Disruptive Proactivity

Buried in Apple’s Developer Conference last month was the release of “a PDF format for AI”. Build a model on one system, and open it identically on another. As PDF did for document sharing, this will do for sharing AI models. The person who uses an AI no longer has to be the person who trained it.

Training is feeding it a load of past data where you know the outcome, and it figures out how to reproduce them. Use is feeding it new data, and it tells you what it thinks the outcome should be.

There are also additional rounds of training when “new” data has become “past” data, with both the outcome it expected and the outcome it received. (One reason the AI outfits use games to develop models is the scoring mechanism gives an instant, simple, and clear metric of success and improvement.)

This approach works easily for numbers, text is harder, but also doable, if you have enough context, or the target is important enough.

There is a twitter account @trumps_feed which is a copy of the twitter feed that Donald reads. There is another feed of what he then does. It is unimaginable that various entities around the world are not feeding both to an AI. It takes very few resources to extend that historically.

That creates you an AI to predict what DJT might say in response to something. Feed it all Donald’s tweets, and you can produce a model of him. It takes a load of processing to build, but once built, can now be freely shared. Given the commercial services that will monitor what particular targets say on twitter, pretty soon, they’ll offer more analysis.

Doing that with facebook / tumblr / instagram / twitter of popular (or otherwise) people, including teenagers, starts to get very creepy very fast. Twitter may be easy, but facebook has emotional colour.  This is also why the AIs looking for intent train a lot better when there’s an emoji for meaning in the training dataset.  

Facebook imply that they already do something like this, as their salesman brag they can tell when users feel something – of course facebook outsource “doing something” with such identifications to the highest bidder. But today’s megacorp unique tool is tomorrow’s app project – everything becomes available to everyone.

Samaritan’s radar shows what happens when institutions get this wrong – but copying of models means it’s no longer just institutions. If someone or their app can read your facebook feed, new tools mean they will be able to make the same inferences facebook claim to do.

The best analogy is simple: Cambridge Analytica’s mindset and tools in the hands of every child in the playground.

Apple would likely prevent such an app on their App Store, but Google Play would let it in with open arms. The AI people would claim that’s not their problem.