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ETHICS IN MACHINE LEARNING AND DATA ANALYTICS

Abhilash Reddy Pabbath Reddy is a seasoned DevSecOps/DevOps and Site Reliability Engineer with a passion for leveraging cutting-edge technologies to enhance cybersecurity and cloud computing solutions. Throughout his career, Abhilash has spearheaded innovative projects that have reshaped the landscape of digital security, harnessing the power of artificial intelligence (AI) and machine learning (ML) to detect and mitigate cyber threats with unparalleled accuracy and efficiency. His expertise in AI/ML operations (AIOps/MLOps) has led to the seamless integration of these methodologies into infrastructure management and deployment pipelines, resulting in streamlined processes, enhanced scalability, and optimized performance. Abhilash holds certifications in cloud computing and Amazon Web Services Solution Architecture, showcasing his commitment to staying at the forefront of industry advancements. He is known for his dedication to academic excellence, having earned a Master’s degree from Texas Tech University and a Bachelor’s degree from Jawaharlal Nehru Technological University. With a strong foundation in both theory and practical application, Abhilash continues to drive technological innovation in cloud computing, aspiring to make a meaningful impact by enabling organizations to achieve their strategic goals through cloud-based solutions.

Dr. Kapil Tarey received his PhD in Computer Science from Devi Ahilya Vishwavidyalaya Indore. He has also done MCA and M.Phil. Computer Science. Presently he is working as Associate Professor in the MCA Department of Chameli Devi Group of Institutions. His major research area includes Cloud Computing, Optimization techniques, Fuzzy Logic and Resources/VM Scheduling. He has published many research papers in SPRINGER and SCOPUS indexed Journals as well as UGC care Journals. He has 2 Indian patents also. Dr. Tarey has 22 years of teaching experience to teach in UG and PG classes.

Dr. Gabriel A. Ogunmola possesses over 8 years of rich experience in academia and holds the esteemed title of Chartered Public Administrator and a registered member of Association for Computing Machinery (ACM). His academic qualifications include an MBA degree in Finance and Human Resource Management, along with a Ph.D. in General Management. Currently serving as an Associate Professor in the Department of Business Administration at Sharda University, Uzbekistan, He has demonstrated a remarkable scholarly track record. His contributions extend beyond the classroom, with numerous research papers published in esteemed international journals indexed by SCI, SSCI, and Scopus. Dr. Ogunmola has been an active participant in several international conferences, showcasing his commitment to advancing knowledge and fostering global academic collaboration. In addition to his role at Sharda University, Dr. Ogunmola serves as a Visiting Professor at the Department of Management and Accounting, Mechanical Engineering Technology, Machine Building Institute Andijan, Uzbekistan, and Collegium Humanum- Warsaw Management University, Andijan branch. His diverse expertise spans areas such as e-business, Web Analytics, Social Media Analytics, Digital Analytics, Technology-Enhanced Learning, and Digital Currency. His comprehensive skill set and dedication to academic excellence make him a valuable asset to both Sharda University and the wider academic community.

Dr. Samrat Ray is Dean and Head of International Relations of International Institute of Management studies, Pune, India. He has completed his PHD in Economics from World’s Top 100 university as per QS rankings Peter the great saint Petersburg polytechnic University, Russia. He has authored more than 100 Scopus indexed publications in reputed journals and also has national and international patents. He has research interest in Behavioral economics, Data science, Sustainability, ethics.

Description

It is necessary to give careful consideration to the ethics of machine learning and data analytics, which is a highly significant and rapidly emerging field. The creation, implementation, and utilization of more complex technologies give rise to significant ethical dilemmas as we continue to incorporate these technologies into an increasing number of aspects of our everyday lives. An illustration of this would be the possibility that machine learning algorithms may unwittingly provide biased outcomes by reinforcing biases that are present in the trained data. The massive collection and utilization of individual data raises a number of additional concerns, including those pertaining to privacy and consent. Considering the current state of affairs, it is of the utmost importance to guarantee that the processes of data analytics and machine learning are transparent and accountable. It is necessary for stakeholders to address a variety of concerns, including those pertaining to algorithmic fairness, ethical decision-making in artificial intelligence, and cultural norms and values. Standards and frameworks for ethical conduct are now being developed with the intention of assisting practitioners and organizations in addressing these complex issues. These frameworks and standards place an emphasis on accountability, openness, fairness, and interpretability. To consider from an ethical point of view, there are greater societal ramifications to take into consideration, in addition to the specific technology ones. A number of issues are included in these concerns, including the requirement for varied and inclusive representation in the development of artificial intelligence, the ownership of data, authorization, and the potential of technology being exploited. One of the most important things to do in order to make the most of machine learning and data analytics while reducing risks is to maintain open and constant communication, collaborate with people from different fields, and be cognizant of ethical considerations. Especially considering the fact that the region is always evolving, this is the case. For the purpose of preventing prejudice and encouraging equal outcomes, it is necessary to make certain that these algorithms are transparent, impartial, and accountable. To find solutions to these ethical issues, it will be necessary for professionals in the domains of computing, ethics, law, sociology, and policymaking to collaborate. What it implies is the incorporation of ethical concerns into the design and development of data analytics systems and machine learning models. It is necessary for decision-makers, engineers, and data scientists to build a culture of ethical xviii | P a g e responsibility in order to promote ethical behaviors and mitigate unanticipated effects through the implementation of these practices

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