Reading 8.4: Loukides, M., M., H. Mason and DJ. Patil. Ethics and Data Science.

Book  URL: https://www.oreilly.com/library/view/ethics-and-data/9781492043898/

Learning Objectives

Demonstrate proficiency in the following areas:

LO 8.4.1 Doing good data science

For example:

A. Identify aspects of putting ethical principles into practice.

LO 8.4.2 Oaths and checklists

For example:

A. Identify appropriate tools for implementing sound ethical practices.

LO 8.4.3 The five C’s

For example:

A. Recognize the main point behind each of the five “C’s”

• Consent

• Clarity

• Consistency

• Control and transparency, and

• Consequences and harm.

B. Recognize when an organization does and does not follow one of the “C’s”

framing guidelines.

C. Explain how to implement the five C’s.

LO 8.4.4 Taking responsibility for our creations (Data’s Day of Reckoning)

For example:

A. Identify major issues in ethics and security training.

B. Argue for a method of developing guiding principles.

C. Describe how to build ethics into a data-driven culture.

• Identify four methods for doing so.

• Describe the ideal role of teams and corporations.

D. Discuss the regulatory environment for data and new technologies in terms

of consent.

Keywords

Kanban (p. 3)                                           Minimal viable product (MVP) (p. 25)

Social impact statement (p. 22)               Digital privacy law (p. 26)

Andon cord (p. 23)