This chapter examines the ethical complexities of Artificial Intelligence (AI) and automated decision-making systems, now integral to fields like healthcare, finance, criminal justice, and education. While AI presents immense opportunities for innovation and efficiency, it also introduces significant ethical challenges. The chapter explores foundational ethical frameworks—Utilitarianism, Deontological Ethics, and Virtue Ethics—offering insight into the moral duties guiding AI development. It examines global and international perspectives, emphasizing the cultural and regulatory variations shaping AI governance. Key ethical issues such as bias, transparency, privacy, and global impacts are explored, supported by case studies across various sectors. Emerging concerns, including deepfakes, autonomous weapons, and AI's impact on employment and inequality, are also addressed. The chapter calls for continuous dialogue and proactive governance to ensure responsible AI development for societal benefit, providing a roadmap for ethical AI governance.

Background and Aim: Students sometimes participate in harmful activities that adversely influence their behaviors and well‐being throughout college, which is one of the sensitive phases in an individual's life.Aim: To assess the health‐related behaviors of university students.Methods: A cross‐sectional study that includes systematic randomly selected 383 students from various colleges of Ras Al Khaimah Medical and Health Sciences University (RAKMHSU), Ras Al Khaimah Emirate, United Arab Emirates. A self‐reported questionnaire included students' demographic traits and behaviors, including safety, medication intake, cigarette smoking, nutrition, physical activity, and health‐related topics.Results: Most participants were females (69.7%), 13.3% were obese while 28.2% were overweight. The data revealed a significant difference between male and female students regarding medication intake without prescription, nutrition, physical activity, and health‐related topics. The data also revealed that the majority of the students were attempting to lose weight, and the former male smokers had fewer trials to quit the use of all tobacco products than females.Conclusion: More than a quarter of participants were overweight, and the majority of students did not adhere to the guidelines for safety and nutritious eating. This study recognized significant health promotion opportunities for university students that can be carried out to establish a healthier youth for society.

This chapter delves into the real impact of our digital dependence on our lives – how it affects our minds, and connections with others. Shedding light on the challenges faced in balancing digital and offline worlds, especially in today's fast-paced society. We see the dangers of spending a lot of time glued to screens and the signs of digital addiction that we overlook. But there's a silver lining filled with practical advice and inspiring tales of people who have found a healthier relationship with technology. From simple tricks like setting screen time limits to embracing offline activities and mindfulness, we discover ways to reclaim control over our digital lives. Looking ahead, we glimpse a promising future where technology supports our well-being, thanks to innovations like AI and 5G that foster positive digital experiences. Whether you're navigating your digital habits, teaching others about digital wellness, supporting patients in healthcare, or shaping policies, this chapter serves as a trusted guide on the journey to a more mindful and fulfilling tech experience.

Artificial Intelligence (AI) and Machine Learning (ML) are rapidly changing the face of Research and Development (R&D). This chapter deals with a profound review of the current status and future trends of AI and ML in R&D. First of all, it gives an overview of huge investments and fast growth in AI, for instance, spending on AI systems worldwide is projected to reach as high as $110 billion by 2024. In the health sector, AI will potentially add up to $150 billion every year by 2026. The chapter highlights some of the most remarkable achievements in AI and ML, including transformer models like GPT-3 or Google's BERT, setting new benchmarks in natural language processing, low-code/no-code platforms democratize AI. Finally, the chapter asserts that AI and ML have the potential to transform R&D while insinuating that such development should be responsible and ethical. In adopting collaborative and open approaches, the stakeholders could reap maximum benefits from AI technologies in boosting innovation and societal benefits across different industries.