Safety and Robustness in Conversational AI (2023)

Abstract: In this position paper, I will present the research interests in my PostDoc on safety and robustness specific to conversational AI, including then relevant overlap from my PhD.

## research interests recently there has been an explosion of chatbot-style systems that utilise large language models (llms) deployed in the real world. however, with this large scale deployment, the safety of these systems is critical @xcite @xcite @xcite . while the nlp community has traditionally explored the ethical issues of text-based models (such as hate speech detection, inherent biases of the system etc), real-world conversations and dialogues differ significantly from structured, written text documents, and this brings with it its own unique set of safety challenges. firstly, a central theme of generative linguistics going back to von humboldt, is that language is 'an infinite use of finite means', i.e there exists many ways to say the same thing. however, current research fails to account for this inherent variability of language, which results in a lack of robustness of these systems to: real-world use cases, noisy perturbations to the input, or even adversarial attacks @xcite @xcite . additionally, in real-world interactions, words alone don't sufficiently communicate intended meaning; listeners often arrive at meaning inferring several other speaker cues, such as prosody or even context. however, these unique human-like ways to communicate may be coopted by designers of these systems to drive up user engagement, encouraging humans to relate to such systems in human-like ways -i.e. these systems are anthropomorphised or personified. assigning human characteristics to dialogue systems can have consequences that could be on one hand, harmless, e.g. referring to automated systems by gender, but on the other, disastrous e.g., people following the advice or instructions of a system to do harm foot_0 . based on these themes, i will present the research interests in my postdoc ( §1.1 and §1.2) on safety and robustness specific to conversational ai, including the relevant overlap from my phd. ## spoken dialogue system (sds) research with chatbot style systems being widely deployed, there needs to be emergent research on safety and robustness, but focusing on real world contexts and the nature of dialogues, rather than (brittle) performance on carefully curated datasets. ethically, more research needs to be done on the core set of communicative competencies truly required for different kinds of tasks in a dialogue system, to avoid users unnecessarily personifying and relying on the system.