Computational Theory of Mind for Human-Machine Teams

Computational Theory of Mind for Human-Machine Teams PDF Author: Nikolos Gurney
Publisher: Springer Nature
ISBN: 3031216717
Category : Computers
Languages : en
Pages : 235

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Book Description
This book constitutes the proceedings of the First International Symposium, ToM for Teams 2021, held in Washington, DC, USA, during November 4–6, 2021, Each chapter in this section tackles a different aspect of AI representing the thoughts and beliefs of human agents. The work presented herein represents our collective efforts to better understand ToM, develop AI with ToM capabilities (ASI), and study how to integrate such systems into human teams.

Computational Theory of Mind for Human-Machine Teams

Computational Theory of Mind for Human-Machine Teams PDF Author: Nikolos Gurney
Publisher: Springer Nature
ISBN: 3031216717
Category : Computers
Languages : en
Pages : 235

Get Book Here

Book Description
This book constitutes the proceedings of the First International Symposium, ToM for Teams 2021, held in Washington, DC, USA, during November 4–6, 2021, Each chapter in this section tackles a different aspect of AI representing the thoughts and beliefs of human agents. The work presented herein represents our collective efforts to better understand ToM, develop AI with ToM capabilities (ASI), and study how to integrate such systems into human teams.

Artificial Intelligence, Social Computing and Wearable Technologies

Artificial Intelligence, Social Computing and Wearable Technologies PDF Author: Waldemar Karwowski and Tareq Ahram
Publisher: AHFE Conference
ISBN: 1958651893
Category : Technology & Engineering
Languages : en
Pages : 414

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Book Description
Proceedings of the AHFE International Conference on Human Factors in Design, Engineering, and Computing (AHFE 2023 Hawaii Edition), Honolulu, Hawaii, USA 4-6, December 2023

Human Factors and Simulation

Human Factors and Simulation PDF Author: Julia Wright and Daniel Barber
Publisher: AHFE International
ISBN: 1958651591
Category : Technology & Engineering
Languages : en
Pages : 273

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Book Description
Proceedings of the 14th International Conference on Applied Human Factors and Ergonomics (AHFE 2023), July 20–24, 2023, San Francisco, USA

Artificial Intelligence in HCI

Artificial Intelligence in HCI PDF Author: Helmut Degen
Publisher: Springer Nature
ISBN: 3031358945
Category : Computers
Languages : en
Pages : 638

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Book Description
This double volume book set constitutes the refereed proceedings of 4th International Conference, AI-HCI 2023, held as part of the 25th International Conference, HCI International 2023, which was held virtually in Copenhagen, Denmark in July 2023. The total of 1578 papers and 396 posters included in the HCII 2023 proceedings was carefully reviewed and selected from 7472 submissions. The first volume focuses on topics related to Human-Centered Artificial Intelligence, explainability, transparency and trustworthiness, ethics and fairness, as well as AI-supported user experience design. The second volume focuses on topics related to AI for language, text, and speech-related tasks, human-AI collaboration, AI for decision-support and perception analysis, and innovations in AI-enabled systems.

Interdisciplinary Approaches to the Structure and Performance of Interdependent Autonomous Human Machine Teams and Systems (A-HMT-S)

Interdisciplinary Approaches to the Structure and Performance of Interdependent Autonomous Human Machine Teams and Systems (A-HMT-S) PDF Author: William Frere Lawless
Publisher: Frontiers Media SA
ISBN: 283251930X
Category : Science
Languages : en
Pages : 220

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Book Description


Human-Machine Shared Contexts

Human-Machine Shared Contexts PDF Author: William Lawless
Publisher: Academic Press
ISBN: 0128223790
Category : Computers
Languages : en
Pages : 448

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Book Description
Human-Machine Shared Contexts considers the foundations, metrics, and applications of human-machine systems. Editors and authors debate whether machines, humans, and systems should speak only to each other, only to humans, or to both and how. The book establishes the meaning and operation of "shared contexts between humans and machines; it also explores how human-machine systems affect targeted audiences (researchers, machines, robots, users) and society, as well as future ecosystems composed of humans and machines. This book explores how user interventions may improve the context for autonomous machines operating in unfamiliar environments or when experiencing unanticipated events; how autonomous machines can be taught to explain contexts by reasoning, inferences, or causality, and decisions to humans relying on intuition; and for mutual context, how these machines may interdependently affect human awareness, teams and society, and how these "machines" may be affected in turn. In short, can context be mutually constructed and shared between machines and humans? The editors are interested in whether shared context follows when machines begin to think, or, like humans, develop subjective states that allow them to monitor and report on their interpretations of reality, forcing scientists to rethink the general model of human social behavior. If dependence on machine learning continues or grows, the public will also be interested in what happens to context shared by users, teams of humans and machines, or society when these machines malfunction. As scientists and engineers "think through this change in human terms," the ultimate goal is for AI to advance the performance of autonomous machines and teams of humans and machines for the betterment of society wherever these machines interact with humans or other machines. This book will be essential reading for professional, industrial, and military computer scientists and engineers; machine learning (ML) and artificial intelligence (AI) scientists and engineers, especially those engaged in research on autonomy, computational context, and human-machine shared contexts; advanced robotics scientists and engineers; scientists working with or interested in data issues for autonomous systems such as with the use of scarce data for training and operations with and without user interventions; social psychologists, scientists and physical research scientists pursuing models of shared context; modelers of the internet of things (IOT); systems of systems scientists and engineers and economists; scientists and engineers working with agent-based models (ABMs); policy specialists concerned with the impact of AI and ML on society and civilization; network scientists and engineers; applied mathematicians (e.g., holon theory, information theory); computational linguists; and blockchain scientists and engineers. - Discusses the foundations, metrics, and applications of human-machine systems - Considers advances and challenges in the performance of autonomous machines and teams of humans - Debates theoretical human-machine ecosystem models and what happens when machines malfunction

The Alignment Problem: Machine Learning and Human Values

The Alignment Problem: Machine Learning and Human Values PDF Author: Brian Christian
Publisher: W. W. Norton & Company
ISBN: 039363583X
Category : Science
Languages : en
Pages : 459

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Book Description
A jaw-dropping exploration of everything that goes wrong when we build AI systems and the movement to fix them. Today’s “machine-learning” systems, trained by data, are so effective that we’ve invited them to see and hear for us—and to make decisions on our behalf. But alarm bells are ringing. Recent years have seen an eruption of concern as the field of machine learning advances. When the systems we attempt to teach will not, in the end, do what we want or what we expect, ethical and potentially existential risks emerge. Researchers call this the alignment problem. Systems cull résumés until, years later, we discover that they have inherent gender biases. Algorithms decide bail and parole—and appear to assess Black and White defendants differently. We can no longer assume that our mortgage application, or even our medical tests, will be seen by human eyes. And as autonomous vehicles share our streets, we are increasingly putting our lives in their hands. The mathematical and computational models driving these changes range in complexity from something that can fit on a spreadsheet to a complex system that might credibly be called “artificial intelligence.” They are steadily replacing both human judgment and explicitly programmed software. In best-selling author Brian Christian’s riveting account, we meet the alignment problem’s “first-responders,” and learn their ambitious plan to solve it before our hands are completely off the wheel. In a masterful blend of history and on-the ground reporting, Christian traces the explosive growth in the field of machine learning and surveys its current, sprawling frontier. Readers encounter a discipline finding its legs amid exhilarating and sometimes terrifying progress. Whether they—and we—succeed or fail in solving the alignment problem will be a defining human story. The Alignment Problem offers an unflinching reckoning with humanity’s biases and blind spots, our own unstated assumptions and often contradictory goals. A dazzlingly interdisciplinary work, it takes a hard look not only at our technology but at our culture—and finds a story by turns harrowing and hopeful.

Advances in Neural Computation, Machine Learning, and Cognitive Research IV

Advances in Neural Computation, Machine Learning, and Cognitive Research IV PDF Author: Boris Kryzhanovsky
Publisher: Springer Nature
ISBN: 3030605779
Category : Technology & Engineering
Languages : en
Pages : 449

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Book Description
This book describes new theories and applications of artificial neural networks, with a special focus on answering questions in neuroscience, biology and biophysics and cognitive research. It covers a wide range of methods and technologies, including deep neural networks, large scale neural models, brain computer interface, signal processing methods, as well as models of perception, studies on emotion recognition, self-organization and many more. The book includes both selected and invited papers presented at the XXII International Conference on Neuroinformatics, held on October 12-16, 2020, Moscow, Russia.

A Decadal Survey of the Social and Behavioral Sciences

A Decadal Survey of the Social and Behavioral Sciences PDF Author: ENGINEERING NATIONAL ACADEMIES OF SCIENCES (AND M.)
Publisher:
ISBN: 9780309670333
Category :
Languages : en
Pages : 26

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Book Description
"The Digest Version of A Decadal Survey of the Social and Behavioral Sciences: A Research Agenda for Advancing Intelligence Analysis summarizes the most important ideas from the full report for the Intelligence Community to consider in the coming decade. This volume provides an overview of the primary opportunities that research in the social and behavioral sciences offers for strengthening national security, specifically the work of the intelligence analyst, and the conclusions and recommendations of the Committee on a Decadal Survey of Social and Behavioral Sciences for Applications to National Survey. This digest version is a succinct roadmap to the critical contribution researchers from these fields make to national security"--Publisher's description

Autonomy and Artificial Intelligence: A Threat or Savior?

Autonomy and Artificial Intelligence: A Threat or Savior? PDF Author: W.F. Lawless
Publisher: Springer
ISBN: 3319597191
Category : Computers
Languages : en
Pages : 324

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Book Description
This book explores how Artificial Intelligence (AI), by leading to an increase in the autonomy of machines and robots, is offering opportunities for an expanded but uncertain impact on society by humans, machines, and robots. To help readers better understand the relationships between AI, autonomy, humans and machines that will help society reduce human errors in the use of advanced technologies (e.g., airplanes, trains, cars), this edited volume presents a wide selection of the underlying theories, computational models, experimental methods, and field applications. While other literature deals with these topics individually, this book unifies the fields of autonomy and AI, framing them in the broader context of effective integration for human-autonomous machine and robotic systems. The contributions, written by world-class researchers and scientists, elaborate on key research topics at the heart of effective human-machine-robot-systems integration. These topics include, for example, computational support for intelligence analyses; the challenge of verifying today’s and future autonomous systems; comparisons between today’s machines and autism; implications of human information interaction on artificial intelligence and errors; systems that reason; the autonomy of machines, robots, buildings; and hybrid teams, where hybrid reflects arbitrary combinations of humans, machines and robots. The contributors span the field of autonomous systems research, ranging from industry and academia to government. Given the broad diversity of the research in this book, the editors strove to thoroughly examine the challenges and trends of systems that implement and exhibit AI; the social implications of present and future systems made autonomous with AI; systems with AI seeking to develop trusted relationships among humans, machines, and robots; and the effective human systems integration that must result for trust in these new systems and their applications to increase and to be sustained.