Deciding Machines: Moral-Scene Assessment for Intelligent Systems

Greenberg, Ariel M.

doi:10.1016/b978-0-12-820543-3.00006-7

Cited by 3 publications

(4 citation statements)

References 15 publications

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“…7). This moral perception reifies potential insults and injuries to persons for the AI to reason over and provides a basis for ethical behavioral choices in interacting with humans (Greenberg 2018).…”

Section: Ethical Aimentioning

confidence: 88%

“…As AI systems evolve to operate autonomously, self-assess and self-regulate, and work effectively alongside humans to accomplish tasks, what will the roles be for the humans and (Asimov 1950), this decomposition (above, left) extracts the perceptual and reasoning capabilities needed for an AI-robot to engage in moral consideration. Ethical decision-making to prevent an AI from harming a human starts with perception (above, right), providing a basis for ethical behavior choices (Greenberg 2018) the robots? The following sections review two projections of the future relationship between humans and robots and then present an alternative possibility.…”

Section: Competing Visions Of the Future Of Ai-robotsmentioning

confidence: 99%

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Designing Robots for the Battlefield: State of the Art

Swett

Hahn

Llorens

2021

Robotics, AI, and Humanity

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There is currently a global arms race for the development of artificial intelligence (AI) and unmanned robotic systems that are empowered by AI (AI-robots). This paper examines the current use of AI-robots on the battlefield and offers a framework for understanding AI and AI-robots. It examines the limitations and risks of AI-robots on the battlefield and posits the future direction of battlefield AI-robots. It then presents research performed at the Johns Hopkins University Applied Physics Laboratory (JHU/APL) related to the development, testing, and control of AI-robots, as well as JHU/APL work on human trust of autonomy and developing self-regulating and ethical robotic systems. Finally, it examines multiple possible future paths for the relationship between humans and AI-robots.

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Section: Ethical Aimentioning

confidence: 88%

Section: Competing Visions Of the Future Of Ai-robotsmentioning

confidence: 99%

Designing Robots for the Battlefield: State of the Art

Swett

Hahn

Llorens

2021

Robotics, AI, and Humanity

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“…While it is common for researchers to use the term "humanmachine teaming" and to speak of "the human" doing this or that with "the machine," a core tenet of our analysis is that the species of intelligent animal is not the primary feature that distinguishes people from machines. Instead, a more salient difference between the two classes of teammates, in the spirit of Locke, Singer, and Strawson, is that humans are persons, who are able to reciprocally recognize the personhood of other humans, whereas machines are not (yet, if they ever could be) persons, and are not (yet) able to recognize personhood, even if they can discriminate humans from other species [1]. In making this distinction, we seek to highlight the fact that there is something special about those with personhood status (and people, in particular) that makes their dyadic behavior fundamentally distinct from that of their machine counterparts.…”

Section: Personhood and Relationships Over Speciesismmentioning

confidence: 99%

Foundational concepts in person-machine teaming

Greenberg

Marble

2023

Front. Phys.

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As we enter an age where the behavior and capabilities of artificial intelligence and autonomous system technologies become ever more sophisticated, cooperation, collaboration, and teaming between people and these machines is rising to the forefront of critical research areas. People engage socially with almost everything with which they interact. However, unlike animals, machines do not share the experiential aspects of sociality. Experiential robotics identifies the need to develop machines that not only learn from their own experience, but can learn from the experience of people in interactions, wherein these experiences are primarily social. In this paper, we argue, therefore, for the need to place experiential considerations in interaction, cooperation, and teaming as the basis of the design and engineering of person-machine teams. We first explore the importance of semantics in driving engineering approaches to robot development. Then, we examine differences in the usage of relevant terms like trust and ethics between engineering and social science approaches to lay out implications for the development of autonomous, experiential systems.

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“…On the other hand, because of the importance of allowing humans to make (and to take responsibility for) their own decisions, a robot may not be robot-responsible for harms that could result from the risky behavior of a competent adult human. Some of the authors of this article are developing a "moral-scene assessment" technology for robots, or "moral vision" for short, that will be able to identify potential harms within a scene and correctly specify which harms ought to be avoided [30]. Completing this project, however, will require marshalling the ethical and practical knowledge of a range of academic fields such as biomedical ethics, neuroscience, law, economics, and philosophy, as well as the expertise and experience of professionals who have experience performing in the role intended to be occupied by the robot.…”

Section: The Challenges Of Nonmaleficencementioning

confidence: 99%

Designing robots that do no harm: understanding the challenges of Ethics for Robots

et al. 2023

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This article describes key challenges in creating an ethics “for” robots. Robot ethics is not only a matter of the effects caused by robotic systems or the uses to which they may be put, but also the ethical rules and principles that these systems ought to follow—what we call “Ethics for Robots.” We suggest that the Principle of Nonmaleficence, or “do no harm,” is one of the basic elements of an ethics for robots—especially robots that will be used in a healthcare setting. We argue, however, that the implementation of even this basic principle will raise significant challenges for robot designers. In addition to technical challenges, such as ensuring that robots are able to detect salient harms and dangers in the environment, designers will need to determine an appropriate sphere of responsibility for robots and to specify which of various types of harms must be avoided or prevented. These challenges are amplified by the fact that the robots we are currently able to design possess a form of semi-autonomy that differs from other more familiar semi-autonomous agents such as animals or young children. In short, robot designers must identify and overcome the key challenges of an ethics for robots before they may ethically utilize robots in practice.

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Deciding Machines: Moral-Scene Assessment for Intelligent Systems

Cited by 3 publications

References 15 publications

Designing Robots for the Battlefield: State of the Art

Designing Robots for the Battlefield: State of the Art

Foundational concepts in person-machine teaming

Designing robots that do no harm: understanding the challenges of Ethics for Robots

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