A pharmaceutical company is using an AI model to identify potential drug candidates from molecular structure data. The model was trained on published research and proprietary lab assay data. An AI risk assessment flags that the model may be unintentionally optimizing for patent-protected molecular configurations. Which risk does this represent?
Select an answer to reveal the explanation.
Short Explanation and Infographic
Here's the deal — b is correct because an AI model trained on data that includes patented molecular configurations may generate or recommend structures that fall within existing patent claims, exposing the organization to patent infringement liability. This is an AI-specific IP risk that arises from the model's ability to generalize from and reproduce patterns in its training data.
Full explanation below image
Full Explanation
B is correct because an AI model trained on data that includes patented molecular configurations may generate or recommend structures that fall within existing patent claims, exposing the organization to patent infringement liability. This is an AI-specific IP risk that arises from the model's ability to generalize from and reproduce patterns in its training data. Hallucination (A) refers to generating incorrect content, not patent replication. Data poisoning (C) requires adversarial intent. Distributional shift (D) refers to performance differences, not IP issues.