Emerging Projects

Consumers

AI Chatbots for Choices

Can personalised AI chatbots enhance consumer decision-making and reduce choice overload in complex product categories?

Technology: Generative AI (e.g., custom chatbots)

Emotional Ad Testing

How can real-time facial expression analysis of consumers’ emotional responses to public health advertisements be used to optimise campaign effectiveness and encourage healthier behaviours?

Technology: Facial Expression Analysis Software, Digital Display/Online Platform

Breath-Based Retail Insights

How can the customer experience be adapted in real time based on non-invasive respiration monitoring of customers in a small retail environment (e.g., a boutique, café, or gallery) to improve customer value and sales?

Technology: Respiration Monitoring Sensors (non-contact, e.g., via smart mat, specialised camera, or unobtrusive sensors), AI (for pattern analysis)

Description

Participants interact with either a standard product information interface or an AI-powered chatbot that provides tailored recommendations and answers based on their stated preferences, with researchers measuring decision satisfaction, cognitive load, and product selection.

Description

Consumers view various versions of public health advertisements (e.g., anti-smoking, healthy eating campaigns) on a screen while their facial expressions are recorded and analysed for emotional responses (e.g., surprise, disgust, happiness). This data is then correlated with self-reported attitudes and behavioural intentions to determine which advertisement designs evoke the most impactful

Description

In a small retail setting, customers’ respiration patterns are discreetly monitored (e.g., via a smart mat at a product display or unobtrusive sensors integrated into seating areas). AI analyses these patterns for indicators of relaxation, engagement, or discomfort (e.g., when faced with too many choices). The insights gained allow the small business to make real-time adjustments, such as modifying music, lighting, product displays, or staff interaction, with the aim of creating a more comfortable and engaging environment, thereby improving customer satisfaction and encouraging purchasing behaviour.

Employees

Wearables for Workplace Stress

Can wearable sensors objectively measure employee stress levels and provide real-time interventions to improve well-being and productivity in high-pressure work environments?

Technology; Wearable Sensors (e.g., heart rate variability monitors)

AI Feedback for Remote Work

To what extent can AI-powered feedback systems improve employee feedback seeking behaviour and enhance skill development in a remote work setting?

Technology: AI (for performance analysis or training)

Temi in Hospitality

Can the Temi robot enhance the operational efficiency and employee job satisfaction in a small hospitality business (e.g., a boutique hotel or independent restaurant) by automating routine tasks, improving internal communication, and providing immediate support to staff during busy periods?

Technology: Temi Robot

Description

Employees in specific roles wear biometric sensors during work tasks, with data linked to self-reported stress and objective performance metrics, and in some conditions, real-time feedback or nudges are provided via a connected app.

Description

Remote employees utilise an AI system that provides automated feedback on their work (e.g., written communication, code quality) and encourages them to proactively seek further guidance, with researchers tracking engagement with the system and skill improvement over time.

Description

In a small hotel or restaurant, the Temi robot is programmed to assist employees with tasks such as delivering small items (e.g., menus, towels to rooms), relaying messages between kitchen and front-of-house staff, or providing quick access to FAQs for common customer queries. Employees can also use Temi for rapid video calls to managers or remote support. Researchers would measure how Temi’s presence affects staff workload, response times to customer requests, employee stress levels, and overall job satisfaction, demonstrating its potential to free up human staff for more complex or personal interactions and improve service quality.

Citizens

Robots for Public Engagement

How do social robots deployed in public spaces influence citizen engagement with local community initiatives and public services?

Technology: Social Robots

Citizen Science for Cities

How can a citizen science digital platform effectively engage a diverse public in collecting and analysing data for urban planning decisions, leading to more inclusive outcomes?

Technology: Digital Platforms/Citizen Science Tools

Voice Feedback for Policy

How can automated voice analysis of citizen feedback provided through public consultation hotlines or digital platforms identify prevalent emotional responses and concerns regarding new government policies or public services, enabling more responsive and empathetic policy adjustments?

Technology: Voice Analysis Software (as described on CanBe Lab’s ‘our-technology’ page)

Description

A social robot is placed in a public area (e.g., a library or community centre) to interact with citizens, providing information about local initiatives, and researchers observe and survey citizens’ engagement levels and perceptions of the robot’s role.

Description

A digital platform is developed to allow citizens to report on urban issues (e.g., accessibility, green spaces) or contribute data through surveys, and researchers analyse the platform’s usability, data quality, and its impact on civic participation and policy recommendations.

Description

When citizens call a public consultation hotline or submit voice messages via a digital platform, their audio is analysed by the voice analysis software. The system identifies aggregate emotional trends (e.g., widespread frustration, confusion, or approval) and common vocal stress indicators. This anonymised and aggregated data provides government bodies with a real-time, nuanced understanding of public sentiment beyond just the literal words, enabling them to make more empathetic policy adjustments, clarify communications, or address underlying emotional concerns that might otherwise be missed.

Bridging the Digital Divide: Improving Translation and Usability in Services Australia’s Online Platforms

This cross-faculty project investigates how Culturally and Linguistically Diverse (CALD) users engage with Services Australia’s digital translation services.

Technology: Screen Based Eye Tracking

Description

This cross-faculty project investigates how Culturally and Linguistically Diverse (CALD) users engage with Services Australia’s digital translation services. Drawing on the advanced capabilities of the Canberra Behavioural Lab (CanBe Lab) and SciTech’s Human-Centred Computing Lab, the research team will use screen-based eye tracking and facial expression analysis to capture how users visually and emotionally respond to translated content in real time. These behavioural insights, combined with focus group findings, will inform evidence-based recommendations to improve accessibility and trust in government digital platforms. The project highlights how behavioural science and human-centred technology can contribute to more equitable digital service delivery.

Project Team

Dr Irfan Khan (Lead, BGL); Dr Hamed Sarbazhosseini (Co‑Lead, SciTech); Dr Ryan Payne (Co‑Lead, BGL); Dr Masoud Mohammadian (Co‑Lead, SciTech); Dr Dawa Wangchuk (Co‑Lead, BGL); Dr Somayeh Bahmannia (Co‑Lead, BGL); Dr Rosetta Romano (Coordinator, SciTech)

Current Projects

Bridging the Digital Divide: Improving Translation and Usability in Services Australia’s Online Platforms

This cross-faculty project investigates how Culturally and Linguistically Diverse (CALD) users engage with Services Australia’s digital translation services.

Project Team
Dr Irfan Khan (Lead, BGL); Dr Hamed Sarbazhosseini (Co‑Lead, SciTech); Dr Ryan Payne (Co‑Lead, BGL); Dr Masoud Mohammadian (Co‑Lead, SciTech); Dr Dawa Wangchuk (Co‑Lead, BGL); Dr Somayeh Bahmannia (Co‑Lead, BGL); Dr Rosetta Romano (Coordinator, SciTech)

AI for kids to visualize their future careers in tradiational and non tradiational job roles

The CanBe Lab is exploring how artificial intelligence can be used to broaden children’s perceptions of future careers, particularly by showcasing non-traditional roles and challenging stereotypes.

Project Lead

Dr. Ryan Payne, Nick Havilah

How we gender robots, and the effect this has on gender norms and society.

The CanBe Lab is investigating how gendered cues in robots influence human interaction, trust, and decision-making.

Project Leads:

Dr. Ryan Payne, Dr. Robin Ladwig

Description

This cross-faculty project investigates how Culturally and Linguistically Diverse (CALD) users engage with Services Australia’s digital translation services. Drawing on the advanced capabilities of the Canberra Behavioural Lab (CanBe Lab) and SciTech’s Human-Centred Computing Lab, the research team will use screen-based eye tracking and facial expression analysis to capture how users visually and emotionally respond to translated content in real time. These behavioural insights, combined with focus group findings, will inform evidence-based recommendations to improve accessibility and trust in government digital platforms. The project highlights how behavioural science and human-centred technology can contribute to more equitable digital service delivery.

Description

The CanBe Lab is exploring how artificial intelligence can be used to broaden children’s perceptions of future careers, particularly by showcasing non-traditional roles and challenging stereotypes. Using generative AI, the project creates personalised, visual narratives that allow students to see themselves in professions they may not have previously considered, from engineering and technology to leadership positions traditionally dominated by a single gender or demographic.

Representation matters. Research shows that when children see role models who reflect their identity, they are more likely to pursue those paths, develop confidence, and build aspirations beyond conventional expectations. By visualising diverse career possibilities, the project helps to break down social and cultural barriers, inspiring curiosity, resilience, and ambition.

This initiative also provides educators and policymakers with insights into how AI can be responsibly applied to support learning, career guidance, and social inclusion. By combining behavioural science with technology, the CanBe Lab can help make a difference to kids on what they think is possible. Ultimately, this work contributes to a more equitable and imaginative future, empowering young people to explore opportunities they might never have envisioned and fostering a generation that values diversity in all areas of work and society.

Description

The CanBe Lab is investigating how gendered cues in robots influence human interaction, trust, and decision-making. As robots become increasingly present in workplaces, schools, and public services, the ways they are perceived can shape engagement, compliance, and social norms. Our research examines how gendered design elements—such as voice, appearance, and behaviour—affect how people respond to robotic systems in real-world and simulated environments.

By combining behavioural science with advanced technologies, including AI-powered observation tools, eye tracking, and facial expression analysis, the lab can measure subtle responses to gendered cues and identify potential biases or unintended consequences. This work is vital for creating inclusive, ethical, and effective automated systems that are designed for diverse populations.

Findings from this project inform guidelines for robot design, AI governance, and ethical technology deployment, ensuring that as automation grows, it supports equitable experiences and reduces reinforcement of stereotypes in society.

Digital or Doomed being forced to use technology for work promotions

The CanBe Lab is exploring how university professors experience subtle pressure to adopt emerging technologies, such as the Temi Robot, in research and teaching.

Leads:

Dr. Ryan Payne, Dr. Sidrah Asif

Using Social Robots to Improve Customer and Student Experience

The CanBe Lab is exploring how the role of a social robot in a learning environment affects student engagement.

Leads:

Dr Sidrah Asif and Professor Raechel Johns.

Description

The CanBe Lab is exploring how university professors experience subtle pressure to adopt emerging technologies, such as the Temi Robot, in research and teaching. As automation and AI become increasingly central to behavioural studies, academics may feel vulnerable—concerned that reluctance to use these tools could limit their research opportunities, funding prospects, or relevance in a rapidly evolving field.

This study aims to explore how academics perceive and respond to subtle pressures to adopt and integrate emerging technologies in their research practices, particularly in the context of institutional metrics for publication success and career progression.

By understanding these dynamics, the research informs policies and training programs that empower researchers to engage with technology thoughtfully, reducing anxiety and inequity while fostering innovation. Ultimately, the project highlights how to balance technological advancement with human readiness and inclusion in academic research.

Description

Social robots, like the humanoid robot TEMI, are changing how customers and students interact with services and learning environments. In service or retail settings, TEMI’s interactions can influence a customer’s mental, emotional, and physical engagement with an organisation. This project studies TEMI’s deployment in a classroom, in three different roles; teaching assistant, tutor, or unit convenor. The project aims to understand how customers and students react to the robot in these different positions and the influence on their engagement in the classroom.

This study aims to investigate how a social robot’s role—as an intern, assistant, or manager—influences the cognitive, emotional, and behavioural engagement of customers in the context of an educational service.

The findings will guide both business and universities on the most effective ways to use social robots in service delivery. For education, the research will advance innovation in digital learning design, supporting equity and graduate employability. For industry, it will help businesses deploy robots in service and retail environments to improve customer engagement.

Canberra Behavioural Lab

What society CanBe with technology.

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