ITLP members weigh in and write on issues and questions at the intersection of technology and law.

 Legislators in California are considering two bills which aim to safeguard the financial viability of the news industry and support journalism by tapping revenues from online platforms. The Institute of Technology, Law and Policy analyzed the legal risks, mitigations and likelihood of each. 

The California Consumer Protection Act should grant Californians the right to know whether their personal information has been used to train GenAI systems. By taking decisive and timely action, the California Privacy Protection Agency can uphold the integrity of the CCPA and fulfill its mission of empowering consumers to exercise their data privacy rights, no matter the technology involved.

As an increasing number of government agencies utilize algorithms in regulatory enforcement processes, the incorporation of AI-powered tools raises a number of difficult questions. This brief explores these concerns and raises considerations stakeholders should bear in mind. 

"Fair use is not just a privilege granted by the courts and blessed by Congress; it is a constitutional requirement. [T]he Court should invalidate the Digital Millennium Copyright Act’s anti-circumvention and anti-trafficking provisions as unconstitutional under the First Amendment." ITLP is among those in this amicus curiae brief for Green v. DOJ.

"Revisions to the Copyright Act should be made to clarify that AI-generated works are unprotectable by copyright, a subject that, clearly, was not contemplated by Congress when it passed the Copyright Act of 1976." Comments in response to the Copyright Office’s Notice of Inquiry (“NOI”) in a study on artificial intelligence (“AI”) and copyright.

As Artificial Intelligence/Machine Learning technologies improve, their use in healthcare is set to continue expanding. The safe adoption and integration of these technologies into the practice of medicine will depend largely on the regulatory structures in place to nurture responsible innovation.  

The regulation of software as a medical device (SaMD), and in particular AI SaMD, requires a shift from the traditional paradigm of medical device regulation to account for the continuous updates that an AI system might receive over its lifetime. The FDA's rapidly evolving regulatory framework that aims to keep up with the pace of technology has consequences for the liability of AI/ML device manufacturers.

There is a pressing need to carefully consider the adverse impacts of technologically-based initiatives aimed at countering terrorism, particularly those involving machine learning and facial recognition, as the biases within these systems tend to have an outsized effect on marginalized and minority groups.