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posted by chromas on Tuesday March 05 2019, @07:07AM   Printer-friendly
from the open-the-pod-bay-doors-HAL dept.

Is Ethical A.I. Even Possible?

When a news article revealed that Clarifai was working with the Pentagon and some employees questioned the ethics of building artificial intelligence that analyzed video captured by drones, the company said the project would save the lives of civilians and soldiers.

"Clarifai's mission is to accelerate the progress of humanity with continually improving A.I.," read a blog post from Matt Zeiler, the company's founder and chief executive, and a prominent A.I. researcher. Later, in a news media interview, Mr. Zeiler announced a new management position that would ensure all company projects were ethically sound.

As activists, researchers, and journalists voice concerns over the rise of artificial intelligence, warning against biased, deceptive and malicious applications, the companies building this technology are responding. From tech giants like Google and Microsoft to scrappy A.I. start-ups, many are creating corporate principles meant to ensure their systems are designed and deployed in an ethical way. Some set up ethics officers or review boards to oversee these principles.

But tensions continue to rise as some question whether these promises will ultimately be kept. Companies can change course. Idealism can bow to financial pressure. Some activists — and even some companies — are beginning to argue that the only way to ensure ethical practices is through government regulation.

"We don't want to see a commercial race to the bottom," Brad Smith, Microsoft's president and chief legal officer, said at the New Work Summit in Half Moon Bay, Calif., hosted last week by The New York Times. "Law is needed."

Possible != Probable. And the "needed law" could come in the form of a ban and/or surveillance of coding and hardware-building activities.


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  • (Score: 3, Insightful) by jb on Wednesday March 06 2019, @06:37AM

    by jb (338) on Wednesday March 06 2019, @06:37AM (#810599)

    The current fad seems to be to pretend that machine learning is the only way to do AI.

    It isn't, as no doubt anyone who'd dabbled in that space for more than 5 minutes before the present (third, as I reckon it) wave of hype around AI began will happily confirm.

    The second wave was much more interesting.

    The fashion of the day was expert systems, i.e. programs that drew on vast databases of logical predicates which modelled the entire decision matrix of the problem domain.

    Turns out doing that is really quite hard (in several different ways), which seems to be why ES fell out of favour (and the 2nd wave of AI hype petered out).

    But expert systems have one enormous benefit over the ML approach: they're auditable.

    ML was an interesting experiment; but if we ever want to have AIs we can even think about trusting, we will need to revisit the ES approach, or some direct descendant of it.

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