2025 Region 10 Transportation Conference

HUMAN CENTERED AI: ETHICS, BIAS MITIGATION, AND CYBERSECURITY

October 9, 2025, 1:00 – 5:00 PM PT

Human Centered AI solutions use a wide range of qualitative data to understand users’ needs, limitations, and choices while factoring system resources and constraints. These HCAI solutions have significant potential to enhance the safety and efficiency of our transportation system while ensuring human-centered elements. These solutions also provide system operators with the opportunity to make more informed decisions and effective strategies and solutions to transportation system challenges. This workshop explores the principles, ethical considerations, and practical applications of HCAI in transportation, with a focus on mitigating bias, ensuring cybersecurity, and fostering responsible AI deployment. By the end of this workshop, participants will be able to:

1. Understand the core principles and fundamentals of Human-Centered AI (HCAI).
2. Evaluate ethical challenges in AI-driven transportation systems.
3. Apply bias detection and mitigation techniques in AI model development.
4. Assess cybersecurity risks and implement risk management best practices for HCAI solutions.
5. Join a community of transportation professionals, AI experts, and policymakers working toward ethical, AI human-centric solutions.

Workshop format and outline:

The workshop has four 50-minute modules. Participants will receive the workshop handout materials for each module along with materials needed for several hands-on interactive activities (participants need to bring their own laptops for the hands-one activities).  The modules covered in the workshop are:

• Module I: Introduction to Human-Centered AI Ethical Frameworks and Theories
  • Overview of HCAI and its societal implications, applications, and design principles
  • Ethics in HCAI technology Applications
  • Key ethical theories (utilitarianism, deontology, virtue ethics)
  • Discuss issues in applying ethical theories to AI

• Module II: HCAI Social Impacts: addressing bias in data and algorithms
  • HCAI design principles
  • Fairness metrics and evaluation procedures
  • Techniques for bias detection in data and mitigation strategies
  • Case studies of AI applications 

• Module III: Cybersecurity Threats and Vulnerabilities in HCAI
  • HCAI Data breaches and privacy concerns
  • Cybersecurity risks from human-AI interaction
  • Adversarial attacks and manipulation of HCAI algorithms and their impact on decision-making
  • Case Study: Vulnerabilities in autonomous and connected vehicles

• Module IV: HCAI Cybersecurity Risk Management Best Practices
  • Introduction of commonly used risk management frameworks (e.g., NIST Cybersecurity Framework, ISO/IEC 27001)
  • User-centered risk assessments for HCAI applications
  • Best Practices in HCAI Cybersecurity risk management

Who Should Attend:

No coding/technical skills are needed for the workshop; case studies and discussions will be accessible.  Participants should have basic awareness of AI/machine learning concepts, exposure to AI policy challenges, and Interest in ethics/responsible technology in transportation application. We encourage members of the following groups to consider participating in the workshop.

• Transportation Professionals and Transportation System Operators
• AI & Data Science Researchers and Practitioners
• Transportation Cybersecurity and Risk Management Specialists
• Transportation Consultants working in AI solutions
• Transportation Policy makers and Civil Rights Advocates

Workshop Instructors: