New study identifies flaws in AI vehicle damage assessment
Vehicle engineering specialist Laird has warned against relying solely on artificial intelligence for vehicle damage assessment.
This comes after it analysed more than 250,000 accident damage assessments as part of its Project X-Ray research into vehicle damage and repair operations.
Based on its findings, it found that some issues which significantly impact repair severity and cost can’t be identified from external images.
It said that artificial intelligence is effective and efficient at visual tasks such as vehicle condition monitoring, panel damage, de-fleeting and hire inspections, but less reliable when assessing accident damage.
Nik Ellis, director of Laird, said: “AI can be good at telling you that a bumper and a wing are damaged. What it can’t necessarily tell you from those photographs is why the wheel is sitting 20mm further back than it should be.
“The first example might be a straightforward cosmetic repair. The second could involve suspension or structural damage, affect whether the vehicle is roadworthy and potentially change the entire economics of the claim. If the system can’t see it, it shouldn’t be allowed to assume it isn’t there.”
He continued: “We use AI every day so this certainly isn’t an anti-AI argument, but a photograph shows you the outside of the car and accident energy doesn’t politely stop at the bumper skin.
“The objective shouldn’t be to choose between AI and engineers. The sensible model is to let each do what it is good at. Use the machine to process enormous amounts of information quickly; use engineering judgement where the answer depends on something the camera cannot see.”
