Requirements for Open Political Information: Transparency Beyond Open Data

• URL: http://arxiv.org/abs/2112.03119v1
• Date: Mon, 6 Dec 2021 15:42:03 GMT
• Title: Requirements for Open Political Information: Transparency Beyond Open Data
• Authors: Andong Luis Li Zhao, Andrew Paley, Rachel Adler, Harper Pack, Sergio Servantez, Alexander Einarsson, Cameron Barrie, Marko Sterbentz, Kristian Hammond
• Abstract summary: We conduct user interviews to identify wants and needs among stakeholders. We use this information to sketch out the foundational requirements for a functional political information technical system.
• Score: 48.7576911714538
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: A politically informed citizenry is imperative for a welldeveloped democracy. While the US government has pursued policies for open data, these efforts have been insufficient in achieving an open government because only people with technical and domain knowledge can access information in the data. In this work, we conduct user interviews to identify wants and needs among stakeholders. We further use this information to sketch out the foundational requirements for a functional political information technical system.

Related papers

• Merging AI Incidents Research with Political Misinformation Research: Introducing the Political Deepfakes Incidents Database [0.0]
  The project is driven by the rise of generative AI in politics, ongoing policy efforts to address harms, and the need to connect AI incidents and political communication research. The database contains political deepfake content, metadata, and researcher-coded descriptors drawn from political science, public policy, communication, and misinformation studies. It aims to help reveal the prevalence, trends, and impact of political deepfakes, such as those featuring major political figures or events.
  arXiv  Detail & Related papers  (2024-09-05T19:24:38Z)
• Future and AI-Ready Data Strategies: Response to DOC RFI on AI and Open Government Data Assets [6.659894897434807]
  The following is a response to the US Department of Commerce's Request for Information (RFI) regarding AI and Open Government Data Assets. We commend the Department for its initiative in seeking public insights on the organization and sharing of data. In our response, we outline best practices and key considerations for AI and the Department of Commerce's Open Government Data Assets.
  arXiv  Detail & Related papers  (2024-07-26T07:31:32Z)
• Collection, usage and privacy of mobility data in the enterprise and public administrations [55.2480439325792]
  Security measures such as anonymization are needed to protect individuals' privacy. Within our study, we conducted expert interviews to gain insights into practices in the field. We survey privacy-enhancing methods in use, which generally do not comply with state-of-the-art standards of differential privacy.
  arXiv  Detail & Related papers  (2024-07-04T08:29:27Z)
• Lomas: A Platform for Confidential Analysis of Private Data [0.0]
  Lomas is a novel open-source platform designed to realize the full potential of the data held by public administrations. It enables authorized users, such as approved researchers and government analysts, to execute algorithms on confidential datasets. Lomas executes these algorithms without revealing the data to the user and returns the results protected by Differential Privacy.
  arXiv  Detail & Related papers  (2024-06-24T19:16:58Z)
• Sociotechnical Implications of Generative Artificial Intelligence for Information Access [4.3867169221012645]
  Generative AI technologies may enable new ways to access information and improve effectiveness of existing information retrieval systems. We present an overview of some of the systemic consequences and risks of employing generative AI in the context of information access.
  arXiv  Detail & Related papers  (2024-05-19T17:04:39Z)
• Having your Privacy Cake and Eating it Too: Platform-supported Auditing of Social Media Algorithms for Public Interest [70.02478301291264]
  Social media platforms curate access to information and opportunities, and so play a critical role in shaping public discourse. Prior studies have used black-box methods to show that these algorithms can lead to biased or discriminatory outcomes. We propose a new method for platform-supported auditing that can meet the goals of the proposed legislation.
  arXiv  Detail & Related papers  (2022-07-18T17:32:35Z)
• Exploring Tenets of Data Democratization [0.0]
  Data democratization is an ongoing process that broadens access to data and facilitates employees to find, access, self-analyze, and share data without additional support. This paper explores the tenets of data democratization through an in-depth review of the literature. The analysis identified twelve attributes that enable data democratization based on the literature review.
  arXiv  Detail & Related papers  (2022-06-24T03:00:29Z)
• Distributed Machine Learning and the Semblance of Trust [66.1227776348216]
  Federated Learning (FL) allows the data owner to maintain data governance and perform model training locally without having to share their data. FL and related techniques are often described as privacy-preserving. We explain why this term is not appropriate and outline the risks associated with over-reliance on protocols that were not designed with formal definitions of privacy in mind.
  arXiv  Detail & Related papers  (2021-12-21T08:44:05Z)
• Explainable Patterns: Going from Findings to Insights to Support Data Analytics Democratization [60.18814584837969]
  We present Explainable Patterns (ExPatt), a new framework to support lay users in exploring and creating data storytellings. ExPatt automatically generates plausible explanations for observed or selected findings using an external (textual) source of information.
  arXiv  Detail & Related papers  (2021-01-19T16:13:44Z)
• A vision for global privacy bridges: Technical and legal measures for international data markets [77.34726150561087]
  Despite data protection laws and an acknowledged right to privacy, trading personal information has become a business equated with "trading oil" An open conflict is arising between business demands for data and a desire for privacy. We propose and test a vision of a personal information market with privacy.
  arXiv  Detail & Related papers  (2020-05-13T13:55:50Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.