Law Commons^™

How Can I Tell If My Algorithm Was Reasonable?, Karni A. Chagal-Feferkorn

Michigan Technology Law Review

Self-learning algorithms are gradually dominating more and more aspects of our lives. They do so by performing tasks and reaching decisions that were once reserved exclusively for human beings. And not only that—in certain contexts, their decision-making performance is shown to be superior to that of humans. However, as superior as they may be, self-learning algorithms (also referred to as artificial intelligence (AI) systems, “smart robots,” or “autonomous machines”) can still cause damage.

When determining the liability of a human tortfeasor causing damage, the applicable legal framework is generally that of negligence. To be found negligent, the tortfeasor must have …

Seeing (Platforms) Like A State: Digital Legibility And Lessons For Platform Governance, Neil Chilson

Catholic University Journal of Law and Technology

The growing backlash against Big Tech companies is a symptom of digital technology increasing the world’s legibility. James C. Scott’s book, Seeing Like a State: How Certain Schemes to Improve the Human Condition Have Failed, explores how past governments responded to increased legibility – for good and for ill. This article shows how Scott’s historical lessons can guide governments and tech platforms as they seek to improve the human condition online.