Paper by Simon Chesterman: “The past decade has seen a proliferation of guides, frameworks, and principles put forward by states, industry, inter- and non-governmental organizations to address matters of AI ethics. These diverse efforts have led to a broad consensus on what norms might govern AI. Far less energy has gone into determining how these might be implemented — or if they are even necessary. This chapter focuses on the intersection of ethics and law, in particular discussing why regulation is necessary, when regulatory changes should be made, and how it might work in practice. Two specific areas for law reform address the weaponization and victimization of AI. Regulations aimed at general AI are particularly difficult in that they confront many ‘unknown unknowns’, but the threat of uncontrollable or uncontainable AI became more widely discussed with the spread of large language models such as ChatGPT in 2023. Additionally, however, there will be a need to prohibit some conduct in which increasingly lifelike machines are the victims — comparable, perhaps, to animal cruelty laws…(More)”
Detecting Human Rights Violations on Social Media during Russia-Ukraine War
Paper by Poli Nemkova, et al: “The present-day Russia-Ukraine military conflict has exposed the pivotal role of social media in enabling the transparent and unbridled sharing of information directly from the frontlines. In conflict zones where freedom of expression is constrained and information warfare is pervasive, social media has emerged as an indispensable lifeline. Anonymous social media platforms, as publicly available sources for disseminating war-related information, have the potential to serve as effective instruments for monitoring and documenting Human Rights Violations (HRV). Our research focuses on the analysis of data from Telegram, the leading social media platform for reading independent news in post-Soviet regions. We gathered a dataset of posts sampled from 95 public Telegram channels that cover politics and war news, which we have utilized to identify potential occurrences of HRV. Employing a mBERT-based text classifier, we have conducted an analysis to detect any mentions of HRV in the Telegram data. Our final approach yielded an F2 score of 0.71 for HRV detection, representing an improvement of 0.38 over the multilingual BERT base model. We release two datasets that contains Telegram posts: (1) large corpus with over 2.3 millions posts and (2) annotated at the sentence-level dataset to indicate HRVs. The Telegram posts are in the context of the Russia-Ukraine war. We posit that our findings hold significant implications for NGOs, governments, and researchers by providing a means to detect and document possible human rights violations…(More)” See also Data for Peace and Humanitarian Response? The Case of the Ukraine-Russia War
“My sex-related data is more sensitive than my financial data and I want the same level of security and privacy”: User Risk Perceptions and Protective Actions in Female-oriented Technologies
Paper by Maryam Mehrnezhad, and Teresa Almeida: “The digitalization of the reproductive body has engaged myriads of cutting-edge technologies in supporting people to know and tackle their intimate health. Generally understood as female technologies (aka female-oriented technologies or ‘FemTech’), these products and systems collect a wide range of intimate data which are processed, transferred, saved and shared with other parties. In this paper, we explore how the “data-hungry” nature of this industry and the lack of proper safeguarding mechanisms, standards, and regulations for vulnerable data can lead to complex harms or faint agentic potential. We adopted mixed methods in exploring users’ understanding of the security and privacy (SP) of these technologies. Our findings show that while users can speculate the range of harms and risks associated with these technologies, they are not equipped and provided with the technological skills to protect themselves against such risks. We discuss a number of approaches, including participatory threat modelling and SP by design, in the context of this work and conclude that such approaches are critical to protect users in these sensitive systems…(More)”.
Atlas of the Senseable City
Book by Antoine Picon and Carlo Ratti: “What have smart technologies taught us about cities? What lessons can we learn from today’s urbanites to make better places to live? Antoine Picon and Carlo Ratti argue that the answers are in the maps we make. For centuries, we have relied on maps to navigate the enormity of the city. Now, as the physical world combines with the digital world, we need a new generation of maps to navigate the city of tomorrow. Pervasive sensors allow anyone to visualize cities in entirely new ways—ebbs and flows of pollution, traffic, and internet connectivity.
This book explores how the growth of digital mapping, spurred by sensing technologies, is affecting cities and daily lives. It examines how new cartographic possibilities aid urban planners, technicians, politicians, and administrators; how digitally mapped cities could reveal ways to make cities smarter and more efficient; how monitoring urbanites has political and social repercussions; and how the proliferation of open-source maps and collaborative platforms can aid activists and vulnerable populations. With its beautiful, accessible presentation of cutting-edge research, this book makes it easy for readers to understand the stakes of the new information age—and appreciate the timeless power of the city…(More)”
Opportunities and Challenges in Reusing Public Genomics Data
Introduction to Special Issue by Mahmoud Ahmed and Deok Ryong Kim: “Genomics data is accumulating in public repositories at an ever-increasing rate. Large consortia and individual labs continue to probe animal and plant tissue and cell cultures, generating vast amounts of data using established and novel technologies. The human genome project kickstarted the era of systems biology (1, 2). Ambitious projects followed to characterize non-coding regions, variations across species, and between populations (3, 4, 5). The cost reduction allowed individual labs to generate numerous smaller high-throughput datasets (6, 7, 8, 9). As a result, the scientific community should consider strategies to overcome the challenges and maximize the opportunities to use these resources for research and the public good. In this collection, we will elicit opinions and perspectives from researchers in the field on the opportunities and challenges of reusing public genomics data. The articles in this research topic converge on the need for data sharing while acknowledging the challenges that come with it. Two articles defined and highlighted the distinction between data and metadata. The characteristic of each should be considered when designing optimal sharing strategies. One article focuses on the specific issues surrounding the sharing of genomics interval data, and another on balancing the need for protecting pediatric rights and the sharing benefits.
The definition of what counts as data is itself a moving target. As technology advances, data can be produced in more ways and from novel sources. Events of recent years have highlighted this fact. “The pandemic has underscored the urgent need to recognize health data as a global public good with mechanisms to facilitate rapid data sharing and governance,” Schwalbe and colleagues (2020). The challenges facing these mechanisms could be technical, economic, legal, or political. Defining what data is and its type, therefore, is necessary to overcome these barriers because “the mechanisms to facilitate data sharing are often specific to data types.” Unlike genomics data, which has established platforms, sharing clinical data “remains in a nascent phase.” The article by Patrinos and colleagues (2022) considers the strong ethical imperative for protecting pediatric data while acknowledging the need not to overprotections. The authors discuss a model of consent for pediatric research that can balance the need to protect participants and generate health benefits.
Xue et al. (2023) focus on reusing genomic interval data. Identifying and retrieving the relevant data can be difficult, given the state of the repositories and the size of these data. Similarly, integrating interval data in reference genomes can be hard. The author calls for standardized formats for the data and the metadata to facilitate reuse.
Sheffield and colleagues (2023) highlight the distinction between data and metadata. Metadata describes the characteristics of the sample, experiment, and analysis. The nature of this information differs from that of the primary data in size, source, and ways of use. Therefore, an optimal strategy should consider these specific attributes for sharing metadata. Challenges specifics to sharing metadata include the need for standardized terms and formats, making it portable and easier to find.
We go beyond the reuse issue to highlight two other aspects that might increase the utility of available public data in Ahmed et al. (2023). These are curation and integration…(More)”.
The Power and Perils of the “Artificial Hand”: Considering AI Through the Ideas of Adam Smith
Speech by Gita Gopinath: “…Nowadays, it’s almost impossible to talk about economics without invoking Adam Smith. We take for granted many of his concepts, such as the division of labor and the invisible hand. Yet, at the time when he was writing, these ideas went against the grain. He wasn’t afraid to push boundaries and question established thinking.
Smith grappled with how to advance well-being and prosperity at a time of great change. The Industrial Revolution was ushering in new technologies that would revolutionize the nature of work, create winners and losers, and potentially transform society. But their impact wasn’t yet clear. The Wealth of Nations, for example, was published the same year James Watt unveiled his steam engine.
Today, we find ourselves at a similar inflection point, where a new technology, generative artificial intelligence, could change our lives in spectacular—and possibly existential—ways. It could even redefine what it means to be human.
Given the parallels between Adam Smith’s time and ours, I’d like to propose a thought experiment: If he were alive today, how would Adam Smith have responded to the emergence of this new “artificial hand”?…(More)”.
The Datapreneurs
Book by Bob Muglia: “Advances in information technology tend to come at a rapid pace. The computer revolution is barely 80 years old, yet we now have computers in our smartphones that are many times more powerful than machines that once filled rooms. Now, in early 2023, the changes are coming so fast that it is literally dizzying. It seems like nearly every day there is an article about some new Artificial Intelligence (AI) capability—be it ChatGPT, Dall-e 2, or Stable Diffusion. It appears that humanity is on the cusp of creating super-intelligent machines that are smarter than all of us combined.
This did not really happen overnight. Bob Muglia, a long-time Microsoft executive, former CEO of Snowflake, and currently a tech investor, explains what brought us to this moment in his new book, The Datapreneurs: The Inventors and Innovations that Enable the AI Future. Muglia takes the reader on a journey from the early days of computing and describes how a succession of data management and analytics technologies have helped build today’s economy and society. Muglia tells his story in part by describing some of the inventors he has known, including famous ones like Bill Gates and Sam Altman, the CEO of OpenAI, the creator of ChatGPT, and others that are not household names—yet, anyway—but could help change the world.
Muglia calls this journey through time and technology “The Arc of Data Innovation.” Each advance on the arc, which he lays out in graphic form in the book, represents one of the key data innovations that have led us to today, where we seem to be on the verge of achieving artificial general intelligence (AGI), producing machines that will be as intelligent as people. He expects this monumental shift to come within the next ten years. Further on, futurists are predicting mass deployment of machines possessing AGI throughout society, when we will be able to harness universal computer intelligence, accelerate innovation, and rapidly address many of today’s seemingly intractable challenges. Muglia believes that the combination of human and machine intelligence could create an era of progress and prosperity where all the people on Earth can have what they need and want without destroying our natural environment…(More)”.
There’s a model for governing AI. Here it is.
Article by Jacinda Ardern: “…On March 15, 2019, a terrorist took the lives of 51 members of New Zealand’s Muslim community in Christchurch. The attacker livestreamed his actions for 17 minutes, and the images found their way onto social media feeds all around the planet. Facebook alone blocked or removed 1.5 million copies of the video in the first 24 hours; in that timeframe, YouTube measured one upload per second.
Afterward, New Zealand was faced with a choice: accept that such exploitation of technology was inevitable or resolve to stop it. We chose to take a stand.
We had to move quickly. The world was watching our response and that of social media platforms. Would we regulate in haste? Would the platforms recognize their responsibility to prevent this from happening again?
New Zealand wasn’t the only nation grappling with the connection between violent extremism and technology. We wanted to create a coalition and knew that France had started to work in this space — so I reached out, leader to leader. In my first conversation with President Emmanuel Macron, he agreed there was work to do and said he was keen to join us in crafting a call to action.
We asked industry, civil society and other governments to join us at the table to agree on a set of actions we could all commit to. We could not use existing structures and bureaucracies because they weren’t equipped to deal with this problem.
Within two months of the attack, we launched the Christchurch Call to Action, and today it has more than 120 members, including governments, online service providers and civil society organizations — united by our shared objective to eliminate terrorist and other violent extremist content online and uphold the principle of a free, open and secure internet.
The Christchurch Call is a large-scale collaboration, vastly different from most top-down approaches. Leaders meet annually to confirm priorities and identify areas of focus, allowing the project to act dynamically. And the Call Secretariat — made up of officials from France and New Zealand — convenes working groups and undertakes diplomatic efforts throughout the year. All members are invited to bring their expertise to solve urgent online problems.
While this multi-stakeholder approach isn’t always easy, it has created change. We have bolstered the power of governments and communities to respond to attacks like the one New Zealand experienced. We have created new crisis-response protocols — which enabled companies to stop the 2022 Buffalo attack livestream within two minutes and quickly remove footage from many platforms. Companies and countries have enacted new trust and safety measures to prevent livestreaming of terrorist and other violent extremist content. And we have strengthened the industry-founded Global Internet Forum to Counter Terrorism with dedicated funding, staff and a multi-stakeholder mission.
We’re also taking on some of the more intransigent problems. The Christchurch Call Initiative on Algorithmic Outcomes, a partnership with companies and researchers, was intended to provide better access to the kind of data needed to design online safety measures to prevent radicalization to violence. In practice, it has much wider ramifications, enabling us to reveal more about the ways in which AI and humans interact.
From its start, the Christchurch Call anticipated the emerging challenges of AI and carved out space to address emerging technologies that threaten to foment violent extremism online. The Christchurch Call is actively tackling these AI issues.
Perhaps the most useful thing the Christchurch Call can add to the AI governance debate is the model itself. It is possible to bring companies, government officials, academics and civil society together not only to build consensus but also to make progress. It’s possible to create tools that address the here and now and also position ourselves to face an unknown future. We need this to deal with AI…(More)”.
The Prediction Society: Algorithms and the Problems of Forecasting the Future
Paper by Hideyuki Matsumi and Daniel J. Solove: “Predictions about the future have been made since the earliest days of humankind, but today, we are living in a brave new world of prediction. Today’s predictions are produced by machine learning algorithms that analyze massive quantities of personal data. Increasingly, important decisions about people are being made based on these predictions.
Algorithmic predictions are a type of inference. Many laws struggle to account for inferences, and even when they do, the laws lump all inferences together. But as we argue in this Article, predictions are different from other inferences. Predictions raise several unique problems that current law is ill-suited to address. First, algorithmic predictions create a fossilization problem because they reinforce patterns in past data and can further solidify bias and inequality from the past. Second, algorithmic predictions often raise an unfalsiability problem. Predictions involve an assertion about future events. Until these events happen, predictions remain unverifiable, resulting in an inability for individuals to challenge them as false. Third, algorithmic predictions can involve a preemptive intervention problem, where decisions or interventions render it impossible to determine whether the predictions would have come true. Fourth, algorithmic predictions can lead to a self-fulfilling prophecy problem where they actively shape the future they aim to forecast.
More broadly, the rise of algorithmic predictions raises an overarching concern: Algorithmic predictions not only forecast the future but also have the power to create and control it. The increasing pervasiveness of decisions based on algorithmic predictions is leading to a prediction society where individuals’ ability to author their own future is diminished while the organizations developing and using predictive systems are gaining greater power to shape the future…(More)”
How Indigenous Groups Are Leading the Way on Data Privacy
Article by Rina Diane Caballar: “Even as Indigenous communities find increasingly helpful uses for digital technology, many worry that outside interests could take over their data and profit from it, much like colonial powers plundered their physical homelands. But now some Indigenous groups are reclaiming control by developing their own data protection technologies—work that demonstrates how ordinary people have the power to sidestep the tech companies and data brokers who hold and sell the most intimate details of their identities, lives and cultures.
When governments, academic institutions or other external organizations gather information from Indigenous communities, they can withhold access to it or use it for other purposes without the consent of these communities.
“The threats of data colonialism are real,” says Tahu Kukutai, a professor at New Zealand’s University of Waikato and a founding member of Te Mana Raraunga, the Māori Data Sovereignty Network. “They’re a continuation of old processes of extraction and exploitation of our land—the same is being done to our information.”
To shore up their defenses, some Indigenous groups are developing new privacy-first storage systems that give users control and agency over all aspects of this information: what is collected and by whom, where it’s stored, how it’s used and, crucially, who has access to it.
Storing data in a user’s device—rather than in the cloud or in centralized servers controlled by a tech company—is an essential privacy feature of these technologies. Rudo Kemper is founder of Terrastories, a free and open-source app co-created with Indigenous communities to map their land and share stories about it. He recalls a community in Guyana that was emphatic about having an offline, on-premise installation of the Terrastories app. To members of this group, the issue was more than just the lack of Internet access in the remote region where they live. “To them, the idea of data existing in the cloud is almost like the knowledge is leaving the territory because it’s not physically present,” Kemper says.
Likewise, creators of Our Data Indigenous, a digital survey app designed by academic researchers in collaboration with First Nations communities across Canada, chose to store their database in local servers in the country rather than in the cloud. (Canada has strict regulations on disclosing personal information without prior consent.) In order to access this information on the go, the app’s developers also created a portable backpack kit that acts as a local area network without connections to the broader Internet. The kit includes a laptop, battery pack and router, with data stored on the laptop. This allows users to fill out surveys in remote locations and back up the data immediately without relying on cloud storage…(More)”.