1 |
Information ethics |
Principles for judging responsible collection, use, sharing, and protection of information. |
2 |
Privacy |
A person’s ability to control how personal information is collected, used, and disclosed. |
3 |
Personal information |
Data that identifies, describes, or can reasonably be linked to an individual. |
4 |
Consent |
Permission for data use based on notice and meaningful choice. |
5 |
Notice |
A clear explanation of what data is collected, why, and how it will be used. |
6 |
Surveillance |
The systematic monitoring of people, behavior, communication, or activity. |
7 |
Profiling |
Using data patterns to infer traits, preferences, risks, or likely behavior. |
8 |
Accountability |
The obligation to explain decisions and accept responsibility for consequences. |
9 |
Liability |
Legal or financial responsibility for harm caused by a decision, product, or system. |
10 |
Due process |
Fair procedures for challenging decisions and correcting errors. |
11 |
Intellectual property |
Creative or informational work protected by law or policy. |
12 |
Copyright |
A legal right controlling reproduction and distribution of original creative work. |
13 |
Fair use |
A limited legal allowance for using copyrighted material under specific contextual factors. |
14 |
Digital divide |
Unequal access to digital technologies, connectivity, skills, or benefits. |
15 |
Accessibility |
Designing systems so people with different abilities can use them effectively. |
16 |
Algorithmic bias |
Systematic unfairness in model outputs caused by data, design, deployment, or social context. |
17 |
System quality |
The degree to which a system is reliable, usable, secure, accurate, and fit for purpose. |
18 |
Data quality |
The fitness of data for use, including accuracy, completeness, consistency, and timeliness. |
19 |
Professional responsibility |
The duty of technology workers and managers to act competently and ethically. |
20 |
Ethical analysis |
A structured evaluation of stakeholders, harms, benefits, rights, duties, and alternatives. |
4. Social Issues#
Information systems create power, convenience, and risk at the same time. This chapter introduces social, ethical, and legal issues that arise when organizations collect data, automate decisions, and depend on digital systems.
Video
Learning Objectives
By the end of this chapter, you will be able to:
Distinguish ethical, social, political, privacy, and security concerns in a system decision.
Analyze an information use through purpose, stakeholders, alternatives, and rights.
Assign responsibility and identify meaningful accountability and correction routes.
Evaluate access, equity, system quality, and human consequences alongside efficiency.
Concept Map
Glossary
#
Term
Explanation
1
Information ethics
Principles for judging responsible collection, use, sharing, and protection of information.
2
Privacy
A person’s ability to control how personal information is collected, used, and disclosed.
3
Personal information
Data that identifies, describes, or can reasonably be linked to an individual.
4
Consent
Permission for data use based on notice and meaningful choice.
5
Notice
A clear explanation of what data is collected, why, and how it will be used.
6
Surveillance
The systematic monitoring of people, behavior, communication, or activity.
7
Profiling
Using data patterns to infer traits, preferences, risks, or likely behavior.
8
Accountability
The obligation to explain decisions and accept responsibility for consequences.
9
Liability
Legal or financial responsibility for harm caused by a decision, product, or system.
10
Due process
Fair procedures for challenging decisions and correcting errors.
11
Intellectual property
Creative or informational work protected by law or policy.
12
Copyright
A legal right controlling reproduction and distribution of original creative work.
13
Fair use
A limited legal allowance for using copyrighted material under specific contextual factors.
14
Digital divide
Unequal access to digital technologies, connectivity, skills, or benefits.
15
Accessibility
Designing systems so people with different abilities can use them effectively.
16
Algorithmic bias
Systematic unfairness in model outputs caused by data, design, deployment, or social context.
17
System quality
The degree to which a system is reliable, usable, secure, accurate, and fit for purpose.
18
Data quality
The fitness of data for use, including accuracy, completeness, consistency, and timeliness.
19
Professional responsibility
The duty of technology workers and managers to act competently and ethically.
20
Ethical analysis
A structured evaluation of stakeholders, harms, benefits, rights, duties, and alternatives.
Lecture Slides
Chapter 4 Slides
These lecture drafts follow the authored sections and aligned assignments.