On Gene Editing, Machine Learning and AI

Last week, Rand Corp. published "Machine Learning and gene editing at the helm of a societal evolution."  Comments from this study included:

  • "Recent headlines outline the enormous leaps made in technology, especially in the field of artificial intelligence, engineering biology and, more broadly, gene editing. The developments are being met with both excitement and concern for the future because of the opportunities these technologies can unlock. 

  • "ML is a powerful tool that can help speed up and scale up screening processes that are necessary in biotechnology. This makes it possible to create effective vaccines faster, speed up drug creation, and predict the evolution of pathogens. It enables the capability to sort through a large database with genetic parts and extract what's useful. ML also allows for more in silica work before moving to the riskier physical side of laboratory work. Creating enzymes to eat plastic and pollutants(e.g., forever chemicals), artificial meats and biofuels could dramatically alter the world we live in in the near and distant future. These technologies are possible solutions to problems of global health, climate change, health equity and other pressing issues.

  • "Most of the implications and thus applications of these advancements fall under the medical sector with some uses in agriculture, energy and climate, but there is potential for their use in other sectors like themilitary, national security or human performance. 

  • "While these technologies can lead to breakthroughs that may vastly improve lives, they may also be used for nefarious purposes. The creation of bioweapons, dangerous chemical compounds and malware are some of the dangers of unfettered access to these technologies."

NOTE: Full report here: https://www.rand.org/pubs/research_reports/RRA2838-1.html

OUR TAKE

  • Broadening the use of AI and bioengineering technologies will require 1) advances in computational power, 2) developing new datasets for model training and ensuring that lab results can reliably be lead to safe solutions in the real-world . 

  • The rapid development of solutions leveraging both artificial intelligence and genetic engineering will challenge policy makers' ability to provide timely oversight.

  • Concerns about individual privacy rights, cost-effectiveness and environmental impact will continue to be debated in this realm of innovation.

Paul Dravis