Discovering the world of artificial intelligence with Axiom Zen.
Gambler's Paradise
An inherent part of gambling is knowing that luck will be a factor; you can plan well, and play the odds, but at the end of the day the dice fall where they may. This truth is apparent as UNU fails to live up to its promise from last year's Kentucky Derby, while at the same time we're seeing AI getting better at predicting Supreme Court decisions. There's no such thing as a sure bet, but when gambling, when is smart - smart enough?
Article of the Week
Why Artificial Intelligences Should Have to Explain Their Actions
If you don't know how your microwave works, it doesn't really matter. But if you're going to let an artificial intelligence drive your car, or teach your children, it's important to be able to ask it why it makes the decisions it makes. This transparency not only allows human intervention when necessary - it also makes us feel safer.

"Enter the right to an explanation, a movement to combat the broad move to a “black box society”—a culture that largely accepts we have no way to understand how technology makes many basic decision for us."
The Bleeding Edge
An excellent example of AI augmenting rather than replacing jobs is this recent study, which used artificial intelligence to predict the likelihood of a future heart attack, giving doctors the tools they needed to keep those patients healthy.

"In a recent study, the AI system was more accurate at predicting these possible occurrences than doctors."
Teaching Machines to Detect Fake News Is Really Hard
Fact-checking is hard. It's hard for humans, but it turns out that it's even harder for AI. Tracking sources isn't enough; you have to categorize whether that source is, in itself, reliable. Some of that is about pattern recognition, knowing whether a source is likely to be a good original or not, and that judgement call is really hard for machines.

"While a 27 percent accuracy rate for a deception detector isn't going to singlehandedly put a stop to the proliferation of fake news any time soon, it underscores the difficulty of teaching a machine to recognize deception."
Last year UNU (a crowd-sourced version of AI) made headlines when it correctly predicted the superfecta of the Kentucky Derby, getting not only the four winners right, but in the correct order. This year? It did... not so well. This goes to show that crowd-sourced gambling still relies on the knowledge of the crowd, which isn't actually prescient,.

"Two of its top four picks missed expectations significantly, and it failed to foresee the emergence of one dark horse. "
Artificial Intelligence Prevails at Predicting Supreme Court Decisions
In an interesting counterpoint to the UNU story, traditional AI (bet that's a term you didn't expect to hear in 2017) faired much better than the crowd-sourced variety. It managed to predict how the Supreme Court would vote better than legal experts.

"From 1816 until 2015, the algorithm correctly predicted 70.2% of the decisions... Knowledgeable legal experts are only about 66% accurate at predicting cases."
We often talk about unexpected industries where artificial intelligence is making huge strides, but one we haven't touched on is reproductive health.

"Technology could one day alleviate the emotional and financial strain of IVF. Scientists have begun devising more precise methods of choosing the embryo with the best shot."
“By far the greatest danger of artificial intelligence is that people conclude too early that they understand it.” ― Eliezer Yudkowsky
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