1.What are some of the biggest ethical concerns with how data analytics is used? 2.Can you provide real-world examples that illustrate these concerns?

Some of the biggest ethical concerns with how data analytics is used include:

• Privacy: With the increasing amount of data being collected, privacy is a major concern. Individuals may not be aware of how much of their personal information is being collected, stored, and analyzed.

• Consent: Often, data is collected without the explicit consent of the individuals it pertains to. Even when consent is given, it may not be fully informed.

• Transparency: There is often a lack of transparency about how data is being used. Companies may use complex algorithms to analyze data, making it difficult for individuals to understand what is being done with their information.

• Bias: Data analytics can perpetuate and amplify existing biases. If the data being analyzed is biased, the results will also be biased. This can lead to unfair outcomes in areas like hiring, lending, and law enforcement.

• Security: With large amounts of data being stored, there is a risk of data breaches. This can lead to sensitive information being accessed by unauthorized individuals.

Real-world examples that illustrate these concerns include:

• Facebook-Cambridge Analytica scandal: This is an example of privacy and consent concerns. Cambridge Analytica collected data from millions of Facebook users without their explicit consent and used it for political advertising.

• Amazon's hiring algorithm: This is an example of bias in data analytics. Amazon found that its algorithm was biased against women because it was trained on resumes submitted to the company over a 10-year period, most of which came from men.

• Equifax data breach: This is an example of security concerns. In 2017, Equifax, one of the three largest credit agencies in the U.S., suffered a data breach that exposed the personal information of 147 million people.