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On May 15, 2024, the first AI4CCAM Stakeholders Forum Workshop was held as a side event at the IT-TRANS Conference in Karlsruhe, Germany. This workshop gathered experts from various organizations to delve into the ethical, perceptual, and cybersecurity dimensions of Trustworthy AI in Connected Cooperative and Automated Mobility (CCAM). The discussions focused on identifying key levers and barriers to CCAM adoption and provided valuable insights to guide the future of AI in automated vehicles. The event facilitated meaningful discussions and provided useful insights to guide the future of AI in automated vehicles. The outcomes of these discussions will contribute to the development of AI4CCAM guidelines for AI that emphasize diversity, inclusion, and cybersecurity.

First, AI4CCAM presented the European Trustworthy AI Framework, which is central to the efforts on Trustworthy AI for CCAM. This framework aims to ensure an adequate ethical and regulatory environment. The four principles for delivering Trustworthy AI are:
• Human autonomy: ensuring users can make informed and autonomous decisions.
• Prevention of harm: protecting against vulnerabilities and ensuring safe AI systems.
• Fairness: avoiding bias and discrimination.
• Explicability: making AI processes and decisions transparent and understandable.

All these principles are crucial for delivering Trustworthy AI in CCAM.

The framework also includes seven ethical key requirements that are needed to implement the principles. These requirements are:
• Human agency and oversight
• Technical robustness and safety
• Data governance and privacy
• Transparency
• Diversity, non-discrimination and fairness
• Societal and environmental well-being
• Accountability

The workshop consisted of roundtable discussions that explored various aspects of delivering Trustworthy AI in CCAM:
• Fairness, Diversity, and Inclusion: Participants explored the requirements for ensuring diversity, non-discrimination, and fairness in the context of connected and automated vehicles (CAVs). They examined implementation strategies focusing on system design and validation and analyzed trade-offs with other priorities like privacy and safety.
• Sharing Road Space with other types of vehicles, including non-CAVs: Participants discussed the integration of CAVs into public transport environments, addressing issues such as space sharing, potential increases in private CAV usage, and safety concerns related to passengers and driverless vehicles.
• Fostering Cybersecurity: Participants examined the significance of cybersecurity and privacy for CCAM, focusing on balancing these aspects from the users’ perspectives.
• Ensuring Transparency in Industry Communication: This group discussed governance techniques to ensure transparent and accurate communication about the capabilities of autonomous vehicles, aiming to avoid over-claiming and ensure clear definitions of roles and accountability.

The workshop saw active participation from all attendees, fostering collaborative discussions that deepened the understanding of the challenges and opportunities in CCAM. The format proved useful for leveraging the expertise of the CCAM community, enriching AI4CCAM’s efforts to develop guidelines for Trustworthy AI.

The workshop concluded with the presentation of the AI4CCAM Participatory Space, an online platform that aims to connect stakeholders from the CCAM environment. Informative content along with interactive components such as discussions or surveys will be used to engage participants to the adoption of Trustworthy AI literacy applied to CCAM.

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