How elderly dementia patients are unwittingly fueling political campaigns

Curated on Posted on by Stefaan Verhulst

Article by Blake Ellis, et al: “The 80-year-old communications engineer from Texas had saved for decades, driving around in an old car and buying clothes from thrift stores so he’d have enough money to enjoy his retirement years.

But as dementia robbed him of his reasoning abilities, he began making online political donations over and over again — eventually telling his son he believed he was part of a network of political operatives communicating with key Republican leaders. In less than two years, the man became one of the country’s largest grassroots supporters of the Republican Party, ultimately giving away nearly half a million dollars to former President Donald Trump and other candidates. Now, the savings account he spent his whole life building is practically empty.

The story of this unlikely political benefactor is one of many playing out across the country.

More than 1,000 reports filed with government agencies and consumer advocacy groups reviewed by CNN, along with an analysis of campaign finance data and interviews with dozens of contributors and their family members, show how deceptive political fundraisers have victimized hundreds of elderly Americans and misled those battling dementia or other cognitive impairments into giving away millions of dollars — far more than they ever intended. Some unintentionally joined the ranks of the top grassroots political donors in the country as they tapped into retirement savings and went into debt, contributing six-figure sums through thousands of transactions…(More)”.

The Number

Curated on Posted on by Stefaan Verhulst

Article by John Lanchester: “…The other pieces published in this series have human protagonists. This one doesn’t: The main character of this piece is not a person but a number. Like all the facts and numbers cited above, it comes from the federal government. It’s a very important number, which has for a century described economic reality, shaped political debate and determined the fate of presidents: the consumer price index.

The CPI is crucial for multiple reasons, and one of them is not because of what it is but what it represents. The gathering of data exemplifies our ambition for a stable, coherent society. The United States is an Enlightenment project based on the supremacy of reason; on the idea that things can be empirically tested; that there are self-evident truths; that liberty, progress and constitutional government walk arm in arm and together form the recipe for the ideal state. Statistics — numbers created by the state to help it understand itself and ultimately to govern itself — are not some side effect of that project but a central part of what government is and does…(More)”.

We’ve Got a Big Problem

Curated on Posted on by Stefaan Verhulst

Blog by Daro: “There is a problem related to how we effectively help people receiving social services and public benefit programs. It’s a problem that we have been thinking, talking, and writing about for years. It’s a problem that once you see it, you can’t unsee it. It’s also a problem that you’re likely familiar with, whether you have direct experience with the dynamics themselves, or you’ve been frustrated by how these dynamics impact your work. In February, we organized a convening at Georgetown University in collaboration with Georgetown’s Massive Data Institute to discuss how so many of us can be frustrated by the same problem but haven’t been able to really make any headway toward a solution. 

For as long as social services have existed, people have been trying to understand how to manage and evaluate those services. How do we determine what to scale and what to change? How do we replicate successes and how do we minimize unsuccessful interventions? To answer these questions we have tried to create, use, and share evidence about these programs to inform our decision-making. However – and this is a big however – despite our collective efforts, we have difficulty determining whether there’s been an increase in using evidence, or most importantly, whether there’s actually been an improvement in the quality and impact of social services and public benefit programs…(More)”.

What AI Can Do for Your Country

Curated on Posted on by Stefaan Verhulst

Article by Jylana L. Sheats: “..Although most discussions of artificial intelligence focus on its impacts on business and research, AI is also poised to transform government in the United States and beyond. AI-guided disaster response is just one piece of the picture. The U.S. Department of Health and Human Services has an experimental AI program to diagnose COVID-19 and flu cases by analyzing the sound of patients coughing into their smartphones. The Department of Justice uses AI algorithms to help prioritize which tips in the FBI’s Threat Intake Processing System to act on first. Other proposals, still at the concept stage, aim to extend the applications of AI to improve the efficiency and effectiveness of nearly every aspect of public services. 

The early applications illustrate the potential for AI to make government operations more effective and responsive. They illustrate the looming challenges, too. The federal government will have to recruit, train, and retain skilled workers capable of managing the new technology, competing with the private sector for top talent. The government also faces a daunting task ensuring the ethical and equitable use of AI. Relying on algorithms to direct disaster relief or to flag high-priority crimes raises immediate concerns: What if biases built into the AI overlook some of the groups that most need assistance, or unfairly target certain populations? As AI becomes embedded into more government operations, the opportunities for misuse and unintended consequences will only expand…(More)”.

Data’s Role in Unlocking Scientific Potential

Curated on Posted on by Stefaan Verhulst

Report by the Special Competitive Studies Project: “…we outline two actionable steps the U.S. government can take immediately to address the data sharing challenges hindering scientific research.

1. Create Comprehensive Data Inventories Across Scientific Domains

We recommend the Secretary of Commerce, acting through the Department of Commerce’s Chief Data Officer and the Director of the National Institute of Standards and Technology (NIST), and with the Federal Chief Data Officer Council (CDO Council) create a government-led inventory where organizations – universities, industries, and research institutes – can catalog their datasets with key details like purpose, description, and accreditation. Similar to platforms like data.gov, this centralized repository would make high-quality data more visible and accessible, promoting scientific collaboration. To boost participation, the government could offer incentives, such as grants or citation credits for researchers whose data is used. Contributing organizations would also be responsible for regularly updating their entries, ensuring the data stays relevant and searchable. 

2. Create Scientific Data Sharing Public-Private Partnerships

A critical recommendation of the National Data Action Plan was for the United States to facilitate the creation of data sharing public-private partnerships for specific sectors. The U.S. Government should coordinate data sharing partnerships with its departments and agencies, industry, academia, and civil society. Data collected by one entity can be tremendously valuable to others. But incentivizing data sharing is challenging as privacy, security, legal (e.g., liability), and intellectual property (IP) concerns can limit willingness to share. However, narrowly-scoped PPPs can help overcome these barriers, allowing for greater data sharing and mutually beneficial data use…(More)”

How Generative AI Content Could Influence the U.S. Election

Curated on Posted on by Stefaan Verhulst

Article by Valerie Wirtschafter: “…The contested nature of the presidential race means such efforts will undoubtedly continue, but they likely will remain discoverable, and their reach and ability to shape election outcomes will be minimal. Instead, the most meaningful uses of generative AI content could occur in highly targeted scenarios just prior to the election and/or in a contentious post-election environment where experience has demonstrated that potential “evidence” of malfeasance need not be true to mobilize a small subset of believers to act.

Because U.S. elections are managed at the state and county levels, low-level actors in some swing precincts or counties are catapulted to the national spotlight every four years. Since these actors are not well known to the public, targeted and personal AI-generated content can cause significant harm. Before the election, this type of fabricated content could take the form of a last-minute phone call by someone claiming to be election worker alerting voters to an issue at their polling place.

After the election, it could become harassment of election officials or “evidence” of foul play. Due to the localized and personalized nature of this type of effort, it could be less rapidly discoverable for unknown figures not regularly in the public eye, difficult to debunk or prevent with existing tools and guardrails, and damaging to reputations. This tailored approach need not be driven by domestic actors—in fact, in the lead up to the 2020 elections, Iranian actors pretended to be members of the Proud Boys and sent threatening emails to Democratic voters in select states demanding they vote for Donald Trump. Although election officials have worked tirelessly to brace for this possibility, they are correct to be on guard…(More)”

Buried Academic Treasures

Curated on Posted on by Stefaan Verhulst

Barrett and Greene: “…one of the presenters who said: “We have lots of research that leads to no results.”

As some of you know, we’ve written a book with Don Kettl to help academically trained researchers write in a way that would be understandable by decision makers who could make use of their findings. But the keys to writing well are only a small part of the picture. Elected and appointed officials have the capacity to ignore nearly anything, no matter how well written it is.

This is more than just a frustration to researchers, it’s a gigantic loss to the world of public administration. We spend lots of time reading through reports and frequently come across nuggets of insights that we believe could help make improvements in nearly every public sector endeavor from human resources to budgeting to performance management to procurement and on and on. We, and others, can do our best to get attention for this kind of information, but that doesn’t mean that the decision makers have the time or the inclination to take steps toward taking advantage of great ideas.

We don’t want to place the blame for the disconnect between academia and practitioners on either party. To one degree or the other they’re both at fault, with taxpayers and the people who rely on government services – and that’s pretty much everybody except for people who have gone off the grid – as the losers.

Following, from our experience, are six reasons we believe that it’s difficult to close the gap between the world of research and the realm of utility. The first three are aimed at government leaders, the last three have academics in mind…(More)”

First-of-its-kind dataset connects greenhouse gases and air quality

Curated on Posted on by Stefaan Verhulst

NOAA Research: “The GReenhouse gas And Air Pollutants Emissions System (GRA²PES), from NOAA and the National Institute of Standards and Technology (NIST), combines information on greenhouse gas and air quality pollutant sources into a single national database, offering innovative interactive map displays and new benefits for both climate and public health solutions.

A new U.S.-based system to combine air quality and greenhouse gas pollution sources into a single national research database is now available in the U.S. Greenhouse Gas Center portal. This geospatial data allows leaders at city, state, and regional scales to more easily identify and take steps to address air quality issues while reducing climate-related hazards for populations.

The dataset is the GReenhouse gas And Air Pollutants Emissions System (GRA²PES). A research project developed by NOAA and NIST, GRA²PES captures monthly greenhouse gas (GHG) emissions activity for multiple economic sectors to improve measurement and modeling for both GHG and air pollutants across the contiguous U.S.

Having the GHG and air quality constituents in the same dataset will be exceedingly helpful, said Columbia University atmospheric scientist Roisin Commane, the lead on a New York City project to improve emissions estimates…(More)”.

Science Diplomacy and the Rise of Technopoles

Curated on Posted on by Stefaan Verhulst

Article by Vaughan Turekian and Peter Gluckman: “…Science diplomacy has an important, even existential imperative to help the world reconsider the necessity of working together toward big global goals. Climate change may be the most obvious example of where global action is needed, but many other issues have similar characteristics—deep ocean resources, space, and other ungoverned areas, to name a few.

However, taking up this mantle requires acknowledging why past efforts have failed to meet their goals. The global commitment to Sustainable Development Goals (SDGs) is an example. Weaknesses in the UN system, compounded by varied commitments from member states, will prevent the achievement of the SDGs by 2030. This year’s UN Summit of the Future is intended to reboot the global commitment to the sustainability agenda. Regardless of what type of agreement is signed at the summit, its impact may be limited.  

Science diplomacy has an important, even existential imperative to help the world reconsider the necessity of working together toward big global goals.

The science community must play an active part in ensuring progress is in fact made, but that will require an expansion of the community’s current role. To understand what this might mean, consider that the Pact for the Future agreed in New York City in September 2024 places “science, technology, and innovation” as one of its five themes. But that becomes actionable either in the narrow sense that technology will provide “answers” to global problems or in the platitudinous sense that science provides advice that is not acted upon. This dichotomy of unacceptable approaches has long bedeviled science’s influence.

For the world to make better use of science, science must take on an expanded responsibility in solving problems at both global and local scales. And science itself must become part of a toolkit—both at the practical and the diplomatic level—to address the sorts of challenges the world will face in the future. To make this happen, more countries must make science diplomacy a core part of their agenda by embedding science advisors within foreign ministries, connecting diplomats to science communities.

As the pace of technological change generates both existential risk and economic, environmental, and social opportunities, science diplomacy has a vital task in balancing outcomes for the benefit of more people. It can also bring the science community (including the social sciences and humanities) to play a critical role alongside nation states. And, as new technological developments enable nonstate actors, and especially the private sector, science diplomacy has an important role to play in helping nation states develop policy that can identify common solutions and engage key partners…(More)”.

How The New York Times incorporates editorial judgment in algorithms to curate its home page

Curated on Posted on by Stefaan Verhulst

Article by Zhen Yang: “Whether on the web or the app, the home page of The New York Times is a crucial gateway, setting the stage for readers’ experiences and guiding them to the most important news of the day. The Times publishes over 250 stories daily, far more than the 50 to 60 stories that can be featured on the home page at a given time. Traditionally, editors have manually selected and programmed which stories appear, when and where, multiple times daily. This manual process presents challenges:

  • How can we provide readers a relevant, useful, and fresh experience each time they visit the home page?
  • How can we make our editorial curation process more efficient and scalable?
  • How do we maximize the reach of each story and expose more stories to our readers?

To address these challenges, the Times has been actively developing and testing editorially driven algorithms to assist in curating home page content. These algorithms are editorially driven in that a human editor’s judgment or input is incorporated into every aspect of the algorithm — including deciding where on the home page the stories are placed, informing the rankings, and potentially influencing and overriding algorithmic outputs when necessary. From the get-go, we’ve designed algorithmic programming to elevate human curation, not to replace it…

The Times began using algorithms for content recommendations in 2011 but only recently started applying them to home page modules. For years, we only had one algorithmically-powered module, “Smarter Living,” on the home page, and later, “Popular in The Times.” Both were positioned relatively low on the page.

Three years ago, the formation of a cross-functional team — including newsroom editors, product managers, data scientists, data analysts, and engineers — brought the momentum needed to advance our responsible use of algorithms. Today, nearly half of the home page is programmed with assistance from algorithms that help promote news, features, and sub-brand content, such as The Athletic and Wirecutter. Some of these modules, such as the features module located at the top right of the home page on the web version, are in highly visible locations. During major news moments, editors can also deploy algorithmic modules to display additional coverage to complement a main module of stories near the top of the page. (The topmost news package of Figure 1 is an example of this in action.)…(More)”

How is editorial judgment incorporated into algorithmic programming?