As self-driving taxis pave their way across the nation, entering the streets of Colorado seems imminent. However, whether the public will embrace this technological leap relies heavily on a complex tapestry of trust. Trust in autonomous machines, particularly in services such as self-driving taxis, is a subject that Amir Behzadan, a professor from the University of Colorado Boulder, explores. In a world increasingly reliant on artificial intelligence for everyday tasks, understanding the nuances of trust can significantly influence the adoption of such technologies.
Behzadan, affiliated with the Department of Civil, Environmental and Architectural Engineering and the Institute of Behavioral Science at CU Boulder, leads a team that seeks to unravel the intricacies of trust and artificial intelligence. Their efforts have resulted in a structured framework intended to bolster the trustworthiness of AI tools that impact human lives. The implications are profound: as AI systems integrate deeper into our daily existence, fostering trust is vital for their acceptance and utilization.
In their recent study, highlighted in the journal “AI and Ethics,” Behzadan and his research colleague, Ph.D. student Armita Dabiri, delve into the fundamental attributes of trustworthy AI. Their research culminates in the development of a conceptual AI tool that encapsulates critical elements of trustworthiness. The duo articulates that trust, often initiated through vulnerability, can be seamlessly translated from human-to-human relationships to those involving humans and technology. This perspective invites a reassessment of how society interacts with emerging AI technologies.
Behzadan meticulously examines the foundational aspects of trust in artificial intelligence, particularly focusing on applications within the built environment. Whether it is navigating the complexities of autonomous vehicles, optimizing smart home security, or enhancing public transportation systems, understanding how trust is formed is crucial. The historical context shows that trust, integral to human cooperation and collaboration, has evolved. From ancient societies forming bonds based on mutual reliance to modern perceptions of AI as potentially alien or challenging, the dynamics of trust have retained their significance.
One of the central tenets of Behzadan’s research is that trust is subjective, varying extensively among individuals based on personal experiences, values, cultural backgrounds, and intrinsic cognitive frameworks. This inherent variability means that even the most reliable AI systems could inspire disparate levels of trust among users. Developers, therefore, face the challenge of tailoring AI technologies to meet diverse user needs and preferences, ensuring that technological advancement does not falter due to misunderstandings or a lack of connection.
Behzadan outlines the importance of reliability, ethics, and transparency in the design of trustworthy AI systems. In contexts where life-altering decisions are made, such as healthcare or autonomous transport, users must be assured of the safety and security of the technology at hand. Moreover, transparency regarding data usage and algorithmic decision-making can significantly alleviate concerns surrounding privacy and control. In situations where users feel observed or manipulated, their willingness to trust diminishes, further emphasizing the need for clear communication about how AI technologies function.
Context is also crucial in establishing trust in AI systems. Behzadan and Dabiri’s work presents an innovative AI tool titled “PreservAI,” which exemplifies sensitivity to contextual nuances. In practical applications, such as when various stakeholders – engineers, urban planners, and government officials – confront the building of a historical structure, the ability of AI to navigate competing priorities effectively can make or break trust. This tool is designed to integrate stakeholder feedback and evaluate various outcomes, demonstrating that AI can abstract critical contextual knowledge much like humans do while collaborating.
User experience plays a significant role in building trust. Technologies that facilitate interactions and allow feedback create an environment in which users can engage actively with AI systems. The importance of ensuring an intuitive, user-friendly design cannot be overstated. Behzadan explains that if users have autonomy in their interactions with AI, they are more likely to develop a rapport with the system, further solidifying their trust. This engagement becomes even more vital when considering how trust can shift, sometimes erratically, depending on experiences with technology.
Trust is inherently dynamic and can fluctuate based on experiences or external events. For example, a potential rider’s enthusiasm for a self-driving taxi may wane following news of accidents involving autonomous vehicles, leading to a crisis of confidence. Yet Behzadan remarks on the potential for rebuilding that trust through improved design and outcomes. The case of Microsoft’s “Tay” chatbot illustrates this point, as the initial failure prompted the company to launch “Zo,” which incorporated lessons learned from the earlier missteps. This iterative approach to trustworthiness is essential for the sustainable development of reliable AI technologies.
The journey toward fostering trust in AI systems is undoubtedly complex, laden with risks. Users must often relinquish some control and share personal data for these systems to operate efficiently. In turn, these AI systems learn and adapt, potentially becoming more effective over time. The crux lies in balancing these elements, ensuring that users feel comfortable and secure in sharing their data while maximizing the utility of AI innovations.
Amir Behzadan emphasizes that the potential for AI is vast; when people trust these systems enough to engage with them meaningfully, it catalyzes an evolution toward more personalized and effective support. This promises not just a technological revolution but also a transformation in the quality of life, as individuals experience tailored solutions that cater to their unique needs. The path forward will require continued dialogue and exploration into the mechanisms of trust, ensuring that as AI becomes more prevalent, it becomes increasingly benign, facilitating a partnership that ultimately empowers users.
This multifaceted exploration into trust and artificial intelligence highlights a pressing issue of our time. As we stand at the brink of widespread adoption of autonomous technologies, understanding the foundational aspects of trust and implementing reliable systems could be the differentiator between acceptance and reluctance. Success in this realm will pave the way for an era of collaboration between humans and AI that enhances not just technological efficacy but the very fabric of societal interactions.
Ultimately, as we witness the evolution of self-driving taxis and other autonomous systems, embracing a framework fortified by trust could lead to breakthroughs that enhance our day-to-day experiences, reducing the skittishness surrounding prevalent AI technologies. With insights from Amir Behzadan and his research efforts, society may harness not only the tools of tomorrow but also the promise they hold for a more interconnected future.
Subject of Research: Trust in Artificial Intelligence and Self-Driving Technology
Article Title: Factors influencing human trust in intelligent built environment systems
News Publication Date: 15-Aug-2025
Web References: AI and Ethics
References: doi:10.1007/s43681-025-00813-6
Image Credits: University of Colorado Boulder
Keywords
Artificial Intelligence, Civil Engineering, Trust in Technology, Autonomous Vehicles, User Experience, Ethical AI.
