Digital Commons Network^™

Data Privacy, Human Rights, And Algorithmic Opacity, Sylvia Lu

Fellow, Adjunct, Lecturer, and Research Scholar Works

Decades ago, it was difficult to imagine a reality in which artificial intelligence (AI) could penetrate every corner of our lives to monitor our innermost selves for commercial interests. Within just a few decades, the private sector has seen a wild proliferation of AI systems, many of which are more powerful and penetrating than anticipated. In many cases, AI systems have become “the power behind the throne,” tracking user activities and making fateful decisions through predictive analysis of personal information. Despite the growing power of AI, proprietary algorithmic systems can be technically complex, legally claimed as trade secrets, and managerially …

Data As The New Oil: A Slippery Slope Of Trade Secret Implications Greased By The California Consumer Privacy Act, Megan Marie Miller

Cybaris®

Following the European model of the General Data Protection Regulation (GDPR), the state of California implemented the California Consumer Privacy Act (CCPA) on January 1, 2020. The CCPA allows any California consumer to demand to see all of the information that a company has saved on them; consumers can also request a full list of all the third parties that their data is shared with, sold to, and for what commercial purpose. This paper reviews the implications of a new law on the disclosure of trade secrets like client lists and algorithms that manipulate consumers’ data. Ultimately, the issue comes …

Privacy Vs. Transparency: Handling Protected Materials In Agency Rulemaking, Christopher S. Yoo, Kellen Mccoy

All Faculty Scholarship

Agencies conducting informal rulemaking proceedings increasingly confront conflicting duties with respect to protected materials included in information submitted in public rulemaking dockets. They must reconcile the broad commitment to openness and transparency reflected in federal law with the duty to protect confidential business information (CBI) and personally identifiable information (PII) against improper disclosure.

This Article presents an analysis of how agencies can best balance these often-countervailing considerations. Part I explores the statutory duties to disclose and withhold information submitted in public rulemaking dockets placed on agencies. It also examines judicial decisions and other legal interpretations regarding the proper way to …

Contracting For Algorithmic Accountability, Cary Coglianese, Erik Lampmann

All Faculty Scholarship

As local, state, and federal governments increase their reliance on artificial intelligence (AI) decision-making tools designed and operated by private contractors, so too do public concerns increase over the accountability and transparency of such AI tools. But current calls to respond to these concerns by banning governments from using AI will only deny society the benefits that prudent use of such technology can provide. In this Article, we argue that government agencies should pursue a more nuanced and effective approach to governing the governmental use of AI by structuring their procurement contracts for AI tools and services in ways that …

Secrets Of The Deep: Defining Privacy Underwater, Annie Brett

UF Law Faculty Publications

The drones are coming, But not just to your neighborhood skies – to the world’s oceans. From recreational robots designed to autonomously follow divers and record video of them to low-cost, remotely operated submersibles that put ocean exploration in the hands of the general public to sophisticated military submersibles able to autonomously gather intelligence throughout the oceans, the underwater drone market is exploding. But unlike on land, this explosion has not been accompanied by similar discussion of privacy concerns. Instead, the ocean’s rapid shift away from an inaccessible operational sanctuary is one that is happening largely silently. And it is …