6 citations · 20 across the 12 of their papers we have counts for
12 papers
AEGIS: Online Adaptive AI Content Safety Moderation with Ensemble of LLM Experts
Shaona Ghosh, Prasoon Varshney, Erick Galinkin +1
As Large Language Models (LLMs) and generative AI become more widespread, the content safety risks associated with their use also increase. We find a notable deficiency in high-qua…
Robustness and Usefulness in AI Explanation Methods
Erick Galinkin
Explainability in machine learning has become incredibly important as machine learning-powered systems become ubiquitous and both regulation and public sentiment begin to demand an…
Towards a Responsible AI Development Lifecycle: Lessons From Information Security
Erick Galinkin
Legislation and public sentiment throughout the world have promoted fairness metrics, explainability, and interpretability as prescriptions for the responsible development of ethic…
Who's Afraid of Thomas Bayes?
Erick Galinkin
In many cases, neural networks perform well on test data, but tend to overestimate their confidence on out-of-distribution data. This has led to adoption of Bayesian neural network…
Winning the Ransomware Lottery: A Game-Theoretic Model for Mitigating Ransomware Attacks
Erick Galinkin
Ransomware is a growing threat to individuals and enterprises alike, constituting a major factor in cyber insurance and in the security planning of every organization. Although the…
The State of AI Ethics Report (January 2021)
Abhishek Gupta, Alexandrine Royer, Connor Wright +9
The 3rd edition of the Montreal AI Ethics Institute's The State of AI Ethics captures the most relevant developments in AI Ethics since October 2020. It aims to help anyone, from m…
The Influence of Dropout on Membership Inference in Differentially Private Models
Erick Galinkin
Differentially private models seek to protect the privacy of data the model is trained on, making it an important component of model security and privacy. At the same time, data sc…
Information Security Games: A Survey
Erick Galinkin
We introduce some preliminaries about game theory and information security. Then surveying a subset of the literature, we identify opportunities for future research.
The State of AI Ethics Report (October 2020)
Abhishek Gupta, Alexandrine Royer, Victoria Heath +12
The 2nd edition of the Montreal AI Ethics Institute's The State of AI Ethics captures the most relevant developments in the field of AI Ethics since July 2020. This report aims to…
Malicious Network Traffic Detection via Deep Learning: An Information Theoretic View
Erick Galinkin
The attention that deep learning has garnered from the academic community and industry continues to grow year over year, and it has been said that we are in a new golden age of art…
Green Lighting ML: Confidentiality, Integrity, and Availability of Machine Learning Systems in Deployment
Abhishek Gupta, Erick Galinkin
Security and ethics are both core to ensuring that a machine learning system can be trusted. In production machine learning, there is generally a hand-off from those who build a mo…
The State of AI Ethics Report (June 2020)
Abhishek Gupta, Camylle Lanteigne, Victoria Heath +6
These past few months have been especially challenging, and the deployment of technology in ways hitherto untested at an unrivalled pace has left the internet and technology watche…