AI in Construction: Predictive maintenance and data privacy

Sinan Pismisoglu | Bradley Arant Boult Cummings LLP

Sinan Pismisoglu, a senior attorney at Bradley Arant Boult Cummings LLP, advises clients on product development, privacy and security compliance, AI ethics, SaaS contracting, Big Data, data licensing and ownership, supply chain and vendor management, and incident preparedness and response. He solves complex cybersecurity, information security, compliance, and operational issues beginning with early planning and prevention through detection, remediation, and crisis management. Sinan collaborates with engineering teams to create compliance-integrated risk management frameworks, governance, and ethics programs for emerging technologies such as AI/ML, cybersecurity, IoT, and cloud models.

Sinan also has substantial experience designing sophisticated table-top exercises based on real-life APT attack scenarios, and advises clients on breach management, setting up malicious and unintentional insider threat programs, insider threat technical monitoring, and jurisdictional restrictions on monitoring. He is particularly experienced in IaaS, SaaS and SIaaS applications, SLA negotiations, global data sovereignty, and data localization, country-based regulatory risks, and the implementation of bring-your-own-key practices against unnoticed government intervention.

Sinan’s area of interest is the cybersecurity issues that arise due to the use of fourth-generation SCADA systems in critical infrastructure. His background also includes commercial and investment disputes in oil and gas EPC contracting. Earlier in his career, he represented foreign governments in investment disputes and advised on EPC contracting strategies.

I. Setting the Stage | 12:00pm – 12:05pm

II. Current Uses of PM in the Construction Sector | 12:05pm – 12:25pm

• PM and Its Importance
  • Definition and applications of PM
  • Role of AI and IoT in PM
• Wearable Technology and Data Analytics
  • Ethical and legal considerations of data collection
  • Case studies of AI-driven PM in construction

III. The Future of PM in Construction | 12:25pm – 12:40pm

• Technological Advancements
  • Predictions on AI and 5G/6G impact
  • Integration with digital twins and augmented reality
• Innovation vs. Tradition
  • Comparing new methods with conventional maintenance practices
  • The transformation of maintenance paradigms

IV. Cybersecurity Threats to PM | 12:40pm – 1:00pm

• Types of Attacks
  • Detailed analysis of various cyberattack vectors
  • Real-world examples and prevention strategies
• IoT Vulnerabilities
  • The importance of IoT device security
  • Best practices for prevention and mitigation
• Attackers and Their Motivations
  • Profiling common attackers
  • Strategies to anticipate and counter various threat actors

Break | 1:00pm – 1:10pm

V. Legal and Regulatory Compliance Regarding PM | 1:10pm – 1:25pm

• Data Privacy
  • GDPR, CPRA, and other regulations
  • Compliance strategies and penalties for non compliance
• Liability
  • Liability in machine failure
  • Legal distinctions between AI systems as products or services
• Industry-Specific Regulations
  • An overview of construction industry regulations affecting PM
  • Compliance methods and best practices

VI. Conclusion and Discussion | 1:25pm – 1:40pm

• The Future Landscape
  • An overview of the potentials and challenges
  • Ethical considerations and the role of legal professionals
• Ethical Considerations
  • Addressing ethical aspects of predictive maintenance, AI, and cybersecurity in construction