Recalibration of Expectations as to AI Capabilities can be Painful and Costly
Monday, July 9, 2018 at 10:32AM
Charlie in Digital Financial Reporting

It is really, really hard to figure out if the claims people make about artificial intelligence (AI) will come to pass.  This article, Self-driving cars are headed toward an AI roadblock, highlights 2015 predictions about when self-driving cars would be on the road. Per those predictions, we should be seeing more driverless cars than we are seeing.

So, what is the problem? In a word: quality. Consider the following excerpt from the above article:

But the dream of a fully autonomous car may be further than we realize. There’s growing concern among AI experts that it may be years, if not decades, before self-driving systems can reliably avoid accidents. As self-trained systems grapple with the chaos of the real world, experts like NYU’s Gary Marcus are bracing for a painful recalibration in expectations, a correction sometimes called “AI winter.” That delay could have disastrous consequences for companies banking on self-driving technology, putting full autonomy out of reach for an entire generation.

How do you evaluate the claims and predictions people pushing technology make? The answer is understanding the details.  That is why documents such as Computer Empathy are important. Today the world is full of people making predicts and claims but there are fewer that are actually delivering the goods.  If you really want to evaluate the predictions and claims of the snake oil salesmen trying to separate you from your money; then pay attention to the details.

It really is that simple.  It may not be easy if you have not been paying attention, you might have some catching up to do.

Don't get me wrong.  AI will work.  The question is what are the true capabilities.  Me, I am focusing on the easy end of the spectrum of AI functionallity, expert systems.  Expert systems is already a proven technology.

Article originally appeared on Intelligent XBRL-based structured digital financial reporting using US GAAP and IFRS (http://xbrl.squarespace.com/).
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