The rapid growth of technologies capable of comprehensively collecting, managing, and allowing us to gain an in-depth picture of the brain, nervous system, and behavior across diverse spatial and temporal dimensions, as well as across different scales of biological organization and data modalities has opened unprecedented avenues for understanding human experiences within their social and physical contexts. In this talk I will discuss some of the key ethical and societal considerations that are raised with these new capabilities. While these cutting-edge capabilities hold immense potential for advancing our knowledge, critical questions must be addressed. This talk will explore inquiries such as what can and should be measured, as well as the ethical considerations surrounding the access and utilization of this wealth of data. From safeguarding user privacy to navigating the potential privacy risks associated with capturing multimodal and multiscale data for individuals and communities. In addition, I will discuss biases, encompassing considerations of which data is deemed superior and the biases embedded in algorithms used to interpret these data. Addressing the potential dissonance between digital phenotypes and self-reported measures further complicates the ethical terrain. Recognizing that a one-size-fit-all solution is elusive, the presentation emphasizes the importance of establishing responsible governance data frameworks. Such governance is essential to ensure the quality, availability, findability, accessibility, usability and utility of these multidimensional datasets. Moreover, a responsible research and innovation can help us navigate the challenges posed by these transformative technologies, ensuring that their societal impact aligns with shared values and principles.

Learning objectives:

1. Identify key ethical and societal considerations raised by the comprehensive, continuous, real-time collection of behavioral data and the use of that data.

2. Recognize the importance of establishing and using responsible governance data frameworks.

3. Assessing facilitators and barriers for ensuring that the societal impact of these data collection and use aligns with shared values and principles.