Artificial intelligence has become deeply embedded in the daily workflow of scientists, promising faster analysis, cheaper processes and unprecedented efficiency.
Powerful point about how AI accelerates progress specifically in data-rich disciplines while potentailly narrowing diversity. The four-year career advancement differential you cite cuts both ways, it creates compounding advantages for those who adopt early but also pressuer to use tools even when they might not be apropriate. What's underappreciated here is how the 87% concern rate actually tracking with increased adoption suggests people are using AI despite their reservations, which is exactly when governance frameworks matter most.
Yeah, totally — AI is speeding things up in data-rich fields, but it’s also tightening the gap between people who can take advantage of those tools and those whose work doesn’t fit neatly into automation.tho, I’m still curious how you see that tension playing out — do you think the pressure to adopt is coming more from institutions, from peers, or just from the fear of falling behind?
That tracks — corporate pressure often is just fear of falling behind in disguise. What interests me is how that pressure filters down to individual researchers who may feel pushed to adopt before they’re ready.
Do you think companies are leaning in because the gains are real, or mainly because no one wants to be the one not using AI?
Powerful point about how AI accelerates progress specifically in data-rich disciplines while potentailly narrowing diversity. The four-year career advancement differential you cite cuts both ways, it creates compounding advantages for those who adopt early but also pressuer to use tools even when they might not be apropriate. What's underappreciated here is how the 87% concern rate actually tracking with increased adoption suggests people are using AI despite their reservations, which is exactly when governance frameworks matter most.
Yeah, totally — AI is speeding things up in data-rich fields, but it’s also tightening the gap between people who can take advantage of those tools and those whose work doesn’t fit neatly into automation.tho, I’m still curious how you see that tension playing out — do you think the pressure to adopt is coming more from institutions, from peers, or just from the fear of falling behind?
I would say from institutions, namely corporations (which directly comes from the fear of falling behind)
That tracks — corporate pressure often is just fear of falling behind in disguise. What interests me is how that pressure filters down to individual researchers who may feel pushed to adopt before they’re ready.
Do you think companies are leaning in because the gains are real, or mainly because no one wants to be the one not using AI?
AI isn’t replacing researchers- it’s exposing the ones who never learned to think beyond the tool.