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In the past decade, Artificial Intelligence (AI) has made significant advancements in various sectors of society, such as education, health, e-commerce, media and entertainment, banking and finance, transportation, and defense, among others. Its application has permeated every sector, leaving no area untouched. However, the utilization of AI brings forth crucial legal, ethical, and technical concerns and obstacles that must be appropriately addressed through thoughtful deliberation, discussions, and the implementation of effective regulations.
AI and Emerging Technologies: Automated Decision-Making, Digital Forensics, and Ethical Considerations provides a comprehensive and insightful roadmap for exploring the advancements, challenges, solutions, and implications of AI in three key areas: the legal field, gaming applications, digital forensic, and decision-making. By delving into these topics, this book offers a deep understanding of how AI can be optimally utilized to deliver maximum benefits to users, all within a single, comprehensive source. One of the focuses of this book is to shed light on the preictal application of emerging technologies in automated decision-making while also addressing the ethical considerations that arise from their use. By examining the integration of these technologies into digital forensics and their impact on other domains, such as gaming applications deep fake, this book presents valuable insights into the broader implications of AI.
Generative Artificial Intelligence (GAI): The field of Machine Learning has accomplished significant advancements over the years, leading to the emergence of a new branch called generative AI. Machine learning mostly focuses on predetermined tasks, such as regression, classification, and prediction. These tasks involve training the model to assess and make judgments using a certain collection of input data. Generative artificial intelligence (GAI) is a distinct field within AI that utilizes machine learning to generate novel and unique information by leveraging huge historical databases. Generative AI has a variety of possible applications, such as generating unique pictures, written content, and musical creations; speech recognition; natural language processing; and computer vision. Generative models can be used to create realistic images for video games, simulations, and virtual reality. This technique is achieved by employing a model that received training on a vast collection of instances and produces new instances that are close to the original dataset. Generative AI employs advanced algorithms that evaluate data patterns to generate novel solutions. The progress in machine learning and deep learning, particularly in generative adversarial networks (GAN) and their modifications, has resulted in the creation of diverse systems across numerous areas.
The book serves as an invaluable resource for anyone seeking to understand and navigate the complex world of AI. By offering a comprehensive exploration of its applications, ethical considerations, and data protection techniques, it provides researchers and scholars, graduate students, software engineers along with data scientists the necessary insights to harness the full potential of AI while ensuring its responsible and ethical use