  Privacy is a human right. It ensures that individuals are free to engage in
discussions, participate in groups, and form relationships online or offline
without fear of their data being inappropriately harvested, analyzed, or
otherwise used to harm them. Preserving privacy has emerged as a critical
factor in research, particularly in the computational social science (CSS),
artificial intelligence (AI) and data science domains, given their reliance on
individuals' data for novel insights. The increasing use of advanced
computational models stands to exacerbate privacy concerns because, if
inappropriately used, they can quickly infringe privacy rights and lead to
adverse effects for individuals -- especially vulnerable groups -- and society.
We have already witnessed a host of privacy issues emerge with the advent of
large language models (LLMs), such as ChatGPT, which further demonstrate the
importance of embedding privacy from the start. This article contributes to the
field by discussing the role of privacy and the issues that researchers working
in CSS, AI, data science and related domains are likely to face. It then
presents several key considerations for researchers to ensure participant
privacy is best preserved in their research design, data collection and use,
analysis, and dissemination of research results.
