By Sayash Kapoor, Mihir Kshirsagar, and Arvind Narayanan Our response to the National AI Research Resource RFI highlights the significance of supporting a research infrastructure that is designed to independently test the validity of the claims of AI performance. In particular, we draw attention to the widespread phenomenon of the industry peddling what we call […]
National AI Research Infrastructure Needs to Support Independent Evaluation of Performance Claims
September 2, 2021 by
GPT-3 Raises Complex Questions for Philosophy and Policy
August 13, 2020 by
GPT-3, a powerful, 175 billion parameter language model developed recently by OpenAI, has been galvanizing public debate and controversy. As the MIT Technology Review puts it: “OpenAI’s new language generator GPT-3 is shockingly good—and completely mindless”. Parts of the technology community hope (and fear) that GPT-3 could brings us one step closer to the hypothetical […]
AI Ethics: Seven Traps
March 25, 2019 by
By Annette Zimmermann and Bendert Zevenbergen The question of how to ensure that technological innovation in machine learning and artificial intelligence leads to ethically desirable—or, more minimally, ethically defensible—impacts on society has generated much public debate in recent years. Most of these discussions have been accompanied by a strong sense of urgency: as more […]
Bridging Tech-Military AI Divides in an Era of Tech Ethics: Sharif Calfee at CITP
February 5, 2019 by
In a time when U.S. tech employees are organizing against corporate-military collaborations on AI, how can the ethics and incentives of military, corporate, and academic research be more closely aligned on AI and lethal autonomous weapons? Speaking today at CITP was Captain Sharif Calfee, a U.S. Naval Officer who serves as a surface warfare officer. […]
What Are Machine Learning Models Hiding?
July 26, 2018 by
Machine learning is eating the world. The abundance of training data has helped ML achieve amazing results for object recognition, natural language processing, predictive analytics, and all manner of other tasks. Much of this training data is very sensitive, including personal photos, search queries, location traces, and health-care records. In a recent series of papers, […]
