MIS Ch. 11

Digital asset management systems

Help companies classify, store, and distribute digital objects and digital data like photographs, graphic images, video, audio content

Explicit knowledge

Knowledge that has been documented

Natural Language Processing (NLP)

Algorithms based on machine learning (and deep learning) that can learn how to identify a speaker's intent from many examples; makes it possible for a computer to understand and analyze natural language--language that humans instinctively use, not formatted to be understood by computers

Genetic algorithms

Another form of machine learning; useful for finding the optimal solution for a specific problem by examining a very large number of alternative solutions for that problem; problem-solving based on ideas inspired by evolutionary biology such as inheritance, mutation, selection, and crossover

Computer-aided design (CAD)

Automates the creation and revision of designs, using computers and sophisticated graphics software; each design modification requires a mold to be made and a prototype to be tested physically (time consuming)

Machine Learning (ML)

Based on an entirely different AI paradigm than expert systems; there are no experts or effort to write computer code for rules; ML has very large data sets with millions of data points and automatically finds patterns and relationships by making statistical inferences

Neural networks

Composed of interconnected units called neurons, artificial neurons are software programs and math models that perform the input and output function of neurons; networks of these find patterns and relationships in very large amounts of data that would be too complicated and difficult for a human being to analyze via machine learning algorithms and computational models based on how human brain operates

Computer vision systems

Deal with how computers can emulate the human visual system to view and extract information from real-world images; incorporate image-processing, pattern recognition, image understanding; EX: FB's facial recognition tool called DeepFace

Knowledge base

Expert systems that model human knowledge as a set of rules collectively

Structured knowledge

Explicit knowledge that exists in formal documents, as well as in formal rules that organizations derive by observing experts and their decision-making behaviors; makes up 20% of org's business content

Data

Flows of events or transactions captured by an organization's systems that are useful for transacting but little else

Enterprise-wide knowledge management systems

General-purpose, firm-wide systems that collect, store, distribute, and apply digital content and knowledge; have capabilities for searching for information, structured and unstructured data, locating employees within the firm, plus supporting technologies

Enterprise Content Management (ECM) system

Helps organizations manage both structured and semi-structured information; capabilities for knowledge capture, storage, retrieval, distribution, and preservation to help firms improve their business processes and decisions; EX: use repositories of structured reports and semi-structured knowledge like email

Communities of practice (COPs)

Informal social networks of professionals and employees within and outside the firm who have similar work-related activities and interests; activities include self-education, group education, conferences, online newsletters, day-to-day sharing of experiences and techniques

Artificial Intelligence (AI)

Involves the attempt to build computer systems that think and act like humans; like computers, it takes data input from the environment, process that data, and produce outputs

Tacit knowledge

Knowledge residing in the minds of employees that has not been documented

"Deep learning"

Neural networks that are more complex, with many layers of transformation of the input data to produce a target output; these are in their infancy right now, used for pattern detection on unlabeled data where the system is not told what to look for specifically but to simply discover patterns in the data

"Intelligent" techniques

Part of knowledge management; includes data mining, expert systems, machine learning, neural networks, natural language processing, computer vision systems, robotics, genetic algorithms, intelligent agents

Learning Management System (LMS)

Provides tools for the management, delivery, tracking, and assessment of various types of employee learning and training

Massive Open Online Courses (MOOCs)

Publicly online courses via the web made available to a very large number of participants; used by businesses to educate their employees

Knowledge workers

Researchers, designers, architects, scientists, and engineers who primarily create knowledge and information for the organization; usually have high levels of education and membership in professional organizations

Unsupervised learning

Same as supervised, but humans do not feed the system examples, instead the system is asked to process the development database and report whatever pattern it finds

Knowledge management

Set of business processes developed in an organization to create, store, transfer, and apply knowledge; increases the ability of the org to learn from its environment and incorporate knowledge into its business processes

Chatbots

Software agents designed to simulate a conversation with one or more human users via textual or auditory methods, trying to understand what you say and respond by answering questions or executing tasks, automated conversations; aka "chatterbots"

Intelligent agents

Software programs that work in the background without direct human intervention to carry out specific, repetitive, and predictable tasks for an individual user, business process, or software application; uses a limited built-in or learned knowledge base to accomplish tasks or make decisions on the user's behalf, like detecting junk mail, schedule appts, find cheapest airfare

Knowledge Work Systems (KWS)

Specialized systems built for engineers, scientists, and other knowledge workers charged with discovering and creating new knowledge for a company

Inference engine

Strategy used to search through the collection of rules and formulate conclusions; works by searching through rules and firing those rules that are triggered by facts the user gathers and enters

Augmented Reality (AR)

Technology for enhancing visualization by overlaying digital data and images onto a physical real-world environment; enhances perception of reality to make real world more interactive and meaningful; EX: military training

Wisdom

The collective and individual experience of applying knowledge to the solution of problems; involves where, when, and how to apply knowledge

Taxonomy

The creation of an appropriate classification scheme to organize info into meaningful categories so that it can be easily accessed; "tag" each knowledge object for classification so it can be easily retrieved

Robotics

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

Expert systems

The first large-scale applications of AI in business and other organizations, accounting for 20% of all AI systems today; they capture the knowledge of individual experts in an org via in-depth interviews and represent that knowledge as sets of rules; made in the 1970's

Supervised learning

The system is "trained" by providing specific examples of desired inputs and outputs identified by humans in advance; used by nearly all machine learning today; this type is used in autonomous vehicles

Virtual reality (VR) systems

Use interactive graphics software to create computer-generated simulations that are so close to reality that users almost believe they are participating in a real-world situation; user has clothing and equipment that records their movements and transmits the info to computer

Knowledge

When a firm expends additional resources to discover patterns in information; can reside in email, voice mail, graphics, unstructured docs, as well as structured docs; has a location and is "sticky" and not universally applicable or easily moved

3-D printing

When machines make solid objects layer by layer, from specifications in a digital file; aka "additive manufacturing"

Pattern detection programs

When neural networks learn patterns from large quantities of data by sifting through the data and finding pathways through the network of thousands of neurons; process is repeated millions of times till the most successful pathways are identified

Organizational learning

When organizations learn to adjust their behavior to reflect that learning by creating new business processes and by changing patterns of management decision making; orgs that respond to environments survive longer than orgs that have poor learning