Work Organization, Jobs, and Tasks standard

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 ...

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Why Centralization Should Be Avoided standard

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 ...

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The Business Banker Loan Origination Software: Optimizing Credit Granting standard

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 ...

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Part 2: Dirac’s reasoning on the discovery of antimatter standard

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 ...

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Part 1: Albert Einstein’s Superior Reasoning Capacity standard

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 Albert Einstein’s theories as exemplary applications. 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 ...

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Investing in Technology: A Strategic Approach for Organizations standard

By: Francois Aubin. Topics: Procurement of enterprise software, Open source, Cognitive Engineering. Summary Software costs can be reduced by 70% to 90% when using open source instead of enterprise alternatives. While it requires the engagement of developers with specialized skills, leading to additional costs, the overall economic benefits are considerable. This cost efficiency primarily stems from its free-to-download nature, sparing businesses the expense of funding the extensive research and development typically undertaken by enterprise vendors. Furthermore, open source software provides enhanced scalability, adeptly adapting to a business’s evolving needs.   The IT Procurement Process in Large Organizations In the realm of modern business, organizations are increasingly relying on technology investments to stay competitive. This typically includes expenditures on enterprise software ...

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Cognitive Task Analysis and AI Agents: Extracting Human Expertise for Enhanced AI Performance standard

The introduction of AI systems, such as ChatGPT, marked a significant milestone in computer technology. Although it may not currently surpass human performance in all tasks, it is progressing at an incredible rate. GPT, or “Generative Pre-trained Transformer,” has the ability to produce new content based on the input it receives. “Generative” refers to its content generation capabilities, while “pre-trained” signifies that the model has already been trained on a massive dataset (commonly known as the “corpus”), which consists of diverse text sources like books, articles, and websites – equivalent to the content of 37.5 million textbooks. This pre-training allows GPT to gain a broad understanding of language and context before being fine-tuned for specific tasks. The term “transformer” pertains ...

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Flying Blind: The Perils of Relying on Machine Learning Without Accurate Data standard

Summary: The most advanced machine learning can produce inaccurate results if the problem is not defined correctly. This is highlighted in the scheduling application for aviation companies. Pilots were unsatisfied due to the flawed algorithm. Introduction: Building schedules for large aviation companies can be a complex task that involving various factors: Seniority, regulations, individual preferences and routes for thousands of pilots and crew members.  It is crucial to integrate all the factors correctly to create a fair and efficient schedule that satisfies everyone. User experience review: The scheduling application was evaluated by conducting one-on-one interviews and observations with 20 pilots from five aviation companies: Delta, United, Air Transat, Air Canada.  The pilots found the application frustrating to use.  They felt ...

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The Illusion of Expertise in Open-Loop Systems standard

Summary: This article debunks the erroneous beliefs regarding the expertise of individuals in making decisions within open-loop systems and presents an approach to overcome their limitations. Open-loop systems don’t provide real-time feedback of the results.  This makes it difficult to adjust strategies effectively.  For instance, in real estate investments or marketing campaigns, the success or failure of a decision is not known for months or years, making it difficult to make informed decisions.  For example, human resource managers receive feedback on an employee’s performance after making the hiring decision . The lack of actual feedback in open-loop systems impairs the accumulation of experience.  Unlike close-loop systems, like driving a car, where numerous decisions are made with real-time feedback.  Open-loop systems ...

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Designing AI Systems that work  standard

Cognitive’s mission is to design AI systems that are practical and understandable.  Current AI technologies, such as ChatGPT for openAI, offer benefits.  However, they can be unpredictable and opaque.  AI systems must be intuitive, efficient, transparent and based on cognitive work processes.  The use of cognitive task analysis (CTA) in combination with AI allows the capture and understanding of how people think and work and the identification of the tasks and goals users wish to accomplish.  This approach ensures that design AI systems are tailored to user needs and that AI systems are practical, efficient, transparent and align seamlessly with the way people think, work and communicate. Cognitive has a dynamic group of experts, researchers, engineers, and operational leaders who ...

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