Art Of Intelligence Research Articles

Developing and validating an artificial intelligent empowerment instrument: evaluating the impact of an artificial intelligent literacy programme for secondary school and university students

Artificial intelligence (AI) is rapidly transforming various sectors of society, requiring a new form of literacy: AI literacy. This study validated a new instrument designed to measure students’ AI empowerment conceptualised as consisting of four components: impact, self-efficacy in AI, creative self-efficacy in AI, and meaningfulness. Confirmatory factor analysis was used to validate the proposed components of the AI empowerment instrument. The sample comprised 224 secondary school and university students who completed an 18-hour AI literacy programme. The results showed that the students’ AI empowerment was significantly increased by the AI literacy programme. Specifically, the AI literacy programme was found to narrow the gender gap in AI empowerment. Furthermore, the results highlighted that prior programming experience did not significantly affect AI empowerment, indicating that AI literacy can be achieved regardless of programming experience. This study provides a theoretical framework for understanding and quantifying the extent to which individuals feel empowered after engaging with AI activities for its conceptual understanding. It provides educators with a tool to measure students’ understanding and confidence in their AI abilities. The study also suggests directions for future research.

The impact of AI marketing activities on consumer-based brand equity: The mediating role of brand experience

In today’s rapidly evolving world, the integration of artificial intelligence (AI) technologies has become paramount, offering unparalleled value propositions and unparalleled consumer experiences. This study delves into the transformative impact of five AI activities on brand experience and consumer-based brand equity within the retail banking landscape of Lebanon. Employing a quantitative deductive approach and a sample of 211 respondents, the research employs structural equation modeling to analyze the data. The findings underscore the significant influence of four AI marketing activities on brand experience, revealing that factors such as information, accessibility, and customization play pivotal roles, while interaction has a less pronounced effect. Importantly, the study unveils that brand experience acts as a partial mediator between AI marketing activities and consumer-based brand equity. These revelations not only illuminate pathways for retail banks in Lebanon to refine their AI strategies but also underscore the importance of leveraging AI-driven marketing initiatives to bolster customer equity, acquisition, and retention efforts in an increasingly competitive market age.

Creating AI business value through BPM capabilities

PurposeAlthough businesses continue to take up artificial intelligence (AI), concerns remain that companies are not realising the full value of their investments. The study aims to provide insights into how AI creates business value by investigating the mediating role of Business Process Management (BPM) capabilities.Design/methodology/approachThe integrative model of IT Business Value was contextualised, and structural equation modelling was applied to validate the proposed serial multiple mediation model using a sample of 448 organisations based in the EU.FindingsThe results validate the proposed serial multiple mediation model according to which AI adoption increases organisational performance through decision-making and business process performance. Process automation, organisational learning and process innovation are significant complementary partial mediators, thereby shedding light on how AI creates business value.Research limitations/implicationsIn pursuing a complex nomological framework, multiple perspectives on realising business value from AI investments were incorporated. Several moderators presenting complementary organisational resources (e.g. culture, digital maturity, BPM maturity) could be included to identify behaviour in more complex relationships. The ethical and moral issues surrounding AI and its use could also be examined.Practical implicationsThe provided insights can help guide organisations towards the most promising AI activities of process automation with AI-enabled decision-making, organisational learning and process innovation to yield business value.Originality/valueWhile previous research assumed a moderated relationship, this study extends the growing literature on AI business value by empirically investigating a comprehensive nomological network that links AI adoption to organisational performance in a BPM setting.

Managing Risk and Quality of AI in Healthcare: Are Hospitals Ready for Implementation?

Artificial intelligence (AI) provides a unique opportunity to help meet the demands of the future healthcare system. However, hospitals may not be well equipped to handle safe and effective development and/or procurement of AI systems. Furthermore, upcoming regulations such as the EU AI Act may enforce the need to establish new management systems, quality assurance and control mechanisms, novel to healthcare organizations. This paper discusses challenges in AI implementation, particularly potential gaps in current management systems (MS), by reviewing the harmonized standard for AI MS, ISO 42001, as part of a gap analysis of a tertiary acute hospital with ongoing AI activities. Examination of the industry agnostic ISO 42001 reveals a technical debt within healthcare, aligning with previous research on digitalization and AI implementation. To successfully implement AI with quality assurance in mind, emphasis should be put on the foundation and structure of the healthcare organizations, including both workforce and data infrastructure.

К ВОПРОСУ О ПОЛИСУБЪЕКТНОСТИ ИНТЕЛЛЕКТУАЛЬНОЙ ДЕЯТЕЛЬНОСТИ В ОТНОШЕНИЯХ ДУХОВНОЙ СОБСТВЕННОСТИ

The relevance of this research is determined by the demand of the analysis of the multiplicity of subjects as sources and carriers of activity in intellectual activity for various purposes (for example, in culture, art, information production, mass communications, etc.). On the other hand, the problems of inter-confessional conflicts and the promotion of spiritual values by various confessions are acute. Also, various issues related to the revival of religiosity are important for Russian atheists, Muslims, Orthodox and other confessions. The aim of the work is to study complex issues of poly-subjectivity in intellectual activity in modern processes of preservation and development of spiritual property. Scientific induction, N. Luhmann’s social differentiation and the concept of poly-subject sociality of the Ural Philosophical School are used as methodological bases. The main results of the study include a shift in the priorities of socio-philosophical research of intellectual activity in the relations of spiritual property from the predominant analysis of dialogues to the analysis of poli-logues, from paired forms of cooperation to simultaneous and multiple cooperation of many subjects with socio-cultural communities and systems of spiritual property. The scientific novelty includes estimates of the local elimination of contradiction of «individual» and «social» in large poly-subject networks of intellectual activity (for example, in the national project for the development of the digital economy). Indeed, the overall possible intensity of intellectual activity of interconnected mono-subjects in the limit transition grows proportionally to the second degree of their number (i.e. a poly-subject network becomes a societal network). The directions of further research are determined by the prospects and problems of analyzing the impending breakthrough in the development of artificial intelligence (AI) and the problems of subjectivity of both these developments and the results of AI activities. Further refinement and development of the poly-subject chronotopic concept of analyzing subjectivity in intellectual activity in relations of spiritual property is recommended for diachronic and synchronous study of their role in social space and social time.

ADVANTAGES AND DRAWBACKS OF CHATGPT IN THE CONTEXT OF DRAFTING SCHOLARLY ARTICLES

Incorporating Artificial Intelligence (AI), particularly ChatGPT, in academic endeavors has attracted significant interest due to its ability to optimize procedures and enhance human capacities. ChatGPT serves as an informed partner, assisting researchers in doing literature reviews, generating ideas, and even composing scholarly articles. Nevertheless, this revolutionary technology gives rise to ethical considerations in scientific investigation, namely authorship, information-data privacy, and bias. The article thoroughly examines the advantages and disadvantages of using ChatGPT for academic purposes. The benefits are seen in its effectiveness in retrieving information, surpassing language obstacles, boosting the synthesis of literature, easing the production of ideas, and assisting in the outlining of manuscripts. On the other hand, the complicated nature of using ChatGPT in scholarly activities is emphasized by worries about scientific integrity, the possibility of spreading disinformation, excessive dependence, and security and privacy issues. Finding a middle ground between utilizing the advantages of ChatGPT and maintaining academic integrity is crucial. Analyzing the dynamics will be crucial in navigating the changing junction of AI and research activities.

Prospects for Machine Learning Activity within the United States National Weather Service

Abstract The National Weather Service (NWS) Office of Science and Technology Integration commissioned a report to assess the status of artificial intelligence (AI) and machine learning (ML) activity within the agency with a view toward identifying existing obstacles and recommending future directions. The purpose of this essay is to communicate the steps that the NWS plans to take to realize the potential benefits of AI in operations. AI activities are growing rapidly within atmospheric sciences, and the NWS is part of this growth. However, the activity is fragmented and lacks the needed infrastructure for improved coordination of effort. Current obstacles to progress include insufficient workforce training in AI/ML, a lack of curated datasets and software that can be used for development and evaluation of these approaches, the absence of a centralized clearing house available to NWS personnel for technical expertise and consultation, limited operational compute resources, and a lack of a clear end-to-end project pathway that encompasses exploration, development, testbed/proving ground, and operational implementation. These limitations are addressable. Training materials specific to NWS interests can be developed through collaboration with existing NOAA centers. Establishing a reference library staffed with AI/ML consultants tasked with collaborating with operational units would reduce siloed efforts and enhance productivity. Establishing funding vehicles for theme-based projects with a sustainable pathway through operational implementation would help bridge the research-to-operations “valley of death.” Given the growth of AI/ML across the U.S. Weather Enterprise and the already substantial involvement of academic and private sector entities, these developments within the NWS will be of interest to the atmospheric science field.

The concept of responsible artificial intelligence as the future of artificial intelligence in medicine

Active deployment of artificial intelligence (AI) systems in medicine creates many challenges. Recently, the concept of responsible artificial intelligence (RAI) was widely discussed, which is aimed at solving the inevitable ethical, legal, and social problems. The scientific literature was analyzed and the possibility of applying the RAI concept to overcome the existing AI problems in medicine was considered. Studies of possible AI applications in medicine showed that current algorithms are unable to meet the basic enduring needs of society, particularly, fairness, transparency, and reliability. The RAI concept based on three principles accountability for AI activities and responsibility and transparency of findings (ART) was proposed to address ethical issues. Further evolution, without the development and application of the ART concept, turns dangerous and impossible the use of AI in such areas as medicine and public administration. The requirements for accountability and transparency of conclusions are based on the identified epistemological (erroneous, non-transparent, and incomplete conclusions) and regulatory (data confidentiality and discrimination of certain groups) problems of using AI in digital medicine [2]. Epistemological errors committed by AI are not limited to omissions related to the volume and representativeness of the original databases analyzed. In addition, these include the well-known black box problem, i.e. the inability to look into the process of forming AI outputs when processing input data. Along with epistemological errors, normative problems inevitably arise, including patient confidentiality and discrimination of some social groups due to the refusal of some patients to provide medical data for training algorithms and as part of the analyzed databases, which will lead to inaccurate AI conclusions in cases of certain gender, race, and age. Importantly, the methodology of the AI data analysis depends on the program code set by the programmer, whose epistemological and logical errors are projected onto the AI. Hence the problem of determining responsibility in the case of erroneous conclusions, i.e. its distribution between the program itself, the developer, and the executor. Numerous professional associations design ethical standards for developers and a statutory framework to regulate responsibility between the links described. However, the state must play the greatest role in the development and approval of such legislation. The use of AI in medicine, despite its advantages, is accompanied by many ethical, legal, and social challenges. The development of RAI has the potential both to solve these challenges and to further the active and secure deployment of AI systems in digital medicine and healthcare.

Artificial intelligence applied in pulmonary hypertension: a bibliometric analysis.

Advances in Artificial Intelligence (AI) offer new Information Technology (IT) opportunities in various applications and fields (industry, health, etc.). The medical informatics scientific community expends tremendous effort on the management of diseases affecting vital organs making it a complex disease (lungs, heart, brain, kidneys, pancreas, and liver). Scientific research becomes more complex when several organs are simultaneously affected, as is the case with Pulmonary Hypertension (PH), which affects both the lungs and the heart. Therefore, early detection and diagnosis of PH are essential to monitor the disease's progression and prevent associated mortality. The issue addressed relates to knowledge of recent developments in AI approaches applied to PH. The aim is to provide a systematic review through a quantitative analysis of the scientific production concerning PH and the analysis of the networks of this production. This bibliometric approach is based on various statistical, data mining, and data visualization methods to assess research performance using scientific publications and various indicators (e.g., direct indicators of scientific production and scientific impact). The main sources used to obtain citation data are the Web of Science Core Collection and Google Scholar. The results indicate a diversity of journals (e.g., IEEE Access, Computers in Biology and Medicine, Biology Signal Processing and Control, Frontiers in Cardiovascular Medicine, Sensors) at the top of publications. The most relevant affiliations are universities from United States of America (Boston Univ, Harvard Med Sch, Univ Oxford, Stanford Univ) and United Kingdom (Imperial Coll London). The most cited keywords are "Classification", "Diagnosis", "Disease", "Prediction", and "Risk". This bibliometric study is a crucial part of the review of the scientific literature on PH. It can be viewed as a guideline or tool that helps researchers and practitioners to understand the main scientific issues and challenges of AI modeling applied to PH. On the one hand, it makes it possible to increase the visibility of the progress made or the limits observed. Consequently, it promotes their wide dissemination. Furthermore, it offers valuable assistance in understanding the evolution of scientific AI activities applied to managing the diagnosis, treatment, and prognosis of PH. Finally, ethical considerations are described in each activity of data collection, treatment, and exploitation to preserve patients' legitimate rights.

Творческий потенциал систем искусственного интеллекта в контексте идеи нового просвещения

The modern world is confronted with a series of global problems, exacerbated by technological advancements. In this context, concerns arise in the public consciousness regarding the potential of artificial intelligence (AI) to surpass humans in intellectual and creative activities. The topic of AI creativity becomes pertinent and sparks debates within the scientific community regarding its creative potential. In response to these challenges, members of the Club of Rome in 2018 propose the concept of a new Enlightenment and the principle of balance as a response to the demands of technological development. These ideas underscore the need for a balanced approach to technical progress, taking into account global values and ethical principles. I explore the definitions of creativity and AI, formulate criteria for assessing creativity, and analyse recent achievements in modelling creative processes in AI. I also focus on the utilisation of various algorithms for implementing diverse forms of creative activities, including text, image and music generation. Additionally, I present diverse opinions of researchers regarding creativity in AI. To systematise these perspectives, I propose a classification which allows their ranking. The conclusion emphasises that currently the issue of evaluating the creative potential of AI lacks a definitive solution, underscoring the relevance of further research. The future outlook may alter this situation, prompting the necessity to focus on predicting potential consequences of technological developments and developing mechanisms for controlling AI activities; humans, after all, bear responsibility for AI actions. Such an approach aligns with the concept of a new Enlightenment which seeks a balance between technological advancements and the preservation of global harmony.

인공지능의 국제법상 책임추궁에 관한 소고

This article examines the invocation of international responsibility arising from activities of the Artificial Intelligence(AI). The AI has capabilities to recognize the circumstances and determine beyond instruction or control of humans, and as a result it has become important how to regulate international responsibility involving the AI activities. This article examines the question whether it is possible and appropriate to apply the Draft Articles on Responsibility of States for Internationally Wrongful Acts adopted by the International Law Commission to international wrongful acts through the AI.
 The AI is characterized as an autonomous entity, in that it performs certain activities without human involvement in its perception and judgment. However, the AI is not currently recognized as an international person by the international community. In this regard, this article classifies types of internationally wrongful acts through the AI, then explores pathways to invoke state responsibility in light of each type of acts. First of all, the rules of attribution shall be streamlined to international activities involving the AI. In particular, the effective control test which has been utilized as a standard for attributing activities of a person or the group of persons to a state is not appropriate in attributing the activities of the AI to relevant state entities. Secondly, this article submits that state responsibility involving the AI activities may be invoked based on due diligence obligation of states. In conclusion, it is not appropriate to apply the current jurisprudence of state responsibility to activities involving the AI, and accordingly it is necessary to consider due diligence obligation in invoking international responsibility of states in utilizing the AI.

Differentiating artificial intelligence activity clusters in Australia

We demonstrate how cluster analysis underpinned by analysis of revealed technology advantage can be used to differentiate geographic regions by activity in artificial intelligence (AI). Our analysis uses novel datasets on Australian AI businesses, intellectual property patents and labour markets to explore location, concentration and intensity of AI activities across 333 geographical regions. We find that Australia's AI business and innovation activity is clustered in geographic locations with higher investment in research and development. Through cluster analysis we identify three tiers of AI capability regions that are developing across the economy: ‘AI hotspots’ (10 regions), ‘Emerging AI regions’ (85 regions) and ‘Nascent AI regions’ (238 regions). While the AI hotspots are mainly concentrated in central business district (CBD) locations, there are examples when they also appear outside CBD in areas where there has been significant investment in innovation and technology hubs. Policy makers and investors can use these results to learn about the current landscape of AI business and innovation activities in Australia, identify potential growth opportunities in AI capabilities and to guide future policy and business decisions.

A Socially Relevant Focused AI Curriculum Designed for Female High School Students

Historically, female students have shown low interest in the field of computer science. Previous computer science curricula have failed to address the lack of female-centered computer science activities, such as socially relevant and real-life applications. Our new summer camp curriculum introduces the topics of artificial intelligence (AI), machine learning (ML) and other real-world subjects to engage high school girls in computing by connecting lessons to relevant and cutting edge technologies. Topics range from social media bots, sentiment of natural language in different media, and the role of AI in criminal justice, and focus on programming activities in the NetsBlox and Python programming languages. Summer camp teachers were prepared in a week-long pedagogy and peer-teaching centered professional development program where they concurrently learned and practiced teaching the curriculum to one another. Then, pairs of teachers led students in learning through hands-on AI and ML activities in a half-day, two-week summer camp. In this paper, we discuss the curriculum development and implementation, as well as survey feedback from both teachers and students.

Intellectual property and artificial intelligence: who is the author?

The economic and legal aspects of the regulation of artificial intelligence (AI) technologies, their influence on scientific and inventive activity are studied. The role of protection of intellectual property (IP) - (patent and copyright) in different economies and jurisdictions in ensuring the balance of competing interests, identifies existing problems and identifies ways to solve them. AI is seen as one of the most important dual-use technologies, a new challenge for the economy and the legal system, a new phenomenon that has a multiplier effect, a legal phenomenon in the structure of legal relations, a new object for legal regulation. AI is able to generate and create various works - science, literature and art. These circumstances raise problems of recognition of authorship, the possibility of authors to dispose of their rights and their use of mechanisms for legal protection of IP objects. The main provisions of the Resolution of the European Parliament of October 20, 2020 on intellectual property rights in the development of artificial intelligence technologies (2020/2015 (INI)), the Resolution of the International Association for the Protection of Intellectual Property (AIPPI) 2020 on the inventory of inventions using AI. The analysis of the legislative and law enforcement practice of the European Patent Office (EPO), the US Patent and Trademark Office (USPTO) and the UK Intellectual Property Office (UKIPO), regional and international documents on the regulation of AI and IP, provides an opportunity to form a unified approach to interpretation of the criteria of protection of the results of AI activities in different jurisdictions, to apply the mechanisms of legal protection of IP objects in the national legislation, emphasizes the importance of IP policy for national security

A meta-review of literature on educational approaches for teaching AI at the K-12 levels in the Asia-Pacific region

Artificial intelligence (AI) teaching is becoming an increasingly popular topic among educators and researchers, but the research on AI curriculum for K-12 classrooms was under-explored. Currently, most studies examine the curriculum content of the United States and the European countries. However, there has been limited research on AI learning design and activities in the Asia-Pacific region. This meta-review examined 14 research papers on AI curriculum for K-12 classrooms that were taken in the Asia-Pacific region from 2018 to 2021 by identifying the content knowledge, tools, platforms, activities, theories and models, assessment methods, and learning outcomes of the selected studies. The results indicated that AI curricula can develop students' AI knowledge and skills, learning attitudes, and interests. Furthermore, the research on AI education was conducted using both qualitative and quantitative methods which are useful for future educators and researchers to understand how they assess students’ AI learning performance. We also derive a set of implications for innovative pedagogical designs in terms of educational standards, curriculum designs, formal/informal education, student learning outcomes, teacher professional development and learning progressions to recommend how governments, researchers and educators could build a widely-accepted and age-appropriate AI curriculum for all K-12 learners.

A Systematic Review on Artificial Intelligence/Deep Learning Applications and Challenges to battle against COVID-19 Pandemic

The eruption of COVID-19 Corona Virus, namely SARS-CoV-2, has created a disastrous condition throughout the world. The cumulative incidence of COVID-19 is increasing rapidly day by day all over the world. Technologies like Artificial Intelligence (AI), Internet of Things (IoT), Big Data and Deep Learning can support healthcare system to fight and look ahead against fast spreading of new disease COVID-19. These technologies can significantly improve treatment consistency and decision making by developing useful algorithms. These technologies can be deployed very effectively to track the disease, to predict growth of the epidemic, design strategies and policy to manage its spread and drug and vaccine development. Motivated by recent advances and applications of artificial intelligence (AI) and big data in various areas, this study aims at emphasizing their importance in responding to the COVID-19 outbreak and preventing the severe effects of the COVID-19 pandemic. This study first presents an overview of AI and big data along with their applications in fighting against COVID-19 and then an attempt is made to standardize ongoing AI and deep learning activities in this area. Finally, this study highlighted challenges and issues associated with State-of-the-Art solutions to effectively control the COVID-19 situation.

Corporate Governance of Artificial Intelligence in the Public Interest

Corporations play a major role in artificial intelligence (AI) research, development, and deployment, with profound consequences for society. This paper surveys opportunities to improve how corporations govern their AI activities so as to better advance the public interest. The paper focuses on the roles of and opportunities for a wide range of actors inside the corporation—managers, workers, and investors—and outside the corporation—corporate partners and competitors, industry consortia, nonprofit organizations, the public, the media, and governments. Whereas prior work on multistakeholder AI governance has proposed dedicated institutions to bring together diverse actors and stakeholders, this paper explores the opportunities they have even in the absence of dedicated multistakeholder institutions. The paper illustrates these opportunities with many cases, including the participation of Google in the U.S. Department of Defense Project Maven; the publication of potentially harmful AI research by OpenAI, with input from the Partnership on AI; and the sale of facial recognition technology to law enforcement by corporations including Amazon, IBM, and Microsoft. These and other cases demonstrate the wide range of mechanisms to advance AI corporate governance in the public interest, especially when diverse actors work together.

ARTIFICIAL INTELLIGENCE AND INTELLECTUAL PROPERTY: PROBLEMS OF REGULATION

The economic and legal aspects of the regulation of artificial intelligence (AI) technologies, their influence on scientific and inventive activity are studied. The role of protection of intellectual property (IP) – (patent and copyright) in ensuring the balance of competing interests, identified problems and identified ways to solve them. AI is seen as one of the most important dual-use technologies, a new challenge for the economy and the legal system, a new phenomenon that has a multiplier effect, a legal phenomenon in the structure of legal relations, a new object for legal regulation. AI is able to generate and create various works – science, literature and art. These circumstances raise problems of recognition of authorship, the possibility of authors to dispose of their rights and their use of mechanisms for legal protection of IP objects. The main provisions of the Resolution of the European Parliament of October 20, 2020 on intellectual property rights in the field of artificial intelligence technologies (2020/2015 (INI)), the Resolution of the International Association for the Protection of Intellectual Property (AIPPI) 2020 on the inventory of inventions using AI. An analysis of the legislative and law enforcement practices of the European Patent Office (EPO), the US Patent and Trademark Office (USPTO) and the UK Intellectual Property Office (UKIPO), regional and international documents on the regulation of AI and IP, designed to form a unified approach to interpretation criteria for the protection of the results of AI activities in different jurisdictions, the use of mechanisms for the legal protection of IP objects, to emphasize the importance of IP policy for national security.

AI strategy of India: policy framework, adoption challenges and actions for government

Purpose The purpose of this study is to provide recommendations for policy framework on artificial intelligence (AI) in India. Design/methodology/approach Studies have been conducted through focus group discussion and the other sources such as different company websites using AI, Indian Government strategy reports on AI, literature studies, different policies implemented on AI in different locations and other relevant documents. After those studies, a charter of recommendation has been provided. This will help the authority to frame the AI policy for India. Findings This study highlights that “National Strategy for AI” for India needs improvement to provide comprehensive inputs for framing policy on AI. This study also implies that focus is to be given on security, privacy issues including issues of governance. Research limitations/implications AI-related technology has immense potential toward the development of organizations. This study implies the necessity of framing a comprehensive policy on AI for India. If there is a comprehensive policy on AI for India, the Indian industries will derive many benefits. Practical implications This study provides inputs on how the industries of India can be benefitted with the help of AI and how R&D can develop the AI activities to harness maximum benefits from this innovative technology. Social implications AI-related policy will have appreciable influence on the society in terms of human–device interactions and communications. The policy framework on AI for India is expected to project far-reaching effects toward deriving benefits to the society. Originality/value This paper has taken a holistic and unique attempt to provide inputs to the policymakers for framing a comprehensive and meaningful policy on AI for India.

Reduction of Cyber Crimes by Effective Use of Artificial Intelligence Techniques

Artificial Intelligence (AI) is a buzz word in the cyber world. It is still a developing science in multiple facets according to the challenges thrown by 21st century. Use of AI has become inseparable from human life. In this day and age one cannot imagine a world without AI as it has much significant impact on human life. The main objective of AI is to develop the technology based activities which represents the human knowledge in order to solve problems. Simply AI is study of how an individual think, work, learn and decide in any scenario of life, whether it may be related to problem solving or learning new things or thinking rationally or to arrive at a solution etc. AI is in every area of human life, naming a few it is into gaming, language processing, speech recognition, expert system, vision system, hand writing recognition, intelligence robots, financial transactions and what not, every activity of human life has become a subset of AI. In spite of numerous uses, AI can also used for destroying the human life, that is the reason human inference is required to monitor the AI activities. Cyber crimes has become quite common and become a daily news item. It is not just a problem faced in one country, it is across the world. Without strong security measures, AI is meaningless as it can be easily accessible by others. It has become a big threat for governments, banks, multinational companies through online attacks by hackers. Lot of individual and organizational data is exploited by hackers and it becomes a big threat to the cyber world. In this connection research in the area of AI and cyber security has gained more importance in the recent times and it is ever lasting also as it is a dynamic and sensitive issue linked to human life.