In his seventh post in the series, Marshall Kirkpatrick focuses on the intersection between artificial intelligence and genomics. By way of reminder, Marshall launched a 30 day series that explores the intersection between AI and the various innovation components on my emerging futures visual.
As he has in each post, Marshall identifies the key subject matter experts that sit at the intersection of AI and the visual component in question. In the case of genomics, the key influencers are: Antonei B Csoka, Ben Hardisty, Diane Wu, and Bodo Brückner. Here is the foresight and related future scenarios identified at the intersection of Artificial Intelligence and genomics (taken straight from Marshall’s post):
You understand me: Machine learning could build complex predictive models of environmental and experiential impacts on an individual’s epigenetic make-up, enabling a new level of life-long personalized medicine and natural management of well-being. The effects of stress, toxic environments, interpersonal and inter-generational experience could all be better understood and accommodated
My robot buddy knows my code: AI could understand our spoken words and the circumstances that surround us, enable us to make complex far-reaching inquiries about our lives, and receive genetically-personalized answers in response. Day to day decisions could benefit from mobile apps using AI to interpret our unique genetic needs
Life made predictable: In a perhaps less desirable scenario, deep learning could so thoroughly decode the universe of genetic mutations that a substantial amount of uncertainty in human life could be removed, perhaps too much. Too little uncertainty and unpleasantness could lead to a loss of perceived free will, creative struggle, serendipity, privacy, and autonomy
The intersection analysis that Marshall pursues via his posts is a great example of deriving the foresight required to navigate in this emerging future. The other posts in the series on AI and intersections can be found via the links below: