A big data ecosystem is evolving in our society in which people may have, or feel they have, little control over the flow of their personal health information, and thus their privacy. Further, although there has been significant discussion related to big data and privacy at the highest levels of government, there is little consensus among scholars and stakeholders as to what privacy actually is, not to mention a lack of data from individuals as to personal conceptions of privacy.

Whole genome sequencing has vast potential to improve the care of generally healthy adults by identifying predispositions for disease to facilitate targeted prevention and screening efforts, by informing treatment options when illnesses do develop, and more. It may also cause more harm than good through false-positive findings, through unnecessary monitoring because of incomplete genetic penetrance, and because the conditions identified by genomic sequencing may lack effective prevention options.

The emergence of genomic medicine has not been without unique concerns that continue to challenge clinicians working in this arena. Genomic test results have implications for individuals other than the person tested. Related to this, interpretation of genomic data often requires several related individuals; and even then what can be known about the meaning of an individual's specific variants is, and will continue to be, a function of big data analysis of the genomic data of many thousands (or even millions) of individuals.

Health-relevant information no longer comes just from electronic medical records but also from the digital footprints left behind when people use mobile applications, search the internet, wear activity monitoring devices, access direct-to-consumer health care testing, or simply converse in social media. Many efforts including those tied to the Precision Medicine Initiative (PMI) are fueling the development of large population-based databases that link clinical and genetic information.

The North Coast Conference on Precision Medicine is a national annual mid-sized conference series held in Cleveland, Ohio. The conference series aims to serve as a venue for the continuing education and exchange of scientific ideas related to the rapidly evolving and highly interdisciplinary landscape that is precision medicine research. The topics for each conference coincide with the national conversation and research agenda set by national research programs focused on precision medicine.

The application of new computerized methods of data analysis to vast collections of medical, biological, and other data is emerging as a central feature of a broad vision of precision medicine (PM) in which systems based on artificial intelligence (AI) assist clinicians in treatment, diagnosis, or prognosis. The use of AI to analyze big data for clinical decision-making opens up a new domain for ELSI inquiry to address a possible future when the implications of genetics and genomics become embedded into algorithms, pervasive yet implicit and difficult to identify.

The purpose of this study is to assess assenting and consenting adolescents choices about learning genomic research results. We will refine existing decision tools and processes to promote informed genomic decision-making through the use of focus groups with adolescents and parents recruited from an existing genomic research study and a diverse, medically-underserved community to assess whether and how recruitment pathways impact perceived value, risks, and benefits of participation in genomic research and return of personal genomic information.