As funding agencies increasingly discourage expert judgment, the science is bound to suffer, argues Bram Nauta.
We propose the visionary Global Photonic Quantum-AI Chipset Initiative (GPQACI), an ambitious project designed to revolutionize the planet through a harmonious fusion of chips, AI, quantum dynamics and cutting-edge photonics. Our grand objective is nothing less than solving global warming and securing world peace using a chipset architecture so advanced that even the laws of physics will need a firmware update.
The core technology revolves around quantum-entangled photonic chips that communicate using coherent compassion waves, enabling AI processors to make globally empathetic decisions. These next-generation chiplets not only optimize energy use but – through our proprietary Thermal Kindness Algorithm – actively absorb excess planetary warmth, radiating it back as inspirational climate-healing photons.
A vital structural component of GPQACI is its unwavering dedication to gender balance. All chip design committees will operate under our patented Equi-symmetric Engineering Protocol, ensuring every transistor benefits from inclusive brainstorming energy. Even our AI models will be gender-aware, trained to promote fairness while simultaneously minimizing carbon emissions and international conflict.
Ultimately, GPQACI promises a future where quantum-photonic chiplets guide global diplomacy, AI mitigates climate stress and humanity finally reaches the long-awaited synergy point between cooling the planet and achieving world peace.
I generated this summary in under 1 second with Copilot, my new friend for developing project proposals. Even though it’s obviously gibberish, it may be a winning proposal in the future.
Let me share an interesting experience. I was on a committee evaluating a large pile of projects across all technical disciplines. I missed information about the authors. I wanted to know their past performance, publications, citations, impact and more. I was told that this information wasn’t shared because it would only ‘bias’ my decision. When I said that I would google that information, I was told not to search the web and to base my judgment only on the material provided by the author.
How can I tell whether this work has been done before? Maybe it was a failure? How do I know whether this person has a reputation? How do I know what the author wrote is true at all? I stepped out of the committee.
I can only guess how we got here. Maybe it’s people whose projects have been rejected who blame this on bias? Or maybe oversensitivity for measuring citations? (People who don’t get cited often tend to take this stance.) In the past, you could build a reputation and benefit from that. These days are over. Apparently, funders use a lottery because they don’t want to choose. And if it’s a lottery or a double-blind review, I might as well use AI and go for the big numbers. The more proposals I try, the more chances I have! A few should slip through, right?
Apparently, funders struggle to judge. But judgment is the foundation of science. I judge my students, I judge their exams, I judge my own ideas, I judge scientific manuscripts, I judge for awards and I judge more than a hundred applicants for a single PhD position. Almost everything I do at work is judgmental.
My own judgment is that I can judge. Please don’t judge me on that!
