I guess the bottom line is that, when it comes to fields like philosophy and history, the literature will be heavily biased by the authors, and if one really wants to reduce this bias the one must consult multiple sources.
Wonderful recommendation. I am listening to 'A History of western philosophy' at the moment and I enjoy every single minute of it. Its my clean and cook book. Not only is it a literary masterpiece, it is a well researched account of exactly what the name says. As a bonus you get the whole story commented by one of the greatest philosophers of the 20th century.
Academic conferences tends to be very technical, so don't expect to be able fully follow the talks. A review paper
By human-equivalent i'd guess you mean equivalent in if not all, but in many different aspects of human intelligence. I wouldn't dare to have an opinion at the moment.
Anyone else?
Yes I am, and I'll soon start looking for PhD-positions either in physics or some interdisciplinary field of interest. I know I seem a bit over-optimistic, and that such radical changes may take maybe at least 30-50 years, but I'd guess most of us will be alive by then so its still relevant. My main point is that step by step theoretical tasks will move to the space of computation and the job of the theoretician will evolve to something else. If one day our computers in our computer aided research starts to output suggestions for models, or links between sets of data we haven't thought about comparing wouldn't those results actually be a collaboration between us and that system? You maybe cant imagine automating everything you do, but I'm sure you can imagine parts of your research being automated. That would allow you to use more mental resources for the conceptual and creative part of the research and so on..
I agree that the conceptual (non-simply-symbol-processing) part of theoretical physics is the tricky part to automate, and even if I am willing to accept that that last 1% will be kept in the monopoly of human beings, but then that's it; theoretical physics will asymptotically reduce to that 1% and stay there until AGI arrives. Its not bound to change over night, but the change will be the product of many small changes where computers start to aid us not by just doing the calculations and simulations but more advanced tasks where we can input sets of equations from two different sub-field and letting the computers using evolutionary algorithms try different combinations, operate on them and so on and find links. The process could end where a joint theory in a common mathematical framework succeeds to derive the phenomena in both sub fields.
EDIT: Have to add that it feels a bit awkward to argue against the future necessity of my "profession"..
For example, music composition, writing fiction, and similar artistic endeavors require that the artist know what people enjoy. I think that that will be done by humans for the foreseeable future.
Regarding music composition; there are already algorithms being developed for predicting the potential of a song becoming a hit. Next step could be algorithms that creates the songs by themselves. Its all about optimization with positive feedback. Algorithm: Create a piece of art A such that A has a high probability of satisfying the ones experiencing it. Input statistics about human nature + reaction to previous generations + reactions to man made art of the same sort. Most people wouldn't care about how that piece of art was made. (But I guess this will take a while)
My goal was/is to start a discussion around: 1. Strategies today for maximizing probability of being needed in the future. 2 Even more interesting, what tasks are hard/easy to automate and why? 3 The consequences automation will have on global economy. So far, the comments covers a little bit of all.
1 Hindsight bias? Quite a diagnosis there. I never specified the level of those algorithms.
2 Which part of theoretical physics is not math? Experiments confirm or reject theoretical conclusions and points theoretical work in different directions. But that theoretical work is in the end symbol processing - something that computers are pretty good at. There could be a variety of ways for a computer to decide if a theorem is interesting just as for a human. Scope, generality and computability of the theorems could be factors. Input Newtonian mechanics and the mathematics of 1850 and output Hamiltonian mechanics just based on the generality of that framework.
Even I have a chapter in a textbook, its not a measure of quality :) Conference proceedings sometimes are published as a book, with ISBN and all.