Ethics in Data Science Class 11 Questions and Answers

Objective Type Questions

1. A person runs a small business and keeps all his/her business records on an unprotected personal computer. These records include essential information about his/her customers. Since it is a small business, that person believes that he/she is unlikely to be a target for hackers. According to him/her, several years have passed, and information on his/her unprotected computer has never been compromised. Are the actions of that person ethical?

a) Yes

b) No

Answer: b) No

 

2. One comes up with an idea to improve the way patient data is collected into electronic medical records, thereby reducing errors and better integrating data entry with patient care workflow. When an experiment is run to evaluate the idea, what kind of data is expected to be used?

a) Prospective data

b) Retrospective data

Answer: a) Prospective data

 

3. A supermarket has prominently displayed boards at various places in the store “We videotape you for your security”. Later, you find out that the supermarket analyzes videos to decide store layout and product placement. You feel that the signage is misleading since the store uses the videos not just for security but also to boost profits. Are the supermarket’s actions ethical?

a) Yes

b) No

Answer: a) Yes

 

4.  Suppose a celebrity goes to a supermarket for shopping. The next day, images of the celebrity taken from the supermarket’s video camera appear on a leading tabloid. Is the supermarket right in selling the images to the tabloid?

a) Yes

b) No

Answer: b) No

 

5. Once I have voluntarily shared some information about myself on the web, it means that this information is no longer private and can be shared freely.

a) True

b) False

Answer: b) False

Ethics in Data Science Class 11 Questions and Answers

6. Undesired analysis of previously collected personal data violates privacy.

a) True

b) False

Answer: a) True

 

7. Undesired dissemination of previously collected data violates privacy.

a) True

b) False

Answer: a) True

 

Ethics in Data Science Class 11 Questions and Answers

 Standard Questions

 

1. Explain in detail how data has evolved over time.

Data Development Over Time: Data has progressed considerably throughout history, from ancient stone tablets to modern digital systems. At first, information was primarily stored manually and was often inaccessible or difficult to use; with computers and the internet came massive advancement in terms of storage and processing capabilities – databases and spreadsheets enabled structured data organization while the global nature of internet enabled global exchange of information.

Ethics in Data Science Class 11 Questions and Answers

2. Explain with relevant examples why data scientists need to understand data and follow data ethics?

Data Ethics and the Role of Data Scientists:

Data scientists must have an in-depth knowledge and respect for data ethics for several reasons. First, they work with large amounts of sensitive and personal data which must be handled responsibly to avoid privacy breaches that compromise individuals. Second, data scientists often create models which impact key decisions in various domains like healthcare, finance and criminal justice – biased models may perpetuate discrimination and social injustices.

 

3. What is data governance framework?

Data Governance Framework: A data governance framework is a structured approach that defines how an organization manages and protects its data assets. This approach includes setting policies, procedures, roles and responsibilities related to managing information within an organization’s information technology systems in an accurate, consistent, secure manner that conforms with regulations.

Ethics in Data Science Class 11 Questions and Answers

4. What are some of the benefits of implementing data governance framework?

 Benefits of Implementing Data Governance Framework:

Establishing a data governance framework offers many advantages for organizations:

(i) Improved Data Quality: By setting standards and processes defined in this framework it improves data accuracy and reliability resulting in better decision-making.

(ii) Regulatory Compliance: Compliance with applicable laws and regulations ensures data practices comply with laws and regulations, decreasing fines or legal issues that might arise as a result.

(iii) Strengthened Data Security: The framework provides controls and protection measures that safeguard sensitive information against unintended access or breaches.

(iv) Increased Efficiency: With well-defined roles and responsibilities, data governance streamlines data-related tasks to reduce redundancies while optimizing resources.

(v) Trust and Credibility: Reliable data and ethical practices help build trust among customers, stakeholders and partners of an organization and improve its credibility.

(vi) Improved Decision-Making: Accessing accurate and timely data allows leaders to make more informed and strategic decisions.

Ethics in Data Science Class 11 Questions and Answers

Higher Order Thinking Skills (HOTS)

Please answer the questions below in no less than 200 words.

1. What, according to you, should be the ethical principles for conducting research that involves dealing with other people’s data?

Ethical Principles for Conducting Research with Other People’s Data:

When engaging in research that involves dealing with data belonging to another, several ethical principles should guide its conduct to protect individuals’ rights, privacy, and well-being. Some key ethical guidelines include the following.

(i) Data Anonymity and Privacy: Researchers should take great care in protecting individual identities while anonymizing data to avoid identification of specific participants. Adequate security measures must also be implemented to protect against unauthorized access and breaches in security.

(ii) Beneficence: Researchers should prioritize participant welfare and ensure that potential benefits outweigh risks when it comes to research projects, which should strive to contribute positively while minimising harm.

(iii) Nonmaleficence: Researchers must take steps to avoid inflicting physical and emotional harm on participants through research; this includes conducting studies that reduce distress while protecting participant safety.

(iv) Transparency and Honesty: Researchers should always be open about their methods, data collection procedures and any potential conflicts of interest that might exist in their research. Honest reporting and disclosure of findings is crucial in maintaining research integrity.

(v) Respect for Autonomy: Researchers should uphold participants’ autonomy and rights, including their right to withdraw at any stage from a study or decline participation altogether.

(vi) Social Responsibilty: Researchers should carefully consider the wider social ramifications of their research, with an aim of meeting society’s challenges responsibly.

Ethics in Data Science Class 11 Questions and Answers

2. Should there be differences in expectations about what is ethical online versus offline regarding handling of data?

Ethical Considerations in Online and Offline Data Handling:

While fundamental ethical principles remain unchanged, there may be distinct expectations regarding data handling online versus offline:

(i) Privacy Concerns: Online data collection often involves tracking user behavior and collecting vast quantities of personal information about them, which may raise privacy concerns among individuals, necessitating enhanced data protection measures as well as clear consent mechanisms.

(ii) Data Security: Given the risk of hackers and unauthorised access, strong data protection in an online environment is of critical importance.

(iii) Anonymity Challenges: Due to the interconnectivity of digital footprints, anonymizing online data can be more challenging than expected. Researchers must take great care in protecting user identities.

(iv) Scope and Scale: Online research can reach an expansive and wide-reaching audience, potentially impacting multiple individuals at once. Researchers should carefully consider their studies’ scale as well as any unforeseen outcomes or implications that may result from them.

(v) Global Reach: Internet research can reach beyond geographical borders to attract a more diverse participant pool. Researchers must be mindful of cultural diversity as well as legal considerations that might differ between jurisdictions.

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