By: Francois Aubin Abstract Human vigilance deteriorates during prolonged, low-event monitoring tasks—a phenomenon well documented in engineering psychology and human-factors research. This paper explores how artificial intelligence (AI) can support human supervision by detecting deviations from normality that humans typically overlook. Drawing on Christopher D. Wickens’s Engineering Psychology and Human Performance and contemporary human-factors theory, it proposes a cognitive-engineered framework for AI-augmented vigilance. The October 2025 Louvre Museum burglary serves as a case study illustrating how contextual normality can conceal abnormality. Finally, the paper extends this framework to security and counterterrorism, showing how AI pattern-recognition can detect subtle precursors to violent or malicious acts. 1. Introduction Sustained human vigilance is subject to decline over time, particularly in predictable environments with ...

By: François Aubin, Jean-Marc Robert, and Daniel Engelberg 1. Overview and Purpose The paper proposes a structured, systematic method for transforming task analysis directly into user interface design, thereby reducing reliance on intuition and individual judgment in the design process.By integrating human factors guidelines into Hierarchical Task Analysis (HTA), the authors aim to create a consistent, traceable process that can be partially automated, accelerating interface development. 2. Foundations Task Analysis and Usability Traditional methods such as GOMS (Goals, Operators, Methods, Selection rules) are useful for modeling user goals and predicting performance metrics (e.g., task execution time), but insufficient for specifying interfaces.The authors therefore extend HTA by systematically linking task operators (the cognitive actions of users) to human factors principles, interface ...

By : Francois Aubin In the financial industry, especially in banking and lending, one of the most important questions is: how do we fairly and consistently judge the quality of a client? For decades, lenders have relied on rating systems—structured ways of evaluating management, financial capacity, and industry context. These systems are not perfect, but they are always better than relying on pure human judgment. Let’s see why, referencing the work of Daniel Kahneman. Human Judgment: Strong on One Metric, Weak on Many Humans are good at making isolated judgments. For example: Does this business owner have more than five years of experience?  Is there a documented backup plan?  Is the debt ratio below a certain threshold?  On these questions, ...

By: Francois Aubin. Back in 2011, Marc Andreessen wrote his now-famous essay, Why Software is Eating the World. At the time, it was a bold prediction. Andreessen foresaw a future where software wouldn’t just support businesses — it would become the business. Traditional industries were being reimagined as software-driven platforms. And he was right. Think about it: Blockbuster was devoured by Netflix, which turned video rental into a software service. Kodak collapsed under the rise of digital photography and photo-sharing apps. Even the smartphone became a software-first device. When Steve Jobs introduced the iPhone in 2007, he didn’t just embed an MP3 player into a phone like Nokia did — he wrapped powerful software around it, enabling a whole new ...

By: Francois Aubin. Introduction Consider the challenge of forecasting demand for parts in industries such as aerospace, where demand is often low-volume, sparse, and subject to sudden shifts. In a recent AI initiative conducted by our team in collaboration with McKinsey & Company for a leading aerospace company, the initial assumption by data scientists was to employ complex, sophisticated forecasting models. However, a cognitive analysis of expert planners revealed that accurate forecasting alone was not their central concern. Rather, their main challenge lay in effectively supervising inventory levels and adapting forecasts dynamically in response to events such as changes in market demand, economic conditions, or policy shifts. Consequently, our team proposed a novel approach focusing on user interface design that ...

By: Francois Aubin. Abstract This paper introduces the term cogniton as a fundamental element of cognitive tasks. A cognitons is defined as the smallest task element, comprising an operator (the action performed) and an object (the information or stimulus acted upon). By examining scenarios from financial decision-making, medical diagnosis, and music reading, we illustrate how complex tasks are assembled from simple, discrete cognitons. We further explore how deconstructing tasks into cognitons facilitates the training of AI agents, making these atomic units as functional as data elements in building advanced AI systems. 1. Introduction Every complex task we perform—from reviewing loan requests to diagnosing health conditions or reading a musical score—can be deconstructed into elemental operations. Here, we define a cogniton ...

By: Francois Aubin. The story of human factors engineering begins in 1949, with a pioneering researcher named Alphonse Chapanis. Tasked with investigating a troubling trend—the high number of accidents involving B-29 aircraft—Chapanis uncovered a critical insight that would forever change how we design systems. At the time, the United States alone experienced about 30 incidents per year, a staggering number that demanded urgent attention. Determined to uncover the root cause, Chapanis decided to observe pilots during takeoff and landing. What he discovered was both simple and profound. The Problem: Design Flaws Leading to Human Error During his observations, Chapanis noticed a critical design flaw: the landing gear and flap controls were placed side by side, with identical shapes. Both controls ...

Abstract: User Interface (UI) design is an intricate discipline where numerous small elements come together to create a cohesive and functional whole. The effectiveness of a UI often hinges on seemingly minor details, such as font size, font type, alignment, spacing, borders, background, shape, grouping, and visuals. When one of these elements is altered without careful consideration, it can disrupt the balance of the entire design, akin to a house of cards collapsing from the removal of a single card. This paper explores the interconnectedness of UI design components and the potential consequences of modifying individual elements without accounting for their broader impact. Introduction: In the realm of UI design, the adage “the whole is greater than the sum of ...

By: Francois Aubin. Cognitive engineering surpasses the limitations of traditional process analysis. Consider the intellectual challenge of playing chess, the precision of making a medical diagnosis, or the strategy behind making an investment decision—these are all complex cognitive processes that require a deep understanding of how people think and make decisions. What makes cognitive engineering so exciting is its unique integration of system design and cognitive analysis. Instead of relying on two separate experts, cognitive engineering empowers the system designer to take on both roles. This approach involves thoroughly exploring how users make decisions, identifying the essential information needed for those decisions, and analyzing the cognitive processes involved in selecting actions. By merging these disciplines, system designers gain a holistic ...

By: Francois Aubin. Skill Acquisition and Learning Cognitive Engineering offers a unique perspective on the processes of learning and training. As discussed in previous chapters, cognitive engineering seeks to understand how individuals process information, make decisions, and use this understanding to design systems that enhance learning and performance. This chapter delves deeper into the application of cognitive engineering principles to skill acquisition and the transitions between different levels of cognitive processing. The SRK Framework: Skill, Rule, and Knowledge-Based Behavior Previously, we explored the Skill, Rule, and Knowledge-based (SRK) model, which categorizes human behavior into three distinct levels of cognitive processing. This model is crucial for understanding how repeated actions can transition from conscious, effortful activities into automatic behaviors. For example, ...