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, ...

By: Francois Aubin. Overview Human activities occur within a larger organizational framework, where the activities of one person are linked to others. Organizations typically divide into units such as departments or offices. For example, a bank might have units for loan officers who interact with clients, adjudications for decision-making, and operations for processing transactions. Within these units, employees have specific jobs with various tasks. For instance, a loan officer’s job includes tasks such as sales, information collection, and client follow-up. These tasks involve sub-tasks such as entering loan applications, validating information, obtaining client support documents, and checking credit bureaus. Designing Work Organization, Jobs, and Tasks The recommendations in this paper primarily focus on paid work but can also apply to ...

By: Francois Aubin. Centralization, while intended to standardize processes and achieve economies of scale, centralization presents significant drawbacks that hinder effective work organization, particularly in decision-making processes. It requires local units within an organization to comply with standardized policies and rely on decisions made by a central authority. This structure restricts local units from making context-specific decisions, leading to frustration and inefficiency.   The Pitfalls of Centralization Lack of Autonomy: Centralization removes decision-making power from local units, despite these units having the most relevant information about their situations. For example, employees at a local branch might understand their specific challenges and opportunities better than a distant central office. However, centralized policies prevent them from acting on this knowledge, which is ...

In the banking sector, the process of granting credit is essential. Business Banker has developed a rigorous decision workflow that is both easy to use and to configure to manage this critical aspect, effectively evaluating credit applications, minimizing financial risks, and ensuring fail-safe regulatory compliance. Foundations of the Decision Workflow: Client Information:The process begins by categorizing clients (individuals, SMEs, large enterprises, financing entities, cooperatives), with each segment requiring a tailored approach strategy. Integrating the client into our systems necessitates identity authentication and the collection of specific information through a comprehensive KYC (Know Your Customer) process. Financing Request:Tailored to the client’s specifics, the request includes: Credit facilities, Collateral securities, Disbursement terms, Obligations to be met. Specific Risk Model: Each client segment ...

By: Francois Aubin. Summary: Cognitive Engineering examines individual interactions and decision-making in technological contexts, emphasizing human reasoning dimensions like information processing, judgment, and problem-solving. This study highlights cognitive skills fundamental to reasoning, including pattern recognition, memory, abstract thinking, and logic, using Direct’s theories.  Cognitive Engineering:The aim is to automate and design better systems by focusing on understanding how individuals interact with technology and make decisions in complex systems. This field scrutinizes the ways in which people process information, make judgments, and tackle problems. The ultimate objective often revolves around enhancing human-machine interaction and refining decision-making processes in environments driven by technology. Human Reasoning:Human Reasoning is the process of drawing inferences or conclusions from established facts and premises. This ability is ...