05 Feb Of the four principles of data ethics listed in Box 10.4 in Chapter ?10 (fairness, accountability, transparency, and explainability), which ?three of them seem most fundamental to
Respond to the following:
- Of the four principles of data ethics listed in Box 10.4 in Chapter 10 (fairness, accountability, transparency, and explainability), which three of them seem most fundamental to achieving ethical data use for individuals?
- What’s the difference between lawfully obtaining personal data and having accountability for obtaining it?
- Provide specific examples of behaviors that you could follow that apply each of the four principles as they relate to data that you would need to collect for the development of the project scenario app.
Be sure to respond to at least one of your classmates’ posts.
Hari Rao Kurupathi
Hello everyone,
Of the four principles of data ethics listed in Box 10.4 in Chapter 10 (fairness, accountability, transparency, and explainability), three seem most fundamental to achieving ethical data use for individuals.
Data ethics help ensure that the data is used appropriately and responsibly by the organizations collecting it. While all four principles of data ethics are essential, the three that resonate with me the most are
- Transparency – Organizations need to be transparent about why they are using the data and make it easily accessible and understandable to everyone on demand
- Fairness – The purpose of collecting the data must not have any discriminatory intent on specific individuals or groups. It must be collected in a way that stays consistent with the public interest and adheres to democratic values.
- Accountability – The people who provide the data to the various organizations must have the ability to maintain oversight and control over the decisions made by the companies. Accountability helps with delivering governance to the data being collected. (1)
What's the difference between lawfully obtaining personal data and having accountability for obtaining it?
- Lawfully obtaining personal data: When organizations try to process personal data, they need to do it lawfully. For example – the user has provided consent to process the data, all the legal obligations have been met, the vital interests of a person are protected, etc. Users also need to know how their data is handled and for what purpose. The data collected should not be mishandled or misused. The organization needs to be open, honest, and clear about who they are, how they plan to use the personal information, and why they collect the data.
- Accountability for obtaining the data: Organizations must have records and compliance to prove they are keeping the data safe and secure. Documentation can help create an audit trail and provide proof when authorities request it. Furthermore, organizations also need to maintain the integrity and privacy of the data collected and protect it from internal and external threats. The data must also be protected from accidental loss or damage. (2)
Please provide specific examples of behaviors that you could follow that apply each of the four principles as they relate to data that you would need to collect for the development of the project scenario app
- Transparency – Let's take the example of the DHS project. While collecting data from the end users, the border patrol, immigration officers, and other law enforcement, we need to ensure they understand our cookie policy to provide a personalized experience. The end users must also review the cookie policies at any time and accept or decline them.
- Fairness – An organization must avoid unnecessary biases that negatively impact business decisions. Organizations must be transparent, inclusive, and open while gathering user data.
- Accountability: Organizations need to hold themselves accountable while collecting data from users. They need to not only clarify how the data will be used in their analysis but also be responsible for compensating their users if there are data breaches and sensitive data is exposed to malicious users
- Explainability – Organizations need to be able to explain their decision-making process to their users in an easily understandable way. For example, smartphone manufacturers can notify customers how their usage data can help with adding new features to the phone
Sources:
- Government digital services – Data ethics framework – Retrieved from – https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/923108/Data_Ethics_Framework_2020.pdf
- Onetrust.com – Understanding the seven principles of GDPR – May 17, 2021 – Retrieved from – https://www.onetrust.com/blog/gdpr-principles/
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