Figure - available from: Journal of Robotics
This content is subject to copyright. Terms and conditions apply.
![(a) Medical robot helping an elderly patient [8]. (b) Architecture of EEG-based e-robot agent [8].](publication/354928093/figure/fig4/AS:1080234346586121@1634559346055/a-Medical-robot-helping-an-elderly-patient-8-b-Architecture-of-EEG-based-e-robot.jpg)
Source publication
![(a) Medical robot helping an elderly patient [8]. (b) Architecture of...](publication/354928093/figure/fig3/AS:1080234342396031@1634559345952/a-Medical-robot-helping-an-elderly-patient-8-b-Architecture-of-EEG-based-e-robot_Q320.jpg)
![(a) Medical robot helping an elderly patient [8]. (b) Architecture of...](publication/354928093/figure/fig4/AS:1080234346586121@1634559346055/a-Medical-robot-helping-an-elderly-patient-8-b-Architecture-of-EEG-based-e-robot_Q320.jpg)
![Gordon robot with silicone brain [14].](publication/354928093/figure/fig5/AS:1080234346590258@1634559346558/Gordon-robot-with-silicone-brain-14_Q320.jpg)
An autonomous household robot passed a self-awareness test in 2015, proving that the cognitive capabilities of robots are heading towards those of humans. While this is a milestone in AI, it raises questions about legal implications. If robots are progressively developing cognition, it is important to discuss whether they are entitled to justice pu...
Citations
... As noted in the Introduction, the concepts of creativity (Ihalainen, 2018;Wachowicz & Goncalves, 2019;Papadopoulou, 2021), legal subjectness and human-like rights (McNally & Inayatullah, 1988;Marko, 2019;Persaud et al., 2021;Kiškis, 2023;Wojtczak, 2020) are increasingly applied to artificial intelligence (AI). This section considers this issue from the developed theoretical basis. ...
Recent developments in artificial intelligence urge clarification of its ethical and legal status. The issue revolves around the concept of subjectness, distinguishing active and responsible conduct from inert performance. We analyze this notion from a physical viewpoint, building on the quantum-theoretic refinement of the concept of uncertainty into quantum and classical types: quantum uncertainty refers to an objective freedom to construct the future, while classical uncertainty denotes subjective ignorance of present states of nature. Subjectness of intelligence is then defined by the kind of uncertainty it is capable to resolve. To analyze different aspects of intelligence, quantum-inspired definitions of decision, subjectness, originality, and meaning are introduced on this basis. These concepts are first calibrated on natural intelligence and then applied to artificial systems, classified as classical and quantum. Classical AI then appears fundamentally alien to subjectness due to its algorithmic nature, limited to the resolution of classical uncertainty. Quantum AI, in contrast, breaks this limit by hosting some degree of proto-subjectness on the level of elementary particles, involved in its operation. Fundamentally, our approach tracks alternative views on subjectness of intelligence to the interpretations of quantum randomness, identifying both as different sides of the same ethical dilemma. Quantum physics then provides fertile ground for possible solutions, aligned with Eastern and Western views on freedom and constraint, subject and context in social life. These results offer a scientific approach to the controversial challenges of socio-technological development, integrating physical and humanitarian perspectives.
... reasoning by using commonsense knowledge in suitable applications, making robots navigate paths well in hospitals and other healthcare settings, and considering ethical issues related to robots. Hence, some of this work could benefit from our own related research on advances in commonsense knowledge based human-robot collaboration (HRC) in particular [7][8][9], specific applications and discussions on robotics [29,30] as well as the general usefulness of commonsense knowledge in various AI systems [34,42]. We can therefore conduct detailed investigations on these aspects as topics of future work, thriving upon our expertise in these areas, as evident from the aforementioned publications. ...
Multimedia data plays an important role in medicine and healthcare since EHR (Electronic Health Records) entail complex images and videos for analyzing patient data. In this article, we hypothesize that transfer learning with computer vision can be adequately harnessed on such data, more specifically chest X-rays, to learn from a few images for assisting accurate, efficient recognition of COVID. While researchers have analyzed medical data (including COVID data) using computer vision models, the main contributions of our study entail the following. Firstly, we conduct transfer learning using a few images from publicly available big data on chest X-rays, suitably adapting computer vision models with data augmentation. Secondly, we aim to find the best fit models to solve this problem, adjusting the number of samples for training and validation to obtain the minimum number of samples with maximum accuracy. Thirdly, our results indicate that combining chest radiography with transfer learning has the potential to improve the accuracy and timeliness of radiological interpretations of COVID in a cost-effective manner. Finally, we outline applications of this work during COVID and its recovery phases with future issues for research and development. This research exemplifies the use of multimedia technology and machine learning in healthcare.
... If robots are introduced into the legal landscape, they will invariably become rights-possessing entities. Therefore, it becomes essential to crystallize standards on the responsibilities bordering on sentience and rationality expected to be discharged by the robots [53]. There are discussions encircling the accountability of robots. ...
The legal ecosystem is continuously confronted with new challenges and disruptions as a result of the technological invasion initiated by cutting-edge technologies, such as Artificial Intelligence (AI) and Robotics, which have taken over the world. The amalgamation of AI-enabled mechanisms and robotics into human life has elevated significant issues. This digital juggernaut cannot stay constant by the legal landscape, and some degree of assimilation is permitted to pave the way for the efficient administration of justice. The current study is significant since there is a substantial absence of legal research into the implications of AI and robotics on legal rights, which undoubtedly impacts the legal ecosystem. In this study, we have examined the significance, progress, and challenges of integrating Robotics and AI into the legal ecosystem, as they pave way for resilient legal infrastructure. Issues such as privacy, ethical grievances, data protection, confidentiality, and integrity issues are evaluated in this study. The study reviewed existing research into AI and robotics intervention in the legal ecosystem to propose a framework for addressing the increased concerns about the implications of technological apparatus in the legal ecosystem. Finally, the study concludes with recommendations that can be adopted for future work.
Massive inclusion of artificial intelligence (AI) in the technosphere and electronic governments urges an update in legal regulation of these and related areas. The issue converges on the key question of whether AI can be endowed with legal personhood and capacity. Opposing views in this respect build on hardly compatible ethics and largely outdated scientific grounds with a clear perspective for deep cultural antagonisms and further fragmentation of the world. We contribute to this debate from the perspective of quantum cognitive science and show how it can resolve some of the current impasses. Our approach builds on the quantum-theoretic refinement of the concept of uncertainty into quantum and classical types: classical uncertainty denotes subjective ignorance of the present state of affairs, while quantum uncertainty accounts for individual freedom to construct the future. We show that legal capacity of intelligence, at bottom, is defined by the type of uncertainty it is capable to resolve. Natural intelligence, in particular, can resolve quantum uncertainties, generating genuine novelty and affective experience in the process. Classical AI, in contrast, is limited to algorithmic computation, bound to produce predefined results regardless of its complexity. Concepts of decision-making, subjectness, creativity, and personal meaning then are recognized as physically inapplicable to such systems. The proposed definitions of these terms complement and sharpen the criteria of legal capacity in the existing legislations, indicating that “autonomy” is essentially equivalent to “appreciation.” Classical AI then appears as fundamentally alien to subjectness and legal capacity both in civil and common laws, resolving a delicate contradiction between them. Quantum-empowered AI, in contrast, escapes this conclusion due to its access to quantum uncertainty, introducing novel challenges with respect to responsibility gaps and meaningful human control. The developed approach aligns with the present legal practice and ethical discourse, contributing to the scientifically informed development of law in technological societies.
The prominence of robots as interdependent social agents continues to grow, leading to important conversations about legal and ethical considerations not just for humans, but also potentially for these autonomous agents (e.g., robot rights). Physical properties of the robot form factor have been shown to significantly impact human interactions with the system, including how law and policy-makers see and ascribe characteristics to it. For social robots in particular, an anthropomorphized or humanoid form factor can lead to assumptions about the robot’s personhood, with potentially harmful ethical consequences. In this paper, we review current outlooks on social robots with regards to policy and personhood, particularly limits of current debates. We then provide a suggested redefinition of personhood for a robot with an emphasis on the dissociation of personhood from the humanoid form. We propose the treatment of robot personhood in terms of as interdependent group personhood rather than physical or anthropomorphic features, and suggest corresponding design principles and regulations about features such as system opacity.
