Ethical Considerations in Adaptive Extended Reality Design: Developing a Heuristic Framework for Designer Training

Core Concepts

Developing a heuristic framework and training toolkit to promote ethical principles among designers engaged in adaptive extended reality (XR) design.

Abstract

The research project aims to address the ethical tensions in persuasive design practices for adaptive extended reality (XR) technologies. The authors propose a Design-Based Research (DBR) methodology to develop "bRight-XR", a framework that incorporates ethical dimensions for use as both a design guidance tool and a training tool for adaptive-XR designers. The key aspects of the proposed methodology are: Design of a heuristic evaluation matrix: Conduct a systematic literature review to identify existing theoretical frameworks, guidelines, and design processes. Conduct semi-directive interviews with experts to gather feedback and projections from the field. Analyze the data to identify and qualify the main dimensions to be included in the heuristic evaluation matrix. Prioritize the heuristic criteria using a hybrid evaluation approach. Test pedagogical prototypes: Apply the scoring method to different pedagogical scenarios using experimental prototypes in adaptive-XR. Collaborate with pedagogical engineers, designers, and technologists to produce the scenarios and prototypes using the Design Fiction approach. Pre-validation of a training kit: Incorporate the outcomes of the Design Fiction investigation into a demonstration and educational toolkit. The toolkit will consist of a heuristic criteria evaluation grid and a set of recommendations. Conduct a preliminary investigation to evaluate the impact of the toolkit on designers, using a questionnaire. Fully document the toolkit, publish it as an Open-Source project, and build it on open science standards to enable interoperability and contributions. The project aims to establish a dialogue among diverse research fields, including cognitive sciences, science and technology studies, and educational sciences, to mitigate the adverse effects that digital technologies can have on individuals in the context of the democratization of adaptive-XR technologies.

Stats

None.

Quotes

None.

Key Insights Distilled From

[DC] bRight XR: How to train designers to keep on the bright side?

by Roma... at arxiv.org 04-18-2024

https://arxiv.org/pdf/2404.11142.pdf

Deeper Inquiries

How can the proposed heuristic framework and training toolkit be adapted to address the ethical challenges posed by the integration of generative techniques (e.g., AI and Large Language Models) in the design process of adaptive-XR technologies?

The integration of generative techniques like AI and Large Language Models in the design process of adaptive-XR technologies introduces complex ethical challenges that need to be addressed. To adapt the proposed heuristic framework and training toolkit to tackle these challenges, several key steps can be taken: Incorporating Ethical Guidelines: The heuristic evaluation matrix can be expanded to include specific criteria related to the ethical use of generative techniques. This can involve assessing the transparency, accountability, and fairness of AI algorithms used in adaptive-XR design. Training on Ethical AI Design: The training toolkit can include modules that educate designers on the ethical implications of using generative techniques. This can involve understanding bias, privacy concerns, and the potential societal impact of AI-powered XR experiences. Case Studies and Scenarios: Integrate case studies and scenarios that highlight ethical dilemmas related to generative techniques. By engaging designers in practical ethical decision-making exercises, they can develop a deeper understanding of how to navigate these challenges. Collaboration with Ethicists: Partnering with ethicists and experts in AI ethics can provide valuable insights into best practices for integrating generative techniques responsibly. Their input can help refine the heuristic framework to better address ethical considerations in adaptive-XR design.

How can the proposed framework and toolkit be extended to address the long-term well-being and eudaimonic considerations of users beyond the immediate design and interaction experience?

To extend the proposed framework and toolkit to address the long-term well-being and eudaimonic considerations of users in adaptive-XR technologies, the following strategies can be implemented: User-Centric Design Principles: Enhance the heuristic evaluation matrix to include criteria that focus on the long-term impact of XR experiences on user well-being. This can involve assessing factors like user autonomy, psychological safety, and overall life satisfaction. Behavioral Monitoring: Integrate tools in the training toolkit that enable designers to monitor user behavior post-interaction with adaptive-XR technologies. By collecting data on user well-being indicators, designers can iteratively improve their designs to promote long-term positive outcomes. User Feedback Mechanisms: Implement mechanisms in the toolkit that facilitate gathering feedback from users about their long-term experiences with XR technologies. This feedback can inform future design iterations and ensure that user well-being remains a central consideration. Educational Modules on Eudaimonia: Develop educational modules within the training toolkit that educate designers on the concept of eudaimonia and its relevance to XR design. By fostering a deeper understanding of how design choices impact users' overall well-being, designers can create more meaningful and sustainable experiences.

What are the potential limitations and drawbacks of the Design-Based Research (DBR) methodology in the context of this project, and how can they be addressed?

While Design-Based Research (DBR) offers valuable insights and practical applications, there are potential limitations and drawbacks that need to be considered in the context of this project: Time and Resource Intensive: DBR can be a time-consuming and resource-intensive methodology, requiring extensive collaboration and iterative design cycles. To address this, project timelines should be carefully planned, and resources allocated efficiently to ensure the successful implementation of the methodology. Generalizability of Findings: The findings from DBR studies may not always be easily generalizable to broader contexts due to the specific nature of the research setting. To mitigate this limitation, researchers can supplement DBR with other research methods to validate and extend the findings to different contexts. Subjectivity in Evaluation: DBR relies on subjective evaluations and interpretations of design interventions, which can introduce bias. To address this, researchers should employ multiple evaluators, triangulate data sources, and use standardized evaluation criteria to enhance the reliability and validity of the findings. Limited External Validity: DBR studies may have limited external validity, as they are often conducted in controlled settings with specific participant groups. To enhance external validity, researchers can consider conducting follow-up studies in real-world settings to validate the findings and ensure their applicability beyond the research context.