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Ethics in Data Science

Total questions: 23

Worksheet time: 12mins

Name
Class
Date
1.

What is the definition of data ethics?

a)

The study of ethical issues related to data collection, storage, and analysis

b)

The use of data to make ethical decisions

c)

The application of ethical principles to data science projects

2.

Which ethical principle states that individuals should have control over their personal data?

a)

Data ownership

b)

Data privacy

c)

Data transparency

3.

What is the term for the practice of removing personally identifiable information from datasets to protect privacy?

a)

Data anonymization

b)

Data encryption

c)

Data deletion

4.

Which of the following is an example of algorithmic bias?

a)

A predictive policing algorithm that targets certain neighborhoods

b)

A recommendation system that suggests similar products based on user preferences

c)

A natural language processing model that translates text from one language to another

5.

What is the term for the practice of making data and algorithms available for public scrutiny?

a)

Open data

b)

Data transparency

c)

Algorithmic accountability

6.

Which ethical principle requires data scientists to be transparent about their methods and findings?

a)

Data transparency

b)

Data accuracy

c)

Data privacy

7.

What is the term for the misuse of data for personal gain or harm?

a)

Data manipulation

b)

Data fraud

c)

Data misuse

8.

What is the term for the process of obtaining informed consent from individuals before collecting their data?

a)

Data protection

b)

Data consent

c)

Data governance

9.

Which ethical principle requires data scientists to consider the potential societal impacts of their work?

a)

Social responsibility

b)

Data accuracy

c)

Data privacy

10.

What is the term for the practice of using data to make decisions that promote fairness and equality?

a)

Data fairness

b)

Data equality

c)

Data justice

11.

Which ethical principle emphasizes the importance of fairness and impartiality in data analysis?

a)

Data neutrality

b)

Data transparency

c)

Data accuracy

12.

What is the term for the process of combining and analyzing multiple datasets to gain new insights?

a)

Data integration

b)

Data aggregation

c)

Data fusion

13.

Which ethical principle requires data scientists to ensure the accuracy and reliability of their data?

a)

Data accuracy

b)

Data transparency

c)

Data privacy

14.

What is the term for the practice of using data to target individuals with personalized advertisements or content?

a)

Data profiling

b)

Data personalization

c)

Data targeting

15.

Which ethical principle requires data scientists to protect the privacy and confidentiality of individuals' data?

a)

Data privacy

b)

Data accuracy

c)

Data transparency

16.

What is the term for the practice of using historical data to train machine learning models, which can perpetuate biases present in the data?

a)

Algorithmic bias

b)

Data bias

c)

Model bias

17.

Which ethical principle requires data scientists to ensure the security and protection of data?

a)

Data security

b)

Data integrity

c)

Data transparency

18.

What is the term for the practice of using data to make decisions that benefit the majority of people?

a)

Data utilitarianism

b)

Data egalitarianism

c)

Data democracy

19.

Which ethical principle requires data scientists to be accountable for the decisions and actions taken based on data analysis?

a)

Algorithmic accountability

b)

Data transparency

c)

Data privacy

20.

What is the term for the practice of using data to infer sensitive information about individuals that was not explicitly provided?

a)

Data interference

b)

Data extraction

c)

Data revelation

21.

Which ethical principle requires data scientists to ensure the availability and accessibility of data for public use?

a)

Open data

b)

Data transparency

c)

Data privacy

22.

What is the term for the practice of using data to discriminate against certain individuals or groups?

a)

Data discrimniation

b)

Data bias

c)

Data profiling

23.

Which ethical principle requires data scientists to ensure the accuracy and reliability of their algorithms?

a)

Algorithmic accuracy

b)

Algorithmic fairness

c)

Algorithmic transparency