System Bits: Oct. 30

Programming autonomous cars; AI controls quantum computers; thermal earmuffs.


Ethics, regional differences for programming autonomous vehicles
MIT researchers have revealed some distinct global preferences concerning the ethics of autonomous vehicles, as well as some regional variations in those preferences based on a recently completed survey.

Ethical questions involving autonomous vehicles are the focus of a new global survey conducted by MIT researchers.

Source: MIT

According to the team, the survey has global reach and a unique scale, with over 2 million online participants from over 200 countries weighing in on versions of a classic ethical conundrum, the “Trolley Problem,” that involves scenarios in which an accident involving a vehicle is imminent, and the vehicle must opt for one of two potentially fatal options. In the case of driverless cars, that might mean swerving toward a couple of people, rather than a large group of bystanders.

Edmond Awad, a postdoc at the MIT Media Lab and lead author of a new paper outlining the results of the project said, “The study is basically trying to understand the kinds of moral decisions that driverless cars might have to resort to. We don’t know yet how they should do that. Still, we found that there are three elements that people seem to approve of the most.” These are sparing the lives of humans over the lives of other animals; sparing the lives of many people rather than a few; and preserving the lives of the young, rather than older people.

The team found the main preferences were to some degree universally agreed upon, but the degree to which they agree with this or not varies among different groups or countries. For instance, the researchers found a less pronounced tendency to favor younger people, rather than the elderly, in what they defined as an “eastern” cluster of countries, including many in Asia.

The paper, “The Moral Machine Experiment,” is being published today in Nature. The authors hail from MIT, Harvard University, the University of British Columbia, and the Toulouse School of Economics.

The researchers suggest that acknowledgement of these types of preferences should be a basic part of informing public-sphere discussion of these issues. In all regions, since there is a moderate preference for sparing law-abiding bystanders rather than jaywalkers, knowing these preferences could, in theory, inform the way software is written to control autonomous vehicles. The question is whether these differences in preferences will matter in terms of people’s adoption of the new technology when vehicles employ a specific rule.

Neural networks enable error correction learning strategies for quantum-based computers
Quantum computers could solve complex tasks that are beyond the capabilities of conventional computers but quantum states are extremely sensitive to constant interference from their environment. Max Planck Institute for the Science of Light researchers plan to combat this using active protection based on quantum error correction, and a team has presented a quantum error correction system capable of learning thanks to artificial intelligence.

Learning quantum error correction: the image visualizes the activity of artificial neurons in the Erlangen researchers’ neural network while it is solving its task.
Source: Max Planck Institute for the Science of Light

As is common knowledge nowadays, in 2016, the computer program AlphaGo won four out of five games of Go against the world’s best human player, and given that a game of Go has more combinations of moves than there are estimated to be atoms in the universe, this required more than just sheer processing power. To do this, AlphaGo used artificial neural networks, which can recognize visual patterns and are even capable of learning. Unlike a human, the program was able to practice hundreds of thousands of games in a short time, eventually surpassing the best human player.

Now, the Erlangen-based researchers are using neural networks of this kind to develop error-correction learning for a quantum computer.

The researchers reminded that artificial neural networks are computer programs that mimic the behavior of interconnected nerve cells (neurons). In the case of the research in Erlangen, those numbered around 200,000 artificial neurons connected with one another.

They believe artificial neural networks could outstrip other error-correction strategies, with the first area of application are quantum computers, as shown by the recent paper. In the paper, the team demonstrates that artificial neural networks with an AlphaGo-inspired architecture are capable of learning – for themselves – how to perform a task that will be essential for the operation of future quantum computers: quantum error correction including the prospect that, with sufficient training, this approach will outstrip other error-correction strategies.

In addition to error correction in quantum computers, the researchers envisage other applications for artificial intelligence including physics systems that could benefit from the use of pattern recognition by artificial neural networks.

Protecting cell phone batteries from extreme temperatures
The batteries that power our phones and computers are picky about the weather. Stray out outside a narrow temperature range — typically 20 to 40 degrees Celsius (70 to 100 degrees Fahrenheit) — and they lose efficiency or fail, UC Berkeley engineers reminded. Now, a team from Berkeley has developed a new thermal regulator that keeps batteries at these “Goldilocks” temperatures even in extreme weather that works through a passive system that does not consume extra energy.

Shown is a schematic and photo of a thermal regulator designed by Berkeley engineers to passively keep lithium-ion batteries within an optimum temperature range. At higher temperatures, wires made of a shape memory alloy hold batteries down close to a heat sink so that excess heat is dissipated. At lower temperatures, the wires loosen so that the resulting air gap helps the batteries retain heat.
Source: UC Berkeley

The optimum temperature range for lithium-ion batteries may not be a serious issue in mild climates such as where UC Berkeley is located but in the middle of winter in New York or Lake Tahoe, it’s not unusual for smartphones to automatically switch off because it’s too cold. Chris Dames, a UC Berkeley professor of mechanical engineering said, “By inventing a new type of thermal regulator, we came up with a single design that can work for both Lake Tahoe in January and Death Valley in August.”

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