metalens
As far as I know, board positions are often filled based on explicitly subjective criteria, e.g. such subjective criteria might be: Who is currently on the board and what personality/skillset/experience does the board need in order to balance its membership? Who does the company & board need in order to: raise as much money as possible, be introduced to the desired go-to-market partners, look good to customers, [insert any other subjective criteria here] etc.
I am not aware of the concept of objective "merit" when it comes to board of directors appointments.
~corrected for bad grammar~
A machine learning model trained to understand Maxwell's Equations can in principle be used perform said simulations, resulting in probably an order or more of magnitude increase in simulation speed. Getting this to work well will reduce the time (and cost) it takes to design optical sensors, radar for autonomous vehicles, smartphone antennas, MRI machines, and more.
Having said that, it would require a lot of heaving lifting to pull this off to achieve near-physical accuracy for real-world physics problems.
A cursory search on Google for "arxiv deep learning electromagnetics" returns results of proofs of concept in this direction.
Except that a disproportionate percentage of poor defendants (who can't afford expensive lawyers) plead guilty before trial because their overworked and underpaid public defenders advise them to.
Logic is that pleading guilty before trial gets you a shorter sentence than going to trial. The alternative is going to trial and being incorrectly found guilty and getting a larger sentence for a crime you didn't commit (your public defender has limited time/resources to make a great case for you).
The American Justice system is particularly unjust to the poor.
Edited for clarity