Taking cues from Terminator mythology might not seem like the best strategy for a tech company to take, but PeopleBrowsr CEO Jodee Rich evoked the rise of the machines several times this morning at the Social Developer Summit in

San Francisco.

“What we’re trying to do is build a Skynet,” Rich said, describing his hopes that the wealth of data in the cloud will help computers better understand human behavior.

It’s a refreshingly cavalier way to for the developers to frame their goals, with the purposeful evocation of pop culture’s reigning idea of machines gone wild.

PeopleBrowsr makes its money by doing sentiment analysis for brands and organizations – they’ve worked with ABC, analyzed Super Bowl tweets for brands and ran a real-time results dashboard for the recent UK elections. But it’s in PeopleBrowsr’s experimental projects that the company's idea of the future of machine learning comes through, an idea propelled by the fact that we’re all documenting history in real-time with Twitter, Facebook and other social media.

We’re documenting history, but Rich expands the import of what we’re doing. “We’re building a collective consciousness in the cloud,” Rich said.

He believes this cloud consciousness will be the key to artificial intelligence.

“With this database of human behavior we have in the cloud, we won’t have to teach machines how to think like humans, just train them to mine the human data to learn behavior,” Rich said.

Towards this, People is building T2, a contextual engine for tweets, what Rich refers to as “human-powered artificial intelligence." Before you send your tweet, T2 scrapes it for data and updates you on conversations going on around you or your subject.

It’s refreshing to hear someone in tech evoke Skynet without all the clichéd connotations associated with the mythology. In all honesty, we should be less concerned about where machine intelligence is going than where the Terminator series has ended up. After what McG did to it, we’re lucky Skynet doesn’t elicit laughter instead of dread.

By Mark Alvarez