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Artificial Intelligence and Machine Learning - Coggle Diagram
Artificial Intelligence and Machine Learning
Privacy and Security Challenges
AI collects personal data that can be hacked or misused.
Examples: leaks, bias, insider access.
Scneario 1 Health App Privacy
A health app sells patient info to advertisers.
Option A - Let it happen for profit.
Option B - Ask for permission and hide personal data.
My Choice - B (people deserve privacy).
Ethical View - Deontology (duty to protect users).
Scenario 2 - Hiring AI Bias
A hiring AI rejects people unfairly because of bias in data.
Option A - Keep using it.
Option B - Fix and retrain it.
My Choice - B (fair hiring matters).
Ethical View - Virtue ethics (doing what’s fair).
Cybersecurity Risks
Hackers can attack or trick AI systems.
Examples: data poisoning, model theft, bad training data.
Scenario 1 - Data Poisoning
Hackers change the training data in an AI system.
Option A - Ignore small issues.
Option B - Check data often and secure it.
My Choice - B (better safe than sorry).
Ethical View - Ethical egoism (protect your own system).
Scenario 2 - Full Automation Failure
Company fires security team and uses AI only.
Option A - Keep automation to save money.
Option B - Bring people back to work with AI.
My Choice - B (humans still needed for judgment).
Ethical View - Care ethics (responsibility to others).
Cybersecurity Advantages
AI helps find and stop threats faster than people.
AI Strengthens Cybersecurity, detects malware, reacts in real time, saves time.
Scenario 2 - Face Recognition
A government uses face recognition for safety.
Option A - Use it everywhere.
Option B - Limit it to protect privacy.
My Choice - B (freedom and privacy matter more).
Ethical View - Social contract theory (respect rights).
Scenario 1 - AI Stops Malware
AI blocks malware automatically.
Option A - Let AI act on its own.
Option B - Have humans double-check actions.
My Choice - B (AI should help, not fully replace us).
Ethical View - Utilitarianism (best result for everyone).
Ethical Challenges
AI can cause unfairness or replace people.
Examples: bias, lack of transparency, job loss.
Scenario 1 - Biased Loan AI
AI denies loans because of bias.
Option A - Keep it for speed.
Option B - Redesign it for fairness.
My Choice - B (everyone deserves equal chance).
Ethical View - Justice theory (fairness).
Scenario 2 - Job Replacement
AI replaces 80% of workers.
Option A - Keep automation for profit.
Option B - Keep some jobs and retrain workers.
My Choice - B (tech should help people, not harm them).
Ethical View - Virtue ethics (compassion).