The Supreme Court declared affirmative action programs at public and private colleges and universities unconstitutional on Thursday in a decision written by Chief Justice John Roberts.
The decision puts an end to systems designed to help Black and Latino students access higher education after centuries of racial discrimination. Colleges and universities will no longer be allowed to seek greater diversity of their student bodies by preferencing race.
Since the labs have extensive programs for students we should ask how this will effect the NNSA lab system. There are also several programs at the labs designed for minority students does this get effected also?
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Another question which I think could be more relevant in the next five years is is AI will essentially be able to replace some portions of the labs workforce. This is tricky one because at LANL part of the money flowing to the lab is about employing local New Mexicans.
https://www.visualcapitalist.com/sp/ranking-industries-by-their-potential-for-ai-automation/
This report argues that 48% of office and admin support could be eliminated by AI. This would be large number of people at LLNL and LANL. At LANL this would effect native NMs far more.
However it is not just admins, it also says 37% engineering, 36 percent physical and life science and 28% math and computer science.
I have some doubts about this, for example in the case of science and engineering, I would guess you would see what we have seen historically is that the number of people working will not decrease but become 37% more effective. Or you get a 37% increase in the number of papers or results for the same people.
Admins is bit tougher since it is not about producing something. My guess is you will not get 48% reduction of admins at the labs but a 48% increase in bureaucracies. In other words as the admins become more efficient it means you can create more and more rules and pile on more things to fill out and the system can still handle it.
Overall I have doubts AI is going to replace any jobs, it might change the nature of how some jobs are done. I suppose it could be possible that in industry it could replace jobs since less workers means more profit. The labs work differently so I do not see AI having much impact other than helping grow the complexity of the place not the efficiency.
I believe one of the UC/LLNL management options presented before the wholesale employee shift to the current for-profit LLNS, was to keep science and engineering staff under UC/LLNL, and subcontract out all other non-science and non-engineering Lab jobs such as HR, security, plant services, etc.
Already seeing this at Livermore in engineering with the required training, then you get a nasty gram a few weeks later from an admin “ you took a GET class and didn’t charge the 15 minutes to the GET account, so you spent an hour trying to back charge 15 minutes to their GET training account. Or worse yet you charged an hour to GET and the class should only have taken you 45 minutes to take!!
In an alternate scenario where AI creates an economic boom, the labs would grow along with the economy as tax revenues increase.
Certainly also, in a transition to a wartime economy if that were to occur, the labs would also obtain increased funding.
In a more general sense, the rapid adoption of new technologies, is almost certain, whether things tend towards an arms race or economic prosperity and peace; so funding will in any case, undergo increase.
It is certainly possible though, to have a decline in employment and budget, for example if future pandemics, war, natural disasters, or emigration were to reduce the US population, or if through some disaster the country fragmented like the Soviet Union.
Also, of course, there could be some system put in place to provide basic income or a government stipend, where humans would no longer be willing or able to work.
It could also be of course, that humans would not be seen as reliable or honest enough to work with sensitive technologies or the development of any technology at all, in the case where AI gains control, also as technology develops humans may simply be unable to contribute anything of value.
In particular, it seems that the human brain is not quantum in nature but rather is some sort of ordinary neural network not able to process quantum information. As these technologies become prevalent, humans may simply not understand key results in science and technology.
In other cases, the human mind may operate too slowly or have too limited a capacity to contribute, in particular in a few years' time machines may exceed human intelligence in a general sense, and the aggregate capacity of humans to process information, will at the same time be much less than that possessed by the AI hardware our factories will produce.