Fil

La réponse du journaliste du NY Times :
That Tesla Data : What It Says and What It Doesn’t
▻http://wheels.blogs.nytimes.com/2013/02/14/that-tesla-data-what-it-says-and-what-it-doesnt

La mayonnaise monte et ça devient un moment décisif dans le combat dantesque entre la presse et la blogosphère…
cf. ▻http://seenthis.net/messages/114778

#TeslaGate

Bianca Bosker : Tesla, The New York Times And The Truth About ’Truth’ In Data
►http://www.huffingtonpost.com/bianca-bosker/tesla-new-york-times-data_b_2698557.html

Data is supposed to be the authoritative alternative to selective anecdotal recollection, though more data seems in some cases to only make our disagreements more heated, with every party able to marshal a seemingly stronger and tailored case. In Tesla-gate, Big Data hasn’t made good on its promise to deliver a Big Truth. It’s only fueled a Big Fight.

The problem is that the data shows what happened, but not why, argued David Weinberger, author of Too Big to Know and a senior researcher at Harvard University’s Berkman Center for Internet and Society. While the stats and facts capture what occurred inside the car, they tell us precious little about the people that made those things happen and why they behaved the way they did.

Observers aren’t interested in the Tesla tiff because they care deeply about whether Broder turned down the heat when he said he did, or set cruise control when he claims, explained Weinberger. Rather, the data is useful to us only as it helps us shape a clear narrative from the data — the story of the smug CEO attacking an innocent journalist, or the tale of the corrupt reporter trying to take down an innocent entrepreneur. Yet hard numbers capture action, not intention, and the conflicting accounts offer no more insight into the “true story” onlookers want to assemble.

“The only reason we care about the data is because it fits into a story that was interesting for reasons that have nothing to do with the data itself,” Weinberger said. “We’re not trying to understand the data or even what happened. We’re trying to understand what the humans in the story were doing. Was Broder driving around to drain the battery, as Musk says? Or was he circling around trying to find the badly-marked power source the way Broder says? What we want to know is human intentionality, and data doesn’t settle that question.”

At least not yet.

Et donc logiquement, le progrès des algorithmes devrait finir par permettre de reconstituer l’intention…

Massachusetts-based startup Affectiva has developed emotion-recognition software that allows the company to track audience reaction to different stimuli — advertising, in particular. Solariat, which applies artificial intelligence to social media marketing, can pick up on people’s intentions based on what they share to a social network.