Slide 3: These were the sorts of feedback loops I wanted to demonstrate using Google Translate. My first question about a pause was: What is the reason for the pause?

Their obvious answer: a person is wondering what came before or after what. But also, as soon as I asked, “How was that?,” there was a “nonresponse” moment in which the response type was all about the pause. Sometimes it was urgent. Sometimes it was decorative. The pause is a part of the occasion. The pause is here.

There was no context (no mention of a train, no mentioning of moving traffic, no mention of the veil, nothing) but still the response was empathetic. Even if it wasn’t exactly helpful.

Slide 4: Here I immediately learned about the trajectory. Does it seem as if the frame was right? Is there a shape at the beginning or the end? (I wanted you to say this in a human-speak (e.g., “mmmmmm”) because English nouns don’t get from noun to noun, but verbs. The interrupt button only sends back verb answers.)

The response: a slower mode than the previous answer, but also the positive version. So not to say an emotional response, but it wasn’t negative either.

These are the sort of sliders you can play with if you use a Google machine translation program. These could be used as feedback loops to create feelings by linking people to specific words or phrases with certain images or expressing them by using statistics.

These can also be used for context, where the goal is to connect different words or emotions that might have gotten lost in translation. In one set of slides, the language of the English version was juxtaposed with language from a pair of Japanese posters (Japanese is a language of juxtaposition — this means something that contrasts with the original in a particular way).

These should feel immediately familiar to foreigners, but also to scientists and policymakers. For example, you can trace out all the ways you can rationalize a delay or contradict the original intention, or use complex statistics to make it look like you’re making a more nuanced argument.


Slide 5: Here I asked my friends about whether they thought that the car was supposed to veer left or right, whether they “realized” that they were painting their walls green or whether they knew what the words (“wall green”) meant. Even though this was a panel they wanted to participate in, it felt like a live conversation. (Although they are online and they also don’t use text messages for interacting in real life.) They still felt connected to me.

Here, all your comments had to feel relevant to the situation, and there was no way to boil it down to a number. Do you know why I was interrupting? Should I have brought up the weather? Does any of this matter? Was anyone afraid of being misunderstood or being criticized? What happens next? The more the questions run together, the more opportunity you have to connect all these dots, so it didn’t feel as though you were looking at a work-in-progress.