Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userArtificial Creations: Ascription, Ownership, Time-Specific Monopolies
84
0
0.0
(
0
)
Added by
Raj Shekhar
Publication date
2020
fields
Informatics Engineering
and research's language is
English
Authors
Raj Shekhar
Ask ChatGPT about the research
No Arabic abstract
Creativity has always been synonymous with humans. No other living species could boast of creativity as humans could. Even the smartest computers thrived only on the ingenious imaginations of its coders. However, that is steadily changing with highly advanced artificially intelligent systems that demonstrate incredible capabilities to autonomously (i.e., with minimal or no human input) produce creative products that would ordinarily deserve intellectual property status if created by a human. These systems could be called artificial creators and their creative products artificial creations. The use of artificial creators is likely to become a part of mainstream production practices in the creative and innovation industries sooner than we realize. When they do, intellectual property regimes (that are inherently designed to reward human creativity) must be sufficiently prepared to aptly respond to the phenomenon of what could be called artificial creativity. Needless to say, any such response must be guided by considerations of public welfare. This study analyzes what that response ought to look like by revisiting the determinants of intellectual property and critiquing its nature and modes. This understanding of intellectual property is then applied to investigate the determinants of intellectual property in artificial creations so as to determine the intrinsic justifications for intellectual property rewards for artificial creativity, and accordingly, develop general modalities for granting intellectual property status to artificial creations. Finally, the treatment of artificial works (i.e., copyrightable artificial creations) and artificial inventions (i.e., patentable artificial creations) by current intellectual property regimes is critiqued, and specific modalities for granting intellectual property status to artificial works and artificial inventions are developed.
rate research
Read More
This study delves into the research question: how does gender influence smartphone ownership and autonomy in using the internet among the youth in rural India? This paper explores the influence of local culture on smartphone ownership and autonomy through an ethnographic study among rural Indian youth by analysing the intersection of gender with other identity axes. The findings show that young peoples smartphone ownership and autonomy is shaped by their social and cultural setting, and could lead to various inequalities in their internet usage. This study shows that gender paves way for various disparities with regard to smartphone ownership and internet usage. Decolonisation of the understanding of smartphone ownership and internet usage patterns of the youth in the Global South suggests a reconsideration of the user experience designs and platform policies.
The rise of Artificial Intelligence (AI) will bring with it an ever-increasing willingness to cede decision-making to machines. But rather than just giving machines the power to make decisions that affect us, we need ways to work cooperatively with AI systems. There is a vital need for research in AI and Cooperation that seeks to understand the ways in which systems of AIs and systems of AIs with people can engender cooperative behavior. Trust in AI is also key: trust that is intrinsic and trust that can only be earned over time. Here we use the term AI in its broadest sense, as employed by the recent 20-Year Community Roadmap for AI Research (Gil and Selman, 2019), including but certainly not limited to, recent advances in deep learning. With success, cooperation between humans and AIs can build society just as human-human cooperation has. Whether coming from an intrinsic willingness to be helpful, or driven through self-interest, human societies have grown strong and the human species has found success through cooperation. We cooperate in the small -- as family units, with neighbors, with co-workers, with strangers -- and in the large as a global community that seeks cooperative outcomes around questions of commerce, climate change, and disarmament. Cooperation has evolved in nature also, in cells and among animals. While many cases involving cooperation between humans and AIs will be asymmetric, with the human ultimately in control, AI systems are growing so complex that, even today, it is impossible for the human to fully comprehend their reasoning, recommendations, and actions when functioning simply as passive observers.
The Internet of Things (IoT) and edge computing applications aim to support a variety of societal needs, including the global pandemic situation that the entire world is currently experiencing and responses to natural disasters. The need for real-time interactive applications such as immersive video conferencing, augmented/virtual reality, and autonomous vehicles, in education, healthcare, disaster recovery and other domains, has never been higher. At the same time, there have been recent technological breakthroughs in highly relevant fields such as artificial intelligence (AI)/machine learning (ML), advanced communication systems (5G and beyond), privacy-preserving computations, and hardware accelerators. 5G mobile communication networks increase communication capacity, reduce transmission latency and error, and save energy -- capabilities that are essential for new applications. The envisioned future 6G technology will integrate many more technologies, including for example visible light communication, to support groundbreaking applications, such as holographic communications and high precision manufacturing. Many of these applications require computations and analytics close to application end-points: that is, at the edge of the network, rather than in a centralized cloud. AI techniques applied at the edge have tremendous potential both to power new applications and to need more efficient operation of edge infrastructure. However, it is critical to understand where to deploy AI systems within complex ecosystems consisting of advanced applications and the specific real-time requirements towards AI systems.
This article conducts a literature review of current and future challenges in the use of artificial intelligence (AI) in cyber physical systems. The literature review is focused on identifying a conceptual framework for increasing resilience with AI through automation supporting both, a technical and human level. The methodology applied resembled a literature review and taxonomic analysis of complex internet of things (IoT) interconnected and coupled cyber physical systems. There is an increased attention on propositions on models, infrastructures and frameworks of IoT in both academic and technical papers. These reports and publications frequently represent a juxtaposition of other related systems and technologies (e.g. Industrial Internet of Things, Cyber Physical Systems, Industry 4.0 etc.). We review academic and industry papers published between 2010 and 2020. The results determine a new hierarchical cascading conceptual framework for analysing the evolution of AI decision-making in cyber physical systems. We argue that such evolution is inevitable and autonomous because of the increased integration of connected devices (IoT) in cyber physical systems. To support this argument, taxonomic methodology is adapted and applied for transparency and justifications of concepts selection decisions through building summary maps that are applied for designing the hierarchical cascading conceptual framework.
With the recent advances of the Internet of Things, and the increasing accessibility of ubiquitous computing resources and mobile devices, the prevalence of rich media contents, and the ensuing social, economic, and cultural changes, computing technology and applications have evolved quickly over the past decade. They now go beyond personal computing, facilitating collaboration and social interactions in general, causing a quick proliferation of social relationships among IoT entities. The increasing number of these relationships and their heterogeneous social features have led to computing and communication bottlenecks that prevent the IoT network from taking advantage of these relationships to improve the offered services and customize the delivered content, known as relationship explosion. On the other hand, the quick advances in artificial intelligence applications in social computing have led to the emerging of a promising research field known as Artificial Social Intelligence (ASI) that has the potential to tackle the social relationship explosion problem. This paper discusses the role of IoT in social relationships detection and management, the problem of social relationships explosion in IoT and reviews the proposed solutions using ASI, including social-oriented machine-learning and deep-learning techniques.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
