A very interesting, and broad (compared to our more statistics-specific discussions in MBAG 8541A) topic is touched in this book: http://time.com/4477557/big-data-biases/. The basic point is: data analytics (from basic descriptive statistics, to inferential statistics, to econometrics and bid data analysis) is subject to all the normal human biases the analysts might possess. The problem, however, is that big data now leads the charge toward behaviour and choice automation.
The book review focuses on ethical dimensions of this problem. There is also a remedial cost dimension - with automated behaviour based on biased algorithms, corrective action cannot take place ex ante automated choice, but only either ex ante analysis (via restricting algorithms) or ex post the algorithm-enabled action takes place. Which, of course, magnifies the costs associated with controlling for biases.
One way or the other - the concept of biased algorithmic models certainly presents some food for thought!