Guests Abhishek Gupta, Camylle Lanteigne, Muriam Fancy, and Ryan Khurana discuss their State of AI Ethics Report, exploring biases in NLP models, troubling trends in AI ethics, lack of transparency in applicant screening, addressing inequality with AI, and the importance of understanding AI security and overcoming misconceptions.
The State of AI Ethics Report aims to compile information and knowledge from diverse perspectives to provide a practical resource for navigating the field of AI ethics.
Machine learning security deserves more attention to prevent biases, compromises of fairness, and ethical concerns.
Deep dives
Motivation for the State of AI FX report
The podcast episode features an interview with researchers from the Montreal AI FX Institute who discuss the motivation behind creating the State of AI FX report. The report aims to bring attention to the most important developments in AI and their societal impacts. The researchers highlight the need to compile information and knowledge from diverse perspectives, including scholars from different fields, to provide a practical and accessible resource for navigating the rapidly evolving field of AI ethics.
Key Topics Covered in the Report
The podcast episode highlights the broad range of topics covered in the State of AI FX report, including agency and responsibility, disinformation, jobs and labor, privacy, machine learning security, and more. The researchers emphasize the importance of considering these topics in AI ethics discussions. They specifically mention the need for increased attention to machine learning security, the impact of AI on labor markets, and the interdisciplinary development of AI to address biases and ethical dilemmas.
Concrete Instances of AI in Problematic Ways
The podcast episode discusses the challenges and ethical concerns associated with the use of AI in various contexts. One example mentioned is the increasing delegation of responsibility to AI systems in employment background checks, which can result in opaque decision-making processes, potential biases, and less transparency for both applicants and hiring organizations. The podcast also highlights the need to address biases and inclusivity issues in AI, such as the impact of biased pre-trained models on people with disabilities and the importance of considering ethical perspectives beyond traditional Western viewpoints.
Under-hyped and Over-hyped Aspects in AI Ethics Discussions
In terms of under-hyped aspects, the podcast episode suggests that machine learning security deserves more attention. It emphasizes the importance of analyzing and addressing potential vulnerabilities in AI systems, such as adversarial attacks, to prevent biases, compromises of fairness, and ethical concerns. On the other hand, the podcast suggests that the concept and capabilities of AI itself may be over-hyped in popular media outlets. It emphasizes the need for more accurate and accessible explanations of AI for the general public, debunking misconceptions, and creating awareness of its limitations.
An interview with the Founder of the Montreal AI Ethics Institute Abhishek Gupta, as well as fellow AI Ethics researchers Camylle Lanteigne, Muriam Fancy, Ryan Khurana, about their recent State of AI Ethics Report.