WEEK 10 — DIGITAL TRANSFORMATION
Cyber Security, Ethics and Social Issues
Navigating the complex landscape of digital transformation risks, ethical AI, and environmental impacts.
CHAPTER 01
The Evolving Threat Landscape
Analyzing cybersecurity risks and governance frameworks in digitally transformed businesses.
SECURITY RISKS
Expansion of the Attack Surface
The attack surface is rapidly expanding through IoT device manipulation, widespread cloud adoption, and remote work infrastructure. These fundamental shifts demand robust and adaptable governance frameworks.
ECONOMIC IMPACT
Organizations face sophisticated cyber threats that specifically target critical infrastructure. The emergence of new attack vectors requires constant vigilance and proactive defense mechanisms.
State-Sponsored Attacks
Highly sophisticated, well-funded cyber operations conducted by nation-states targeting critical infrastructure and intellectual property.
Ransomware
Malicious software designed to block access to a computer system or data until a substantial sum of money is paid.
Supply Chain Vulnerabilities
Exploiting weaknesses in third-party software or hardware providers to compromise the broader target organization's network.
CHAPTER 02
Case Study: CRA Data Leak
Analyzing the real-world impact of data breaches and the critical importance of privacy compliance.
REAL-WORLD IMPACT
The H&R Block Canada Breach
Dating back to 2020, hackers obtained confidential data used by H&R Block Canada, leading to unauthorized access. Imposters successfully changed direct deposit information and stole over $6 million in fraudulent refunds.
The Canadian Revenue Agency (CRA) confirmed that an internal error led to the exposure of over 30,000 Canadian taxpayers' personal information, including Social Insurance Numbers (SIN) and highly sensitive financial details.
THE PRIVACY ACT
Research a recent cyber security breach. Who caused it? What vulnerability enabled it? How could it have been prevented?
Class Discussion
CHAPTER 03
Ethics in Digital Transformation
Evaluating the ethical implications of emerging technologies and data-driven business models.
PRIVACY & AI
Data Minimization and Governance
Modern digital business models often rely on extensive data collection. Privacy by design methodologies advocate for data minimization: instead of simply protecting collected data, avoid collecting unnecessary data altogether.
THE PRIVACY PARADOX
Algorithm governance is essential for ethical AI. Models must demonstrate transparency and explainability, ensuring that automated decision-making processes are clear, unbiased, and subject to human oversight.
Social Bias
AI systems replicating or amplifying existing social prejudices and historical inequalities present in the training data.
Racial Bias
Disproportionate outcomes or discriminatory patterns affecting specific racial groups due to unrepresentative datasets.
Gender Bias
Algorithms making skewed predictions or recommendations that unfairly target, stereotype, or exclude based on gender.
Cognitive Bias
Human cognitive flaws inadvertently embedded into the design or evaluation of AI models, leading to systematically flawed reasoning.
CHAPTER 04
Social Issues & Sustainability
Addressing broader societal impacts, including misinformation, digital monopolies, and the carbon footprint of AI.
SOCIETAL IMPACT
Trust, Power, and the Environment
The era of Generative AI has brought unprecedented challenges regarding misinformation and synthetic media. Even professional reports sometimes hallucinate events, fundamentally complicating truth and digital information integrity.
Corporations face the difficult responsibility of content moderation, constantly balancing the urgent need to battle misinformation against the ethical risks of overreaching censorship.
DIGITAL MONOPOLIES
ENVIRONMENTAL SUSTAINABILITY
The Soaring Cost of AI Training
Training costs for frontier AI models are rising exponentially. GPT-3 (2020) cost approximately $2M-$4.6M, while Gemini Ultra (2023) ranged from $30M to $191M. If this trend continues, the largest training runs could exceed a billion dollars by 2027.
CONCLUSION
Summary
Digital transformation brings profound cybersecurity threats and significant ethical responsibilities. As AI and cloud technologies rapidly advance, organizations must actively address algorithmic bias, defend information integrity, and mitigate the escalating environmental impacts of computing.
KEY TAKEAWAYS
- Cybersecurity threats like ransomware and supply chain attacks have severe economic impacts.
- Ethical AI requires transparency, explainability, and the proactive elimination of algorithmic biases.
- The environmental footprint of AI models is growing exponentially, demanding sustainable computing practices.
- Digital monopolies and synthetic media pose significant new challenges to societal trust and information integrity.