AI and ML

Privacy and Security Challenges

Security Risks

Data Privacy

Collection, storage, and use of personal data.

Compliance with regulations (e.g., GDPR, CCPA).

Vulnerabilities in AI/ML models.

Adversarial attacks and data breaches.

Cybersecurity Advantages

Behavioral Analytics

Threat Detection

Real-time monitoring for suspicious activities.

Automated response to security incidents.

Identifying anomalies in user behavior.

Predicting and mitigating cyber threats.

Ethical Challenges

Cybersecurity Risks

False Positives/Negative

Adversarial Attacks

Incorrectly identifying threats.

Failing to detect actual threats.

enerating misleading outputs.

Manipulating AI/ML models.

Transparency and Accountability

Fairness and Bias

Explainability of AI/ML decisions.

Accountability for outcomes (e.g., biases).

Ensuring fairness in algorithmic decisions.

Mitigating biases in training data and models.

Ethical Scenarios

Data Privacy: A healthcare AI system collects patient data for diagnosis. The system's algorithms have the capability to analyze genetic information for personalized treatment recommendations.

Ethical Option: Ensure explicit consent and anonymize data to protect patient privacy.

Unethical Option: Share identifiable genetic data without informed consent, risking patient confidentiality.

Transparency and Accountability:An AI-driven hiring platform uses algorithms to screen job applicants. However, candidates express concerns about the fairness and transparency of the selection process.

Unethical Option: Use opaque algorithms that discriminate based on irrelevant factors such as race or gender.

Ethical Option: Provide clear explanations of how the AI system operates and ensure candidates understand the criteria used for evaluation.

I would advocate for the ethical option of transparency. Transparency supports ethical principles like fairness and justice, as outlined in theories of ethical consequentialism and social contract theory.

I would choose the ethical option of obtaining informed consent and anonymizing data. This aligns with principles of respect for autonomy and privacy, supported by ethical theories like Kantian ethics and principles of beneficence.