Mapping my Emotional Response to a Black Mirror Trailer with Affectiva
I came across Affectiva while reading an IDEO article about affective computing. I started off with watching a YouTube clip of puppies and horses, and didn’t get much of a response out of the software. So I decided to see what I could find on YouTube regarding Black Mirror.
I’ve only watched the “Hang the DJ” episode so far this season, so many of the content frames were new to me in the trailer. I couldn’t help but be self-aware of being recorded while I watched. I remember thinking to myself something along the lines of “I’m being watched by the software, should I show on my face how I feel on the inside?” I could be wrong, but I feel like the anger and disgust emotions were more strong and instant while watching the trailer, while I remember thinking to myself that maybe I should try to show I like something and attempted to smile.
Sometimes when I thought I was smiling, I assumed that Affectiva would show joy. But contempt? I didn’t have the thought in my mind that I was watching something “deserving scorn”. I remember thinking something was beautiful or funny — I this case hearing “What a Wonderful World” while a shot of a car driving through the desert was displayed. It made me crack some kind of emotion on my face.
As I watch people scrolling on their phones in everyday life, I feel it’s rare it is to see a strong reaction in public for anything other than comedy. People are more than willing to let the world see them laughing out loud to a funny text or video. Perhaps many people are more likely to hide their feelings and maybe just knit their brows when reading something irritating on Facebook or from a co-worker.
Is there a way for me to be observed without knowing I’m observed, and is that ethical?
There are many ways this technology could be interesting for use in the entertainment business. Different age demographics might respond more powerfully to certain segments of a movie. Reactions might be different enough to warrant segmentation in marketing or even endings for a plot. I do feel that after using this software its use will be most powerful when people make strong, unexpected facial reactions. It might still need some fine-tuning when the subject knows its being watched.