  Self-driving labs (SDLs) combine fully automated experiments with artificial
intelligence (AI) that decides the next set of experiments. Taken to their
ultimate expression, SDLs could usher a new paradigm of scientific research,
where the world is probed, interpreted, and explained by machines for human
benefit. While there are functioning SDLs in the fields of chemistry and
materials science, we contend that synthetic biology provides a unique
opportunity since the genome provides a single target for affecting the
incredibly wide repertoire of biological cell behavior. However, the level of
investment required for the creation of biological SDLs is only warranted if
directed towards solving difficult and enabling biological questions. Here, we
discuss challenges and opportunities in creating SDLs for synthetic biology.
