More papers are getting published than any human could possibly read. Those publications are getting stacked up across many different fields and in the case of machine learning the sheer volume of content is staggering. You could try to only focus on a specific journal or two, but some of the most cutting edge research barely goes into the journal system anymore. A lot of it is just sort of pushed out online and those cutting edge researchers are on to the next project. It feels like a vicious cycle of papers for the sake of papers. My efforts to communicate and share my thoughts are generally focused on the medium I’m using and having some reason to share it with people. Within that framework of the necessity to communicate something is hopefully a better line in the sand for what should end up in a paper. We may hit an inflection point where only the top researchers in a field are able to pull together references and share content in a way that is widely read and dispersed. It would be a method of gatekeeping by sustained successful communication, but this could create a type of bubble around a top set of researchers and it could very well obscure the future edge of technology.
This is a topic that I’m really concerned about obviously. I have spent a good portion of my morning thinking about the future of academic research and the fragile current nature of the broader academy of academic thought. Intergenerational equity within the academy is about the effective storage and sharing of knowledge across the shoulders of giants as the intersection of technology and modernity occurs. Solutions to that quandary are probably beyond any single weblog post or thinking session. It will take a collective action within the academy to rebalance the means of communication toward something new. Somebody within a major field will need to hold some type of conference, lead a nationwide chautauqua, or create an institute to begin that process. Ultimately the system of introducing knowledge in any academic discipline involves lectures where a profession reduces a mountain of content into a presentable set of mapped coursework. That process sometimes ends up in books being published and other times a few of those textbooks become the standard across a discipline. Even the best ones either evolve over time or are replaced by the next set. That is a natural part of communicating the essence of an ever growing mountain of knowledge.
I keep thinking that maybe every discipline will end up with a sort of encyclopedia of knowledge for that core area of exploration. Just like people built out giant tomes of knowledge to share content when print was the primary medium of communication, some type of modern encyclopedia for a field could provide a foundation for begging to understand a vast accumulation of knowledge within a field. You have to have some way of opening the door to people wanting to learn about the content, but most of them cannot start at the end of the stream of knowledge by reading the latest work by the foremost experts in the field. They need some type of foundational knowledge to be able to understand and consider that work at the bleeding edge of what is possible. In some of the sciences reading the mathematics presented on the page alone requires a certain amount of knowledge before it could be comprehended. My abilities in mathematics are decent, but occasionally when reading a machine learning paper the mathematics on a page are daunting and take me a bit to try to figure out exactly what the researcher is trying to communicate to me as long strings of math are not annotated and commented like code to help people along the way of reading them from start to finish.