Slack CEO: How We’ll Use AI to Reduce Information Overload
Slack established an AI and machine-learning division called Search, Learning & Intelligence early last year to reduce that “information avalanche.” Slack has already incorporated a few featuresthat SLI developed. What are your specific goals for that group?
The third is trying to make sense of the whole corpus [of information in Slack] and have that improve over time, ideally in a way that doesn’t require any manual input [from users]. The computers will do it all; people can just communicate the way they would normally communicate. You could imagine an always-on virtual chief of staff who reads every single message in Slack and then synthesizes all that information based on your preferences, which it has learned about over time. And with implicit and explicit feedback from you, it would recommend a small number of things that seem most important at the time. So whether you’re waking up in the morning or getting out of a meeting or getting off an airplane, when you check Slack, there could be this virtual chief of staff waiting for you, ideally with a near-perfect list of those things that are important to you.
That’s an intriguing idea. What else is SLI researching?
Organizational insights. We had this really fascinating internal project that looked at the strength of connections [within Slack] between the different departments in our company and the ratio of public to private messages along those axes. So if you look at Slack from the perspective of our facilities team, [it turns out] they talk to finance, HR, and security but almost never talk to engineering. If you look at Slack from the perspective of our marketing team, they talk to sales, product, and finance.
I would—and I think everyone would—like to have a private version of a report that looks at things like: Do you talk to men differently than you talk to women?