摘要: In the first real test of AI in a crisis, the results are mixed. While many individual applications are helping, the tech remains immature and unable to address complex public policy issues.

 

 

One common belief about AI is that it will help solve the most complex problems in the world. A great example is nuclear fusion, a longtime grail goal, as it would offer virtually unlimited power with little or no pollution. With episodes of hope and hype, the realization of this goal has been elusive. Now it appears that AI may be the key, with a working demonstration expected within five years. If true, commercial viability could happen within a couple of decades.

Given the promise of AI, it is not surprising that in a pandemic all eyes have turned to this technology for a vaccine or effective treatment. However, most AI applications learn from large amounts of data, and with a “novel” virus, this information is in short supply. What data is available may not provide an accurate picture and that picture may change over time as more information is collected and correlated. For instance, months into the pandemic, the Centers for Disease Control added six new symptoms for the disease.

The downstream results of this are inaccurate models of virus spread and mortality prediction and also questions about its diagnostic contributions, leaving humanity to fly mostly blind. Basically, garbage in, garbage out. While AI has assisted in fighting the pandemic with disinfecting robots and the delivery of supplies within hospitals, AI leader Kai-Fu Lee gives AI a B- so far for its contribution towards fighting the virus.

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轉貼自: informationweek

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