I left academia after my PhD. Here are a few reasons why:

1. The problems studied in TCS today are primarily of focus simply from previously being of focus, with no ground in eventual practical impact. In the field of data structures, for example, there have been a host of papers on the dynamic optimality of binary search trees, that is, finding the best BST in terms of visiting the fewest nodes for a sequence of element accesses ( Demaine et al., SICOMP '07, Iacono & Langerman, SODA '16, Kozma & Saranurak, SICOMP '19, to name a few), without asking why we are restricting to a binary search tree in the first place. Our work considered instead a general data structure for partial orders, a new angle which resulted in top tier publications—but garnered few citations, as it is not what the community is focused on. At the end of the day, 42 paper folds get you to the moon, and practical efficiency must get beyond asymptotic analysis—O(log n) should be treated more like a factor of around 20—significant due to being a large constant, not due to its growth rate. An honest assessment surmises theoretical computer science of practical significance was largely completed in the 20th century.


2. Academia is a socialist institution. Papers and grants are voted upon by reviewers, rather than having merit tested in the market. This is how it has to be—research must be available to all for progress to be made. But reviewers are far more fallible than consumers, and papers are often rejected for bad reasons. The incentive misalignment is palpable—reviewers often write only a few sentences reviewing a 20+ page paper, after having multiple months to write a review. It is this same structure that allows esoteric research to flourish and highly impactful research to be undervalued—the feedback mechanism is a weak differentiator of good and bad ideas. I still believe academia is important—letting smart people pursue pure mathematics and funding research without commercial ties serves a critical role, but it is not an efficient system. Graduate students/postdocs are underpaid and lecturers/professors overworked in order for it to persist.


3. The academic community is extremely competitive and can be somewhat ruthless. It took a year to publish our lattice paper (SWAT '20), since the paper corrected a mistake in an earlier paper (Talamo and Vocca, SICOMP '99). The authors of the previous paper were consistently recruited as subreviewers and denied the issue in their work, which was too technical for other reviewers (and perhaps the authors themselves) to discern. In another example, very little credit was given to our min-cut paper (SWAT '20) in Gawrychowski, Mozes, Weimann, ICALP '20, and Mukhopadhyay & Nanongkai, STOC '20, the former of which at times copied even the format of our paper. While communication with both sets of authors helped resolve the issues, to which I am thankful, it is disheartening to have to fight for small slivers of academic credit.

For those wishing to pursue a PhD, I would first consider that there is typically much more to do in applications than in core science, but if one loves learning and is mathematically gifted, I would recommend pursuing it in artificial intelligence, where the applications are of huge practical importance and it is still (currently) possible to make meaningful intellectual contributions. This could easily change in a few years if we achieve AGI (as I suspect we will).