Mind Matters Natural and Artificial Intelligence News and Analysis

Roman Yampolskiy

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Evolving Technology

Can Computers Evolve to Program Themselves Without Programmers?

How much computing power would we need to evolve the programmer’s intelligence via Darwinian evolution

At Science earlier this year, we were told that “Researchers have created software that borrows concepts from Darwinian evolution, including ‘survival of the fittest,’ to build AI programs that improve generation after generation without human input.” Critics say it’s not that easy. Computer scientist Roman Yampolskiy (pictured) discusses the problem in an open access paper, starting with a joke: On April 1, 2016 Dr. Yampolskiy posted the following to his social media accounts: “Google just announced major layoffs of programmers. Future software development and updates will be done mostly via recursive self-improvement by evolving deep neural networks”. The joke got a number of “likes” but also, interestingly, a few requests from journalists for interviews on this “developing story”. To non-experts Read More ›

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Computer error.

AI Will Fail, Like Everything Else, Eventually

The more powerful the AI, the more serious the consequences of failure

A day does not go by without a news article reporting some amazing breakthrough in artificial intelligence. In fact, progress in AI has been so steady that some futurists, such as Ray Kurzweil, project current trends into the future and anticipate the headlines of tomorrow. Consider some developments from the world of technology: 2004 DARPA sponsors a driverless car grand challenge. Technology developed by the participants eventually allows Google to develop a driverless automobile and modify existing transportation laws. 2005 Honda’s ASIMO humanoid robot is able to walk as fast as a human, delivering trays to customers in a restaurant setting. The same technology is now used in military robots. 2007 Computers learned to play a perfect game of checkers, Read More ›

Schrift

Unexplainability and Incomprehensibility of AI

In the domain of AI safety, the more accurate the explanation is, the less comprehensible it is

With AI decision-making, a non-trivial explanation can’t be both accurate and understandable but it can be inaccurate and comprehensible. There is a huge difference between understanding something and almost understanding it.

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3D Rendering of abstract highway path through digital binary towers in city. Concept of big data, machine learning, artificial intelligence, hyper loop, virtual reality, high speed network.

How Do We Know What Superintelligent AI Will Do?

If superintelligent systems existed, logic demonstrates that they would be unpredictable

A lower intelligence can’t accurately predict all decisions of a higher intelligence, a concept known as Vinge’s Principle.

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Your Software Could Have More Rights Than You

Depending on politics and court judgments, legal loopholes could lead to AI personhood

We have already witnessed an example of such an indignity. and consequent outrage, from many feminist scholars when Sophia the robot was granted citizenship in Saudi Arabia, a country notorious for unequal treatment of women.

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