AISafety 2021
Artificial Intelligence Safety 2021

Table of Contents

• Preface
  
  

Trustworthiness of Knowledge-Based AI

• Applying Strategic Reasoning for Accountability Ascription in Multiagent Teams
  Vahid Yazdanpanah, Sebastian Stein, Enrico Gerding, Nicholas R. Jennings
• Impossibility of Unambiguous Communication as a Source of Failure in AI Systems
  William Howe, Roman Yampolskiy

Session 2: Robustness of Machine Learning Approaches

• Assessing the Reliability of Deep Learning Classifiers Through Robustness Evaluation and Operational Profiles
  Xingyu Zhao, Wei Huang, Alec Banks, Victoria Cox, David Flynn, Sven Schewe, Xiaowei Huang
• Towards Robust Perception Using Topological Invariants
  Romie Banerjee, Feng Liu, Pei Ke
• Measuring Ensemble Diversity and Its Effects on Model Robustness
  Lena Heidemann, Adrian Schwaiger, Karsten Roscher

Session 3: Perception and Adversarial Attacks

• Deep Neural Network Loses Attention to Adversarial Images
  Shashank Kotyan, Danilo Vasconcellos Vargas
• An Adversarial Attacker for Neural Networks in Regression Problems
  Kavya Gupta, Jean-Christophe Pesquet, Beatrice Pesquet-Popescu, Fateh Kaakai, Fragkiskos Malliaros
• Coyote: A Dataset of Challenging Scenarios in Visual Perception for Autonomous Vehicles
  Suruchi Gupta, Ihsan Ullah, Michael Madden

Session 4: Qualification / Certification of AI-Based Systems

• Towards a Safety Case for Hardware Fault Tolerance in Convolutional Neural Networks Using Activation Range Supervision
  Florian Geissler, Syed Qutub, Sayanta Roychowdhury, Ali Asgari, Yang Peng, Akash Dhamasia, Ralf Graefe, Karthik Pattabiraman, Michael Paulitsch
• Artificial Intelligence for Future Skies: On-going Standardization Activities to Build the Next Certification/Approval Framework for Airborne and Ground Aeronautic Products
  Christophe Gabreau, Béatrice Pesquet-Popescu, Fateh Kaakai, Baptiste Lefevre
• Using Complementary Risk Acceptance Criteria to Structure Assurance Cases for Safety-Critical AI Components
  Michael Klaes, Rasmus Adler, Lisa Jöckel, Janek Groß, Jan Reich

Poster Papers

• Uncontrollability of Artificial Intelligence
  Roman Yampolskiy
• Domain Shifts in Reinforcement Learning: Identifying Disturbances in Environments
  Tom Haider, Felippe Schmoeller Roza, Dirk Eilers, Karsten Roscher, Stephan Günnemann
• Chess as a Testing Grounds for the Oracle Approach to AI Safety
  James Miller, Roman Yampolskiy, Olle Häggström, Stuart Armstrong
• Socio-technical co-Design for Accountable Autonomous Software
  Ayan Banerjee, Imane Lamrani, Katina Michael, Diana Bowman, Sandeep Gupta
• Epistemic Defenses against Scientific and Empirical Adversarial AI Attacks
  Nadisha-Marie Aliman, Leon Kester
• On the Differences between Human and Machine Intelligence
  Roman Yampolskiy
• A Mixed Integer Programming Approach for Verifying Properties of Binarized Neural Networks
  Christopher Lazarus, Mykel Kochenderfer