Ethical Treatment of Robots and the Hard Problem of Robot Emotions

Emotions are important cognitive faculties that enable animals to behave intelligently in real time. The author argues that many important current and future applications of autonomous robots will require them to have a rich emotional repertoire, but this raises the question of whether it is possible for robots to experience their emotions consciously, as people do. Under what conditions would phenomenal experience of emotions be possible for robots? This is, in effect, the “hard problem” of robot emotions. This paper outlines a scientific approach to the question grounded in experimental neurophenomenology.

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Could Robots Feel Pain?

Advances in Computational Intelligence and Robotics - Androids, Cyborgs, and Robots in Contemporary Culture and Society ◽

10.4018/978-1-5225-2973-6.ch007 ◽

2018 ◽

pp. 151-175

Author(s):

Bruce MacLennan

Keyword(s):

Autonomous Robots ◽

Hard Problem ◽

Biological Functions ◽

Empirical Methods ◽

The Hard Problem ◽

Empirical Approaches

This chapter considers the question of whether a robot could feel pain or experience other emotions and proposes empirical methods for answering this question. After a review of the biological functions of emotion and pain, the author argues that autonomous robots have similar functions that need to be fulfilled, which require systems analogous to emotion and pain. Protophenomenal analysis, which involves parallel reductions in the phenomenological and neurological domains, is explained and applied to the “hard problem” of robot emotion and pain. The author outlines empirical approaches to answering the fundamental questions on which depends the possibility of robot consciousness in general. The author then explains the importance of sensors distributed throughout a robot's body for the emergence of coherent emotional phenomena in its awareness. Overall, the chapter elucidates the issue of robot pain and emotion and outlines an approach to resolving it empirically.

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Not All Structure and Dynamics Are Equal

Entropy ◽

10.3390/e23091226 ◽

2021 ◽

Vol 23 (9) ◽

pp. 1226

Author(s):

Garrett Mindt

Keyword(s):

Good Reason ◽

Hard Problem ◽

Phenomenal Experience ◽

Intrinsic Structure ◽

David Chalmers ◽

Structure And Dynamics ◽

Recent Developments ◽

The Hard Problem ◽

The Relationship

The hard problem of consciousness has been a perennially vexing issue for the study of consciousness, particularly in giving a scientific and naturalized account of phenomenal experience. At the heart of the hard problem is an often-overlooked argument, which is at the core of the hard problem, and that is the structure and dynamics (S&D) argument. In this essay, I will argue that we have good reason to suspect that the S&D argument given by David Chalmers rests on a limited conception of S&D properties, what in this essay I’m calling extrinsic structure and dynamics. I argue that if we take recent insights from the complexity sciences and from recent developments in Integrated Information Theory (IIT) of Consciousness, that we get a more nuanced picture of S&D, specifically, a class of properties I’m calling intrinsic structure and dynamics. This I think opens the door to a broader class of properties with which we might naturally and scientifically explain phenomenal experience, as well as the relationship between syntactic, semantic, and intrinsic notions of information. I argue that Chalmers’ characterization of structure and dynamics in his S&D argument paints them with too broad a brush and fails to account for important nuances, especially when considering accounting for a system’s intrinsic properties. Ultimately, my hope is to vindicate a certain species of explanation from the S&D argument, and by extension dissolve the hard problem of consciousness at its core, by showing that not all structure and dynamics are equal.

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The Hard Problem of Consciousness and John McDowell’s Epistemological Disjunctivism

Вопросы философии ◽

10.31857/s004287440007357-7 ◽

2019 ◽

Keyword(s):

Hard Problem ◽

Epistemological Disjunctivism ◽

The Hard Problem

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Zombies and Dolls

10.1093/oso/9780198728443.003.0002 ◽

2018 ◽

Author(s):

Marcello Massimini ◽

Giulio Tononi

Keyword(s):

Body Problem ◽

Thought Experiments ◽

Turing Test ◽

Hard Problem ◽

Mind Body Problem ◽

The Hard Problem ◽

The Mind ◽

The Brain

This chapter uses thought experiments and practical examples to introduce, in a very accessible way, the hard problem of consciousness. Soon, machines may behave like us to pass the Turing test and scientists may succeed in copying and simulating the inner workings of the brain. Will all this take us any closer to solving the mysteries of consciousness? The reader is taken to meet different kind of zombies, the philosophical, the digital, and the inner ones, to understand why many, scientists and philosophers alike, doubt that the mind–body problem will ever be solved.

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Teleosemantics and the hard problem of content

Philosophical Psychology ◽

10.1080/09515089.2021.1942814 ◽

2021 ◽

pp. 1-25

Author(s):

Stephen Francis Mann ◽

Ross Pain

Keyword(s):

Hard Problem ◽

The Hard Problem ◽

Hard Problem Of Content

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Offline Algorithms in Low-Frequency Trading

Queue ◽

10.1145/3442632.3448307 ◽

2020 ◽

Vol 18 (6) ◽

pp. 37-51

Author(s):

Terence Kelly

Keyword(s):

Real Time ◽

Real World ◽

High Frequency ◽

Low Frequency ◽

Combinatorial Auctions ◽

Hard Problem ◽

Np Hard ◽

High Stakes ◽

Drill Bits ◽

Np Hard Problem

Expectations run high for software that makes real-world decisions, particularly when money hangs in the balance. This third episode of the Drill Bits column shows how well-designed software can effectively create wealth by optimizing gains from trade in combinatorial auctions. We'll unveil a deep connection between auctions and a classic textbook problem, we'll see that clearing an auction resembles a high-stakes mutant Tetris, we'll learn to stop worrying and love an NP-hard problem that's far from intractable in practice, and we'll contrast the deliberative business of combinatorial auctions with the near-real-time hustle of high-frequency trading. The example software that accompanies this installment of Drill Bits implements two algorithms that clear combinatorial auctions.

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