I was surprised to learn the degree that electric grids — and subsequently, electricity generation in general — involves prediction. The video I watched described how electricity is generated prior to use, and then distributed based on demand. To ensure that the proper amount of electricity is generated, engineers must predict what anticipated demand will be on a given day. Thus, should they inaccurately predict the demand, they could generate too much electricity (which wastes resources and is difficult to store) or too little electricity (owing to power outages.) I was also surprised by how much electric engineers rely on weather forecasting to make said predictions. The video I watched went on to describe how weather forecasting is crucial to many forms of renewable energy, such as solar panels. I can think of many ways in which this data may be useful: for example, if a particular day is forecasted to be hotter than normal, electric engineers can anticipate increased electricity use as more people rely on ACs to keep cool. Though I doubt predictions of this sort are done on such a local level, I would be interested to see how specific they need to be to have the best accuracy possible.
As such, if I had conducted the interview, I would have focussed more on this point as it illustrates the applicability of prediction. When electricity generation is mentioned, I would anticipate that few people wonder how yield quotas are contrived. Thus, I would expect that few people, not unlike myself prior to watching my video, are aware of the degree that prediction is involved in different aspects of their daily lives. Instead of glossing over the more mundane uses of prediction, I would elaborate on how these mundane practises are far more complex than most people realise or stop to wonder about.