Chapter 8: Ethics Throughout the Data Science CycleContent check — Data Science, Chapter 8: Ethics Throughout the Data Science Cycle

Which option best explains the significance of informed consent during the data collection phase?

Who is responsible for obtaining informed consent from individuals or companies before collecting their data?

Which of the following is an important ethical principle to consider during the data collection phase?

What could be a serious consequence of a data security breach during the development process of a data science project?

How can organizations mitigate the risk of data breaches during the development process?

Which of the following are valid sources of data for a data science project? Select all that apply.

What type of data can be shared in a data science project?

Who should be given access to the data in a data science project?

Which department is responsible for handling regulatory compliance in an organization?

What is the main purpose of considering fairness and equity in machine learning models?

A new social media platform is looking for ways to improve its content-delivery algorithm so that it appeals to a broader audience. Currently, the platform is being used primarily by college-aged students. Which of these datasets would be the most appropriate data to collect and analyze to improve the algorithm and reduce potential bias in the content-delivery model?

What type of data would be considered an outlier in machine learning models?

Why is it important to monitor and regularly test algorithms for any potential bias?

The admissions team of a large university would like to conduct research on which factors contribute the most to student success, thereby improving their selection process for new students. The dataset that they plan to use has numerical features such as high school GPA and scores on standardized tests as well as categorical features such as name, address, email address, and whether they played sports or did other extracurricular activities. The analysis of the data will be done by a team that involves student workers. Which of these features should be anonymized before the student workers can get to work?

In what situation can data be anonymized even if it falls under intellectual property rights?

Data source attribution promotes trust and transparency by:

Applying universal design principles in data visualization and data source attribution helps ensure that people in which group are able to view and use the data?

What is the term used for properly crediting and acknowledging the sources of data in data science and research?

What is one ethical responsibility of data scientists and researchers when presenting data?

There was a growing concern at the Environmental and Agriculture Department about the rising levels of CO₂ in the atmosphere. It was clear that human activities, especially the burning of fossil fuels, were the primary cause of this increase. The department assigned a team of data scientists to research the potential consequences of climate patterns in the United States. They studied the trends of CO₂ emissions over the years and noticed a significant uptick in recent times. The team simulated various scenarios using climate models and predicted that if the current trend continues, there will be disastrous consequences for the climate. The four graphs displayed in Figure 8.11 depict the identical dataset from four different researchers. Out of the four graphs, which one accurately represents the CO₂ data without any type of distortion or misrepresentation? Figure 8.11 Source: Hannah Ritchie, Max Roser and Pablo Rosado (2020) - "CO₂ and Greenhouse Gas Emissions." Published online at OurWorldInData.org. Retrieved from: 'https://ourworldindata.org/co2-and-greenhouse-gas-emissions' [Online Resource]