As a PhD student, I feel a lot of pressure to sound smart. When I present, usually in the setting of group meetings, but also in formal presentations such as those we practiced in Great Presentations, I feel a lot of pressure to come off as a productive researcher. This is evident in the tons of stuff I try to fit in my talks. While I have had no talks that went overtime, the truth is I had always prepared more content than I delivered. My urge to tell more—wanting to give more background on robots, wanting to show every visual to convey the complexity of my chip design—stems from the uncertainty that my output passes muster for the field I’m entering. “I’ve put in so much work! Surely everything I did is worth telling about,” I think to myself when planning my talks, “If I made any of this seem simpler than it is, my audience may confuse my work for an easy project.” Leaving out any detail and every bug I encountered would be such disservice to the hours poured into making progress. The pressure to give dense talks is also due to an impression I get from being an audience in other presentations, those given by professors and more senior students. As a PhD student still learning the arcane language of my field, I often find it hard to understand talks by more established researchers, and when I do understand, the efforts that went into the research always seem herculean. As a result of these pressures, I feel I aim to impress (and possibly to beg approval) rather than to communicate when I am on the stage. When I am pressed for time to hit all the points I planned, my mind becomes singularly focused on powering through the content; my story gets muddled, I forget to breathe, and “um”s, “so”s, “I think”s break out. Being rushed is also bad for my body language: I break connection with the audience, I cease to interact with my visuals, and I stare at my own visuals. Committing to giving a good presentation, especially one that communicates rather than merely dazzles the audience with myriad details, and in particular one that fits in the talk’s time limits, requires courage. Crafting such a presentation requires omitting the details in the research that were often the hardest parts to overcome. The presenter has to be confident the research is sound even when parts have to be left out. Having a well-timed presentation gives the audience the chance to absorb the story, and it gives the presenter valuable time and a clear head to be aware of the talk’s delivery. Among all the feedback I got from the Great Presentations class, this advice to exercise restraint while planning talks is the most important, since it affects so many other aspects of presenting. The other major finding I had in Great Presentations is about practicing and improvising. Now that I frequently speak about my own research, I’ve come to understand presentations as assemblages of many smaller talks. Oftentimes, presentations are ad-hoc: I may be describing my research as part of a conversation, or I may be put on the spot at a meeting. In every setting, the time allocation and level to which my audience is up to speed varies, so I change the way I assemble my mini talks accordingly. However, while the overall speeches are tailored, the mini talks are often well practiced and get carried over between presentations. When I observe other researchers give presentations, I suspect they are also piecing together previous material. In this method of giving presentations, slides and visuals are an organizational crutch that help cue the presenter’s mind on which rehearsed segment to launch into. Improvising while drawing upon recycled material is itself not a bad thing. I am much more at ease when giving a recycled presentation segment, and as a result my delivery is much smoother. A professional improv comedian once told me, in improvised skits, individual actors often recall lines from previous shows and creatively adapt them to new situations. The interplay between practice and improvisation is demonstrated in Dr. Martin Luther King’s August 28, 1963 speech: the entire segment starting at “I Have a Dream” was off-script, but rhetorical experts point out its elements coming from King’s past speeches and sermons. But the hazard of endlessly repeating segments of old talks is failure to consider whether the mini talks are up to date. As my research progresses, my mini talks should obviously change as well. Furthermore, while giving a familiar talk is comforting for me, I may have failed to consider better ways to describe my research. Question-answer interactions during talks help break the cycle of repeating old ideas. Audience questions taught me as the presenter what ideas are not getting across. I noticed I often resort to rehearsed answers: I start back at the beginning in attempt to tell the full story. Instead, I should aim for depth in my answers. If the question asker didn’t nail the question, guide her to ask the deeper question. Answers to good questions are the best chance to fill in the details that had been left out, and they are the precursors to mini talks to include in the future presentations. Giving great presentations takes time, certainly more time than simply throwing together PowerPoint slides and winging through the talk on stage. But expending time to prepare great presentations is worthwhile. We admire researchers who adeptly communicate their work. Deciding what details to include and what to leave out—to attempt presenting new ideas in untried talk segments, or to resort to familiar spiels—these decisions are the heart of the art of giving great presentations.
We all have our writing mannerisms. One of mine is the three-item list: “…attend meetings, email, and brainstorm…” “…mode of locomotion, sensing ability, and the extent of robot automation…” “…visual sensing, complex AI, and dynamic body control…” “…planning, sensing, and motor control…” “…SPEC for general purpose computing, PARSEC for multithreaded applications, and Whetstone for floating-point-intensive applications…” “…the use of the computer, the needs of the user or organization who owns the computer, and the overall size of the represented problem…” All of these halting, heavy-handed structures came from the small collection of writing I penned for Academic Writing. In recent years, I’ve striven to write concisely. Writing for coursework asks me to hit key points in brief answers, and writing for work demands summarizing remarks to bullet points fit for emails or PowerPoint. This drive to increase the information density in every sentence has caused me to rely on long formal words and unnatural sentence structures to deliver detail. The snippets I listed are the worst examples. In peer editing sessions, I paid attention to where I lose my reader in each piece of writing. Usually I succeed in my great escape the moment I invoke the three-item list, those dreaded chains of noun phrases that so strain the reader’s attention. Instead of packing in detail, I should have expanded on them. Every noun phrase deserves an animated verb—each link should have had the freedom to tell a story, fleshing out its meaning and relevance. Clear and friendly writing uses short words. It should pack the same amount of content that can be absorbed at the speed of reading the text out loud. Smooth writing should also send the reader down to the full stop without stumbling or having to double back to pick up missed words or phrases. Somewhere in the journey of having to read more and write more every day, I have forgotten the joy of reading slowly and out loud. Surely, doing so would have called attention to the three-item lists and compelled me to iron out them out. In writing, telling the story comes first. Compelling science writing is like telling a good story to a friend: it should be chronological, and it should set up scenes and characters only as needed to move the plot. If the science necessitates a definition or a reference to prior work, do so in their deserved sentences or paragraphs, and keep them short. With this advice, I would expand my three-item lists into characters and events as needed to tell the story. During the peer editing sessions in this class, I would sometimes stumble while reading or not understand the intended meaning of a sentence. I would grow weary of the defense “but that’s how it’s written in my field!” This response is flawed and begs two questions—Does everyone in the field indeed agree on the meaning of the text in question, when the writing is ambiguous or inscrutable? What good is it to enforce language barriers to distinguish insiders from outsiders of the field? I admire academics that can explain advanced topics in plain language. They are the writers and speakers who inspire the public and educate newcomers to the field, and I suspect they are also adept at pitching their newest research to sponsors and reviewers, because not all of those readers are ever in the exact same field. The skills for writing for my discourse community and for a general audience should not be so different—even experts appreciate context and clear writing. Good science is accessible. Writing that captivates a broader audience than necessary is better than that which persuades too few. Computer science as a field has the luxury of being relevant in the lives of most of the world population. But with that broad audience comes the hazards of folk science and distrust. We can defend against such dangers through plain, excellent writing, ensuring that the science is accessible to the interested. Elevating the standards for communication is a central imperative in science, and fields can either wither from neglecting this obligation or, by embracing the art, thrive.