AI in the Library

Digital mental health tools (DMHTs) offer a potential solution to overcoming economic, cultural, and geographic barriers to the increasing demand for mental health care, but their adoption raises significant ethical, legal, and social concerns.

This paper conducts a systematic review and interdisciplinary analysis of the ethical challenges of generative AI technologies (N = 37), highlighting significant concerns such as privacy, data protection, copyright infringement, misinformation, biases, and societal inequalities. The ability of generative AI to produce convincing deepfakes and synthetic media, which threaten the foundations of truth, trust, and democratic values, exacerbates these problems. The paper combines perspectives from various disciplines, including education, media, and healthcare, underscoring the need for AI systems that promote equity and do not perpetuate social inequalities.

Artificial intelligence (AI) algorithmic tools that analyze and evaluate recorded meeting data may provide many new opportunities for employees, teams, and organizations. Yet, these new and emerging AI tools raise a variety of issues related to privacy, psychological safety, and control. Based on in-depth interviews with 50 American, Chinese, and German employees, this research identified five key tensions related to algorithmic analysis of recorded meetings: employee control of data versus management control of data, privacy versus transparency, reduced psychological safety versus enhanced psychological safety, learning versus evaluation, and trust in AI versus trust in people.

From 2017:
Artificial Intelligence (AI) has the potential to fundamentally change the way we work, live, and interact. The development of these large-scale AI will depend on access to ever larger and richer medical and behavioral datasets. There is now strong evidence that the tools used historically to find a balance between using the data in aggregate and protecting people’s privacy, de-identification, doesn’t scale to big data datasets.