Bringing Communities In, Achieving AI for All


Article by Shobita Parthasarathy and Jared Katzman: “…To this end, public and philanthropic research funders, universities, and the tech industry should be seeking out partnerships with struggling communities, to learn what they need from AI and build it. Regulators, too, should have their ears to the ground, not just the C-suite. Typical members of a marginalized community—or, indeed, any nonexpert community—may not know the technical details of AI, but they understand better than anyone else the power imbalances at the root of concerns surrounding AI bias and discrimination. And so it is from communities marginalized by AI, and from scholars and organizations focused on understanding and ameliorating social disadvantage, that AI designers and regulators most need to hear.

Progress toward AI equity begins at the agenda-setting stage, when funders, engineers, and corporate leaders make decisions about research and development priorities. This is usually seen as a technical or management task, to be carried out by experts who understand the state of scientific play and the unmet needs of the market… A heartening example comes from Carnegie Mellon University, where computer scientists worked with residents in the institution’s home city of Pittsburgh to build a technology that monitored and visualized local air quality. The collaboration began when researchers attended community meetings where they heard from residents who were suffering the effects of air pollution from a nearby factory. The residents had struggled to get the attention of local and national officials because they were unable to provide the sort of data that would motivate interest in their case. The researchers got to work on prototype systems that could produce the needed data and refined their technology in response to community input. Eventually their system brought together heterogeneous information, including crowdsourced smell reports, video footage of factory smokestacks, and air-quality and wind data, which the residents then submitted to government entities. After reviewing the data, administrators at the Environmental Protection Agency agreed to review the factory’s compliance, and within a year the factory’s parent company announced that the facility would close…(More)”.

Collaborating with Journalists and AI: Leveraging Social Media Images for Enhanced Disaster Resilience and Recovery


Paper by Murthy Dhiraj et al: “Methods to meaningfully integrate journalists into crisis informatics remain lacking. We explored the feasibility of generating a real-time, priority-driven map of infrastructure damage during a natural disaster by strategically selecting journalist networks to identify sources of image-based infrastructure-damage data. Using the REST Twitter API, 1,000,522 tweets were collected from September 13-18, 2018, during and after Hurricane Florence made landfall in the United States. Tweets were classified by source (e.g., news organizations or citizen journalists), and 11,638 images were extracted. We utilized Google’s AutoML Vision software to successfully develop a machine learning image classification model to interpret this sample of images. As a result, 80% of our labeled data was used for training, 10% for validation, and 10% for testing. The model achieved an average precision of 90.6%, an average recall of 77.2%, and an F1 score of .834. In the future, establishing strategic networks of journalists ahead of disasters will reduce the time needed to identify disaster-response targets, thereby focusing relief and recovery efforts in real-time. This approach ultimately aims to save lives and mitigate harm…(More)”.

A new index is using AI tools to measure U.S. economic growth in a broader way


Article by Jeff Cox: “Measuring the strength of the sprawling U.S. economy is no easy task, so one firm is sending artificial intelligence in to do the job.

The Zeta Economic Index, launched Monday, uses generative AI to analyze what its developers call “trillions of behavioral signals,” largely focused on consumer activity, to score growth on both a broad level of health and a separate measure on stability.

At its core, the index will gauge online and offline activity across eight categories, aiming to give a comprehensive look that incorporates standard economic data points such as unemployment and retail sales combined with high-frequency information for the AI age.

“The algorithm is looking at traditional economic indicators that you would normally look at. But then inside of our proprietary algorithm, we’re ingesting the behavioral data and transaction data of 240 million Americans, which nobody else has,” said David Steinberg, co-founder, chairman and CEO of Zeta Global.

“So instead of looking at the data in the rearview mirror like everybody else, we’re trying to put it out in advance to give a 30-day advanced snapshot of where the economy is going,” he added…(More)”.

How the Rise of the Camera Launched a Fight to Protect Gilded Age Americans’ Privacy


Article by Sohini Desai: “In 1904, a widow named Elizabeth Peck had her portrait taken at a studio in a small Iowa town. The photographer sold the negatives to Duffy’s Pure Malt Whiskey, a company that avoided liquor taxes for years by falsely advertising its product as medicinal. Duffy’s ads claimed the fantastical: that it cured everything from influenza to consumption, that it was endorsed by clergymen, that it could help you live until the age of 106. The portrait of Peck ended up in one of these dubious ads, published in newspapers across the country alongside what appeared to be her unqualified praise: “After years of constant use of your Pure Malt Whiskey, both by myself and as given to patients in my capacity as nurse, I have no hesitation in recommending it.”

Duffy’s lies were numerous. Peck (misleadingly identified as “Mrs. A. Schuman”) was not a nurse, and she had not spent years constantly slinging back malt beverages. In fact, she fully abstained from alcohol. Peck never consented to the ad.

The camera’s first great age—which began in 1888 when George Eastman debuted the Kodak—is full of stories like this one. Beyond the wonders of a quickly developing art form and technology lay widespread lack of control over one’s own image, perverse incentives to make a quick buck, and generalized fear at the prospect of humiliation and the invasion of privacy…(More)”.

AI-Ready FAIR Data: Accelerating Science through Responsible AI and Data Stewardship


Article by Sean Hill: “Imagine a future where scientific discovery is unbound by the limitations of data accessibility and interoperability. In this future, researchers across all disciplines — from biology and chemistry to astronomy and social sciences — can seamlessly access, integrate, and analyze vast datasets with the assistance of advanced artificial intelligence (AI). This world is one where AI-ready data empowers scientists to unravel complex problems at unprecedented speeds, leading to breakthroughs in medicine, environmental conservation, technology, and more. The vision of a truly FAIR (Findable, Accessible, Interoperable, Reusable) and AI-ready data ecosystem, underpinned by Responsible AI (RAI) practices and the pivotal role of data stewards, promises to revolutionize the way science is conducted, fostering an era of rapid innovation and global collaboration…(More)”.

Water Shortages in Latin America: How Can Behavioral Science Help?


Article by Juan Roa Duarte: “Today in 2024, one of Latin America’s largest cities, Bogota, is facing significant challenges due to prolonged droughts exacerbated by El Niño. As reservoir levels plummet, local governments have implemented water rationing measures to manage the crisis. However, these rationing measures have remained unsuccessful after one month of implementation—in fact, water usage increased during the first week.1 But why? What solution can finally help solve this crisis?

In this article, we will explore how behavioral science can help Latin American cities mitigate their water shortages—and how, surprisingly, a method my hometown Bogota used back in the ‘90s can shed some light on this current issue. We’ll also explore some modern behavioral science strategies that can be used in parallel…(More)”

Open government, civic tech and digital platforms in Latin America: A governance study of Montevideo’s urban app ‘Por Mi Barrio’


Paper by Carolina Aguerre and Carla Bonina: “Digital technologies have a recognised potential to build more efficient, credible, and innovative public institutions in Latin America. Despite progress, digital transformation in Latin American governments remains limited. In this work, we explore a peculiar yet largely understudied opportunity in the region: pursuing digital government transformation as a collaborative process between the government and civil society organisations. To do so, we draw from information systems research on digital government and platforms for development, complemented with governance theory from political science and conduct an interpretive in-depth case study of an urban reporting platform in Montevideo called ‘Por Mi Barrio’. The study reveals three mutually reinforced orders of governance in the trajectory of the project and explain how the collaboration unfolded over time: (i) a technical decision to use open platform architectures; (ii) the negotiation of formal and informal rules to make the project thrive and (iii) a shared, long-term ideology around the value of open technologies and technical sovereignty grounded in years of political history. Using a contextual explanation approach, our study helps to improve our understanding on the governance of collaborative digital government platforms in Latin America, with specific contributions to practice…(More)”.

A lack of data hampers efforts to fix racial disparities in utility cutoffs


Article by Akielly Hu: “Each year, nearly 1.3 million households across the country have their electricity shut off because they cannot pay their bill. Beyond risking the health, or even lives, of those who need that energy to power medical devices and inconveniencing people in myriad ways, losing power poses a grave threat during a heat wave or cold snap.

Such disruptions tend to disproportionately impact Black and Hispanic families, a point underscored by a recent study that found customers of Minnesota’s largest electricity utility who live in communities of color were more than three times as likely to experience a shutoff than those in predominantly white neighborhoods. The finding, by University of Minnesota researchers, held even when accounting for income, poverty level, and homeownership. 

Energy policy researchers say they consistently see similar racial disparities nationwide, but a lack of empirical data to illustrate the problem is hindering efforts to address the problem. Only 30 states require utilities to report disconnections, and of those, only a handful provide data revealing where they happen. As climate change brings hotter temperatures, more frequent cold snaps, and other extremes in weather, energy analysts and advocates for disadvantaged communities say understanding these disparities and providing equitable access to reliable power will become ever more important…(More)”.

Positive Pathways report


Report by Michael Lawrence and Megan Shipman: “Polycrisis analysis reveals the complex and systemic nature of the world’s problems, but it can also help us pursue “positive pathways” to better futures. This report outlines the sorts of systems changes required to avoid, mitigate, and navigate through polycrisis given the dual nature of crises as harmful disasters and opportunities for transformation. It then examines the progression between three prominent approaches to systems change—leverage points, tipping points, and multi-systemic stability landscapes—by highlighting their advances and limitations. The report concludes that new tools like Cross-Impact Balance analysis can build on these approaches to help navigate through polycrisis by identifying stable and desirable multi-systemic equilibria…(More)”

Government + research + philanthropy: How cross-sector partnerships can improve policy decisions and action


Paper by Jenni Owen: “Researchers often lament that government decision-makers do not generate or use research evidence. People in government often lament that researchers are not responsive to government’s needs. Yet there is increasing enthusiasm in government, research, and philanthropy sectors for developing, investing in, and sustaining government-research partnerships that focus on government’s use of evidence. There is, however, scant guidance about how to do so. To help fill the gap, this essay addresses (1) Why government-research partnerships matter; (2) Barriers to developing government-research partnerships; (3) Strategies for addressing the barriers; (4) The role of philanthropy in government-research partnerships. The momentum to develop, invest in, and sustain cross-sector partnerships that advance government’s use of evidence is exciting. It is especially encouraging that there are feasible and actionable strategies for doing so…(More)”.