Vinoth Pandian Sermuga Pandian

HC
3papers
25citations
Novelty18%
AI Score15

3 Papers

HCMay 13, 2022
Grounding Explainability Within the Context of Global South in XAI

Deepa Singh, Michal Slupczynski, Ajit G. Pillai et al.

In this position paper, we propose building a broader and deeper understanding around Explainability in AI by 'grounding' it in social contexts, the socio-technical systems operate in. We situate our understanding of grounded explainability in the 'Global South' in general and India in particular and express the need for more research within the global south context when it comes to explainability and AI.

HCApr 4, 2020
BlackBox Toolkit: Intelligent Assistance to UI Design

Vinoth Pandian Sermuga Pandian, Sarah Suleri

User Interface (UI) design is an creative process that involves considerable reiteration and rework. Designers go through multiple iterations of different prototyping fidelities to create a UI design. In this research, we propose to modify the UI design process by assisting it with artificial intelligence (AI). We propose to enable AI to perform repetitive tasks for the designer while allowing the designer to take command of the creative process. This approach makes the machine act as a black box that intelligently assists the designers in creating UI design. We believe this approach would greatly benefit designers in co-creating design solutions with AI.

HCJan 27, 2020
NASA-TLX Web App: An Online Tool to Analyse Subjective Workload

Vinoth Pandian Sermuga Pandian, Sarah Suleri

NASA Task Load Index (NASA-TLX) is a widely used assessment technique to compute subjective workload experienced during a task. It evaluates workload using six dimensions: mental demand, physical demand, temporal demand, frustration, effort, and performance. This paper presents a web app to assist experimenters in using NASA-TLX to commute subjective workload. The web app enables the experimenter to conduct various experiments simultaneously and offers the participants a concise interface to provide their subjective evaluation. It performs the calculations at the backend and provides the computed results comprehensively. The web app provides a dashboard for the experimenter to visualize and export the summary of results. Qualitative feedback from 12 experimenters indicated that the NASA-TLX web app is relevant, helpful, and easy to use.