Computer Science 102: Fundamentals of Information Technology Ch 7. Knowledge Management & Artificial Intelligence

knowledge management

• the concept of finding, gathering, assessing, organizing, and sharing information or knowledge

• the four steps are gather, classify, analyze, and share

classifying

information can be filtered, cataloged, and even linked to other pieces of information

What happens during the last step in knowledge management?

1. It is shared.

2. It is generated.

3. It is placed into categories.

4. It is analyzed.

It is shared.

How many major steps are in the process of knowledge management?

1. 1

2. 5

3. 3

4. 4

4

The process of finding, gathering, assessing, organizing, and sharing information is known as what?

1. Knowledge technology

2. Information technology

3. Information management

4. Knowledge management

Knowledge management

What is the first step in knowledge management?

1. Classify

2. Share

3. Gather

4. Analyze

Gather

What happens during the classification step?

1. The information is collaborated.

2. The information is gathered from within the company.

3. The information is organized.

4. The information is given to departments within the company.

The information is organized.

Data

basic facts or values

Information

collection of facts organized so that they have additional value

Knowledge

awareness and understanding of information and the ways the information can be made useful to support a task or make a decision

Knowledge Management System (KMS)

is an organized collection of people, procedures, software, databases and devices to create, store, share, and utilize the knowledge and experience of an organization

Which of the following is NOT a typical approach to sharing knowledge within an organization?

1. Policies, procedures, and guidelines

2. Communities of practice

3. Collaborative software

4. A Wikipedia search

5. Meeting software

A Wikipedia search

Which of the following approaches is NOT typically used in knowledge management software?

1. Graphical representation

2. Tagging

3. Statistical analysis

4. Content management system

5. Taxonomies

Statistical analysis

Which of the following is an example of the average score that a class of students in a particular school received on a math exam?

1. Tacit knowledge

2. Data

3. Information

4. Explicit knowledge

Information

Which of the following is a reason for a company to implement a knowledge management system?

1. There is leftover budget money at the end of the year, and the IT department thinks a new software program is the way to spend it.

2. Some of the company's policies and procedures will be revised in the coming year.

3. A new Human Resources manager who is a recent, external hire is telling everyone that a KMS is the way to go and that she used one at her old company.

4. An early retirement program was offered, and many senior managers across the organization are interested in taking advantage of it.

An early retirement program was offered, and many senior managers across the organization are interested in taking advantage of it.

Knowledge that is not easy to measure and difficult to formalize is referred to as _____.

1. tacit knowledge

2. informal knowledge

3. explicit knowledge

4. inherent wisdom

5. textbook knowledge

tacit knowledge

explicit

information in tangible forms

implicit

information that does not originate in a tangible form but can be transferred into a tangible form

tacit

information that is hard to capture in a tangible form

knowledge management

a series of steps that include identifying, collecting, storing, and sharing explicit, implicit and tacit information

intranet

an internal site with stored information about virtually anything related to the organization

organizational KM theory

focuses on organizational structures and how an organization is designed culturally and hierarchically to manage knowledge and knowledge processes

ecological KM theory

focuses on people, relationships and learning communities

techno-centric theory

• focuses on technology and the process of designing technology enablers to help facilitate

• the flow of knowledge and the storage of information

lessons learned databases

a storage place used to capture knowledge that has been obtained from employees that would not usually be in an explicit or written form

after action reviews

sessions that include team members, a facilitator, and a scribe

storytelling

the process by which a person or team of people attempt to gather tacit knowledge (information not in written form) and transfer that knowledge into explicit knowledge (written form)

cross-project learning

a strategy many consultants and project managers use to transfer knowledge gained from one project to another project

knowledge mapping

a map or guide used by all employees within a company to direct them to areas where there are pockets of information

Why is knowledge management important?

1. To capture all information about the organization on the company's Intranet website

2. It is important for leaders to know everything that happens within their organization.

3. Knowledge management is a theory and is not important.

4. Knowledge management is about making the right information available to the right people.

Knowledge management is about making the right information available to the right people.

The knowledge management strategy used to capture information obtained from observations, perception and feedback from team members after a project is complete is called a(n) _____.

1. Knowledge mapping

2. Techno-centric theory

3. After action review

4. Job shadow

After action review

What is knowledge management?

1. A series of steps that include identifying, collecting, storing, and sharing explicit, implicit and tacit information

2. Transferring written information into verbal information within an organization

3. Job shadowing another person within the company

4. Explicit knowledge from employees

A series of steps that include identifying, collecting, storing, and sharing explicit, implicit and tacit information

What is tacit knowledge, and why is it important in knowledge management practices?

1. Tacit knowledge is implicit knowledge, and it is important because it is in written form and can be used in corporate training.

2. Tacit knowledge is information in tangible written form important in knowledge management for use on Share Point websites.

3. Tacit knowledge is information that is hard to capture in a tangible form. It is important in knowledge management because necessary information may exist in the minds of experts that is necessary to document for others to learn.

4. Tacit knowledge is information gained by job shadowing and is important because leaders can use the information from tacit knowledge to increase revenue.

Tacit knowledge is information that is hard to capture in a tangible form. It is important in knowledge management because necessary information may exist in the minds of experts that is necessary to document for others to learn.

What is an organizational knowledge management theory?

1. The primary focus of organizational structure and how an organization is designed culturally and hierarchically, to manage knowledge and knowledge processes

2. The interaction of people within organizations and the internal and external factors that draw people together to share knowledge

3. Discussions within learning communities

4. An ecological theory

The primary focus of organizational structure and how an organization is designed culturally and hierarchically, to manage knowledge and knowledge processes

Artificial Intelligence (AI)

people, hardware, software, data, and knowledge used to develop computer systems that demonstrate characteristics of intelligent behavior

Expert Systems

make it possible for a novice to perform at the level of an expert in very specific situations

The component of an expert system that looks for information and relationships in the knowledge base to provide answers, predictions, and suggestions is called a/an:

1. Knowledge base.

2. Inference engine.

3. Interference engine.

4. Rule set.

Inference engine.

Which of the following is NOT a component of intelligent behavior?

1. Determining what is important.

2. Handling simple situations.

3. Reacting quickly and correctly to new situations.

4. Applying knowledge gained from experiences.

Handling simple situations.

Which of the following is NOT an application of artificial intelligence?

1. Transaction processing.

2. Natural language processing.

3. Learning systems.

4. Robotics.

Transaction processing.

What are three critical components of an expert system?

1. Expertise, rules, and decisions.

2. Knowledge base, inference engine, and user interface.

3. Hardware, software and data.

4. Domain experts, knowledge engineers, and knowledge users.

Knowledge base, inference engine, and user interface.

How do artificial intelligence systems replicate intelligent behavior?

1. By replicating human decision-making for certain types of well-defined problems.

2. By making it possible to manipulate data in any type of database management system.

3. By simulating the reasoning and decision-making of experts in very specific situations.

4. By performing simple tasks very quickly.

By replicating human decision-making for certain types of well-defined problems.

artificial intelligence

• sometimes abbreviated as AI

• arm of computer science that focuses on enabling computers to take on human characteristics, perform people tasks, and think human thoughts

reactive machine

• study a chess board, anticipate moves, and then choose its next move from all the possible outcomes

• singular purpose or a specialized duty

limited memory

allows machines to look at past information and apply it to current situations

theory of mind

machines that are truly interactive, that register human thoughts and emotions and respond with their own emotions or behaviors

self-awareness

highest stage of artificial intelligence development and are the most like humans

What is a reactive machine capable of doing?

1. Being programmed for a singular task

2. Mimicking human emotion

3. Adjusting its reaction based on the situation

4. Navigating a self-driving vehicle

Being programmed for a singular task

What is artificial intelligence?

1. Enabling computers to take on human characteristics

2. A type of computer software that allows printing of 3-D objects

3. Using a computer to complete a quiz or survey

4. Faking your ability to handle a task at work

Enabling computers to take on human characteristics

What is the primary drawback of a limited memory machine?

1. Its inability to learn from its experiences

2. Its focus on completing only a singular function

3. Its function to change its emotion based on the situation

4. Its ability to register human emotion

Its inability to learn from its experiences

Self-driving cars are an example of what type of artificial intelligence capabilities?

1. Self-awareness

2. Theory of mind

3. Reactive machines

4. Limited memory

Limited memory

How are self-aware robots and machines most like humans?

1. They can perform basic job functions

2. They have awareness

3. They resemble the human face

4. They can be programmed to do one task

They have awareness

artificial intelligence

the area of study within computer science that focuses on mimicking human thinking and behavior within the computers we use

LISP

a computer programming language

In LISP and artificial intelligence, self-modifying programs are:

1. Sought-after

2. Unwise

3. Undesirable

4. Dangerous

Sought-after

Artificial intelligence is the area of computer science that focuses on:

1. There is no such thing as artificial intelligence.

2. Replacing human thinking with animal thinking

3. Mimicking human thinking and behavior

4. Replacing human thinking with machine thinking

Mimicking human thinking and behavior

Which of the following is NOT a characteristic of LISP?

1. Created in 1958

2. Oldest computer language in existence

3. Operates on data and programs

4. Designed by John McCarthy

Oldest computer language in existence

LISP is an acronym that stands for:

1. List partitioning

2. Language instance symbolic programming

3. List processing

4. Limited interactive system programming

List processing

How likely is it that MIT had an effect on LISP being used in artificial intelligence?

1. Unlikely

2. None of the answers are correct

3. Only Slightly Possible

4. Impossible

None of the answers are correct

ChatGPT

• an AI chatbot that can fill in the blanks and answer a wide range of questions

• stands for Chat Generative Pretrained Transformer

large language model (LLM)

• a neural network that has been trained on data from the internet

• uses deep learning, it generates unique responses

Which of the following is not an appropriate ask for ChatGPT?

1. SQL statements for a database query

2. A potential outline for a novel

3. The script for a new movie

4. How to circumvent privacy laws

How to circumvent privacy laws

ChatGPT and other AI chatbots use this technology to generate responses.

1. Deep learning

2. Python

3. Git

4. Data mapping

Deep learning

You suspect that someone has used ChatGPT to come up with an essay response. Which tool would you most likely use to determine the likelihood of such usage?

1. OpenAI

2. Duplichecker

3. PlagScan

4. GPTZero

GPTZero

After generating a response from ChatGPT, what should your next step be?

1. Review it for accuracy

2. Report it to OpenAI

3. Re-run the same text back through

4. Publish it

Review it for accuracy

At the heart of ChatGPT is a(n) _____

1. MySQL database

2. Large language model

3. GitHub platform

4. Webcrawler

Large language model

ethics

moral principles guiding behavior

artificial intelligence (AI)

creating machines with human-like intelligence

singularity

the time when machines are more intelligent than their human creators and there is a runaway growth of machines

algorithms

• a set of sequential rules to be followed in problem-solving

• if the creator has any inherent biases or is judgmental in some way, those biases can be built into the machine

roboethics

focuses on what rules need to be created for robots to behave ethically and also on rules for the design of ethical robots

_____ has come to represent a time when machines become more intelligent than humans and begin to grow at an accelerated rate.

1. Singularity

2. Prosperity

3. Progress

4. The machine age

Singularity

Machines that can do things like speech recognition, visual perception, and decision making are said to have what?

1. Programmable memory

2. Artificial intelligence

3. Machine language programming

4. Machine learning

Artificial intelligence

An entity can be said to have _____ when it can be wronged or has feelings of some sort.

1. moral status

2. physical status

3. artificial intelligence

4. viability

moral status

A sequential set of rules that can be programmed into a machine to solve a problem is known as what?

1. Guidance directives

2. Machine language

3. An algorithm

4. An instruction set

An algorithm

The field of study called _____ has to do with creating rules for ethical robot behavior and designing ethical robots.

1. roboethics

2. singularity research

3. robot programming

4. AI ethics

roboethics

Machine Learning

• a type of intelligence technology that provides computers with advanced abilities to execute processes without being specifically programmed to do so

• Supervised Machine Learning

• Unsupervised Machine Learning

Supervised Machine Learning

a set of training programs and data with which it can train itself and subsequently make accurate inferences as it encounters new data sets or unfamiliar situations

Unsupervised Machine Learning

geared towards facilitating the computer to map out patterns and relationships by itself from randomly presented data and make realistic predictions to achieve its goal

Artificial Intelligence

a branch of computer science that constitutes underlying technology that enables computers to simulate human intelligence

Artificial Intelligence is _____

1. is a branch of computer science that renders supervision to expert machines

2. a branch of computer science that constitutes underlying technology which enables computers to simulate human intelligence

3. a branch of computer algorithms that facilitates an expert machine make accurate predictions

4. is a branch of computer science constituting underlying technology that governs expert machines

a branch of computer science that constitutes underlying technology which enables computers to simulate human intelligence

Components of artificial intelligence include _____

1. upgrading, problem-solving, reasoning, and acting.

2. designing, sensing, language understanding, and problem-solving

3. sensing, language understanding, problem-solving, reasoning, and acting

4. problem defining, acting, designing, and program updating

sensing, language understanding, problem-solving, reasoning, and acting

The process of an expert machine having the abilities to analyze and map relationships in an unfamiliar or random data set is _____

1. unsupervised software intelligence

2. unsupervised machine learning

3. supervised artificial intelligence

4. supervised machine learning

unsupervised machine learning

Supervised machine learning is _____

1. is a group of software experts used to constantly monitor intelligent machine

2. a set of training programs a computer can use to train itself and later use to make accurate inferences as it encounters new data sets or unfamiliar situations.

3. is computer aided training

4. a set of training programs and data which the software developer can use to make accurate inferences as the expert machine encounters new data sets or unfamiliar situations.

a set of training programs a computer can use to train itself and later use to make accurate inferences as it encounters new data sets or unfamiliar situations.

Which of the following statements about machine learning is TRUE?

1. Machine learning is the intelligent technology an expert system uses to make accurate predictions

2. Machine learning is the intelligence technology that provides computers with advanced abilities to execute processes without being specifically programmed to do so

3. Machine learning is the intelligence technology developed for expert machines to facilitate the learning processes of various tasks

4. Machine learning is the intelligence technology that ensure the expert computer responds accurately to its algorithm

Machine learning is the intelligence technology that provides computers with advanced abilities to execute processes without being specifically programmed to do so

natural language

a language employed by people to communicate with each other, hence, a language that has naturally evolved

Natural language processing (NLP)

allows a machine to understand an ambiguous natural language

training data set

gathers examples of similar situations and the correct behavior

actual learning

Builds a model capable of inferring through probability what makes a behavior correct

testing data set

applies the built model to new situations and guess the correct behavior for each one

Which of the options is not a NLP application?

1. Named entity recognition

2. Sentiment analysis

3. Translation from English to French

4. Translation from C++ to Java

Translation from C++ to Java

Mark the only sentence that is true.

1. Machine learning is a subdivision of deep learning.

2. NLP is the acronym for Neural Language Processing.

3. Shallow learning is the simplest form of deep learning.

4. Deep learning is a subdivision of machine learning.

Deep learning is a subdivision of machine learning.

Which are the three steps of deep learning?

1. Gather a testing set, build a model using random forests, generate a learner.

2. Gather a testing set, build a deeper, and use neural networks.

3. Gather a training set, build a model using neural networks, apply the model to a testing set.

4. Gather a training set, build a deeper set, and generate a random forests learner.

Gather a training set, build a model using neural networks, apply the model to a testing set.

Deep learning allows dealing with much more information than other approaches. Mark the option that makes it interesting for NLP applications.

1. Machine learning cannot be applied to NLP.

2. Texts may be represented by forms more complex than simple bag of words.

3. The traditional machine learning task regression is no longer necessary.

4. Neural language processing needs lots of data.

Texts may be represented by forms more complex than simple bag of words.

Which of the following machine learning algorithms is the base for deep learning?

1. Boosting

2. Support Vector Machines

3. Neural Networks

4. Random Forests

Neural Networks