Taking us back to the original post. Jobs for people with training in computer science and biology usually pay pretty well. The problem is that they require extensive training and society has a hard time prioritizing education to provide the training people need.
I wouldn't go to computer science or biology today. Both are oversaturated with people thinking they are the ticket to a great career. I would look at applied physics and some of the science based engineering disciplines. A new science and computation based approach to mechanical, aerospace, civil, and chemical engineering is changing the world. Bioengineering and environmental engineering are growing rapidly. If you can build the math and computer skills to make it, those are the big growth areas of the 21st century. Molecular biology is really really complicated. Messing with it usually does more harm than good. So I suspect the pharmaceutical industry is not a growth area for the next century. And the phalanxes of post-docs sorting out the pathways regulating each gene are going to soon find that the details they unearth are usually not relevant. Sure that gene is involved in cancer risk...but what are you going to do about it if the network is so complicated that external modification messes up too many other parts of cell function. (Just like everything is made of quarks and electrons, but we don't use quantum chromodynamics for engineering, everything in biology depends on molecular biology but molecular biology isn't that useful.) While everyone focuses on biology with dreams of improving health, science based tools for materials science and fabrication are changing the world. Now if only we could solve some political problems so we could train a few billion people to join the effort...
OK, it is standard to argue on slashdot, but it is more interesting to learn and build better ideas. You have interesting points, but are missing the big picture. If you want to be technical I did say 'economic growth rate' which is the exponential rate constant, so steady exponential growth would have zero first derivative of the economic growth rate.
Modern electronics is dominated by classical E&M. Quantum mechanics is important. But the idea of electronic computers was clear and they were being used well before anyone used quantum mechanics to build solid state transistors to make them much more efficient and powerful. On the other hand, in 1800, no one knew what electricity was and no one had any idea that electric currents could emit radio waves to communicate around the planet. By 1900 the electron had been discovered, Niagara falls power plant was powering electric lights in a city and radio communication had begun. The scientific innovations of the 19th century were profoundly transformational. The 20th century added some important pieces...and you are right that biology is where the 20th century really holds its own. But even the green revolution has its roots well into the 19th century. Most of the technology for the green revolution dates back to the 1800s. It was the social embrace of better seed varieties, fertilizer, irrigation, machinery and scientific management much more than genetic engineering that transformed our food supply. Of course the original post has the provocative title 'Greatest era of innovation' and that is subjective. But I think you haven't put a dent in my argument that the 19th century has a pretty strong case for it.
Yes, all the studies showing problems with personalized learning are simply showing that we had not yet figured out how to do it well. There is simply no way that a one-size-fits all bureaucracy can educate as well as a system with tools that allow teachers to tailor activities to individual children. The problem is that personalized education is a much harder problem than many believe. It is easy to make an app that adapts the math problems assigned to a student's performance. But it is much harder to produce group learning activities that match varied skills. And if you put kids each on a single computer which is 'personalized', you can be sure they will learn less than if they are working together learning the social skills and executive function needed to succeed in the world. Eventually we'll succeed in personalizing teaching of social skills, executive function, reading, and math. But it is a hard problem.
In many ways the problem is like artificial intelligence. It is a much harder problem than people thought. But that doesn't mean that it is impossible and as parts of it are solved it slowly changes everything.
In seeking the unattainable, simplicity only gets in the way. -- Epigrams in Programming, ACM SIGPLAN Sept. 1982