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Monday, March 22, 2021

On Recommendation Systems

 Anther well considered piece, on recommendation systems, link to original post includes more useful references.  Note the inclusion of elements of 'trust'.  Intro below. 

The Increasing Influence of Recommendation Systems in Our Everyday Lives by Irving Wladlensky-Berger in his blog ... 

A few years ago, I attended a seminar by University of Toronto professor Avi Goldfarb on the economic value of AI. Goldfarb explained that the best way to assess the impact of a new radical technology is to look at how the technology reduces the cost of a widely used function. Computers, for example, are powerful calculators whose cost of arithmetic and other digital operations have dramatically decreased over the past several decades. As a result, we’ve learned to define all kinds of tasks in terms of digital operations, e.g., financial transactions, inventory management, word processing, photography. Similarly, the Internet and World Wide Web have drastically reduced the cost of communications and of access to all kinds of information, - including numbers, text, pictures, music and videos.

Viewed through this lens, the data and AI revolution can be viewed as reducing the cost of predictions. Predictions mean anticipating what is likely to happen in the future. Over the past decade, increasingly powerful computers, advanced machine learning algorithms, and the explosive growth of big data have enabled us to extract insights from the data and turn them into valuable predictions. As was previously the case with digital operations, communications and access to information, - we’re now able to reframe all kinds of applications as prediction problems. A major such family of applications are recommendation engines or recommender systems, which Wikipedia defines as “a subclass of information filtering system that seeks to predict the ‘rating’ or ‘preference’ a user would give to an item.”  ... '

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