Next-Generation Personal Genomic Studies: Extending Social Intelligence Genomic Genomics to Cognitive Performance Genomics in Quantified Creativity and Thinking Fast and Slow

by | Mar 15, 2013 | Research Publications

Author:

Swan, Melanie

Abstract:

A significant shift is underway as the fields of health and biology are re-organizing into the larger ecosystems of information sciences and complexity sciences. The era of big data is transforming all economic sectors including health and biology. Three big health data streams are being integrated into a standardized investigative method in the realization of personalized medicine – creating individualized risk profiles and interventions such that medical conditions may be combatted during the 80% of their life-cycle while they are still pre-clinical. These three big health data streams are traditional medical data, ‘omics’ data (genomics, microbiomics, proteomics, etc.), and biometrie quantified-self daily analytic data. Sequencing costs have continued to decrease such that consumer ‘omics’ data is increasingly available. Simultaneously, the potentially fast-arriving wearable electronics platform (smartwatches, disposable patches, augmented eyewear, etc.) means that it could become possible to unobtrusively collect vast amounts of previously-unavailable objective metric data for each individual and parlay this into personalized physical and mental health optimization platforms. Two experimental protocols are presented here putting this model of integrated health data streams into action and extending recent social intelligence genomics research into the realm of cognitive performance genomics. The DIYgenomics Quantified Creativity study investigates potential linkage between personal genomics and the creative process of the individual. The DIYgenomics Thinking Fast and Slow study examines cognitive bias in thinking (loss aversion and optimism bias) versus personal genomic profiles. The studies integrate big health data streams including traditional health data, personal genomics, quantified self-reported data, standardized questionnaires, and personalized intervention. Copyright © 2013 Association for the Advancement of Artificial Intelligence.

Document:

https://www.aaai.org/ocs/index.php/SSS/SSS13/paper/viewPaper/5704

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