There are cases where data analytics helps to deter the chances for stereotyping, such as with content/product marketing based on our purchase history. There are also many times where organizations are accused of stereotyping based on marketing by customer segmentation. In most cases, these two algorithms are used together. In many video streaming sites, where initially there is not enough data on the viewer, an organization will rely on customer segment algorithms from which to recommend videos. But as a trend is observed by the videos that are viewed, recommendations are provided based on the viewer's history.  Ironically, it's this history which may in turn inform segmentation stereotypes when new users join with no viewing history only demographic data.

To best target an audience, ideally one would use both algorithms that utilize our data and customer segmented data. But in some cases, both our personal history and the segment the algorithm selects for us might be biased.

 

Review the following articles on subjects such as, "Can data stereotype?" and "Can stereotyping impact the data analysis?"

• Stop The Stereotypes: Data That Actually Drives Social Strategy For Millennials (Forbes)

Link: https://www.forbes.com/sites/forbescommunicationscouncil/2017/05/04/stop-the-stereotypes-data-that-actually-drives-social-strategy-for-millennials/?sh=54cb1e948edf

• Using Big Data to Sell to Individuals Instead of Stereotypes (SmartData Collective)

Link: https://www.smartdatacollective.com/using-big-data-sell-individuals-instead-stereotypes/

• Do Big Data and Analytics Fuel Discrimination? (SevenTablets)

Link: https://7t.co/blog/big-data-analytics-discrimination/

• Stereotype Inaccuracy: A Belief Impervious to Data (Psychology Today)

Link: https://www.psychologytoday.com/us/blog/rabble-rouser/201408/stereotype-inaccuracy-belief-impervious-data

 

Part 1

In part 1, evaluate these concepts and recommend ethical solutions to these problems in a report.

Part 2

Also, in two to three paragraph summary, provide one technique that you feel is the most essential for deterring stereotyping in data, including an assessment of "why. In your summary, provide detail for "why" this strategy is the most essential to you and how it supports integrity in the data analysis.