Scientists Scramble to Save Climate Data from Trump—Again

Curated on Posted on by Stefaan Verhulst

Article by Chelsea Harvey: “Eight years ago, as the Trump administration was getting ready to take office for the first time, mathematician John Baez was making his own preparations.

Together with a small group of friends and colleagues, he was arranging to download large quantities of public climate data from federal websites in order to safely store them away. Then-President-elect Donald Trump had repeatedly denied the basic science of climate change and had begun nominating climate skeptics for cabinet posts. Baez, a professor at the University of California, Riverside, was worried the information — everything from satellite data on global temperatures to ocean measurements of sea-level rise — might soon be destroyed.

His effort, known as the Azimuth Climate Data Backup Project, archived at least 30 terabytes of federal climate data by the end of 2017.

In the end, it was an overprecaution.

The first Trump administration altered or deleted numerous federal web pages containing public-facing climate information, according to monitoring efforts by the nonprofit Environmental Data and Governance Initiative (EDGI), which tracks changes on federal websites. But federal databases, containing vast stores of globally valuable climate information, remained largely intact through the end of Trump’s first term.

Yet as Trump prepares to take office again, scientists are growing more worried.

Federal datasets may be in bigger trouble this time than they were under the first Trump administration, they say. And they’re preparing to begin their archiving efforts anew.

“This time around we expect them to be much more strategic,” said Gretchen Gehrke, EDGI’s website monitoring program lead. “My guess is that they’ve learned their lessons.”

The Trump transition team didn’t respond to a request for comment.

Like Baez’s Azimuth project, EDGI was born in 2016 in response to Trump’s first election. They weren’t the only ones…(More)”.

Can AI review the scientific literature — and figure out what it all means?

Curated on Posted on by Stefaan Verhulst

Article by Helen Pearson: “When Sam Rodriques was a neurobiology graduate student, he was struck by a fundamental limitation of science. Even if researchers had already produced all the information needed to understand a human cell or a brain, “I’m not sure we would know it”, he says, “because no human has the ability to understand or read all the literature and get a comprehensive view.”

Five years later, Rodriques says he is closer to solving that problem using artificial intelligence (AI). In September, he and his team at the US start-up FutureHouse announced that an AI-based system they had built could, within minutes, produce syntheses of scientific knowledge that were more accurate than Wikipedia pages1. The team promptly generated Wikipedia-style entries on around 17,000 human genes, most of which previously lacked a detailed page.How AI-powered science search engines can speed up your research

Rodriques is not the only one turning to AI to help synthesize science. For decades, scholars have been trying to accelerate the onerous task of compiling bodies of research into reviews. “They’re too long, they’re incredibly intensive and they’re often out of date by the time they’re written,” says Iain Marshall, who studies research synthesis at King’s College London. The explosion of interest in large language models (LLMs), the generative-AI programs that underlie tools such as ChatGPT, is prompting fresh excitement about automating the task…(More)”.

Courts in Buenos Aires are using ChatGPT to draft rulings

Curated on Posted on by Stefaan Verhulst

Article by Victoria Mendizabal: “In May, the Public Prosecution Service of the City of Buenos Aires began using generative AI to predict rulings for some public employment cases related to salary demands.

Since then, justice employees at the office for contentious administrative and tax matters of the city of Buenos Aires have uploaded case documents into ChatGPT, which analyzes patterns, offers a preliminary classification from a catalog of templates, and drafts a decision. So far, ChatGPT has been used for 20 legal sentences.

The use of generative AI has cut down the time it takes to draft a sentence from an hour to about 10 minutes, according to recent studies conducted by the office.

“We, as professionals, are not the main characters anymore. We have become editors,” Juan Corvalán, deputy attorney general in contentious administrative and tax matters, told Rest of World.

The introduction of generative AI tools has improved efficiency at the office, but it has also prompted concerns within the judiciary and among independent legal experts about possiblebiases, the treatment of personal data, and the emergence of hallucinations. Similar concerns have echoed beyond Argentina’s borders.

“We, as professionals, are not the main characters anymore. We have become editors.”

“Any inconsistent use, such as sharing sensitive information, could have a considerable legal cost,” Lucas Barreiro, a lawyer specializing in personal data protection and a member of Privaia, a civil association dedicated to the defense of human rights in the digital era, told Rest of World.

Judges in the U.S. have voiced skepticism about the use of generative AI in the courts, with Manhattan Federal Judge Edgardo Ramos saying earlier this year that “ChatGPT has been shown to be an unreliable resource.” In Colombia and the Netherlands, the use of ChatGPT by judges was criticized by local experts. But not everyone is concerned: A court of appeals judge in the U.K. who used ChatGPT to write part of a judgment said that it was “jolly useful.”

For Corvalán, the move to generative AI is the culmination of a years-long transformation within the City of Buenos Aires’ attorney general’s office.In 2017, Corvalán put together a group of developers to train an AI-powered system called PROMETEA, which was intended to automate judicial tasks and expedite case proceedings. The team used more than 300,000 rulings and case files related to housing protection, public employment bonuses, enforcement of unpaid fines, and denial of cab licenses to individuals with criminal records…(More)”.

Using generative AI for crisis foresight

Curated on Posted on by Stefaan Verhulst

Article by Antonin Kenens and Josip Ivanovic: “What if the next time you discuss a complex future and its potential crises, it could be transformed from a typical meeting into an immersive experience? That’s exactly what we did at a recent strategy meeting of UNDP’s Crisis Bureau and Bureau for Policy and Programme Support.  

In an environment where workshops and meetings can often feel monotonous, we aimed to break the mold. By using AI-generated videos, we brought our discussion to life, reflecting the realities of developing nations and immersing participants in the critical issues affecting our region.  In today’s rapidly changing world, the ability to anticipate and prepare for potential crises is more crucial than ever. Crisis foresight involves identifying and analyzing possible future crises to develop strategies that can mitigate their impact. This proactive approach, highlighted multiple times in the pact for the future, is essential for effective governance and sustainable development in Europe and Central Asia and the rest of the world.

graphical user interface
Visualization of the consequences of pollution in Joraland.

Our idea behind creating AI-generated videos was to provide a vivid, immersive experience that would engage viewers and stimulate active participation by sharing their reflections on the challenges and opportunities in developing countries. We presented fictional yet relatable scenarios to gather the participants of the meeting around a common view and create a sense of urgency and importance around UNDP’s strategic priorities and initiatives. 

This approach not only captured attention but also sparked deeper engagement and thought-provoking conversations…(More)”.

What AI Can’t Do for Democracy

Curated on Posted on by Stefaan Verhulst

Essay by Daniel Berliner: “In short, there is increasing optimism among both theorists and practitioners over the potential for technology-enabled civic engagement to rejuvenate or deepen democracy. Is this optimism justified?

The answer depends on how we think about what civic engagement can do. Political representatives are often unresponsive to the preferences of ordinary people. Their misperceptions of public needs and preferences are partly to blame, but the sources of democratic dysfunction are much deeper and more structural than information alone. Working to ensure many more “citizens’ voices are truly heard” will thus do little to improve government responsiveness in contexts where the distribution of power means that policymakers have no incentive to do what citizens say. And as some critics have argued, it can even distract from recognizing and remedying other problems, creating a veneer of legitimacy—what health policy expert Sherry Arnstein once famously derided as mere “window dressing.”

Still, there are plenty of cases where contributions from citizens can highlight new problems that need addressing, new perspectives by which issues are understood, and new ideas for solving public problems—from administrative agencies seeking public input to city governments seeking to resolve resident complaints and citizens’ assemblies deliberating on climate policy. But even in these and other contexts, there is reason to doubt AI’s usefulness across the board. The possibilities of AI for civic engagement depend crucially on what exactly it is that policymakers want to learn from the public. For some types of learning, applications of AI can make major contributions to enhance the efficiency and efficacy of information processing. For others, there is no getting around the fundamental needs for human attention and context-specific knowledge in order to adequately make sense of public voices. We need to better understand these differences to avoid wasting resources on tools that might not deliver useful information…(More)”.

A Second Academic Exodus From X?

Curated on Posted on by Stefaan Verhulst

Article by Josh Moody: “Two years ago, after Elon Musk bought Twitter for $44 billion, promptly renaming it X, numerous academics decamped from the platform. Now, in the wake of a presidential election fraught with online disinformation, a second exodus from the social media site appears underway.

Academics, including some with hundreds of thousands of followers, announced departures from the platform in the immediate aftermath of the election, decrying the toxicity of the website and objections to Musk and how he wielded the platform to back President-elect Donald Trump. The business mogul threw millions of dollars behind Trump and personally campaigned for him this fall. Musk also personally advanced various debunked conspiracy theories during the election cycle.

Amid another wave of exits, some users see this as the end of Academic Twitter, which was already arguably in its death throes…

LeBlanc, Kamola and Rosen all mentioned that they were moving to the platform Bluesky, which has grown to 14.5 million users, welcoming more than 700,000 new accounts in recent days. In September, Bluesky had nine million users…

A study published in PS: Political Science & Politics last month concluded that academics began to engage less after Musk bought the platform. But the peak of disengagement wasn’t when the billionaire took over the site in October 2022 but rather the next month, when he reinstated Donald Trump’s account, which the platform’s previous owners deactivated following the Jan. 6, 2021, insurrection, which he encouraged.

The researchers reviewed 15,700 accounts from academics in economics, political science, sociology and psychology for their study.

James Bisbee, a political science professor at Vanderbilt University and article co-author, wrote via email that changes to the platform, particularly to the application programming interface, or API, undermined their ability to collect data for their research.

“Twitter used to be an amazing source of data for political scientists (and social scientists more broadly) thanks in part to its open data ethos,” Bisbee wrote. “Since Musk’s takeover, this is no longer the case, severely limiting the types of conclusions we could draw, and theories we could test, on this platform.”

To Bisbee, that loss is an understated issue: “Along with many other troubling developments on X since the change in ownership, the amputation of data access should not be ignored.”..(More)”

The Death of Search

Curated on Posted on by Stefaan Verhulst

Article by Matteo Wong: “For nearly two years, the world’s biggest tech companies have said that AI will transform the web, your life, and the world. But first, they are remaking the humble search engine.

Chatbots and search, in theory, are a perfect match. A standard Google search interprets a query and pulls up relevant results; tech companies have spent tens or hundreds of millions of dollars engineering chatbots that interpret human inputs, synthesize information, and provide fluent, useful responses. No more keyword refining or scouring Wikipedia—ChatGPT will do it all. Search is an appealing target, too: Shaping how people navigate the internet is tantamount to shaping the internet itself.

Months of prophesying about generative AI have now culminated, almost all at once, in what may be the clearest glimpse yet into the internet’s future. After a series of limited releases and product demos, mired with various setbacks and embarrassing errors, tech companies are debuting AI-powered search engines as fully realized, all-inclusive products. Last Monday, Google announced that it would launch its AI Overviews in more than 100 new countries; that feature will now reach more than 1 billion users a month. Days later, OpenAI announced a new search function in ChatGPT, available to paid users for now and soon opening to the public. The same afternoon, the AI-search start-up Perplexity shared instructions for making its “answer engine” the default search tool in your web browser.

For the past week, I have been using these products in a variety of ways: to research articles, follow the election, and run everyday search queries. In turn I have scried, as best I can, into the future of how billions of people will access, relate to, and synthesize information. What I’ve learned is that these products are at once unexpectedly convenient, frustrating, and weird. These tools’ current iterations surprised and, at times, impressed me, yet even when they work perfectly, I’m not convinced that AI search is a wise endeavor…(More)”.

Congress should designate an entity to oversee data security, GAO says

Curated on Posted on by Stefaan Verhulst

Article by Matt Bracken: “Federal agencies may need to rethink how they handle individuals’ personal data to protect their civil rights and civil liberties, a congressional watchdog said in a new report Tuesday.

Without federal guidance governing the protection of the public’s civil rights and liberties, agencies have pursued a patchwork system of policies tied to the collection, sharing and use of data, the Government Accountability Office said. 

To address that problem head-on, the GAO is recommending that Congress select “an appropriate federal entity” to produce guidance or regulations regarding data protection that would apply to all agencies, giving that entity “the explicit authority to make needed technical and policy choices or explicitly stating Congress’s own choices.”

That recommendation was formed after the GAO sent a questionnaire to all 24 Chief Financial Officers Act agencies asking for information about their use of emerging technologies and data capabilities and how they’re guaranteeing that personally identifiable information is safeguarded.

The GAO found that 16 of those CFO Act agencies have policies or procedures in place to protect civil rights and civil liberties with regard to data use, while the other eight have not taken steps to do the same.

The most commonly cited issues for agencies in their efforts to protect the civil rights and civil liberties of the public were “complexities in handling protections associated with new and emerging technologies” and “a lack of qualified staff possessing needed skills in civil rights, civil liberties, and emerging technologies.”

“Further, eight of the 24 agencies believed that additional government-wide law or guidance would strengthen consistency in addressing civil rights and civil liberties protections,” the GAO wrote. “One agency noted that such guidance could eliminate the hodge-podge approach to the governance of data and technology.”

All 24 CFO Act agencies have internal offices to “handle the protection of the public’s civil rights as identified in federal laws,” with much of that work centered on the handling of civil rights violations and related complaints. Four agencies — the departments of Defense, Homeland Security, Justice and Education — have offices to specifically manage civil liberty protections across their entire agencies. The other 20 agencies have mostly adopted a “decentralized approach to protecting civil liberties, including when collecting, sharing, and using data,” the GAO noted…(More)”.

Who Is Responsible for AI Copyright Infringement?

Curated on Posted on by Stefaan Verhulst

Article by Michael P. Goodyear: “Twenty-one-year-old college student Shane hopes to write a song for his boyfriend. In the past, Shane would have had to wait for inspiration to strike, but now he can use generative artificial intelligence to get a head start. Shane decides to use Anthropic’s AI chat system, Claude, to write the lyrics. Claude dutifully complies and creates the words to a love song. Shane, happy with the result, adds notes, rhythm, tempo, and dynamics. He sings the song and his boyfriend loves it. Shane even decides to post a recording to YouTube, where it garners 100,000 views.

But Shane did not realize that this song’s lyrics are similar to those of “Love Story,” Taylor Swift’s hit 2008 song. Shane must now contend with copyright law, which protects original creative expression such as music. Copyright grants the rights owner the exclusive rights to reproduce, perform, and create derivatives of the copyrighted work, among other things. If others take such actions without permission, they can be liable for damages up to $150,000. So Shane could be on the hook for tens of thousands of dollars for copying Swift’s song.

Copyright law has surged into the news in the past few years as one of the most important legal challenges for generative AI tools like Claude—not for the output of these tools but for how they are trained. Over two dozen pending court cases grapple with the question of whether training generative AI systems on copyrighted works without compensating or getting permission from the creators is lawful or not. Answers to this question will shape a burgeoning AI industry that is predicted to be worth $1.3 trillion by 2032.

Yet there is another important question that few have asked: Who should be liable when a generative AI system creates a copyright-infringing output? Should the user be on the hook?…(More)”

Social Innovation and the Journey to Transformation

Curated on Posted on by Stefaan Verhulst

Special series by Skoll for the Stanford Social Innovation Review: “…we explore system orchestration, collaborative funding, government partnerships, mission-aligned investing, reimagined storytelling, and evaluation and learning. These seven articles highlight successful approaches to collective action and share compelling examples of social transformation.

The time is now for philanthropy to align the speed and scale of our investments with the scope of the global challenges that social innovators seek to address. We hope this series will spark fresh thinking and new ideas for how we can create durable systemic change quickly and together…(More)”.