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Thursday, January 12, 2017

ACM Statement on Algorithmic Transparency and Accountability

The well known ACM professional society issued a statement about algorithmic transparency and accountability today.  I have been a member and participant for many years.   Algorithms have been part of computing forever, but only recently have they been closely examined regarding their implications, especially as they interact with the public.  And we interact with them every day.

 Algorithms are models, and inherently have bias.  They make and position decisions for and with us. This will further expand with the use of AI.   The ACM statement, the first few paragraphs below, the complete document is at the link, does an excellent job of laying out the problem, and their professional position.  Well stated:

Statement on Algorithmic Transparency and Accountability
Computer algorithms are widely employed throughout our economy and society to make decisions that have far-reaching impacts, including their applications for education, access to credit, healthcare, and employment.    The ubiquity of algorithms in our everyday lives is an important reason to focus on addressing challenges associated with the design and technical aspects of algorithms and preventing bias from the onset.

An algorithm is a self-contained step-by-step set of operations that computers and other 'smart' devices carry out to perform calculation, data processing, and automated reasoning tasks. 

Increasingly, algorithms implement institutional decision-making based on analytics, which involves the discovery, interpretation, and communication of meaningful patterns in data. Especially valuable in areas rich with recorded information, analytics relies on the simultaneous application of statistics, computer programming, and operations research to quantify performance.

There is also growing evidence that some algorithms and analytics can be opaque, making it impossible to determine when their outputs may be biased or erroneous. Computational models can be distorted as a result of biases contained   ..... " 

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