For many years GMWatch has made the science-based case that the process of CRISPR/Cas gene editing is neither precise in operation nor predictable in outcome. In doing so, we have gone against the much-hyped narrative that this technology is precise, efficient, and predictable.

Now, in what has become a typically cynical pivot by the pro-GMO lobby and its attendant media, it’s being admitted that CRISPR/Cas gene-editing tools are not precise after all and produce unintended effects both at the intended edit site (on-target) and elsewhere in the genome (off-target).

However, this admission has come about only in the context of gene editing scientists supposedly coming up with a “solution” to the problem – in the shape of CRISPR pioneer Jennifer Doudna and her team using AI with the aim of designing more specific and efficient CRISPR/Cas gene-editing tools.

Based at the Innovative Genomics Institute at UC Berkeley, USA, which Doudna founded, the researchers wanted to see if their AI model system approach could build custom gene-editing tools that operate more efficiently and with less off-target alterations. But a closer look at the research suggests that the reality doesn’t live up to the hype with which it’s been greeted.