Ethical Dilemmas and Coping Strategies in the Use of Psychological Scales in the Era of Big Data

Focusing on the ethical risks arising from the reconstruction of psychological scales due to innovations in big data technology, a systematic analysis is conducted on the research and current use of psychological scales within the context of big data. Ethical issues are explored across five dimensions: data privacy and security, the effectiveness of informed consent, data bias and algorithmic worship, sociocultural sensitivity, and the marginalization of vulnerable groups' rights. In response, five strategies are proposed: establishing a comprehensive data lifecycle protection mechanism, innovating informed consent models, optimizing algorithm fairness assessments, constructing diverse datasets, and empowering vulnerable groups. Future research and practice must seek a balance between technological innovation and ethical safeguards to ensure the fairness, transparency, and sustainable development of psychological scales in the era of big data.