Abstract

The twenty-first century is frequently considered as the era of Artificial Intelligence (AI) and prompting numerous inquiries about its effects on society. It has already profoundly been changed various practices in different fields, and research ethics is no exception. With its powerful capabilities for automation, prediction, and data analysis, AI has become a transformative force in scientific research. However, the integration of AI into research processes introduces a range of complex ethical challenges that demand urgent attention. These include questions about who is accountable for AI-generated findings, how authorship and credit should be assigned, how to preserve data privacy, how to detect and prevent algorithmic bias and scientific misconduct. Without clear ethical frameworks and proper oversight, the use of AI could undermine research integrity, distort authorship practices, and compromise public trust in science. This article addresses key ethical issues, including accountability, data privacy, authorship, transparency, bias, and the possibility of scientific misconduct. The paper provides a logical framework for navigating the ethical use of AI in research, drawing on current empirical investigations and ethical standards. It ends by highlighting the necessity of strong regulatory monitoring, trans disciplinary ethical governance, and openness in AI-assisted approaches.