Eric Holloway: This is an expected outcome based on the fact that computers cannot generate mutual information, where two variables are dependent on each other.
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The unchallenged manipulation of search engine results during elections is a new phenomenon made possible by the domination of the internet by a few big players.
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Critics of the emotional robotics industry say that the view of emotions (assumed in the industry to be only six) is oversimplified and that the robots are likely to promote stereotypes.
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Machine learning is a powerful and important tool that is likely to be of great value (and perhaps great risk) to man. Machines can be designed to change with time but it is man, and only man, who learns.
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Can we make approximations that are so close to ourselves that the fact that they are approximations no longer matters?
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Artificial intelligence often fails at crucial points. It must then be supplemented by human intelligence. Many software systems that look to their users like pure advanced artificial intelligence hide a lot of human effort behind a technological mask.
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A greater focus should be on restoring the foundations of our nation over building superweapons. And the key foundation is all human beings’ right to life.
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Because Marx held that the value of goods resided in the labor required to produce them, if goods were produced by automatons, without human labor, the economy would fall apart and capitalism would fail.
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If we have simply taken the big software, hardware, and social media companies who dominate our lives for granted, the reactions from the business world to Life after Google: The Fall of Big Data and the Rise of the Blockchain Economy should give us a lot to think about.
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Jay Richards, author of The Human Advantage: The Future of American Work in an Age of Smart Machines,sees it as more of a retooling than a meltdown. But retooling does mean change, work, cost, and risk.
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AI (machine learning) was probably faster and cheaper but the whole point of the system was supposed to be justice which, whatever the explanation, proved too difficult to calculate…
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In 2017, a group of 26 AI researchers got together at Oxford and created a report which offers a number of examples of malicious technologies of the near future.
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Companies sometimes pretend to be using AI or machine learning when they are actually using human employees for various reasons. One reason is that they have promised potential investors more high tech than they can deliver. Sometimes, as we learned recently at The Guardian, it gets a bit sticky…
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Karl D. Stephan: Zimbabwe, an African country well-known for its human-rights abuses, has received advanced Chinese AI technology from a startup company in exchange for letting the firm have access to the country’s facial-recognition database. So China is helping the government of Zimbabwe to keep tabs on its citizens as well.
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Algorithmic strategies can only be as good as the information that goes into them. Ignoring how the information is created causes us to misunderstand the dynamics of value creation. Algorithms can leverage information, they can’t create it.
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Human life is full of these challenges. Some knowledge simply cannot be conveyed—or understood or accepted—in a propositional form. For example, a nurse counselor may see clearly that her elderly post-operative patient would thrive better in a retirement home. But she cannot just tell him so.
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If specifically human intelligence is related to consciousness, the robotics engineers might best leave consciousness out of their goals for their products and focus on more tangible ones.
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The biggest problem today isn’t the sheer mass of data so much as the difficulty of determining what it is worth. The answer lies, unfortunately, in the undone studies and the unreported events. Machine learning will be a much greater help when those problems are addressed.
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Hutson describes one test last year where a computer scientist at UC Berkeley subtly altered a stop sign with stickers. It fooled an autonomous vehicle’s image recognition system into “thinking” it was a 45 mph speed limit sign. Humans could immediately recognize the stop sign, but the car did not. Autonomous car makers wonder, could hackers turn them into terror weapons?
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Why do we constantly hear that driverless, autonomous vehicles will soon be sharing the road with us? Wolmar blames “gullible journalists who fail to look beyond the extravagant claims of the press releases pouring out of tech companies and auto manufacturers, hailing the imminence of major developments that never seem to materialise.”
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