I’ve gone to a number of job talks lately, since the department is interviewing people, which brought up something I’ve been mulling over since I started grad school. I’ve gone to a huge number of engineering talks aimed at “a general audience.” There are levels of generality, from “control theorists not studying distributed control of hybrid dynamical systems” to “people who look at systems engineering” to “electrical engineers” to “engineers” to “technical people” to “layperson.” A shockingly large number of people I’ve seen talk fail to grasp the fineness of these gradations.
One problem is the “intelligence of the group” issue. In order to pitch their talk to a wider audience, the speaker will dumb down a portion of their research or will abstract away some details. In the former case, they obscure their own contribution by making the problem seem easy. If they then go and introduce some complicated algorithm to solve the problem, the audience may wonder why they went to all that effort. In the latter, they often make their problem seem very similar to another problem that is very simple. When pressed on the point they may fumble because it’s easier to abstract away than to put in the details afterwards. Both simplification and abstraction are important to make the material accesible, but I’ve seen many talks run afoul of underestimating the audience’s ability to follow the argument and find the inconsistencies.
Often times speakers mis-focus their attention. I’ve seen this happen in several ways. Sometimes they wrote the talk for some one hour seminar to a more general audience and then tried to give it to a narrower group in less time. Other times they have just one set of slides for all versions of the talk and get bogged down in the beginning. These can be fixed by just making a fresh set of slides for every talk. Slightly less frequently, they feel the problem needs 5 motivating examples in order to get people interested and they spend all the time explaining their examples. This also happens when work is interdisciplinary. For example, do not give a talk to machine learning people by emphasizing all the points that are more of interest to cancer biologists.
The last and most egregious problem, I think, is that speakers do not have an objective to their talk. Maybe it’s the actor in me, but giving a talk is like doing a monologue, and you can’t just get up on stage and read the text of the monologue without pointing every line and without making the whole thing have an overarching objective. The objective of a job talk should be self-evident (although not to everyone, it seems). Conference talks need objectives too. Most importantly, if you have a poster you better have an objective or people will leave while you’re talking, a truly disheartening experience, as I well know.
I’m not saying that giving a talk is easy — it is a piece of theater, and like all pieces of theater it can be amazing, terrible, or “not quite work.” But thinking about all these talks really reminds me that these aren’t things you can just “phone in,” especially if they are about your research. And some people just don’t think about that enough before getting up there.