Paper by Cass R. Sunstein and Lucia Reisch: “Do people like algorithms? In this study, intended as a promissory note and a description of a research strategy, we offer the following highly preliminary findings. (1) In a simple choice between a human being and an algorithm, across diverse settings and without information about the human being or the algorithm, people in our tested groups are about equally divided in their preference. (2) When people are given a very brief account of the data on which an algorithm relies, there is a large shift in favor of the algorithm over the human being. (3) When people are given a very brief account of the experience of the relevant human being, without an account of the data on which the relevant algorithm relies, there is a moderate shift in favor of the human being. (4) When people are given both (a) a very brief account of the experience of the relevant human being and (b) a very brief account of the data on which the relevant algorithm relies, there is a large shift in favor of the algorithm over the human being. One lesson is that in the tested groups, at least one-third of people seem to have a clear preference for either a human being or an algorithm – a preference that is unaffected by brief information that seems to favor one or the other. Another lesson is that a brief account of the data on which an algorithm relies does have a significant effect on a large percentage of the tested groups, whether or not people are also given positive information about the human alternative. Across the various surveys, we do not find persistent demographic differences, with one exception: men appear to like algorithms more than women do. These initial findings are meant as proof of concept, or more accurately as a suggestion of concept, intended to inform a series of larger and more systematic studies of whether and when people prefer to rely on algorithms or human beings, and also of international and demographic differences…(More)”.
What is the value of data? A review of empirical methods
Paper by Diane Coyle and Annabel Manley: “With the growing use of digital technologies, data have become core to many organizations’ decisions, with its value widely acknowledged across public and private sectors. Yet few comprehensive empirical approaches to establishing the value of data exist, and there is no consensus about which methods should be applied to specific data types or purposes. This paper examines a range of data valuation methodologies proposed in the existing literature. We propose a typology linking methods to different data types and purposes…(More)”.
Driving Excellence in Official Statistics: Unleashing the Potential of Comprehensive Digital Data Governance
Paper by Hossein Hassani and Steve McFeely: “With the ubiquitous use of digital technologies and the consequent data deluge, official statistics faces new challenges and opportunities. In this context, strengthening official statistics through effective data governance will be crucial to ensure reliability, quality, and access to data. This paper presents a comprehensive framework for digital data governance for official statistics, addressing key components, such as data collection and management, processing and analysis, data sharing and dissemination, as well as privacy and ethical considerations. The framework integrates principles of data governance into digital statistical processes, enabling statistical organizations to navigate the complexities of the digital environment. Drawing on case studies and best practices, the paper highlights successful implementations of digital data governance in official statistics. The paper concludes by discussing future trends and directions, including emerging technologies and opportunities for advancing digital data governance…(More)”.
The Ethics of Sharing: Privacy, Data, and Common Goods
Paper by Sille Obelitz Søe & Jens-Erik Mai: “Given the concerns about big tech’s hoarding of data, creation of profiles, mining of data, and extrapolation of new knowledge from their data warehouses, there is a need and interest in devising policies and regulations that better shape big tech’s influence on people and their lives. One such proposal is to create data commons. In this paper, we examine the idea of data commons as well as the concept of sharing in relation to the concept of personal data. We argue that personal data are different in nature from the objects of classical commons wherefore the logic of “sharing is caring” is flawed. We, therefore, develop an ethics of sharing taking privacy into account as well as the idea that sometimes the right thing to do is not sharing. This ethics of sharing is based in a proposal to conceptualize data commons as MacIntyrean practices and Wittgensteinian forms of life…(More)”.
Public Sector Use of Private Sector Personal Data: Towards Best Practices
Paper by Teresa Scassa: “Governments increasingly turn to the private sector as a source of data for various purposes. In some cases, the data that they seek to use is personal data. The public sector use of private sector personal data raises several important law and public policy concerns. These include the legal authority for such uses; privacy and data protection; ethics; transparency; and human rights. Governments that use private sector personal data without attending to the issues that such use raises may breach existing laws, which in some cases may not be well-adapted to evolving data practices. They also risk undermining public trust.
This paper uses two quite different recent examples from Canada where the use of private sector personal data by public sector actors caused considerable backlash and led to public hearings and complaints to the Privacy Commissioner. The examples are used to tease out the complex and interwoven law and policy issues. In some cases, the examples reveal issues that are particular to the evolving data society and that are not well addressed by current law or practice. The paper identifies key issues and important gaps and makes recommendations to address these. Although the examples discussed are Canadian and depend to some extent on Canadian law and institutions, the practices at issue are ones that are increasingly used around the world, and many of the issues raised are broadly relevant…(More)”.
Changing Facebook’s algorithm won’t fix polarization, new study finds
Article by Naomi Nix, Carolyn Y. Johnson, and Cat Zakrzewski: “For years, regulators and activists have worried that social media companies’ algorithms were dividing the United States with politically toxic posts and conspiracies. The concern was so widespread that in 2020, Meta flung open troves of internal data for university academics to study how Facebook and Instagram would affect the upcoming presidential election.
The first results of that research show that the company’s platforms play a critical role in funneling users to partisan information with which they are likely to agree. But the results cast doubt on assumptions that the strategies Meta could use to discourage virality and engagement on its social networks would substantially affect people’s political beliefs.
“Algorithms are extremely influential in terms of what people see on the platform, and in terms of shaping their on-platform experience,” Joshua Tucker, co-director of the Center for Social Media and Politics at New York University and one of the leaders on the research project, said in an interview.
“Despite the fact that we find this big impact in people’s on-platform experience, we find very little impact in changes to people’s attitudes about politics and even people’s self-reported participation around politics.”
The first four studies, which were released on Thursday in the journals Science and Nature, are the result of a unique partnership between university researchers and Meta’s own analysts to study how social media affects political polarization and people’s understanding and opinions about news, government and democracy. The researchers, who relied on Meta for data and the ability to run experiments, analyzed those issues during the run-up to the 2020 election. The studies were peer-reviewed before publication, a standard procedure in science in which papers are sent out to other experts in the field who assess the work’s merit.
As part of the project, researchers altered the feeds of thousands of people using Facebook and Instagram in fall of 2020 to see if that could change political beliefs, knowledge or polarization by exposing them to different information than they might normally have received. The researchers generally concluded that such changes had little impact.
The collaboration, which is expected to be released over a dozen studies, also will examine data collected after the Jan. 6, 2021, attack on the U.S. Capitol, Tucker said…(More)”.
Interested but Uncertain: Carbon Markets and Data Sharing among U.S. Crop Farmers
Paper by Guang Han and Meredith T. Niles: “The potential for farmers and agriculture to sequester carbon and contribute to global climate change goals is widely discussed. However, there is currently low participation in agricultural carbon markets and a limited understanding of farmer perceptions and willingness to participate. Furthermore, farmers’ concerns regarding data privacy may complicate participation in agricultural carbon markets, which necessitates farmer data sharing with multiple entities. This study aims to address research gaps by assessing farmers’ willingness to participate in agricultural carbon markets, identifying the determinants of farmers’ willingness regarding carbon markets participation, and exploring how farmers’ concerns for data privacy relate to potential participation in agricultural carbon markets. Data were collected through a multistate survey of 246 farmers and analyzed using descriptive statistics, factor analysis, and multinomial regression models. We find that the majority of farmers (71.8%) are aware of carbon markets and would like to sell carbon credits, but they express high uncertainty about carbon market information, policies, markets, and cost impacts. Just over half of farmers indicated they would share their data for education, developing tools and models, and improving markets and supply chains. Farmers who wanted to participate in carbon markets were more likely to have higher farm revenues, more likely to share their data overall, more likely to share their data with private organizations, and more likely to change farming practices and had more positive perceptions of the impact of carbon markets on farm profitability. In conclusion, farmers have a general interest in carbon market participation, but more information is needed to address their uncertainties and concerns…(More)”.
The GPTJudge: Justice in a Generative AI World
Paper by Grossman, Maura and Grimm, Paul and Brown, Dan and Xu, Molly: “Generative AI (“GenAI”) systems such as ChatGPT recently have developed to the point where they are capable of producing computer-generated text and images that are difficult to differentiate from human-generated text and images. Similarly, evidentiary materials such as documents, videos and audio recordings that are AI-generated are becoming increasingly difficult to differentiate from those that are not AI-generated. These technological advancements present significant challenges to parties, their counsel, and the courts in determining whether evidence is authentic or fake. Moreover, the explosive proliferation and use of GenAI applications raises concerns about whether litigation costs will dramatically increase as parties are forced to hire forensic experts to address AI- generated evidence, the ability of juries to discern authentic from fake evidence, and whether GenAI will overwhelm the courts with AI-generated lawsuits, whether vexatious or otherwise. GenAI systems have the potential to challenge existing substantive intellectual property (“IP”) law by producing content that is machine, not human, generated, but that also relies on human-generated content in potentially infringing ways. Finally, GenAI threatens to alter the way in which lawyers litigate and judges decide cases.
This article discusses these issues, and offers a comprehensive, yet understandable, explanation of what GenAI is and how it functions. It explores evidentiary issues that must be addressed by the bench and bar to determine whether actual or asserted (i.e., deepfake) GenAI output should be admitted as evidence in civil and criminal trials. Importantly, it offers practical, step-by- step recommendations for courts and attorneys to follow in meeting the evidentiary challenges posed by GenAI. Finally, it highlights additional impacts that GenAI evidence may have on the development of substantive IP law, and its potential impact on what the future may hold for litigating cases in a GenAI world…(More)”.
The Eyewitness Community Survey: An Engaging Citizen Science Tool to Capture Reliable Data while Improving Community Participants’ Environmental Health Knowledge and Attitudes
Paper by Melinda Butsch Kovacic: “Many youths and young adults have variable environmental health knowledge, limited understanding of their local environment’s impact on their health, and poor environmentally friendly behaviors. We sought to develop and test a tool to reliably capture data, increase environmental health knowledge, and engage youths as citizen scientists to examine and take action on their community’s challenges. The Eyewitness Community Survey (ECS) was developed through several iterations of co-design. Herein, we tested its performance. In Phase I, seven youths audited five 360° photographs. In Phase II, 27 participants works as pairs/trios and audited five locations, typically 7 days apart. Inter-rater and intra-rater reliability were determined. Changes in participants’ knowledge, attitudes, behaviors, and self-efficacy were surveyed. Feedback was obtained via focus groups. Intra-rater reliability was in the substantial/near-perfect range, with Phase II having greater consistency. Inter-rater reliability was high, with 42% and 63% of Phase I and II Kappa, respectively, in the substantial/near-perfect range. Knowledge scores improved after making observations (p ≤ 0.032). Participants (85%) reported the tool to be easy/very easy to use, with 70% willing to use it again. Thus, the ECS is a mutually beneficial citizen science tool that rigorously captures environmental data and provides engaging experiential learning opportunities…(More)”.
Datafication, Identity, and the Reorganization of the Category Individual
Paper by Juan Ortiz Freuler: “A combination of political, sociocultural, and technological shifts suggests a change in the way we understand human rights. Undercurrents fueling this process are digitization and datafication. Through this process of change, categories that might have been cornerstones of our past and present might very well become outdated. A key category that is under pressure is that of the individual. Since datafication is typically accompanied by technologies and processes aimed at segmenting and grouping, such groupings become increasingly relevant at the expense of the notion of the individual. This concept might become but another collection of varied characteristics, a unit of analysis that is considered at times too broad—and at other times too narrow—to be considered relevant or useful by the systems driving our key economic, social, and political processes.
This Essay provides a literature review and a set of key definitions linking the processes of digitization, datafication, and the concept of the individual to existing conceptions of individual rights. It then presents a framework to dissect and showcase the ways in which current technological developments are putting pressure on our existing conceptions of the individual and individual rights…(More)”.