What if you could remix your laugh from fake to ‘real’?
We fake laughter all the time. We do it to be polite, hide our ignorance, and even to fit in. Our social interactions sometimes depend on it.
The synthHAsizer is a tool for playing with this verbal display of communication. With it, visitors record their own fake laugh and use sonic filters to remix it from fake to real.
We don’t know how fake laughter evolved, but we do know it is part of our speech, and follows specific sonic patterns. Unlike real, guttural laughter, fake laughter is ‘spoken’, and we’ve learned to recognize its forgery.
Studies show that fake and real laughs vary in speed, pitch, breath sounds, and crescendo—and this is consistent across cultures.
We actually get better at discerning real from fake laughter as we get older, peaking in perception in our late 30s.
The most important sonic variable known so far is speed—laughs that are sped up or decreased in duration by 33% sound more real. And this means we also get better at figuring out the social motives of fake laughter.
With the syntHAsizer, gallery visitors can record their own fake laugh, remix the speed and pitch, play back their ‘real’ laugh and keep tuning until they perceived it as ‘real’.
Do we want AIs to be able to produce ‘real’ laughter?
As this piece was launched at Science Gallery, Alexa started laughing, and it turns out we were not comfortable with that.
This object invites visitors to explore and debate the sonic qualities of fake and real laughter as well as the possibility for AIs to produce ‘real’ laughter.
Referenced Studies + Articles
The animal nature of spontaneous human laughter (Gregory A. Bryant, 2014)
Amazon Knows Why Alexa Was Laughing At Its Customers (New York Times, 2018)