Below are a number of key points from my presentation at the 2022 American Intellectual Property Law Association mid-winter meeting. My talk was primarily structured around my paper Rise of the Intelligent Information Brokers: Role of Computational Law Applications in Administering the Dynamic Cybersecurity Threat Surface in IoT, 19 Minn. J.L. Sci. & Tech. 337 (2018). The AI-enabled computational law application (CLAI) that I modeled is called “Prometheus.”
Cybersecurity Labels: In the U.S., NIST is driving the development of cybersecurity labels. Current labeling schemas have a couple of shortcomings:
(2) They provide static product information, whereas the information should be viewed as dynamic.
Product Metadata: Cybersecurity labels are useful in that they can function as product metadata, which can be analyzed by the CLAI app.
Machine Learning Data-Set: The CLAI app covers all informational sources that comprise a product’s legal specs. These function as the CLAI’s instructive dataset. These sources come from traditional and non-traditional sources.
Consumer Interface: CLAI app uses ML and NLP to analyze all of the informational sources. The consumer receives information from the app, through a variety of UI, such as flags or chat.