Panel Discussion:
Responsible AI Deployment in Critical Infrastructure: Bal

Panelists: Yang-Sun Lee, Sanghyun Seo, Dongwann Kang, Hangbae Chang

Chair: Mucheol Kim

Artificial intelligence has progressed from laboratory curiosity to foundational technology embedded throughout critical infrastructure supporting modern society. Energy grids employ AI for demand forecasting and grid stabilization. Transportation systems leverage AI for traffic optimization and autonomous vehicle control. Healthcare facilities depend on AI for diagnostic support and treatment planning. Financial systems utilize AI for fraud detection and risk management. Communication networks deploy AI for resource allocation and threat detection. The benefits are substantial: improved efficiency, enhanced decision-making, cost reduction, and capability expansion.

However, AI deployment in critical infrastructure raises profound challenges spanning technical reliability, security vulnerabilities, ethical implications, and societal trust. AI system failures in safety-critical applications can cause cascading consequences—an incorrect medical diagnosis, a traffic system malfunction, a grid control error. Adversarial attacks threaten AI integrity, potentially enabling malicious actors to manipulate critical systems through carefully crafted inputs. Privacy concerns arise from extensive data collection required for AI training and operation. Bias in training data and algorithms can perpetuate or amplify societal inequities. Lack of explainability complicates accountability when AI systems make consequential decisions affecting human lives.

This panel discussion convenes experts spanning intelligent systems, cybersecurity, data analytics, and infrastructure management to examine responsible AI deployment in critical infrastructure. Panelists will address several key questions:

Technical Reliability and Safety: How do we ensure AI systems operating in critical infrastructure meet rigorous safety and reliability standards? What validation and verification methodologies appropriate for safety-critical AI? How should organizations balance AI innovation with conservative engineering principles that have traditionally governed critical infrastructure?

Security and Adversarial Robustness: What security threats do AI systems face when deployed in critical infrastructure? How can we design AI systems resistant to adversarial attacks and data poisoning? What role does AI play in both attacking and defending critical infrastructure?

Privacy and Data Protection: How can critical infrastructure leverage AI while respecting privacy rights and data protection regulations? What privacy-preserving AI techniques are mature enough for production deployment? How do we navigate tensions between data minimization principles and data-hungry AI models?

Explainability and Accountability: Should critical infrastructure AI systems be required to provide human-understandable explanations for their decisions? How do explainability requirements interact with model performance? Who bears responsibility when AI systems fail—developers, operators, regulators?

Ethical Considerations and Societal Impact: How do we ensure equitable access to AI-enabled critical infrastructure services? What mechanisms prevent AI systems from perpetuating bias? How should public participation inform AI deployment decisions affecting communities?

Governance and Regulation: What regulatory frameworks should govern AI in critical infrastructure? How can regulations promote innovation while ensuring safety and accountability? What roles should industry standards, certification, and third-party auditing play?

International Cooperation: How can nations collaborate on AI standards for critical infrastructure while respecting sovereign interests? What international mechanisms could facilitate responsible AI development and deployment?

The panel will explore these questions through case studies, recent research findings, and practical deployment experiences. Audience participation will be encouraged through Q&A, enabling dialogue between panelists and attendees representing diverse perspectives from academia, industry, and government.