A Look Into the Future of AI Governance
Brian Higgins Blogs
Latest from Brian Higgins
Eliminating Structural Bias in Data-Based Technologies: A Path Forward
As national protests over systemic and structural racism in America continue, community organizers, Black scholars, and others fighting injustice and unequal treatment are once again raising awareness of a long-standing problem lurking within artificial intelligence data-based technologies: bias.
The campaign to root out bias–or eliminate biased systems altogether–has been amplified in recent weeks in the wake of reports of a black Michigan man who was apparently arrested solely on the misidentification decision of a facial…
Eliminating Structural Bias in Data-Based Technologies: A Path Forward
As national protests over systemic and structural racism in America continue, community organizers, Black scholars, and others fighting injustice and unequal treatment are once again raising awareness of a long-standing problem lurking within artificial intelligence data-based technologies: bias.
The campaign to root out bias–or eliminate biased systems altogether–has been amplified in recent weeks in the wake of reports of a black Michigan man who was apparently arrested solely on the misidentification decision of a facial…
EU’s New Plan for Regulating Artificial Intelligence: What US Companies Should Know
EU’s New Plan for Regulating Artificial Intelligence: What US Companies Should Know
Artificial Intelligence, Risk Disclosures, and a New SEC Materiality Test
When Microsoft shared in 2018 that certain “deficiencies” surrounding its artificial intelligence practices could “subject[] us to competitive harm, legal liability, and brand or reputational harm,” it set the stage for other companies to self-report perceived risks associated with developing, using and producing AI technologies. Disclosing risks–a Securities and Exchange Commission (SEC) requirement imposed on public companies since 2005–raises a number of important considerations for both public as well as private companies, including transparency, accuracy,…
Artificial Intelligence, Risk Disclosures, and a New SEC Materiality Test
When Microsoft shared in 2018 that certain “deficiencies” surrounding its artificial intelligence practices could “subject[] us to competitive harm, legal liability, and brand or reputational harm,” it set the stage for other companies to self-report perceived risks associated with developing, using and producing AI technologies. Disclosing risks–a Securities and Exchange Commission (SEC) requirement imposed on public companies since 2005–raises a number of important considerations for both public as well as private companies, including transparency, accuracy,…
First They Wanted Data, Now Cyber Thieves Are After Deep Learning Models: Legal Response Options
Imagine you’ve spent months developing and deploying a revenue-generating deep neural network model only to discover that an attacker has stolen the model’s knowledge and will soon offer a service that will steer potential users away from yours. Flashes of late nights and weekends spent collecting and cleaning data cross your mind, accompanied by a sinking feeling when you think about the significant monetary investment made in computation power. The joy you felt finding just…
First They Wanted Data, Now Cyber Thieves Are After Deep Learning Models: Legal Response Options
Imagine you’ve spent months developing and deploying a revenue-generating deep neural network model only to discover that an attacker has stolen the model’s knowledge and will soon offer a service that will steer potential users away from yours. Flashes of late nights and weekends spent collecting and cleaning data cross your mind, accompanied by a sinking feeling when you think about the significant monetary investment made in computation power. The joy you felt finding just…
Recent Court Decisions Boost the Outlook for Artificial Intelligence Patents
Machine learning enthusiasts have long touted the technology’s ability to perform–and sometimes exceed–human mental endeavors, such as identifying objects in images, generating a portrait painting, deciding to grant a loan application, optimizing a route to a destination, and efficiently responding to website visitor or customer queries. In recent years, such computerized “mental processes” have been denied patent protection, a trend underscored by U.S. federal district and Federal Circuit patent decisions issued in the wake of…