Final Prep - Knowledge Management & AI PDF

**Chapter 11: Managing Knowledge and Artificial Intelligence** **11-1. What is the role of knowledge management systems in business?** - Identify the key differences between tacit and explicit knowledge. -  - Describe the process of organizational learning. - Define...

**Chapter 11: Managing Knowledge and Artificial Intelligence** **11-1. What is the role of knowledge management systems in business?** - Identify the key differences between tacit and explicit knowledge. -  - Describe the process of organizational learning. - Define and describe computer vision systems, natural language processing systems, and robotics, and give examples of their applications in organizations. - Natural Language Processing Human language is not always precise. It is often ambiguous, and meanings of words can depend on complex variables such as slang, regional dialects, and social context. Natural language processing (NLP) makes it possible for a computer to understand and analyze natural language---language that human beings instinctively use, not language specially formatted to be understood by computers. NLP algorithms are typically based on machine learning, including deep learning, which can learn how to identify a speaker's intent from many examples. You can see natural language processing at work in leading search engines such as Google, spam filtering systems, and text mining sentiment analysis (discussed in Chapter 6). Tokyo-based Mizuho Bank employs advanced speech recognition technology, IBM® Watson™ content analytics software, and a cloud services infrastructure to improve contact center agents' interactions with customers. After converting the customer's speech to textual data, the solution applies natural language processing algorithms based on machine learning analysis of interactions with thousands of customers. The system learns more and more from each customer interaction so that it can eventually infer the customer's specific needs or goals at each point of the conversation. It then formulates the optimal response, which is delivered in real time as a prompt on the agent's screen. By helping contact center agents more efficiently sense and respond to customer needs, this solution reduced the average duration of customer interactions by more than 6 percent (IBM, 2020). Computer Vision Systems Computer vision systems deal with how computers can emulate the human visual system to view and extract information from real-world images. Such systems incorporate image processing, pattern recognition, and image understanding. An example is Facebook's facial recognition tool called DeepFace, which is nearly as accurate as the human brain in recognizing a face. DeepFace helps Facebook improve the accuracy of Facebook's existing facial recognition capabilities to ensure that every photo of a Facebook user is connected to that person's Facebook account. Computer vision systems are also used in autonomous vehicles such as drones and self-driving cars (see the chapter-ending case), industrial machine vision systems (e.g., inspecting bottles), military applications, and robotic tools. In health care, computer vision technology is being used for tumor evaluations. For instance, Amsterdam University Medical Center (AUMC), one of Europe's largest academic oncology centers, is using SAS Visual Data Mining and Machine Learning tools to increase the speed and accuracy of chemotherapy response assessments. Tumors used to be manually evaluated using computerized tomography (CT) scans after treatment. How a tumor reacts to treatment determines whether lifesaving surgery is possible or if a different chemotherapy regimen is necessary. Prior evaluation methods conducted by humans were limited to what doctors could see. AUMC's new computer vision technology capabilities for automatic segmentation help doctors to quickly identify changes in the shape and size of tumors and note their color. The AI models show total tumor volume and a 3D representation of each tumor, allowing doctors to more accurately determine whether lifesaving surgery is viable or if a different treatment strategy should be chosen (Amsterdam UMC, 2021). Robotics Robotics deals with the design, construction, operation, and use of movable machines that can substitute for humans along with computer systems for their control, sensory feedback, and information processing. Robots cannot substitute entirely for people but are programmed to perform a specific series of actions automatically. They are often are used in dangerous environments (such as bomb detection and deactivation and recently for delivering medical supplies to coronavirus-contaminated locations), manufacturing processes, military operations (drones), and medical procedures (surgical robots). The most widespread use of robotic technology has been in manufacturing. For example, automobile assembly lines employ robots to do heavy lifting, welding, applying glue, and painting. People still do most of the final assembly of cars, especially when installing small parts or wiring that needs to be guided into place. A Renault SA plant in Cleon, France, now uses robots from Universal Robots AS of Denmark to drive screws into engines, especially those that go into places people find hard to access. The robots verify that parts are properly fastened and check to make sure the correct part is being used. The Renault robots are also capable of working in proximity to people and slowing down or stopping to avoid hurting them. Growing use of robotic systems, along with other technologies described in this chapter and this text has kindled widespread fears that automation is taking away people's jobs. The Interractive Session on Organizations explores this topic. **11-2. What are artificial intelligence (AI) and machine learning? How do businesses use AI?** - Define artificial intelligence (AI) and the major AI techniques. - -  - Define an expert system, describe how it works, and explain its value to business. - -  - Define machine learning, explain how it works, and give some examples of the kinds of problems it can solve. - - Define neural networks and deep learning neural network¸ s, describing how they work and how they benefit organizations.  - -  - Define and describe genetic algorithms and intelligent agents. Explain how each works and the kinds of problems for which each is suited. - **11-3. What types of systems are used for enterprise-wide knowledge management, and how do they provide value for businesses?**  - **Define and describe the various types of enterprise-wide knowledge management systems and explain how they provide value for businesses.** - -  -  **Chapter 12: Enhancing Decision Making** **12-1. What are the different types of decisions, and how does the decision-making process work?**  List four structured decisions that a manager at the operational level in an organization is likely to have to make. **IDK chat:** **Employee Shift Scheduling** -- Determining work schedules for employees to ensure smooth daily operations. **Inventory Management** -- Deciding when to reorder stock based on current inventory levels, sales trends, and demand forecasts. **Approving Customer Returns or Refunds** -- Evaluating and processing customer return requests based on company policies. **Generating Daily Operational Reports** -- Reviewing and documenting sales, production output, or employee performance to track business efficiency. - - **According to the classical model of management, what are the five roles of management?** - **Explain what is meant by the term management filter.**  - Explain how management information systems and transaction processing systems interact. Distinguish between a production report and a parameterized report. NEMA BRATE EVO SA CHATA **Interaction Between Management Information Systems (MIS) and Transaction Processing Systems (TPS):** - A **Transaction Processing System (TPS)** records and processes daily business transactions (e.g., sales, payroll, inventory updates). - A **Management Information System (MIS)** collects data from TPS and other sources, processes it, and generates reports to support decision-making. - TPS provides raw transaction data, while MIS organizes, summarizes, and analyzes this data for managerial use. **Difference Between a Production Report and a Parameterized Report:** - A **Production Report** is a standard, pre-defined report generated on a regular schedule (e.g., daily sales reports). - A **Parameterized Report** allows users to input specific criteria (parameters) to generate customized reports based on selected filters (e.g., sales data for a specific region or time period). - - List three different production reports that might be generated by a sales department. Three different **production reports** that might be generated by a sales department include: - **Daily Sales Report** -- Summarizes total sales transactions, revenue, and key performance metrics for a specific day. - **Monthly Sales Performance Report** -- Analyzes sales trends over the month, comparing results to targets and previous months. - **Customer Purchase Report** -- Provides insights into customer buying patterns, including top-selling products and customer demographics. - - **Explain how a business would use data from the Internet of Things.** **12-2. How do information systems support the activities of managers and management decision making?** - Describe the nature and value of a business analytics toolset.  - Explain how predictive analytics works and what it uses. **12-4. How do different decision-making constituencies in an organization use business intelligence?** - List each of the major decision-making constituencies in an organization and describe the types of decisions each makes. -  - Describe how MIS, DSS, or ESS provide decision support for each of these groups. - \+  - **Define and describe the balanced scorecard method and business performance management**. **Chapter 13: Building Information Systems** **. How does building new systems produce organizational change?**  - Define the term paradigm shift, and explain why it often fails. - Describe the purpose of a formal post-implementation audit.  **13-2. What are the core activities in the systems development process?** - Explain why a systems analysis will often incorporate a feasibility study. - Explain the role of a systems designer and their work related to systems analysis.  - Explain the role of the programming phase of a system development process. Who provides this service? **13-3. What are the principal methodologies for modeling and designing systems?** - Compare object-oriented and traditional structured approaches for modeling and designing systems. **13-4. What are alternative methods for building information systems?**  - **Define the traditional systems life cycle. Describe its advantages and disadvantages for systems building.** **13-5. What are new approaches for system building in the digital firm era?**  **define rapid application development (RAD), agile development, automated software testing, low-code and no-code development, and DevOps, and explain how they can improve system building.**  - - **Explain the features of mobile application development and responsive web design.**  -