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The danger in mixing medicine and algorithms might also lie in the trust algorithms engender, creating a false picture of simplicity, efficiency and objectivity that papers over a system that's inherently convoluted, overpriced and unfair. [ABSTRACT FROM AUTHOR]

The importance given to understanding and preventing bias and unfairness is evident in the mainstream artificial intelligence conferences. [ABSTRACT FROM AUTHOR]

The importance given to understanding and preventing bias and unfairness is evident in the mainstream artificial intelligence conferences. [ABSTRACT FROM AUTHOR]

The article discusses microsimulation modeling. Microsimulation provides a creative solution to the challenges surrounding enterprise decision management. It is a computational technique used to predict the behavior of a system by predicting the behavior of microlevel units. Microsimulation models work by taking a representative sample of units and applying parameterized algorithms to simulate not only processes, but also behaviors and outcomes. Microsimulation is best used for analyzing systems where decision-making occurs at the transaction or unit level.

As more departments of business adopt machine learning, we're finding that ethical decision-making is at risk due to bias within the algorithm involved. [ABSTRACT FROM AUTHOR]

The American Medical Informatics Association wants the Food and Drug Administration to improve its conceptual approach to regulating medical devices that leverage self-updating artificial intelligence algorithms. [ABSTRACT FROM AUTHOR]

The American Medical Informatics Association wants the Food and Drug Administration to improve its conceptual approach to regulating medical devices that leverage self-updating artificial intelligence algorithms. [ABSTRACT FROM AUTHOR]

The article offers brief information on Sacks Equalization Model based on a mathematical algorithm from financial consultant Sy Sacks.

Researchers at Stanford—and their collaborators—have developed an algorithm to identify patients' susceptibility using EHR data. [ABSTRACT FROM AUTHOR]

A clinically validated automated artificial intelligence algorithm has been shown to tell the differences between normal and abnormal images. [ABSTRACT FROM AUTHOR]

The article discusses the vulnerability of robo advisors to choice manipulation and bait-and-switch schemes. Topics mentioned include the concern of scholars that they will work against the interest of the clients, the comment of professor Tom Baker of University of Pennyslvania Law School on the need for enough inquiry about the algorithm, and the architecture of the platform that can influence the decision of the client.

By adding a little bit of "noise" to the results of database searches, the technique confounds algorithms that would seek to extract private information from the results of multiple customized sequential searches. [ABSTRACT FROM AUTHOR]