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Articles 1 - 6 of 6
Full-Text Articles in Internet Law
Trademarks In An Algorithmic World, Christine Haight Farley
Trademarks In An Algorithmic World, Christine Haight Farley
Washington Law Review
According to the sole normative foundation for trademark protection—“search costs” theory—trademarks transmit useful information to consumers, enabling an efficient marketplace. The marketplace, however, is in the midst of a fundamental change. Increasingly, retail is virtual, marketing is data-driven, and purchasing decisions are automated by AI. Predictive analytics are changing how consumers shop. Search costs theory no longer accurately describes the function of trademarks in this marketplace. Consumers now have numerous digital alternatives to trademarks that more efficiently provide them with increasingly accurate product information. Just as store shelves are disappearing from consumers’ retail experience, so are trademarks disappearing from their …
Fair Play: Notes On The Algorithmic Soccer Referee, Michael J. Madison
Fair Play: Notes On The Algorithmic Soccer Referee, Michael J. Madison
Articles
The soccer referee stands in for a judge. Soccer’s Video Assistant Referee (“VAR”) system stands in for algorithms that augment human deciders. Fair play stands in for justice. They are combined and set in a polycentric system of governance, with implications for designing, administering, and assessing human-machine combinations.
Ethical Testing In The Real World: Evaluating Physical Testing Of Adversarial Machine Learning, Kendra Albert, Maggie Delano, Jonathon Penney, Afsaneh Ragot, Ram Shankar Siva Kumar
Ethical Testing In The Real World: Evaluating Physical Testing Of Adversarial Machine Learning, Kendra Albert, Maggie Delano, Jonathon Penney, Afsaneh Ragot, Ram Shankar Siva Kumar
Articles, Book Chapters, & Popular Press
This paper critically assesses the adequacy and representativeness of physical domain testing for various adversarial machine learning (ML) attacks against computer vision systems involving human subjects. Many papers that deploy such attacks characterize themselves as “real world.” Despite this framing, however, we found the physical or real-world testing conducted was minimal, provided few details about testing subjects and was often conducted as an afterthought or demonstration. Adversarial ML research without representative trials or testing is an ethical, scientific, and health/safety issue that can cause real harms. We introduce the problem and our methodology, and then critique the physical domain testing …
Can An Improved Disclosure Mechanism Moderate Algorithm-Based Software Patentability In The Public Interest?, Vinicius Sala
Can An Improved Disclosure Mechanism Moderate Algorithm-Based Software Patentability In The Public Interest?, Vinicius Sala
Cybaris®
No abstract provided.
“Can I Profit From My Own Name And Likeness As A College Athlete?” The Predictive Legal Analytics Of A College Player’S Publicity Rights Vs. First Amendment Rights Of Others, Roger M. Groves
Roger M. Groves
Two federal court decisions during 2013 have changed the game for college students versus the schools, the NCAA and video game makers. This article explores whether for the first time in history these athletes can profit from their own name and likeness and prevent others from doing so. But those cases still leave many untested applications to new facts – facts that the courts have not faced. Particularly intriguing is how 21st Century technology will apply to this area in future litigation. No publicity rights case or article to date has explored the application of predictive analytics, computer programs, algorithms, …
From Google To Tolstoy Bot: Should The First Amendment Protect Speech Generated By Algorithms?, Margot Kaminski
From Google To Tolstoy Bot: Should The First Amendment Protect Speech Generated By Algorithms?, Margot Kaminski
Publications
No abstract provided.