What My 1980s Party Photos Have in Common with Modern Research

We did things in the 80s assuming no one was recording. Research made the same assumption. AI is pressing play.

Imagine this: It’s the 1980s. You’re at a party, shoulder pads, mulets, and all, never imagining it would be replayed decades later. Now, let’s extend that analogy to research. For the last half-century, countless studies have been conducted, most with good intentions but without the expectation that AI would someday dissect them with unparalleled precision - yes, rerunning the experiments at lightning speed, testing all assumptions and conclusions without bias or influence.

AI isn’t just going to validate or debunk what’s been done. It will lead the future of research. It will rapidly examine variables for bias, whether tied to funding sources, institutional pressures, or subtle assumptions baked into methodologies. In some cases, it may feel like those hidden moments (never meant to see the light of day) are being exposed. I wonder what respected research/researchers will be exposed.

But this is more than a retrospective. AI will become an active research partner, generating hypotheses, running complex simulations, and even designing experiments. What does that mean for the future of graduate schools and research funding? Universities will need to evolve. PhD students may work alongside AI, focusing on creative interpretation and ethical oversight. Funding models will shift; no longer just rewarding volume, but rewarding collaborative, AI-enhanced breakthroughs. Will universities be the place where research funding (both federally and privately) is concentrated?

Is there an “Epstein files” element here? Not in scale, but in principle, yes. Research that was never intended for such scrutiny will be reevaluated. But this isn’t about scandal; this is an opportunity. Just as we grow from our past, research will mature in transparency, ensuring the future of discovery is both more accountable and more impactful than we ever imagined.