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)”.

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)”.

Google’s Expanded ‘Flood Hub’ Uses AI to Help Us Adapt to Extreme Weather

Curated on Posted on by Stefaan Verhulst

Article by Jeff Young: “Google announced Tuesday that a tool using artificial intelligence to better predict river floods will be expanded to the U.S. and Canada, covering more than 800 North American riverside communities that are home to more than 12 million people. Google calls it Flood Hub, and it’s the latest example of how AI is being used to help adapt to extreme weather events associated with climate change.

“We see tremendous opportunity for AI to solve some of the world’s biggest challenges, and climate change is very much one of those,” Google’s Chief Sustainability Officer, Kate Brandt, told Newsweek in an interview.

At an event in Brussels on Tuesday, Google announced a suite of new and expanded sustainability initiatives and products. Many of them involve the use of AI, such as tools to help city planners find the best places to plant trees and modify rooftops to buffer against city heat, and a partnership with the U.S. Forest Service to use AI to improve maps related to wildfires.

Google Flood Hub Model AI extreme weather
A diagram showing the development of models used in Google’s Flood Hub, now available for 800 riverside locations in the U.S. and Canada. Courtesy of Google Research…

Brandt said Flood Hub’s engineers use advanced AI, publicly available data sources and satellite imagery, combined with hydrologic models of river flows. The results allow flooding predictions with a longer lead time than was previously available in many instances…(More)”.

Generative AI, Jobs, and Policy Response

Curated on Posted on by Stefaan Verhulst

Paper by the Global Partnership on AI: “Generative AI and the Future of Work remains notably absent from the global AI governance dialogue. Given the transformative potential of this technology in the workplace, this oversight suggests a significant gap, especially considering the substantial implications this technology has for workers, economies and society at large. As interest grows in the effects of Generative AI on occupations, debates centre around roles being replaced or enhanced by technology. Yet there is an incognita, the “Big Unknown”, an important number of workers whose future depends on decisions yet to be made
In this brief, recent articles about the topic are surveyed with special attention to the “Big Unknown”. It is not a marginal number: nearly 9% of the workforce, or 281 million workers worldwide, are in this category. Unlike previous AI developments which focused on automating narrow tasks, Generative AI models possess the scope, versatility, and economic viability to impact jobs across multiple industries and at varying skill levels. Their ability to produce human-like outputs in areas like language, content creation and customer interaction, combined with rapid advancement and low deployment costs, suggest potential near-term impacts that are much broader and more abrupt than prior waves of AI. Governments, companies, and social partners should aim to minimize any potential negative effects from Generative AI technology in the world of work, as well as harness potential opportunities to support productivity growth and decent work. This brief presents concrete policy recommendations at the global and local level. These insights, are aimed to guide the discourse towards a balanced and fair integration of Generative AI in our professional landscape To navigate this uncertain landscape and ensure that the benefits of Generative AI are equitably distributed, we recommend 10 policy actions that could serve as a starting point for discussion and implementation…(More)”.

AI chatbots do work of civil servants in productivity trial

Curated on Posted on by Stefaan Verhulst

Article by Paul Seddon: “Documents disclosed to the BBC have shed light on the use of AI-powered chatbot technology within government.

The chatbots have been used to analyse lengthy reports – a job that would normally be done by humans.

The Department for Education, which ran the trial, hopes it could boost productivity across Whitehall.

The PCS civil service union says it does not object to the use of AI – but clear guidelines are needed “so the benefits are shared by workers”.

The latest generation of chatbots, powered by artificial intelligence (AI), can quickly analyse reams of information, including images, to answer questions and summarise long articles.

They are expected to upend working practices across the economy in the coming years, and the government says they will have “significant implications” for the way officials work in future.

The education department ran the eight-week study over the summer under a contract with London-based company Faculty.ai, to test how so-called large language models (LLMs) could be used by officials.

The firm’s researchers used its access to a premium version of ChatGPT, the popular chatbot developed by OpenAI, to analyse draft local skills training plans that had been sent to the department to review.

These plans, drawn up by bodies representing local employers, are meant to influence the training offered by local further education colleges.

Results from the pilot are yet to be published, but documents and emails requested by the BBC under Freedom of Information laws offer an insight into the project’s aims.

According to an internal document setting out the reasons for the study, a chatbot would be used to summarise and compare the “main insights and themes” from the training plans.

The results, which were to be compared with summaries produced by civil servants, would test how Civil Service “productivity” might be improved.

It added that language models could analyse long, unstructured documents “where previously the only other option for be for individuals to read through all the reports”.

But the project’s aims went further, with hopes the chatbot could help provide “useful insights” that could help the department’s skills unit “identify future skills needs across the country”…(More)”.