scholarly journals Artificial intelligence in healthcare: possibilities of patent protection

2021 ◽  
Vol 14 (2) ◽  
pp. 270-276
Author(s):  
T. N. Erivantseva ◽  
Yu. V. Blokhina
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Patent Protection ◽  
Legal Protection ◽  
Patent Law ◽  
Process Automation ◽  
Scientific Publications ◽  
Key Aspects ◽  
Modern Technologies

The article provides an overview of the advantages and issues associated with the use of artificial intelligence (AI) and machine learning (ML) in medicine. Based on the analysis of scientific publications, the leading healthcare areas using AI and ML have been identified. The applied problems that modern technologies allow to solve are described, as well as the goals that can be achieved using such technologies. The legal protection issues of technologies using AI are highlighted. A comparison is given of the key aspects of copyright and patent law, and the advantages of patent law and comprehensive patent protection of technologies for process automation in healthcare are presented. The possibilities of complex patent protection and its strategy in the leading areas of AI use in healthcare are considered on specific examples.

scholarly journals In defence of machine learning: Debunking the myths of artificial intelligence

2018 ◽  
Vol 14 (4) ◽  
pp. 734-747 ◽  
Author(s):  
Constance de Saint Laurent
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Recent Progress ◽  
Life Time ◽  
Clear Understanding ◽  
Social Scientists ◽  
Scientific Publications ◽  
The Past ◽  
Potential Benefits ◽  
The Media

There has been much hype, over the past few years, about the recent progress of artificial intelligence (AI), especially through machine learning. If one is to believe many of the headlines that have proliferated in the media, as well as in an increasing number of scientific publications, it would seem that AI is now capable of creating and learning in ways that are starting to resemble what humans can do. And so that we should start to hope – or fear – that the creation of fully cognisant machine might be something we will witness in our life time. However, much of these beliefs are based on deep misconceptions about what AI can do, and how. In this paper, I start with a brief introduction to the principles of AI, machine learning, and neural networks, primarily intended for psychologists and social scientists, who often have much to contribute to the debates surrounding AI but lack a clear understanding of what it can currently do and how it works. I then debunk four common myths associated with AI: 1) it can create, 2) it can learn, 3) it is neutral and objective, and 4) it can solve ethically and/or culturally sensitive problems. In a third and last section, I argue that these misconceptions represent four main dangers: 1) avoiding debate, 2) naturalising our biases, 3) deresponsibilising creators and users, and 4) missing out some of the potential uses of machine learning. I finally conclude on the potential benefits of using machine learning in research, and thus on the need to defend machine learning without romanticising what it can actually do.

scholarly journals Convergence of Artificial Intelligence and Intellectual Property Rights

2021 ◽  
Vol 1 ◽  
pp. 4-8
Author(s):  
I.A. Zenin ◽  
Keyword(s):  
Artificial Intelligence ◽  
Intellectual Property Rights ◽  
Patent Protection ◽  
Legal Protection ◽  
Human Mind ◽  
Legal Analysis ◽  
Creative Activity ◽  
Scientific Evaluation ◽  
Intellectual Activity ◽  
Legal Structures

The purpose is to identify and evaluate the doctrinal definitions of the concept and recommendations on ensuring the protection of the results created by AI as products of the functioning of its technologies using the norms of the current copyright, patent and other legislation. At the same time, the goal of scientific evaluation of the existing legal definitions of the concept of AI and its accompanying categories is pursued. The methodology includes methods of logical, historical, systematic and comparative legal analysis of legal definitions, methods of translation (implementation) of doctrinal categories in normative legal acts, interpretation of differences in copyright and patent protection of the results of human creative activity and the need to take them into account when deciding on the possibility of legal protection of products generated by artificial intelligence. Result. As part of the assessment of the existing doctrinal and legal definitions of the concept of AI, its technologies and the possibilities of protecting the protective results created in the course of their operation, conclusions are drawn in favor of legal structures. In the sense of the latter: artificial intelligence is recognized as a human-created “complex of technological solutions”; operations performed by this complex are not identified with human actions, but are recognized only as their similarity (“imitation»); the results of these operations are not equated with the creative achievements of the natural (human) mind, but are recognized as their visibility, which can only be compared (“compared”) with the products of the cognitive functions of the human brain as the results of its “intellectual activity”.

scholarly journals THE FINANCIAL ASPECT OF IoT PROCESS AUTOMATION IN CREATING NEW VALUE FOR THE ECONOMY

2020 ◽  
Vol 18 (2) ◽  
Author(s):  
Nedeljko Šikanjić ◽  
Zoran Ž. Avramović ◽  
Esad Jakupović
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Scientific Paper ◽  
General Purpose ◽  
Advanced Technology ◽  
Process Automation ◽  
Advanced Technologies ◽  
Financial Benefits ◽  
Financial Aspect

In today’s world, devices with possibility to communicate, are emerging and growing daily. This advanced technology is bringing ideas of how to use these devices, in order to gain financial benefits for enterprises, business and economy in general. Purpose of research in this scientific paper is to discover, what are the trends in connecting these devices, called internet of things (IoT), what are financial aspects of implementing IoT solutions and how leaders in area of cloud computing and IoT, are implementing additional advanced technologies such as machine learning and artificial intelligence, to improve processes and gain increase in revenue, while bringing automation in place for the end users. Development of informational society is not only bringing innovation to everyday life, but is also providing effect on the economy. This effect reflects on various business platforms, companies and organizations while increasing the quality of the end product or service that is being provided.

scholarly journals ASSESSMENT OF TRENDS IN THE APPLICATION OF DIGITAL MARKETING

10.23856/3303 ◽  
2019 ◽  
Vol 33 (2) ◽  
pp. 28-35 ◽  
Author(s):  
Inta Kotane ◽  
Daina Znotina ◽  
Serhii Hushko
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Applied Research ◽  
Business Models ◽  
Digital Marketing ◽  
The Internet ◽  
Sources Of Information ◽  
Scientific Publications ◽  
Method Analysis ◽  
Descriptive Method

One of the conditions for the future development of companies is the identification and use of digital capabilities. In recent years, the environment in which we live and work has changed radically. If the emergence of the Internet was revolutionary in the way we communicate and obtain information, currently the availability and mobility of technologies affects consumers' habits and promotes the transformation of classic business models. Aim of the study: to explore and learn about the development trends of digital marketing. Applied research methods: monographic descriptive method, analysis, synthesis, statistical method. The study based on scientific publications, statistics and other sources of information. The results of the study show that in 2019 digital marketing tools are most actively used: artificial intelligence / augmented reality / machine learning; video marketing; chatbots, virtual assistants.

scholarly journals Modern technologies of marketing research and market analysis

2021 ◽  
Vol 2021 (2) ◽  
pp. 29-39
Author(s):  
Oleh Duma ◽  
◽  
M. Melnyk ◽  
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Big Data ◽  
Human Life ◽  
Marketing Research ◽  
Research Process ◽  
Target Market ◽  
Advantages And Disadvantages ◽  
Marketing Activities ◽  
Modern Technologies

Nowadays, marketing research is increasingly important for the success of enterprises. Conducting marketing research reduces the risk of making wrong decisions in the analysis and development of marketing strategies, planning and control of marketing activities. The article provides an overview of the emergence of marketing research, explores the latest methods of marketing research, their advantages and disadvantages, the possibility of its application at different stages of marketing activities. Scientific approaches to the interpretation of the concepts "marketing research", "methods of marketing research" are systematized. The latest methods of marketing research that widely use AI, Big Data, ML, TRI * M, have been studied. The technologies of mobile advertising, areas of use of artificial intelligence, the essence and features of the formation of Big Data and machine learning were researched in the article. The benefits of using artificial intelligence, big data and machine learning to conduct marketing research were researched in the article. Analytical materials are confirmed by cases from the practice of marketing research. All research outcomes were proved by cases of Independent Media, TNS Ukraine, British Council, Chat fuel and Coca - Cola. The scheme of the marketing research process is supplemented by the possibilities of applying the latest technologies, which are grouped by stages. Any marketing research is a sequence of steps. Each of them uses a set of tools that provide collection, processing and analysis of data about the target market, customers, or economic processes. Each of these stages can be implemented using the modern technologies that are widely used in various spheres of human life. The directions of application the artificial intelligence, Big data, machine learning for carrying out office researches, field researches, pilot researches and a method of focus groups are offered. The analysis of realization of methods of marketing researches on the basis of Big Data, AI, ML is carried out.

Robot Process Automation (RPA) and Its Future

2022 ◽  
pp. 35-58
Author(s):  
Ozge Doguc
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Computer Vision ◽  
Customer Satisfaction ◽  
Human Behavior ◽  
The Other ◽  
Human Intervention ◽  
Process Automation ◽  
Robotic Process Automation ◽  
Human Agent

Many software automation techniques have been developed in the last decade to cut down cost, improve customer satisfaction, and reduce errors. Robotic process automation (RPA) has become increasingly popular recently. RPA offers software robots (bots) that can mimic human behavior. Attended robots work in tandem with humans and can operate while the human agent is active on the computer. On the other hand, unattended robots operate behind locked screens and are designed to execute automations that don't require any human intervention. RPA robots are equipped with artificial intelligence engines such as computer vision and machine learning, and both robot types can learn automations by recording human actions.

scholarly journals The A.I. storyteller: Perpetuating orality using developments in machine learning

2021 ◽  
Author(s):  
Soo Anne Mahabir Mahabir
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Theoretical Foundation ◽  
Physical Computing ◽  
Generative Art ◽  
Artificial Intelligence Research ◽  
Theatrical Design ◽  
Video Recordings ◽  
Art Philosophy ◽  
Key Aspects

Oral histories are a part of all cultures and societies, however, our knowledge and interest in these practices has waned, and arguably with it, a sense of social identity and belonging in many contemporary communities and cultures. This paper pulls from aspects of experiential and theatrical design, generative art philosophy, physical computing, and machine learning in artificial intelligence research combined with a theoretical foundation of Adorno, Benjamin, and Ong to discuss and propose the creation of an embodied and immersive story experience. This project will overturn key aspects of traditional orality to encourage interactivity with, and ownership of, the stories and will prompt discussion about its use as an archival process that will promote perpetuation rather than preservation, moving beyond the current processes of audio and video recordings.

Robot Process Automation (RPA) and Its Future

2020 ◽  
pp. 469-492
Author(s):  
Ozge Doguc
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Computer Vision ◽  
Customer Satisfaction ◽  
Human Behavior ◽  
The Other ◽  
Human Intervention ◽  
Process Automation ◽  
Robotic Process Automation ◽  
Human Agent

Many software automation techniques have been developed in the last decade to cut down cost, improve customer satisfaction, and reduce errors. Robotic process automation (RPA) has become increasingly popular recently. RPA offers software robots (bots) that can mimic human behavior. Attended robots work in tandem with humans and can operate while the human agent is active on the computer. On the other hand, unattended robots operate behind locked screens and are designed to execute automations that don't require any human intervention. RPA robots are equipped with artificial intelligence engines such as computer vision and machine learning, and both robot types can learn automations by recording human actions.

Sign in / Sign up

Export Citation Format

Share Document