no code implementations • 21 Apr 2022 • Samson Tan, Araz Taeihagh, Kathy Baxter
We explore how different risks may manifest in various types of ML systems, the factors that affect each risk, and how first-order risks may lead to second-order effects when the system interacts with the real world.
no code implementations • ACL 2021 • Samson Tan, Shafiq Joty, Kathy Baxter, Araz Taeihagh, Gregory A. Bennett, Min-Yen Kan
Questions of fairness, robustness, and transparency are paramount to address before deploying NLP systems.
no code implementations • 22 Jul 2020 • Mikolaj firlej, Araz Taeihagh
The operationalization of emerging policies of human control results in the typology of direct and indirect human controls exercised over the use of AS.
no code implementations • 29 Oct 2019 • Hazel Si Min Lim, Araz Taeihagh
We discuss steps taken to address these issues, highlight the existing research gaps and the need to mitigate these issues through the design of AV's algorithms and of policies and regulations to fully realise AVs' benefits for smart and sustainable cities.
no code implementations • 16 Jul 2018 • Araz Taeihagh, Hazel Si Min Lim
Our analyses reveal that, thus far, governments have in most instances avoided stringent measures in order to promote AV developments and the majority of responses are non-binding and focus on creating councils or working groups to better explore AV implications.