Théophile Demazure

• Professor (Assistant) at HEC Montréal

Organisations across various industries are still exploring the potential of Generative Artificial Intelligence (GenAI) to automate a variety of knowledge work processes, including managing innovation. While innovation is often viewed as a product of individual creativity, it more commonly unfolds through a collaborative process where creativity in...

Information systems (IS) can help address environmental challenges. However, adopting Green IS can be challenging even for eco-friendly individuals given the behavioral adjustments required and the difficulties surrounding the generation of effective, long-lasting pro-environmental behaviors. We propose psychological flexibility (PF) as an internal...

Organizations across various industries are still exploring the potential of Generative Artificial Intelligence (GenAI) to enhance knowledge work. While innovation is often viewed as a product of individual creativity, it more commonly unfolds through a highly structured, collaborative process where creativity intertwines with knowledge work. Howev...

Explainable artificial intelligence aims to bring transparency to artificial intelligence (AI) systems by translating, simplifying, and visualizing its decisions. While society remains skeptical about AI systems, studies show that transparent and explainable AI systems can help improve the Human-AI trust relationship. This manuscript presents two s...

Virtual Reality (VR) is known for its ability to immerse users in a parallel universe. Accordingly, VR offers great potential for mindfulness therapy, especially in a post-pandemic world. However, the extent to which our senses should be recruited to yield an optimal feeling of presence in the Virtual Environment (VE) remains unclear. This study in...

Arguably, automation is fast transforming many enterprise business processes, transforming operational jobs into monitoring tasks. Consequently, the ability to sustain attention during extended periods of monitoring is becoming a critical skill. This manuscript presents a Brain-Computer Interface (BCI) prototype which seeks to combat decrements in...

There is a need to train newcomers to NeuroIS on neuroscientific tools and methodologies. Due to the pandemic, existing syllabi required adaptation to enable remote training. In this paper, we present a syllabus aimed at providing hands-on distance learning and EEG training. The proposed syllabus was pretested during a Ph.D. course on Neuroscience...

Explainable Artificial Intelligence (XAI) aims to bring transparency to AI systems by translating, simplifying, and visualizing its decisions. While society remains skeptical about AI systems, studies show that transparent and explainable AI systems result in improved confidence between humans and AI. We present preliminary results from a study des...

Remote electroencephalography (EEG) studies offers the exciting opportunity to gather data within a participants’ home environment. However, remote EEG data collection trades some internal validity for ecological validity. When interacting with interfaces or other artifacts in remote settings, neurophysiological responses and behaviour may display...

We report results of a study that utilizes a BCI to drive an interactive interface countermeasure that allows users to self-regulate sustained attention while performing an ecologically valid, long-duration business logistics task. An engagement index derived from EEG signals was used to drive the BCI while fNIRS measured hemodynamic activity for t...

In today’s data-driven information technology environment, the ability of humans to sustain attention over long periods of time has become an increasingly important skill. We report work in progress to create a novel passive brain computer interface (pBCI), designed to modulate a user’s level of sustained attention in an ecologically valid informat...

Brain Computer Interfaces (BCI) have the potential to provide a means –through interactive countermeasures– to modulate sustained attention (SA) and reduce operator error. We report on progress towards a contribution in this area, through a passive hybrid brain-computer interface designed to modulate a user’s level of sustained attention measured u...