The History of AI Rights Research

• URL: http://arxiv.org/abs/2208.04714v2
• Date: Sat, 27 Aug 2022 07:14:22 GMT
• Title: The History of AI Rights Research
• Authors: Jamie Harris
• Abstract summary: Report documents the history of research on AI rights and other moral consideration of artificial entities. It highlights key intellectual influences on this literature as well as research and academic discussion addressing the topic more directly.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: This report documents the history of research on AI rights and other moral consideration of artificial entities. It highlights key intellectual influences on this literature as well as research and academic discussion addressing the topic more directly. We find that researchers addressing AI rights have often seemed to be unaware of the work of colleagues whose interests overlap with their own. Academic interest in this topic has grown substantially in recent years; this reflects wider trends in academic research, but it seems that certain influential publications, the gradual, accumulating ubiquity of AI and robotic technology, and relevant news events may all have encouraged increased academic interest in this specific topic. We suggest four levers that, if pulled on in the future, might increase interest further: the adoption of publication strategies similar to those of the most successful previous contributors; increased engagement with adjacent academic fields and debates; the creation of specialized journals, conferences, and research institutions; and more exploration of legal rights for artificial entities.

Related papers

• Transforming Science with Large Language Models: A Survey on AI-assisted Scientific Discovery, Experimentation, Content Generation, and Evaluation [58.064940977804596]
  A plethora of new AI models and tools has been proposed, promising to empower researchers and academics worldwide to conduct their research more effectively and efficiently. Ethical concerns regarding shortcomings of these tools and potential for misuse take a particularly prominent place in our discussion.
  arXiv  Detail & Related papers  (2025-02-07T18:26:45Z)
• Publication Trends in Artificial Intelligence Conferences: The Rise of Super Prolific Authors [1.5998912722142724]
  We analyzed 87,137 papers from 11 AI conferences to examine publication trends over the past decade. Our findings reveal a consistent increase in both the number of papers and authors, reflecting the growing interest in AI research. In light of this analysis, the AI research community should consider revisiting authorship policies, addressing equity concerns, and evaluating the workload of junior researchers.
  arXiv  Detail & Related papers  (2024-11-28T06:56:49Z)
• Now, Later, and Lasting: Ten Priorities for AI Research, Policy, and Practice [63.20307830884542]
  Next several decades may well be a turning point for humanity, comparable to the industrial revolution. Launched a decade ago, the project is committed to a perpetual series of studies by multidisciplinary experts. We offer ten recommendations for action that collectively address both the short- and long-term potential impacts of AI technologies.
  arXiv  Detail & Related papers  (2024-04-06T22:18:31Z)
• The complementary contributions of academia and industry to AI research [0.0]
  We characterize the impact and type of AI produced by industry and academia over the last 25 years. We find that articles published by industry teams tend to get greater attention, with a higher chance of being highly cited and citation-disruptive. We find that academic-industry collaborations struggle to replicate the novelty of academic teams and tend to look similar to industry teams.
  arXiv  Detail & Related papers  (2024-01-04T03:08:13Z)
• Analyzing the Impact of Companies on AI Research Based on Publications [1.450405446885067]
  We compare academic- and company-authored AI publications published in the last decade. We find that the citation count an individual publication receives is significantly higher when it is (co-authored) by a company.
  arXiv  Detail & Related papers  (2023-10-31T13:27:04Z)
• Artificial intelligence adoption in the physical sciences, natural sciences, life sciences, social sciences and the arts and humanities: A bibliometric analysis of research publications from 1960-2021 [73.06361680847708]
  In 1960 14% of 333 research fields were related to AI, but this increased to over half of all research fields by 1972, over 80% by 1986 and over 98% in current times. In 1960 14% of 333 research fields were related to AI (many in computer science), but this increased to over half of all research fields by 1972, over 80% by 1986 and over 98% in current times. We conclude that the context of the current surge appears different, and that interdisciplinary AI application is likely to be sustained.
  arXiv  Detail & Related papers  (2023-06-15T14:08:07Z)
• The ethical ambiguity of AI data enrichment: Measuring gaps in research ethics norms and practices [2.28438857884398]
  This study explores how, and to what extent, comparable research ethics requirements and norms have developed for AI research and data enrichment. Leading AI venues have begun to establish protocols for human data collection, but these are are inconsistently followed by authors.
  arXiv  Detail & Related papers  (2023-06-01T16:12:55Z)
• Human-Centered Responsible Artificial Intelligence: Current & Future Trends [76.94037394832931]
  In recent years, the CHI community has seen significant growth in research on Human-Centered Responsible Artificial Intelligence. All of this work is aimed at developing AI that benefits humanity while being grounded in human rights and ethics, and reducing the potential harms of AI. In this special interest group, we aim to bring together researchers from academia and industry interested in these topics to map current and future research trends.
  arXiv  Detail & Related papers  (2023-02-16T08:59:42Z)
• Characterising Research Areas in the field of AI [68.8204255655161]
  We identified the main conceptual themes by performing clustering analysis on the co-occurrence network of topics. The results highlight the growing academic interest in research themes like deep learning, machine learning, and internet of things.
  arXiv  Detail & Related papers  (2022-05-26T16:30:30Z)
• Building Bridges: Generative Artworks to Explore AI Ethics [56.058588908294446]
  In recent years, there has been an increased emphasis on understanding and mitigating adverse impacts of artificial intelligence (AI) technologies on society. A significant challenge in the design of ethical AI systems is that there are multiple stakeholders in the AI pipeline, each with their own set of constraints and interests. This position paper outlines some potential ways in which generative artworks can play this role by serving as accessible and powerful educational tools.
  arXiv  Detail & Related papers  (2021-06-25T22:31:55Z)

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.