Robot Rights? Let's Talk about Human Welfare Instead
- URL: http://arxiv.org/abs/2001.05046v1
- Date: Tue, 14 Jan 2020 20:54:29 GMT
- Title: Robot Rights? Let's Talk about Human Welfare Instead
- Authors: Abeba Birhane and Jelle van Dijk
- Abstract summary: We argue that robots, as artifacts emerging out of and mediating human being, are the kinds of things that could be granted rights in the first place.
We conclude that, if human being is our starting point and human welfare is the primary concern, the negative impacts emerging from machinic systems remain the most pressing ethical discussion in AI.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: The 'robot rights' debate, and its related question of 'robot
responsibility', invokes some of the most polarized positions in AI ethics.
While some advocate for granting robots rights on a par with human beings,
others, in a stark opposition argue that robots are not deserving of rights but
are objects that should be our slaves. Grounded in post-Cartesian philosophical
foundations, we argue not just to deny robots 'rights', but to deny that
robots, as artifacts emerging out of and mediating human being, are the kinds
of things that could be granted rights in the first place. Once we see robots
as mediators of human being, we can understand how the `robots rights' debate
is focused on first world problems, at the expense of urgent ethical concerns,
such as machine bias, machine elicited human labour exploitation, and erosion
of privacy all impacting society's least privileged individuals. We conclude
that, if human being is our starting point and human welfare is the primary
concern, the negative impacts emerging from machinic systems, as well as the
lack of taking responsibility by people designing, selling and deploying such
machines, remains the most pressing ethical discussion in AI.
Related papers
- Debunking Robot Rights Metaphysically, Ethically, and Legally [0.10241134756773229]
We argue that machines are not the kinds of things that may be denied or granted rights.
From a legal perspective, the best analogy to robot rights is not human rights but corporate rights.
arXiv Detail & Related papers (2024-04-15T18:23:58Z) - HumanoidBench: Simulated Humanoid Benchmark for Whole-Body Locomotion and Manipulation [50.616995671367704]
We present a high-dimensional, simulated robot learning benchmark, HumanoidBench, featuring a humanoid robot equipped with dexterous hands.
Our findings reveal that state-of-the-art reinforcement learning algorithms struggle with most tasks, whereas a hierarchical learning approach achieves superior performance when supported by robust low-level policies.
arXiv Detail & Related papers (2024-03-15T17:45:44Z) - Giving Robots a Hand: Learning Generalizable Manipulation with
Eye-in-Hand Human Video Demonstrations [66.47064743686953]
Eye-in-hand cameras have shown promise in enabling greater sample efficiency and generalization in vision-based robotic manipulation.
Videos of humans performing tasks, on the other hand, are much cheaper to collect since they eliminate the need for expertise in robotic teleoperation.
In this work, we augment narrow robotic imitation datasets with broad unlabeled human video demonstrations to greatly enhance the generalization of eye-in-hand visuomotor policies.
arXiv Detail & Related papers (2023-07-12T07:04:53Z) - SACSoN: Scalable Autonomous Control for Social Navigation [62.59274275261392]
We develop methods for training policies for socially unobtrusive navigation.
By minimizing this counterfactual perturbation, we can induce robots to behave in ways that do not alter the natural behavior of humans in the shared space.
We collect a large dataset where an indoor mobile robot interacts with human bystanders.
arXiv Detail & Related papers (2023-06-02T19:07:52Z) - The dynamic nature of trust: Trust in Human-Robot Interaction revisited [0.38233569758620045]
Socially assistive robots (SARs) assist humans in the real world.
Risk introduces an element of trust, so understanding human trust in the robot is imperative.
arXiv Detail & Related papers (2023-03-08T19:20:11Z) - Aligning Robot and Human Representations [50.070982136315784]
We argue that current representation learning approaches in robotics should be studied from the perspective of how well they accomplish the objective of representation alignment.
We mathematically define the problem, identify its key desiderata, and situate current methods within this formalism.
arXiv Detail & Related papers (2023-02-03T18:59:55Z) - HERD: Continuous Human-to-Robot Evolution for Learning from Human
Demonstration [57.045140028275036]
We show that manipulation skills can be transferred from a human to a robot through the use of micro-evolutionary reinforcement learning.
We propose an algorithm for multi-dimensional evolution path searching that allows joint optimization of both the robot evolution path and the policy.
arXiv Detail & Related papers (2022-12-08T15:56:13Z) - Robots with Different Embodiments Can Express and Influence Carefulness
in Object Manipulation [104.5440430194206]
This work investigates the perception of object manipulations performed with a communicative intent by two robots.
We designed the robots' movements to communicate carefulness or not during the transportation of objects.
arXiv Detail & Related papers (2022-08-03T13:26:52Z) - Doing Right by Not Doing Wrong in Human-Robot Collaboration [8.078753289996417]
We propose a novel approach to learning fair and sociable behavior, not by reproducing positive behavior, but rather by avoiding negative behavior.
In this study, we highlight the importance of incorporating sociability in robot manipulation, as well as the need to consider fairness in human-robot interactions.
arXiv Detail & Related papers (2022-02-05T23:05:10Z) - A Review on Trust in Human-Robot Interaction [0.0]
A new field of research in human-robot interaction, namely human-robot trust, is emerging.
This paper reviews the past works on human-robot trust based on the research topics and discuss selected trends in this field.
arXiv Detail & Related papers (2021-05-20T21:50:03Z) - I Need Your Advice... Human Perceptions of Robot Moral Advising
Behaviors [2.0743129221959284]
We explore how robots should communicate in moral advising scenarios.
Our results suggest that, in fact, both humans and robots are judged more positively when they provide the advice that favors the common good over an individual's life.
These results raise critical new questions regarding people's moral responses to robots and the design of autonomous moral agents.
arXiv Detail & Related papers (2021-04-14T16:45:02Z)
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.