Ethical Challenges in Data-Driven Dialogue Systems

Understand

The use of dialogue systems as a medium for human-machine interaction is an increasingly prevalent paradigm.

• A growing number of dialogue systems use conversation strategies that are learned from large datasets.
• There are well documented instances where interactions with these system have resulted in biased or even offensive conversations due to the data-driven training process.
• Here, we highlight potential ethical issues that arise in dialogue systems research, including: implicit biases in data-driven systems, the rise of adversarial examples, potential sources of privacy violations, safety concerns, special considerations for reinforcement learning systems, and reproducibility concerns.