Canva's first Chief Algorithms Officer on what the data misses - with Nirmal Govind

Nirmal Govind has spent thirty years trying to predict human behaviour, and he keeps finding the edges of it.

He joined Netflix when the company still had two original shows to its name, and over the decade that followed his work spread into almost every corner of the business: the engineering that makes a video start playing the moment you hit play, the quality checks on content arriving from studios, and eventually the data behind what a company spending twenty billion dollars a year should actually make. He is now Canva's first ever Chief Algorithms Officer.

One of the things his team ran was a test on artwork. Each time a new show launched they would put a batch of different images in front of viewers to see which one made people stop and click, and internally, colleagues would call it in advance. These were people who had spent years studying what audiences do, and they had strong instincts about what would land. Most of the time they were wrong. Human taste, it turns out, is not something you get much better at guessing just because you have watched it closely for a long time.

Kate and Nirmal spend a good while in that territory, in the places where the data runs out. There is a lovely example of a director who chose to open the second episode of a show by continuing a battle scene from the first, with no titles and no credits, just straight back into it. Twenty minutes in, the opening credits finally rolled, and the team watched a wave of people leave in the middle of the episode. Obvious in hindsight. Credits mean an ending, and the audience took the hint.

In this episode, Kate talks with Nirmal about what a Chief Algorithms Officer actually does all day, why an algorithm should let you finish a two-minute job and leave, what happened when he asked an AI tool to size up an opportunity and the answer came back three times off, and plenty more.