On some Foundational Aspects of Human-Centered Artificial Intelligence

• URL: http://arxiv.org/abs/2112.14480v1
• Date: Wed, 29 Dec 2021 09:58:59 GMT
• Title: On some Foundational Aspects of Human-Centered Artificial Intelligence
• Authors: Luciano Serafini, Raul Barbosa, Jasmin Grosinger, Luca Iocchi, Christian Napoli, Salvatore Rinzivillo, Jacques Robin, Alessandro Saffiotti, Teresa Scantamburlo, Peter Schueller, Paolo Traverso, Javier Vazquez-Salceda
• Abstract summary: There is no clear definition of what is meant by Human Centered Artificial Intelligence. This paper introduces the term HCAI agent to refer to any physical or software computational agent equipped with AI components. We see the notion of HCAI agent, together with its components and functions, as a way to bridge the technical and non-technical discussions on human-centered AI.
• Score: 52.03866242565846
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The burgeoning of AI has prompted recommendations that AI techniques should be "human-centered". However, there is no clear definition of what is meant by Human Centered Artificial Intelligence, or for short, HCAI. This paper aims to improve this situation by addressing some foundational aspects of HCAI. To do so, we introduce the term HCAI agent to refer to any physical or software computational agent equipped with AI components and that interacts and/or collaborates with humans. This article identifies five main conceptual components that participate in an HCAI agent: Observations, Requirements, Actions, Explanations and Models. We see the notion of HCAI agent, together with its components and functions, as a way to bridge the technical and non-technical discussions on human-centered AI. In this paper, we focus our analysis on scenarios consisting of a single agent operating in dynamic environments in presence of humans.

Related papers

• Aligning Generalisation Between Humans and Machines [74.120848518198]
  Recent advances in AI have resulted in technology that can support humans in scientific discovery and decision support but may also disrupt democracies and target individuals. The responsible use of AI increasingly shows the need for human-AI teaming. A crucial yet often overlooked aspect of these interactions is the different ways in which humans and machines generalise.
  arXiv  Detail & Related papers  (2024-11-23T18:36:07Z)
• A.I. go by many names: towards a sociotechnical definition of artificial intelligence [0.0]
  Defining artificial intelligence (AI) is a persistent challenge, often muddied by technical ambiguity and varying interpretations. This essay makes a case for a sociotechnical definition of AI, which is essential for researchers who require clarity in their work.
  arXiv  Detail & Related papers  (2024-10-17T11:25:50Z)
• Explainable Human-AI Interaction: A Planning Perspective [32.477369282996385]
  AI systems need to be explainable to the humans in the loop. We will discuss how the AI agent can use mental models to either conform to human expectations, or change those expectations through explanatory communication. While the main focus of the book is on cooperative scenarios, we will point out how the same mental models can be used for obfuscation and deception.
  arXiv  Detail & Related papers  (2024-05-19T22:22:21Z)
• The Ethics of Advanced AI Assistants [53.89899371095332]
  This paper focuses on the opportunities and the ethical and societal risks posed by advanced AI assistants. We define advanced AI assistants as artificial agents with natural language interfaces, whose function is to plan and execute sequences of actions on behalf of a user. We consider the deployment of advanced assistants at a societal scale, focusing on cooperation, equity and access, misinformation, economic impact, the environment and how best to evaluate advanced AI assistants.
  arXiv  Detail & Related papers  (2024-04-24T23:18:46Z)
• Position Paper: Agent AI Towards a Holistic Intelligence [53.35971598180146]
  We emphasize developing Agent AI -- an embodied system that integrates large foundation models into agent actions. In this paper, we propose a novel large action model to achieve embodied intelligent behavior, the Agent Foundation Model.
  arXiv  Detail & Related papers  (2024-02-28T16:09:56Z)
• On the Emergence of Symmetrical Reality [51.21203247240322]
  We introduce the symmetrical reality framework, which offers a unified representation encompassing various forms of physical-virtual amalgamations. We propose an instance of an AI-driven active assistance service that illustrates the potential applications of symmetrical reality.
  arXiv  Detail & Related papers  (2024-01-26T16:09:39Z)
• Applying HCAI in developing effective human-AI teaming: A perspective from human-AI joint cognitive systems [10.746728034149989]
  Research and application have used human-AI teaming (HAT) as a new paradigm to develop AI systems. We elaborate on our proposed conceptual framework of human-AI joint cognitive systems (HAIJCS) We propose a conceptual framework of human-AI joint cognitive systems (HAIJCS) to represent and implement HAT.
  arXiv  Detail & Related papers  (2023-07-08T06:26:38Z)
• A Mental-Model Centric Landscape of Human-AI Symbiosis [31.14516396625931]
  We introduce a significantly general version of human-aware AI interaction scheme, called generalized human-aware interaction (GHAI) We will see how this new framework allows us to capture the various works done in the space of human-AI interaction and identify the fundamental behavioral patterns supported by these works.
  arXiv  Detail & Related papers  (2022-02-18T22:08:08Z)
• Human-Centered AI for Data Science: A Systematic Approach [48.71756559152512]
  Human-Centered AI (HCAI) refers to the research effort that aims to design and implement AI techniques to support various human tasks. We illustrate how we approach HCAI using a series of research projects around Data Science (DS) works as a case study.
  arXiv  Detail & Related papers  (2021-10-03T21:47:13Z)
• Human-centered Explainable AI: Towards a Reflective Sociotechnical Approach [18.14698948294366]
  We introduce Human-centered Explainable AI (HCXAI) as an approach that puts the human at the center of technology design. It develops a holistic understanding of "who" the human is by considering the interplay of values, interpersonal dynamics, and the socially situated nature of AI systems.
  arXiv  Detail & Related papers  (2020-02-04T02:30:33Z)

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.