Collaboration will focus on three key areas specifically for the automotive diagnosis and repair industry
Leesburg, Va.—The National Institute for Automotive Service Excellence (ASE) has announced a partnership with Convertible AI, a professional services company focused on artificial intelligence.
This collaboration will to explore the development of AI accreditation criteria specifically for the automotive diagnosis and repair industry, addressing a critical need for standardization in AI-powered automotive service applications.
“A common theme for decades has been the fear that new technology will replace technicians and turn them into parts installers,” said Dave Johnson, president and CEO of ASE. “Quite the opposite has happened. The demand for highly trained technicians has continued to rise as vehicles have consistently become more technologically complex. Likewise, tools to diagnose and repair vehicles have also become more technologically advanced. These tools require a technician to be well-trained and knowledgeable while increasing efficiency.”
ASE will lead this initiative to investigate industry-wide standards for automotive AI applications. This partnership leverages ASE’s extensive expertise and network of over 250,000 certified professionals to ensure that emerging AI technologies in the automotive service sector align with the highest standards of safety, reliability and performance.
“As we move into a future where AI tools could become as integral to a technician’s toolbox as traditional diagnostic equipment, it’s crucial that we, along with industry professionals, explore rigorous benchmarks for their use,” said Johnson. “This partnership with Convertible AI represents a significant step forward in our mission to promote excellence in overall vehicle service. By investigating potential AI accreditation criteria, we aim to enhance diagnostic accuracy and service quality for automotive professionals nationwide, ensuring that technological advancements align with our industry’s commitment to excellence and safety.”
The collaboration will focus on three key areas:
- Assess AI performance and fairness: Evaluate accuracy, bias mitigation and consistency across diverse automotive scenarios and vehicle types. This includes examining how AI systems perform across different makes, models and years of vehicles, as well as various diagnostic challenges.
- Examine AI transparency and accountability: Investigate explainability, observability and auditability of AI-driven diagnostic recommendations. This involves exploring ways to make AI decision-making processes more transparent to technicians and developing methods to track and verify AI-generated diagnoses.
- Define ethical guidelines and best practices: Explore responsible AI implementation, including privacy protection, data governance and alignment with automotive industry standards. This encompasses developing frameworks for ethical AI use in automotive services and ensuring compliance with industry regulations.
Comments are closed.