Abstract
Can human factors save our democracy? We are in the midst of the U.S. presidential primary campaigns – an ideal time for the Human Factors and Ergonomics Society to weigh in on the subject of how to improve the voting process, particularly given that there have already been a number of allegations of voting snafus in the past few weeks. In fact, the importance of the work reported here by our friends from Georgia Tech (Gable et al.) can’t be underestimated. Let me tell a story.
I served as an expert witness in the lawsuit that was brought by a group of citizens in Palm Beach County, Florida, in 2000. Their claim was that the poor human factors/ergonomics (HF/E) of the ballot caused them to accidentally vote for Pat Buchanan for president when they intended to vote for Al Gore. The ballot, which is reproduced in the Gable et al. article here, didn’t have the benefit of HF/E expertise, resulting in a poor design that was prone to the error claimed by the plaintiffs. I was retained to explain just that: how the poor HF/E of the ballot resulted in the errors in question.
I’ll be the first to admit, however, that the other expert in the case had a story to tell that made my testimony almost irrelevant. He was an expert in what’s called quantitative political science. He came armed with overwhelmingly persuasive statistical models that showed how the number of votes cast for Buchanan was a consistent ratio relative to various variables in every other county in Florida – until you got to Palm Beach County, where the number of Buchanan votes was dramatically higher than the statistical model predicted.
The judge ruled that, although the evidence supported our case, there was no remedy under Florida law for such a thing, so the erroneous vote had to stand. Whoever won Palm Beach County won Florida. Whoever won Florida became the 43rd president of the United States. Thus, poor HF/E changed history. I won’t comment on whether it was changed for good or bad. Let’s hope, then, that the work published here by Gable et al. will be listened to.
I predict that we HF/E professionals will find ourselves incorporating risk analysis into our efforts more and more in the future.
The next article, by Suzanne Beltman and colleagues, shows how human factors can be used to address another important problem, reducing energy consumption. The authors show that it’s a tricky problem requiring different types of feedback for different types of energy users. In the meantime, they describe some innovative approaches to building user requirements that, potentially, have wide applicability.
Then we offer you something different: an article that explicitly takes on moral/ethical issues, namely, what guidelines we should put in place to ensure that robots, including flying drones, will be used for good rather than evil. Stowers et al. offer some very thought-provoking ideas on this subject, which make me wonder if we shouldn’t take more time, in general, to consider the ethics of our work.
Hobbs and Lyall offer another article about drones. They provide a framework for addressing the human factors of operating drones. The framework they present should have wide applicability as we rush into an increasingly automated future.
Finally, Horberry et al. address safety through human-centered design. Their example is from the mining industry, but anyone concerned with safety (which, I dare say, is – or at least ought to be – just about everyone in the HF/E profession) will find some potentially usable and creative ideas. They describe a tool, the operability and maintainability analysis technique, that integrates participatory ergonomics with risk analysis. I predict that we HF/E professionals will find ourselves incorporating risk analysis into our efforts more and more in the future. I certainly see that today in the medical device area, where I live.
As always, we welcome your feedback, and keep those manuscripts coming.
