A Robot with Personality: How to (responsibly) design a digital persona?

To develop neural generative interaction models which are consistent with a personality and to demonstrate the impact of such personality in Human-Robot Interaction whilst also considering the societal impacts of personality choices.
Description of the Project: 

Social Robots and other artificial agents are often designed to have a digital persona. A digital persona can be viewed as a composite of elements of identity (such as demographics and background facts), behaviour, and interaction style.
These are deliberate design choices, often influenced by common perceptions, such as female voices being more `pleasant' when choosing a synthesised voice and gender.However, these design choices bear the risk of reinforcing social stereotypes, according to the UNESCO (West et al., 2019).

In this project, we will we will be looking to reflect personality not only by different synthesised voices, but also personality expressed in language and multimodal behaviour, conversational content and interaction style, building upon previous work on using neural generative models for personality-based linguistic style generation and generating responses which factually consistent with a persona profile.

We will also look to consider what role such persona profiles play in the context of human-robot interaction, whilst working closely with social psychologists to anticipate the social impacts these artificial personas might have. In particular, we will investigate:

(i) the (objective) impact/importance of robot persona (including gender) in HRI
(ii) if/how robots can/should effectively respond to abuse/inappropriate behaviour

Eventually, we aim to build a data-driven mapping between conversational behaviour (e.g. voice, linguistic style and content) and perceived personality traits, such as gender, age, trustworthiness etc.

Resources required: 
High Performance Computing, different humanoid robotic platforms, such as Pepper etc.
Project number: 
240016
First Supervisor: 
University: 
Heriot-Watt University
First supervisor university: 
Heriot-Watt University
Essential skills and knowledge: 
Neural Networks
Desirable skills and knowledge: 
Natural Language Processing, Social Robotics
References: 

Anastasia  Kuzminykh,   Jenny  Sun,   Nivetha  Govindaraju,  Jeff  Avery,  and  Edward  Lank.  2020.    Genie in the bottle: Anthropomorphized perceptions ofconversational agents.   In Proceedings of the 2020 CHI Conference on Human Factors in ComputingSystems, pages 1–13.

Clifford Nass and Scott Brave. 2007. Wired for Speech:How Voice Activates and Advances the Human-Computer Relationship. The MIT Press.

Shereen   Oraby,    Lena   Reed,    Shubhangi   Tandon, Sharath T.S., Stephanie Lukin, and Marilyn Walker. 2018.   Controlling personality-based stylistic variation with neural natural language generators. In Proceedings of the 19th Annual SIGdial Meeting on Dis-course and Dialogue.

Selina  Jeanne  Sutton.  2020.   Gender  ambiguous,  notgenderless:   Designing  gender  in  voice  user  inter-faces (vuis) with sensitivity.  InProceedings of the2nd Conference on Conversational User Interfaces,pages 1–8.

Mark West,  Rebecca Kraut,  and Han Ei Chew. 2019.I’d blush if i could:  closing gender divides in dig-ital  skills  through  education.Technical  ReportGEN/2019/EQUALS/1 REV, UNESCO