Managing bioengineering complexity with AI techniques.
Our capabilities for systematic design and engineering of biological systems are rapidly increasing. Effectively engineering such systems, however, requires the synthesis of a rapidly expanding and changing complex body of knowledge, protocols, and methodologies. Many of the problems in managing this complexity, however, appear susceptible to being addressed by artificial intelligence (AI) techniques, i.e., methods enabling computers to represent, acquire, and employ knowledge. Such methods can be employed to automate physical and informational "routine" work and thus better allow humans to focus their attention on the deeper scientific and engineering issues. This paper examines the potential impact of AI on the engineering of biological organisms through the lens of a typical organism engineering workflow. We identify a number of key opportunities for significant impact, as well as challenges that must be overcome.
Raytheon BBN Technologies, 10 Moulton Street, Cambridge, MA 02138, United States. Electronic address: jakebeal@gmail.com.
Jacob
J
Beal
Raytheon BBN Technologies, 10 Moulton Street, Cambridge, MA 02138, United States.
Aaron
A
Adler
Raytheon BBN Technologies, 10 Moulton Street, Cambridge, MA 02138, United States.
Fusun
F
Yaman
D001185:Artificial Intelligence; D057205:Automation, Laboratory / Q000379:methods; D057005:Bioengineering / Q000379:methods*; D019295:Computational Biology / Q000379:methods / Q000639:trends; D006801:Humans; D008962:Models, Theoretical; D058615:Synthetic Biology / Q000379:methods*; D049490:Systems Biology / Q000379:methods*
Artificial intelligence; Automation; Synthetic biology