Artificial Intelligence (AI) is transforming scientific research by enabling computers to perform tasks that require human intelligence - such as data analysis, pattern recognition, prediction, and language processing.

AI is now integrated into every stage of the research process: from idea generation and literature review to data collection, analysis, and publication. Using tools like machine learning, deep learning, and natural language processing (NLP), researchers can analyze massive datasets, detect hidden trends, and accelerate discoveries across fields like medicine, biology, chemistry, and social sciences.

The benefits of AI include speed, accuracy, efficiency, and innovation, allowing scientists to process information and generate hypotheses faster than ever. However, ethical challenges such as data bias, lack of transparency, accountability, plagiarism risks, and privacy concerns must be addressed through responsible AI governance.

• Inclusion criteria
• Age ≥ 18
• Able to provide informed consent
• Has direct experience with research and/or AI tools used in research (often within the last 1-3 years)
• Speaks/reads the study language (e.g., English/Arabic)
• Available to complete the study activity (survey)
• Exclusion criteria
• No AI is involved.
• It's only theory/principles with no checklist or questions.
• It covers only one issue (privacy-only, bias-only) when you need full ethics.
• Not enough info to assess (no data source, no model description, no intended use).
• It's a small classroom/toy example with no real impact.

Principal investigators / co-investigators

Research assistants / lab members

Data scientists / statisticians

Students (Masters/PhD) working on AI-supported research