Aristotle stated that all communities aimed at “the good” thing and take “the best” as a goal (Aristotle, 1983). Favoritism occurs when a civil servant helps his/her relatives illegally and unjustly, backs them (Özsemerci, 2002), or treats anyone or any group of people better than others regardless of their high professional performance. Favoritism, a reality in many countries, shows underdevelopment in democracy and is a major reason for lack of productivity (Kim, 2004). Cronyism and favoritism are hidden forms of corruption, which lead directly to the conflict of interest and create corruption risks in the exercise of official powers.Cronyism and favoritism in appointing faculty in the higher education system are unethical practices that can have detrimental effects on the quality and integrity of education. Such practices involve showing favoritism towards individuals based on personal connections, rather than their academic qualifications and achievements, practical skills, and merit. Cronyism and favoritism can result in the appointment of underqualified or incompetent faculty members, which can negatively impact the learning experience of students and the overall reputation of the educational institution and the society.The consequences of cronyism and favoritism in appointing faculty in the higher education system can be significant. It can result in a decline in the quality of education, as underqualified or incompetent faculty members may not possess the necessary skills, knowledge, or expertise to effectively teach and mentor students. It can also lead to unfair competition among faculty members, as those who are appointed based on merit may feel low self-esteem, lack of confidence, demoralized and discouraged, while those appointed through cronyism may lack motivation to perform their duties effectively.To combat cronyism and favoritism in appointing faculty in the higher education system, it is important to establish merit-based hiring processes and transparency. This can include creating clear job descriptions and qualifications for faculty positions, advertising vacancies widely through proper channel, conducting fair and unbiased evaluations of candidates based on their qualifications, skills, experience and expertise, and involving multiple stakeholders in the hiring process to ensure checks and balances.It is also crucial to promote a culture of integrity and ethical behavior in educational institutions, where appointments are made based on merit and the best interests of students and the institution as a whole. This review paper highlights the crucial factors of Cronyism and Favoritism in appointing faculty in Higher Education System.

Dr. Pawan Singh

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Deepfakes the term was coined in 2018 by a Reddit user who created a Reddit forum dedicated to the creation and use of deep learning software for synthetically face swapping female celebrities into pornographic videos. According to Sumsub’s research in 2023, the top-5 identity fraud types in 2023 are AI-powered fraud, money muling networks, fake IDs, account takeovers, and forced verification. The country most attacked by deepfakes is Spain; the most forged document worldwide is the UAE passport, whereas Latin America is the region where fraud has increased in every country. On November 24, 2023, the Union Government of India issued an advisory to social media intermediaries to identify misinformation and deepfakes. A deepfake refers to a specific kind of synthetic media where a person in an image or video is swapped with another person’s likeness. AI-generated deepfakes have emerged as a complex and pervasive challenge in today’s digital landscape, enabling the creation of remarkably convincing yet falsified multimedia content. This review paper examines the multifaceted landscape of deepfakes, encompassing their technological underpinnings, societal implications, detection methodologies, and ethical considerations. The review aggregates and synthesizes a broad array of scholarly articles, studies, and reports to elucidate the diverse typologies of deepfakes, including face-swapping, voice cloning, and synthetic media, while delineating the intricate methodologies employed in their fabrication. This review culminates in an overview of future directions and recommendations, advocating for proactive measures to counter the escalating threat posed by AI-generated deepfakes.