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Businesses have a moral duty to explain how algorithms make decisions that affect people

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Increasingly, businesses rely on algorithms that use data provided by users to make decisions that affect people. For example, Amazon, Google, and Facebook use algorithms to tailor what users see, and Uber and Lyft use them to match passengers with drivers and set prices. Do users, customers, employees, and others have a right to know how companies that use algorithms make their decisions? In a new analysis, researchers explore the moral and ethical foundations to such a right. They conclude that the right to such an explanation is a moral right, then address how companies might do so.
The analysis, by researchers at Carnegie Mellon University, appears in ....

Bryanr Routledge , Carnegie Mellon University , Council Of The European Union , Society For Business Ethics , European Union , European Parliament , Business Ethics Quarterly , Tae Wan Kim , Associate Professor , Business Ethics , Tepper School , General Data Protection Regulation , Carnegie Mellon , Business Economics , Advertising Public Relations , Policy Ethics , Guidelines Treaties Agreements , Intellectual Property , Licenses Patents , Information Management Tracking Systems , Technology Engineering Computer Science , Computer Science , கார்னகி மெலந் பல்கலைக்கழகம் , சபை ஆஃப் தி ஐரோப்பிய தொழிற்சங்கம் , ஐரோப்பிய தொழிற்சங்கம் , ஐரோப்பிய பாராளுமன்றம் ,

Building a foundation for high-power tech

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IMAGE: Brandon Grainger (left) and Paul Ohodnicki received $820,000 from the Office of Naval Research to create new materials and manufacturing processes for ultra-wide bandgap semiconductors.
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Credit: University of Pittsburgh
As electrification advancement accelerates and more renewables are integrated into the electric grid, improved power electronics systems are needed to convert AC or DC power into a usable form. New semiconductor device materials and advanced magnetic materials can enable an unprecedented combination of voltage levels and power handling capabilities.
However, the latest class of new switching devices, which use so-called ultra-wide bandgap (UWBG) semiconductor materials, will also require improved soft magnetic materials and manufacturing approaches not currently available. ....

Paul Ohodnicki , Ahmed Talaat , Brandon Grainger , University Of Pittsburgh Swanson School Engineering , University Of Pittsburgh , Us Office Of Naval Research , Energy Development , Pittsburgh Swanson School , Naval Research , Engineering Science , Advanced Magnetics , Eaton Faculty Fellow , Chemistry Physics Materials Sciences , Energy Fuel Non Petroleum , Superconductors Semiconductors , Technology Engineering Computer Science , Electrical Engineering Electronics , பிராண்டன் க்ரேயிஂகர் , பல்கலைக்கழகம் ஆஃப் பிட்ஸ்பர்க் ஸ்வான்சன் பள்ளி பொறியியல் , பல்கலைக்கழகம் ஆஃப் பிட்ஸ்பர்க் , எங்களுக்கு அலுவலகம் ஆஃப் கடற்படை ஆராய்ச்சி , ஆற்றல் வளர்ச்சி , பிட்ஸ்பர்க் ஸ்வான்சன் பள்ளி , கடற்படை ஆராய்ச்சி , பொறியியல் அறிவியல் , வேதியியல் இயற்பியல் பொருட்கள் அறிவியல் ,

Compound may prevent risk of a form of arrhythmia from common medications

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IMAGE: Xiaoqin Zou, professor of physics, biochemistry, and a member of the Dalton Cardiovascular Research Center and Institute for Data Science and Informatics at the University of Missouri
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Credit: University of Missouri
Dozens of commonly used drugs, including antibiotics, antinausea and anticancer medications, have a potential side effect of lengthening the electrical event that triggers contraction, creating an irregular heartbeat, or cardiac arrhythmia called acquired Long QT syndrome. While safe in their current dosages, some of these drugs may have a more therapeutic benefit at higher doses, but are limited by the risk of arrhythmia.
Through both computational and experimental validation, a multi-institutional team of researchers has identified a compound that prevents the lengthening of the heart s electrical event, or action potential, resulting in a major step toward safer use and expanded therapeutic efficacy of these med ....

Jianmin Cui , Mira Cohen , Xiaoqin Zou , Institute For Data Science , Skandalaris Center , Institute Of Clinical , Entrepreneurial Acceleration Program , Office Of Technology Management , Washington University Office Of Technology Management , Translational Sciences , University Of Missouri , Research Innovation In Biotechnology , Proceedings Of The National Academy Sciences , Dalton Cardiovascular Research Center , Washington University In St , Institute For Molecular Cardiology , National Academy , Mckelvey School , Washington University , Distinguished Professor , Molecular Cardiology , Renaissance School , Stony Brook University , Data Science , Washington University Office , Technology Management ,

Quantum machine learning hits a limit

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LOS ALAMOS, N.M., May 12, 2021 A new theorem from the field of quantum machine learning has poked a major hole in the accepted understanding about information scrambling.
Our theorem implies that we are not going to be able to use quantum machine learning to learn typical random or chaotic processes, such as black holes. In this sense, it places a fundamental limit on the learnability of unknown processes, said Zoe Holmes, a post-doc at Los Alamos National Laboratory and coauthor of the paper describing the work published today in
Physical Review Letters.
Thankfully, because most physically interesting processes are sufficiently simple or structured so that they do not resemble a random process, the results don t condemn quantum machine learning, but rather highlight the importance of understanding its limits, Holmes said. ....

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Tests of bitumen pave way to rational approaches in road building

Credit: Kazan Federal University
First co-author, Junior Research Associate of the Rheological and Thermochemical Research Lab Richard Djimasbe, comments, To obtain bitumen as a half-solid product from heavy oil, you have to extract light fractions, and the rest is non-oxidized bitumen. Because of the relatively low ratio of light fractions in heavy oil, it s a simple and cheap way of bitumen production. The method allows for rational use of both heavy oil and light oil.
Lab Head Mikhail Varfolomeev adds, One of the priorities of our World-Level Research Center in Liquid Hydrocarbons is the use of heavy oils, which constitute the majority of reserves both in Russia and in the world. One of the most important parts of this is extraction and refining of heavy petroleum reserves. The paper makes steps in that direction. ....

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