends at Inclusive Economy Lab (IEL) conducted analysis using Census microdata to estimate the number of Illinois households who are enrolled in Medicaid and SNAP but do not file their federal or state tax forms…(More)”.
Generative AI and Policymaking for the New Frontier
Essay by Beth Noveck: “…Embracing the same responsible experimentation approach taken in Boston and New Jersey and expanding on the examples in those interim policies, this November the state of California issued an executive order and a lengthy but clearly written report, enumerating potential benefits from the use of generative AI.
These include:
- Sentiment Analysis — Using generative AI (GenAI) to analyze public feedback on state policies and services.
- Summarizing Meetings — GenAI can find the key topics, conclusions, action items and insights.
- Improving Benefits Uptake — AI can help identify public program participants who would benefit from additional outreach. GenAI can also identify groups that are disproportionately not accessing services.
- Translation — Generative AI can help translate government forms and websites into multiple languages.
- Accessibility — GenAI can be used to translate materials, especially educational materials into formats like audio, large print or Braille or to add captions.
- Cybersecurity —GenAI models can analyze data to detect and respond to cyber attacks faster and safeguard public infrastructure.
- Updating Legacy Technology — Because it can analyze and generate computer code, generative AI can accelerate the upgrading of old computer systems.
- Digitizing Services — GenAI can help speed up the creation of new technology. And with GenAI, anyone can create computer code, enabling even nonprogrammers to develop websites and software.
- Optimizing Routing — GenAI can analyze traffic patterns and ride requests to improve efficiency of state-managed transportation fleets, such as buses, waste collection trucks or maintenance vehicles.
- Improving Sustainability — GenAI can be applied to optimize resource allocation and enhance operational efficiency. GenAI simulation tools could, for example, “model the carbon footprint, water usage and other environmental impacts of major infrastructure projects.”
Because generative AI tools can both create and analyze content, these 10 are just a small subset of the many potential applications of generative AI in governing…(More)”.
Predictive Policing Software Terrible At Predicting Crimes
Article by Aaron Sankin and Surya Mattu: “A software company sold a New Jersey police department an algorithm that was right less than 1% of the time
Crime predictions generated for the police department in Plainfield, New Jersey, rarely lined up with reported crimes, an analysis by The Markup has found, adding new context to the debate over the efficacy of crime prediction software.
Geolitica, known as PredPol until a 2021 rebrand, produces software that ingests data from crime incident reports and produces daily predictions on where and when crimes are most likely to occur.
We examined 23,631 predictions generated by Geolitica between Feb. 25 to Dec. 18, 2018 for the Plainfield Police Department (PD). Each prediction we analyzed from the company’s algorithm indicated that one type of crime was likely to occur in a location not patrolled by Plainfield PD. In the end, the success rate was less than half a percent. Fewer than 100 of the predictions lined up with a crime in the predicted category, that was also later reported to police.
Diving deeper, we looked at predictions specifically for robberies or aggravated assaults that were likely to occur in Plainfield and found a similarly low success rate: 0.6 percent. The pattern was even worse when we looked at burglary predictions, which had a success rate of 0.1 percent.
“Why did we get PredPol? I guess we wanted to be more effective when it came to reducing crime. And having a prediction where we should be would help us to do that. I don’t know that it did that,” said Captain David Guarino of the Plainfield PD. “I don’t believe we really used it that often, if at all. That’s why we ended up getting rid of it.”…(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)”.
It’s like jury duty, but for getting things done
Article by Hollie Russon Gilman and Amy Eisenstein: “Citizens’ assemblies have the potential to repair our broken politics…Imagine a democracy where people come together and their voices are heard and are translated directly into policy. Frontline workers, doctors, teachers, friends, and neighbors — young and old — are brought together in a random, representative sample to deliberate the most pressing issues facing our society. And they are compensated for their time.
The concept may sound radical. But we already use this method for jury duty. Why not try this widely accepted practice to tackle the deepest, most crucial, and most divisive issues facing our democracy?
The idea — known today as citizens’ assemblies — originated in ancient Athens. Instead of a top-down government, Athens used sortition — a system that was horizontal and distributive. The kleroterion, an allotment machine, randomly selected citizens to hold civic office, ensuring that the people had a direct say in their government’s dealings….(More)”.
Leveraging Social Media Data for Emergency Preparedness and Response
Report by the National Academies of Sciences, Engineering, and Medicine: “Most state departments of transportation (DOTs) use social media to broadcast information and monitor emergencies, but few rely heavily on social media data. The most common barriers to using social media for emergencies are personnel availability and training, privacy issues, and data reliability.
NCHRP Synthesis 610: Leveraging Social Media Data for Emergency Preparedness and Response, from TRB’s National Cooperative Highway Research Program, documents state DOT practices that leverage social media data for emergency preparedness, response, and recovery…(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)”.