Course Description

Synopsis:

This course explores the ethical, security, and regulatory challenges posed by AI in finance and other industries. It highlights key risks—bias, privacy violations, transparency gaps, and security threats—while offering practical solutions and regulatory insights.

Key Issues & Examples:

• Ethical Risks:
  • Bias: Amazon’s AI hiring tool discriminated against women.
  • Privacy: Clearview AI scraped social media images without consent.
  • Transparency: Facebook’s opaque algorithms raised accountability concerns.
• Security Threats:
  • Data poisoning, adversarial attacks, and deepfake misuse.
• Regulatory Complexity:
  • Fragmented laws (EU’s AI Act, GDPR, CCPA) complicate global compliance.
• Solutions & Best Practices:
  • Governance: Implement AI ethics boards (e.g., Microsoft, IBM).
  • Bias Mitigation: Use diverse datasets and fairness audits.
  • Security: Adopt encryption, differential privacy, and robust access controls.
  • Compliance: Align with frameworks like GDPR (EU), NIST (US), and Singapore’s Model AI Governance.

Conclusion:

AI’s potential is immense, but its risks demand proactive governance, transparency, and cross-border regulatory alignment. By learning from failures (e.g., Equifax breach) and emulating leaders (e.g., Apple’s privacy-by-design), organizations can harness AI responsibly.

Intended For:

• Audit Professionals / PAIP
• Finance Professionals  / PAIB
• Public Sector Finance
• C-suite & Directors

Competency Mapping: 

• CPE Category 2 = 1.0 Hours