There is a significant difference the way a person with PhD approaches unsolved problems vs a person without PhD. A person with PhD will typically like to inve

There is a significant difference the way a person with PhD approaches unsolved problems vs a person without PhD. A person with PhD will typically like to invest huge chunk of time to digest much of the prior art. They want to systematically understand what worked and what didn't in the past. They then bring in their unique understanding of small set of techniques/cross-domain expertise to combine with prior art to attack the problem. It is important for them to craft well designed experiments and lean on tools like mathematics to guide their next steps. Their goal is to make sure anonymous reviewers of their work are satisfied with proof they present of their hypothesis. A person without PhD typically doesn't want to take a lot of time going through years worth of prior art. Their approach usually boils down to developing intuition via initial random search and then iterative experiments to strengthen intuition. If this doesn't work out over a period of time, they will probably want to move on to something else instead of keep creating next little insignificant bump of progress. The frame of mind is get to near-instant gratification as opposed to possibly spending all of your life in to something that wouldn't make any impact in real world but might build useful steps for future generations. It is hard to say one approach is better than other for all classes of problem. However using the first approach requires certain training, rigor, discipline and, most importantly, frame of mind - we call PhD. It is only recently and in few fields like AI that research careers have become desirable from financial perspective. However in most of the fields, things are very different and you would rarely see anyone demanding to be theoretical mathematician or quantum physicist, for example, without a relevant PhD while also receiving modest income with no promotions or stock options. However, it has become clear that for many advanced problems the random search approach typically maxes out quickly because search space becomes prohibitively large and developing correct intuitions requires climbing knowledge pyramids of epic proportions. For example, invention of transistors, GPS or techniques like initialization or dropout in deep learning wouldn't have been possible without PhD style multi-generation approach and concrete mathematical understanding. Having said that, I'm against hard liners who create rules that being researcher requires PhD and one without it cannot innovate or do creative work. Many complex and most valuable innovations have been done by non-PhDs such as Faraday, Edison and Wright Brothers - interestingly in all of these cases people with academic degrees gloriously failed working on same turf, for longer time and better funding (Davy, Langley etc).