Chloé Azencott on Nostr: All what I've ever wanted, scientifically, in the last 20+ years, was to use maths ...

All what I've ever wanted, scientifically, in the last 20+ years, was to use maths and computer science to help advance biomedical knowledge. Machine learning for bioinformatics was a great (and, by then, niche) way to do that.

But now I've spent more than half of my career wading through the mud that started building up when statistical machine learning came out of its relative niche obscurity and was rebranded as artificial intelligence. It's becoming harder and harder not to drown, not to feel so very alone in both horrified by what's now sold as generative AI and believing in the usefulness of statistical models (not necessarily very computationally intensive, or rather, necessarily not very computationally intensive) for meaningful endeavors.

I sometimes wonder about giving it all up, but truth be told, I love my job. I love my research questions. I love digging and trying to make sense of a little piece of statistics here or of biology there. I love accompanying young researchers as they blossom and become experts in their own little corner of this super interesting field. I love listening to my colleagues explain how they build and use deep learning models that help answer actual biological questions. I love teaching and being thanked by students for introducing them to machine learning, even though some of them then go on to have brilliant careers at one of the Magnificent Seven, making me wonder how complicit I am.

Also, I wouldn't know what else to do. So on I go, trying to make the most of my academic freedom to keep doing unfashionable things and resisting the hype at a sweet spot.