| Vol-2301 urn:nbn:de:0074-2301-6 Copyright © 2019 for the individual papers by the papers' authors. Copying permitted for private and academic purposes. This volume is published and copyrighted by its editors.

# SafeAI 2019
AAAI Workshop on Artificial Intelligence Safety

### Proceedings of the AAAI Workshop on Artificial Intelligence Safety 2019
co-located with the Thirty-Third AAAI Conference on Artificial Intelligence 2019 (AAAI 2019)

### Honolulu, Hawaii, January 27, 2019.

Edited by

### Huáscar Espinoza *
Seán Ó hÉigeartaigh **
Xiaowei Huang ***
José Hernández-Orallo ****
Mauricio Castillo-Effen *****

* CEA LIST, Gif-sur-Yvette, France
** University of Cambridge, Cambridge, United Kingdom
*** University of Liverpool, Liverpool, United Kingdom
**** Universitat Politècnica de València, Valencia, Spain
***** Lockheed Martin, Advanced Technology Laboratories, Arlington, VA, USA

## Table of Contents

- Preface

### Frontmatter

- Author Index
- Keyword Index
- Table of Contents

### Invited Talk

- Impossibility and Uncertainty Theorems in AI Value Alignment (or why your AGI should not have a utility function)
  Peter Eckersley

### Session 1: Safe Planning and Operation of Autonomous Systems

- Minimizing the Negative Side Effects of Planning with Reduced Models
  Sandhya Saisubramanian, Shlomo Zilberstein
- Robust Motion Planning and Safety Benchmarking in Human Workspaces
  Shih-Yun Lo, Shani Alkoby, Peter Stone
- Enter the Matrix: Safely Interruptible Autonomous Systems via Virtualization
  Mark Riedl, Brent Harrison

### Session 2: New Paradigms in AI and AGI Safety

- Towards Robust End-to-End Alignment
  Lê Nguyên Hoang
- Integrative Biological Simulation, Neuropsychology, and AI Safety
  Gopal Sarma, Adam Safron, Nick Hay

### Session 3: Safety in Automated Driving

- How Many Operational Design Domains, Objects, and Events?
  Philip Koopman, Frank Fratrik
- Monitoring Safety of Autonomous Vehicles with Crash Prediction Networks
  Saasha Nair, Sina Shafaei, Stefan Kugele, Mohd Hafeez Osman, Alois Knoll

### Session 4: Safety-Related AI Requirements and Characteristics

- Requirements Assurance in Machine Learning
  Alec Banks, Rob Ashmore
- Surveying Safety-relevant AI Characteristics
  Jose Hernandez-Orallo, Fernando Martínez-Plumed, Shahar Avin, Sean O Heigeartaigh

### Session 5: Adversarial Machine Learning

- Detecting Backdoor Attacks on Deep Neural Networks by Activation Clustering
  Bryant Chen, Wilka Carvalho, Nathalie Baracaldo, Heiko Ludwig, Benjamin Edwards, Taesung Lee, Ian Molloy, Biplav Srivastava
- DPATCH: An Adversarial Patch Attack on Object Detectors
  Xin Liu, Huanrui Yang, Ziwei Liu, Linghao Song, Yiran Chen, Hai Li
- Attacks on Machine Learning: Lurking Danger for Accountability
  Katja Auernhammer, Ramin Tavakoli Kolagari, Markus Zoppelt

### Short Poster Papers

- Towards International Standards for Evaluating Machine Learning
  Frank Rudzicz, P Alison Paprica, Marta Janczarski
- Counterfactual Explanations of Machine Learning Predictions: Opportunities and Challenges for AI Safety
  Kacper Sokol, Peter Flach
- Safe Temporal Planning for Urban Driving
  Bence Cserna, William Doyle, Tianyi Gu, Wheeler Ruml
- Linking Artificial Intelligence Principles
  Yi Zeng, Enmeng Lu, Cunqing Huangfu
- Emergence of Addictive Behaviors in Reinforcement Learning Agents
  Vahid Behzadan, Roman V. Yampolskiy, Arslan Munir
- Temporally Extended Metrics for Markov Decision Processes
  Philip Amortila, Marc G. Bellemare, Prakash Panangaden, Doina Precup
- AutoMPC: Efficient Multi-Party Computation for Secure and Privacy-Preserving Cooperative Control of Connected Autonomous Vehicles
  Tao Li, Lei Lin, Siyuan Gong
- Security-preserving Support Vector Machine with Fully Homomorphic Encryption
  Saerom Park, Jaewook Lee, Jung Hee Cheon, Juhee Lee, Jaeyun Kim, Junyoung Byun
- Bamboo: Ball-Shape Data Augmentation Against Adversarial Attacks from All Directions
  Huanrui Yang, Jingchi Zhang, Hsin-Pai Cheng, Wenhan Wang, Yiran Chen, Hai Li

2019-01-02: submitted by José Hernández-Orallo, metadata incl. bibliographic data published under Creative Commons CC0
2019-01-20: published on CEUR-WS.org |valid HTML5|