Embodied, Situated, and Grounded Intelligence: Implications for AI

• URL: http://arxiv.org/abs/2210.13589v1
• Date: Mon, 24 Oct 2022 20:24:30 GMT
• Title: Embodied, Situated, and Grounded Intelligence: Implications for AI
• Authors: Tyler Millhouse, Melanie Moses, Melanie Mitchell
• Abstract summary: In April of 2022, the Santa Fe Institute hosted a workshop on embodied, situated, and grounded intelligence. The workshop brought together computer scientists, psychologists, philosophers, social scientists, and others to discuss the science of embodiment and related issues in human intelligence.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In April of 2022, the Santa Fe Institute hosted a workshop on embodied, situated, and grounded intelligence as part of the Institute's Foundations of Intelligence project. The workshop brought together computer scientists, psychologists, philosophers, social scientists, and others to discuss the science of embodiment and related issues in human intelligence, and its implications for building robust, human-level AI. In this report, we summarize each of the talks and the subsequent discussions. We also draw out a number of key themes and identify important frontiers for future research.

Related papers

• Advancing Social Intelligence in AI Agents: Technical Challenges and Open Questions [67.60397632819202]
  Building socially-intelligent AI agents (Social-AI) is a multidisciplinary, multimodal research goal. We identify a set of underlying technical challenges and open questions for researchers across computing communities to advance Social-AI.
  arXiv  Detail & Related papers  (2024-04-17T02:57:42Z)
• 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)
• 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)
• Artificial Intelligence and Life in 2030: The One Hundred Year Study on Artificial Intelligence [74.2630823914258]
  The report examines eight domains of typical urban settings on which AI is likely to have impact over the coming years. It aims to provide the general public with a scientifically and technologically accurate portrayal of the current state of AI. The charge for this report was given to the panel by the AI100 Standing Committee, chaired by Barbara Grosz of Harvard University.
  arXiv  Detail & Related papers  (2022-10-31T18:35:36Z)
• Coordinated Science Laboratory 70th Anniversary Symposium: The Future of Computing [80.72844751804166]
  In 2021, the Coordinated Science Laboratory CSL hosted the Future of Computing Symposium to celebrate its 70th anniversary. We summarize the major technological points, insights, and directions that speakers brought forward during the symposium. Participants discussed topics related to new computing paradigms, technologies, algorithms, behaviors, and research challenges to be expected in the future.
  arXiv  Detail & Related papers  (2022-10-04T17:32:27Z)
• 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)
• Frontiers in Collective Intelligence: A Workshop Report [0.0]
  Foundations of Intelligence project seeks to advance the field of artificial intelligence by promoting interdisciplinary research on the nature of intelligence. In August of 2021, the Santa Fe Institute hosted a workshop on collective intelligence. The workshop brought together computer scientists, biologists, philosophers, social scientists, and others to share their insights about how intelligence can emerge from interactions among multiple agents.
  arXiv  Detail & Related papers  (2021-12-13T18:23:09Z)
• Frontiers in Evolutionary Computation: A Workshop Report [0.0]
  Foundations of Intelligence in Natural and Artificial Systems project seeks to advance the field of artificial intelligence. In July of 2021, the Santa Fe Institute hosted a workshop on evolutionary computation.
  arXiv  Detail & Related papers  (2021-10-20T00:11:39Z)
• Foundations of Intelligence in Natural and Artificial Systems: A Workshop Report [0.0]
  In March of 2021, the Santa Fe Institute hosted a workshop as part of its Foundations of Intelligence in Natural and Artificial Systems project. Speakers from diverse disciplines gathered to develop a taxonomy of intelligence. In this report, we summarize the insights offered by each speaker and identify the themes that emerged during the talks and subsequent discussions.
  arXiv  Detail & Related papers  (2021-05-05T17:11:58Z)
• AI in society and culture: decision making and values [0.0]
  Several academic debates, social consultations and impact studies are available to reveal the key aspects of the changing human-machine ecosystem. In details, sociocultural filters, taxonomy of human-machine decisions and perspectives of value-based AI are in the focus of this literature review. For better understanding, it is proposed to invite stakeholders in the prepared large-scale survey about the next generation AI that investigates issues that go beyond the technology.
  arXiv  Detail & Related papers  (2020-04-29T07:09:39Z)

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.