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1. Whose responsibility is it to ensure that algorithms are not discriminatory? Explain. 2. Google, Facebook, and many other widely used software platforms have been accused of using algorithms that present biased search results or news feeds. Should such platforms be bias free (at least as much as possible), or is it acceptable for platforms to reflect the biases of the developers? Explain.

1. Whose responsibility is it to ensure that algorithms are not discriminatory? Explain. 2. Google, Facebook, and many other widely used software platforms have been accused of using algorithms that present biased search results or news feeds. Should such platforms be bias free (at least as much as possible), or is it acceptable for platforms to reflect the biases of the developers? Explain.

Understanding Business
Understanding Business
12th Edition
ISBN:9781259929434
Author:William Nickels
Publisher:William Nickels
Chapter1: Taking Risks And Making Profits Within The Dynamic Business Environment
Section: Chapter Questions
Problem 1CE
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Ethical Dilemma When Algorithms Discriminate Promising companies the ability to get to know their customers and maximize the benefit gained from each one, CRM systems could be called a marketer's dream. CRM software allows companies to look closely at customer behavior, drilling down to smaller and smaller market segments. Once so segmented, customers can be targeted with specific promotions. For the company, this process reaps the greatest returns from marketing efforts because only those customers are targeted who are likely to respond to the marketing campaign. From a customer's perspective, CRM systems seem like a great idea. You finally stop receiving advertisements for things that don't interest you. But what if a company uses its CRM software in a more discriminating way? Where do companies draw the line between using CRM data to offer certain clients customized deals and unethically discriminating against other customers? For example, lenders, which often segment their customers according to their creditworthiness, might use this credit risk data to target customers having a low credit rating with underhanded payday or subprime loans. Although these customers are riskier for the lender, the higher fees and interest charged for credit make these customers especially lucrative. CRM and all software contain countless algorithms for manipulating, aggregating, and summarizing data. Algorithms reflect a set of rules to be followed in calculations and other problem-solving operations. While there is a widespread belief that such algorithms must be objective and fair, CRM software, and the underlying algorithms, is not free of human bias. Instances of bias reported in the popular press include a report that Google's online advertising system displayed an advertisement for high-income jobs for men more often than for women. Similarly, ads for accessing arrest records were significantly more likely to show up on searches for distinctively black names. In a similar way, CRM systems based on biased or discriminatory algorithms can potentially do more harm than good, destroying rather than building customer relationships. Questions 1. Whose responsibility is it to ensure that algorithms are not discriminatory? Explain. 2. Google, Facebook, and many other widely used software platforms have been accused of using algorithms that present biased search results or news feeds. Should such platforms be bias free (at least as much as possible), or is it acceptable for platforms to reflect the biases of the developers? Explain.
Transcribed Image Text:Ethical Dilemma When Algorithms Discriminate Promising companies the ability to get to know their customers and maximize the benefit gained from each one, CRM systems could be called a marketer's dream. CRM software allows companies to look closely at customer behavior, drilling down to smaller and smaller market segments. Once so segmented, customers can be targeted with specific promotions. For the company, this process reaps the greatest returns from marketing efforts because only those customers are targeted who are likely to respond to the marketing campaign. From a customer's perspective, CRM systems seem like a great idea. You finally stop receiving advertisements for things that don't interest you. But what if a company uses its CRM software in a more discriminating way? Where do companies draw the line between using CRM data to offer certain clients customized deals and unethically discriminating against other customers? For example, lenders, which often segment their customers according to their creditworthiness, might use this credit risk data to target customers having a low credit rating with underhanded payday or subprime loans. Although these customers are riskier for the lender, the higher fees and interest charged for credit make these customers especially lucrative. CRM and all software contain countless algorithms for manipulating, aggregating, and summarizing data. Algorithms reflect a set of rules to be followed in calculations and other problem-solving operations. While there is a widespread belief that such algorithms must be objective and fair, CRM software, and the underlying algorithms, is not free of human bias. Instances of bias reported in the popular press include a report that Google's online advertising system displayed an advertisement for high-income jobs for men more often than for women. Similarly, ads for accessing arrest records were significantly more likely to show up on searches for distinctively black names. In a similar way, CRM systems based on biased or discriminatory algorithms can potentially do more harm than good, destroying rather than building customer relationships. Questions 1. Whose responsibility is it to ensure that algorithms are not discriminatory? Explain. 2. Google, Facebook, and many other widely used software platforms have been accused of using algorithms that present biased search results or news feeds. Should such platforms be bias free (at least as much as possible), or is it acceptable for platforms to reflect the biases of the developers? Explain.
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