Evidence-Based Government Is Alive and Well

Curated on Posted on by Stefaan Verhulst

Article by Zina Hutton: “A desire to discipline the whimsical rule of despots.” That’s what Gary Banks, a former chairman of Australia’s Productivity Commission, attributed the birth of evidence-based policy to back in the 14th century in a speech from 2009. Evidence-based policymaking isn’t a new style of government, but it’s one with well-known roadblocks that elected officials have been working around in order to implement it more widely.

Evidence-based policymaking relies on evidence — facts, data, expert analysis — to shape aspects of long- and short-term policy decisions. It’s not just about collecting data, but also applying it and experts’ analysis to shape future policy. Whether it’s using school enrollment numbers to justify building a new park in a neighborhood or scientists collaborating on analysis of wastewater to try to “catch” illness spread in a community before it becomes unmanageable, evidence-based policy uses facts to help elected and appointed officials decide what funds and other resources to allocate in their communities.

Problems with evidence-based governing have been around for years. They range from a lack of communication between the people designing the policy and its related programs and the people implementing them, to the way that local government struggles to recruit and maintain employees. Resource allocation also shapes the decisions some cities make when it comes to seeking out and using data. This can be seen in the way larger cities, with access to proportionately larger budgets, research from state universities within city limits and a larger workforce, have had more success with evidence-based policymaking.
“The largest cities have more personnel, more expertise, more capacity, whether that’s for collecting administrative data and monitoring it, whether that’s doing open data portals, or dashboards, or whether that’s doing things like policy analysis or program evaluation,” says Karen Mossberger, the Frank and June Sackton Professor in the School of Public Affairs at Arizona State University. “It takes expert personnel, it takes people within government with the skills and the capacity, it takes time.”

Roadblocks aside, state and local governments are finding innovative ways to collaborate with one another on data-focused projects and policy, seeking ways to make up for the problems that impacted early efforts at evidence-based governance. More state and local governments now recruit data experts at every level to collect, analyze and explain the data generated by residents, aided by advances in technology and increased access to researchers…(More)”.

Who owns data about you?

Curated on Posted on by Stefaan Verhulst

Article by Wendy Wong: “The ascendancy of artificial intelligence hinges on vast data accrued from our daily activities. In turn, data train advanced algorithms, fuelled by massive amounts of computing power. Together, they form the critical trio driving AI’s capabilities. Because of its human sources, data raise an important question: who owns data, and how do the data add up when they’re about our mundane, routine choices?

It often helps to think through modern problems with historical anecdotes. The case of Henrietta Lacks, a Black woman living in Baltimore stricken with cervical cancer, and her everlasting cells, has become well-known because of Rebecca Skloot’s book, The Immortal Life of Henrietta Lacks,and a movie starring Oprah Winfrey. Unbeknownst to her, Lacks’s medical team removed her cancer cells and sent them to a lab to see if they would grow. While Lacks died of cancer in 1951, her cells didn’t. They kept going, in petri dishes in labs, all the way through to the present day.

The unprecedented persistence of Lacks’s cells led to the creation of the HeLa cell line. Her cells underpin various medical technologies, from in-vitro fertilization to polio and COVID-19 vaccines, generating immense wealth for pharmaceutical companies. HeLa is a co-creation. Without Lacks or scientific motivation, there would be no HeLa.

The case raises questions about consent and ownership. That her descendants recently settled a lawsuit against Thermo Fisher Scientific, a pharmaceutical company that monetized products made from HeLa cells, echoes the continuing discourse surrounding data ownership and rights. Until the settlement, just one co-creator was reaping all the financial benefits of that creation.

The Lacks family’s legal battle centred on a human-rights claim. Their situation was rooted in the impact of Lacks’s cells on medical science and the intertwined racial inequalities that lead to disparate medical outcomes. Since Lacks’s death, the family had struggled while biotech companies profited.

These “tissue issues” often don’t favour the individuals providing the cells or body parts. The U.S. Supreme Court case Moore v. Regents of the University of California deemed body parts as “garbage” once separated from the individual. The ruling highlights a harsh legal reality: Individuals don’t necessarily retain rights of parts of their body, financial or otherwise. Another federal case, Washington University v. Catalona, invalidated ownership claims based upon the “feeling” it belongs to the person it came from.

We can liken this characterization of body parts to how we often think about data taken from people. When we call data “detritus” or “exhaust,” we dehumanize the thoughts, behaviours and choices that generate those data. Do we really want to say that data, once created, is a resource for others’ exploitation?…(More)”.

When is a Decision Automated? A Taxonomy for a Fundamental Rights Analysis

Curated on Posted on by Stefaan Verhulst

Paper by Francesca Palmiotto: “This paper addresses the pressing issues surrounding the use of automated systems in public decision-making, with a specific focus on the field of migration, asylum, and mobility. Drawing on empirical research conducted for the AFAR project, the paper examines the potential and limitations of the General Data Protection Regulation and the proposed Artificial Intelligence Act in effectively addressing the challenges posed by automated decision making (ADM). The paper argues that the current legal definitions and categorizations of ADM fail to capture the complexity and diversity of real-life applications, where automated systems assist human decision-makers rather than replace them entirely. This discrepancy between the legal framework and practical implementation highlights the need for a fundamental rights approach to legal protection in the automation age. To bridge the gap between ADM in law and practice, the paper proposes a taxonomy that provides theoretical clarity and enables a comprehensive understanding of ADM in public decision-making. This taxonomy not only enhances our understanding of ADM but also identifies the fundamental rights at stake for individuals and the sector-specific legislation applicable to ADM. The paper finally calls for empirical observations and input from experts in other areas of public law to enrich and refine the proposed taxonomy, thus ensuring clearer conceptual frameworks to safeguard individuals in our increasingly algorithmic society…(More)”.

NYC Releases Plan to Embrace AI, and Regulate It

Curated on Posted on by Stefaan Verhulst

Article by Sarah Holder: “New York City Mayor Eric Adams unveiled a plan for adopting and regulating artificial intelligence on Monday, highlighting the technology’s potential to “improve services and processes across our government” while acknowledging the risks.

The city also announced it is piloting an AI chatbot to answer questions about opening or operating a business through its website MyCity Business.

NYC agencies have reported using more than 30 tools that fit the city’s definition of algorithmic technology, including to match students with public schools, to track foodborne illness outbreaks and to analyze crime patterns. As the technology gets more advanced, and the implications of algorithmic bias, misinformation and privacy concerns become more apparent, the city plans to set policy around new and existing applications…

New York’s strategy, developed by the Office of Technology and Innovation with the input of city agency representatives and outside technology policy experts, doesn’t itself establish any rules and regulations around AI, but lays out a timeline and blueprint for creating them. It emphasizes the need for education and buy-in both from New York constituents and city employees. Within the next year, the city plans to start to hold listening sessions with the public, and brief city agencies on how and why to use AI in their daily operations. The city has also given itself a year to start work on piloting new AI tools, and two to create standards for AI contracts….

Stefaan Verhulst, a research professor at New York University and the co-founder of The GovLab, says that especially during a budget crunch, leaning on AI offers cities opportunities to make evidence-based decisions quickly and with fewer resources. Among the potential use cases he cited are identifying areas most in need of affordable housing, and responding to public health emergencies with data…(More) (Full plan)”.

How a billionaire-backed network of AI advisers took over Washington

Curated on Posted on by Stefaan Verhulst

Article by Brendan Bordelon: “An organization backed by Silicon Valley billionaires and tied to leading artificial intelligence firms is funding the salaries of more than a dozen AI fellows in key congressional offices, across federal agencies and at influential think tanks.

The fellows funded by Open Philanthropy, which is financed primarily by billionaire Facebook co-founder and Asana CEO Dustin Moskovitz and his wife Cari Tuna, are already involved in negotiations that will shape Capitol Hill’s accelerating plans to regulate AI. And they’re closely tied to a powerful influence network that’s pushing Washington to focus on the technology’s long-term risks — a focus critics fear will divert Congress from more immediate rules that would tie the hands of tech firms.

Acting through the little-known Horizon Institute for Public Service, a nonprofit that Open Philanthropy effectively created in 2022, the group is funding the salaries of tech fellows in key Senate offices, according to documents and interviews…Current and former Horizon AI fellows with salaries funded by Open Philanthropy are now working at the Department of Defense, the Department of Homeland Security and the State Department, as well as in the House Science Committee and Senate Commerce Committee, two crucial bodies in the development of AI rules. They also populate key think tanks shaping AI policy, including the RAND Corporation and Georgetown University’s Center for Security and Emerging Technology, according to the Horizon web site…

In the high-stakes Washington debate over AI rules, Open Philanthropy has long been focused on one slice of the problem — the long-term threats that future AI systems might pose to human survival. Many AI thinkers see those as science-fiction concerns far removed from the current AI harms that Washington should address. And they worry that Open Philanthropy, in concert with its web of affiliated organizations and experts, is shifting the policy conversation away from more pressing issues — including topics some leading AI firms might prefer to keep off the policy agenda…(More)”.

Gender Reboot: Reprogramming Gender Rights in the Age of AI

Curated on Posted on by Stefaan Verhulst

Book by Eleonore Fournier-Tombs: “This book explores gender norms and women’s rights in the age of AI. The author examines how gender dynamics have evolved in the spheres of work, self-image and safety, and education, and how these might be reflected in current challenges in AI development. The book also explores opportunities in AI to address issues facing women, and how we might harness current technological developments for gender equality. Taking a narrative tone, the book is interwoven with stories and a reflection on the raising young children during the COVID-19 pandemic. It includes both expert and personal interviews to create a nuanced and multidimensional perspective on the state of women’s rights and what might be done to move forward…(More)”.

The Good and Bad of Anticipating Migration

Curated on Posted on by Stefaan Verhulst

Article by Sara Marcucci, Stefaan Verhulst, María Esther Cervantes, Elena Wüllhorst: “This blog is the first in a series that will be published weekly, dedicated to exploring innovative anticipatory methods for migration policy. Over the coming weeks, we will delve into various aspects of these methods, delving into their value, challenges, taxonomy, and practical applications. 

This first blog serves as an exploration of the value proposition and challenges inherent in innovative anticipatory methods for migration policy. We delve into the various reasons why these methods hold promise for informing more resilient, and proactive migration policies. These reasons include evidence-based policy development, enabling policymakers to ground their decisions in empirical evidence and future projections. Decision-takers, users, and practitioners can benefit from anticipatory methods for policy evaluation and adaptation, resource allocation, the identification of root causes, and the facilitation of humanitarian aid through early warning systems. However, it’s vital to acknowledge the challenges associated with the adoption and implementation of these methods, ranging from conceptual concerns such as fossilization, unfalsifiability, and the legitimacy of preemptive intervention, to practical issues like interdisciplinary collaboration, data availability and quality, capacity building, and stakeholder engagement. As we navigate through these complexities, we aim to shed light on the potential and limitations of anticipatory methods in the context of migration policy, setting the stage for deeper explorations in the coming blogs of this series…(More)”.

Towards a Considered Use of AI Technologies in Government 

Curated on Posted on by Stefaan Verhulst

Report by the Institute on Governance and Think Digital: “… undertook a case study-based research project, where 24 examples of AI technology projects and governance frameworks across a dozen jurisdictions were scanned. The purpose of this report is to provide policymakers and practitioners in government with an overview of controversial deployments of Artificial Intelligence (AI) technologies in the public sector, and to highlight some of the approaches being taken to govern the responsible use of these technologies in government. 

Two environmental scans make up the majority of the report. The first scan presents relevant use cases of public sector applications of AI technologies and automation, with special attention given to controversial projects and program/policy failures. The second scan surveys existing governance frameworks employed by international organizations and governments around the world. Each scan is then analyzed to determine common themes across use cases and governance frameworks respectively. The final section of the report provides risk considerations related to the use of AI by public sector institutions across use cases…(More)”.

How ChatGPT and other AI tools could disrupt scientific publishing

Curated on Posted on by Stefaan Verhulst

Article by Gemma Conroy: “When radiologist Domenico Mastrodicasa finds himself stuck while writing a research paper, he turns to ChatGPT, the chatbot that produces fluent responses to almost any query in seconds. “I use it as a sounding board,” says Mastrodicasa, who is based at the University of Washington School of Medicine in Seattle. “I can produce a publication-ready manuscript much faster.”

Mastrodicasa is one of many researchers experimenting with generative artificial-intelligence (AI) tools to write text or code. He pays for ChatGPT Plus, the subscription version of the bot based on the large language model (LLM) GPT-4, and uses it a few times a week. He finds it particularly useful for suggesting clearer ways to convey his ideas. Although a Nature survey suggests that scientists who use LLMs regularly are still in the minority, many expect that generative AI tools will become regular assistants for writing manuscripts, peer-review reports and grant applications.

Those are just some of the ways in which AI could transform scientific communication and publishing. Science publishers are already experimenting with generative AI in scientific search tools and for editing and quickly summarizing papers. Many researchers think that non-native English speakers could benefit most from these tools. Some see generative AI as a way for scientists to rethink how they interrogate and summarize experimental results altogether — they could use LLMs to do much of this work, meaning less time writing papers and more time doing experiments…(More)”.

The growing energy footprint of artificial intelligence

Curated on Posted on by Stefaan Verhulst

Paper by Alex de Vries: “Throughout 2022 and 2023, artificial intelligence (AI) has witnessed a period of rapid expansion and extensive, large-scale application. Prominent tech companies such as Alphabet and Microsoft significantly increased their support for AI in 2023, influenced by the successful launch of OpenAI’s ChatGPT, a conversational generative AI chatbot that reached 100 million users in an unprecedented 2 months. In response, Microsoft and Alphabet introduced their own chatbots, Bing Chat and Bard, respectively.

 This accelerated development raises concerns about the electricity consumption and potential environmental impact of AI and data centers. In recent years, data center electricity consumption has accounted for a relatively stable 1% of global electricity use, excluding cryptocurrency mining. Between 2010 and 2018, global data center electricity consumption may have increased by only 6%.

 There is increasing apprehension that the computational resources necessary to develop and maintain AI models and applications could cause a surge in data centers’ contribution to global electricity consumption.

This commentary explores initial research on AI electricity consumption and assesses the potential implications of widespread AI technology adoption on global data center electricity use. The piece discusses both pessimistic and optimistic scenarios and concludes with a cautionary note against embracing either extreme…(More)”.