Ethics, Privacy, Security & Social Impact in MIS

Ethical Issues in Information Systems

Key Ethical Dilemmas

Ethical issues arise when information systems conflict with moral principles. Common dilemmas include:

• Privacy vs. Convenience: Collecting user data for personalized services (e.g., ads) but risking misuse.
• Intellectual Property: Unauthorized copying of software or digital content.
• Accountability: Who is responsible when an AI system makes a harmful decision?
• Accessibility: Ensuring digital tools are usable by people with disabilities.

How Ethical Frameworks Help

Organizations use ethical frameworks to guide decisions:

mindmap
  root((Ethical Frameworks))
    Utilitarianism["Maximize overall good (e.g., Google’s AI for social good)"]
    Rights["Respect individual rights (e.g., GDPR in EU)"]
    Justice["Fair distribution of benefits/burdens (e.g., Ncell’s data pricing)"]
    Common Good["Serve society (e.g., eSewa’s digital inclusion)"]

Worked Example: Nabil Bank’s Loan Approval System

• Issue: The bank’s AI system denied loans to rural applicants due to biased training data (urban-centric).
• Ethical Conflict: Justice (fair access) vs. Efficiency (automated processing).
• Solution: Retrained the AI with diverse data and added human oversight.

Privacy and Security Challenges

Privacy Laws and Compliance

Privacy laws protect personal data. Key regulations:

Cybersecurity Threats

Cyberattacks exploit vulnerabilities in information systems:

flowchart TD
  A["Threat"] --> B["Malware\n(e.g., ransomware on NTC servers)"]
  A --> C["Phishing\n(e.g., fake eSewa login pages)"]
  A --> D["Data Breach\n(e.g., Khalti user data leak)"]
  A --> E["Denial-of-Service\n(e.g., Pathao app crashes during Diwali)"]

Worked Example: Khalti Data Breach (2021)

• Attack: Hackers accessed 21,000 user records via a third-party vendor.
• Impact: Loss of trust, regulatory fines (PDPA), and reputational damage.
• Prevention: Multi-factor authentication (MFA) and vendor security audits.

Social Issues and Digital Divide

Digital Divide in Nepal

The gap between those with and without digital access creates inequalities:

pie
  title Digital Divide Factors
  "Infrastructure" : 35
  "Affordability" : 30
  "Digital Literacy" : 25
  "Language Barriers" : 10

Real-World Impact:

• E-Commerce: Daraz struggles to reach rural Nepal due to poor internet.
• Education: Students in Kathmandu use online resources, while remote areas rely on textbooks.
• Government Services: eSewa works for urban users but excludes illiterate seniors.

Case Study: NTC’s Broadband Expansion

• Goal: Reduce digital divide by expanding fiber in rural areas.
• Challenge: High costs and low demand in remote villages.
• Solution: Subsidized plans and digital literacy training.

Ethical AI and Bias

Bias in AI Systems

AI can reinforce societal biases if trained on flawed data:

mindmap
  root((AI Bias Sources))
    Historical Data["e.g., Hiring tools favoring male candidates"]
    Algorithmic Design["e.g., Facial recognition failing on darker skin tones"]
    User Feedback Loops["e.g., YouTube’s recommendation algorithm amplifying extremism"]

Worked Example: YouTube’s Radicalization Algorithm

• Issue: AI recommended extremist content to users based on engagement.
• Ethical Violation: Common Good (harmed society) vs. Profit (increased watch time).
• Fix: Human reviewers and content moderation tools.

Exam Tip

How to Score Full Marks

1. Case Analysis: Always link ethical/social issues to real companies (e.g., "How would Nabil Bank resolve this?").
2. Law Application: Compare GDPR vs. PDPA in 2–3 bullet points for data privacy questions.
3. Visuals: Draw a flowchart for ethical dilemmas or a pie chart for digital divide factors.
4. Pros/Cons: For cybersecurity, list 2 threats and 2 countermeasures (e.g., "Phishing → MFA").
5. Critical Thinking: Justify your stance (e.g., "Is it ethical for Daraz to sell counterfeit goods? Argue both sides.").

Final Challenge: "A Nepali bank uses AI to detect fraud but accidentally flags transactions from rural women as ‘suspicious.’ How would you address this using ethical frameworks and privacy laws?" (Hint: Use the Utilitarianism vs. Justice framework and PDPA’s data protection clauses.)