New Microsoft Word Document

Which one of these ways is NOT how AI learns?

Supervised Learning

Proactive Learning

Unsupervised Learning

Reinforcement Learning

Which of the following are attributes of Weak or Narrow AI?

Make decisions based on programmed algorithms and training data in a specific domain

Learn new tasks to solve new problems

Teach itself new strategies in a variety of domains

Perform specific tasks

What is the role that philosophy plays in AI?

Determine viable learning models and measure performance

Provide guidance on ethical considerations

Determine the application in software and hardware

In which of the following ways can Artificial Intelligence (AI) be defined?

AI is an augmented intelligence, whihc helps human experts make evidence-based informed decisions while the machines do the time-consuming work

AI is the application of computing to help machines solve problems in intelligent ways without humans having to hard code the desired outcomes manually

AI is about giving machines the intelligence and capabilities to think like humans so they can do every job that a human can

Which of these statements describes AI accurately from the speakers point of view?

AI will be the downfall of humanity

AI is human intelligence simulated wholly within a computer

AI enables computers to understand certain kinds of data that they could not have understood before, such as natural language, auditory and visual data

Which of the following are applications of Computer Vision?

Detecting fraudulent transactions Un-selected is correct

Detecting fraudulent transactions is not selected.This is correct.

Finding symptoms in X-Ray and MRI scans Correct

Computer Vision make it possible to find symptoms in X-Ray and MRI scans and even detect cancerous moles in skin images.

Finding symptoms in X-Ray and MRI scans is selected.This is correct.

Computer Vision make it possible to find symptoms in X-Ray and MRI scans and even detect cancerous moles in skin images.

On-demand online tutors Un-selected is correct

On-demand online tutors is not selected.This is correct.

Self-driving cars Correct

Computer Vision is the reason self-driving cars can steer their way on streets and highways and avoid hitting obstacles.

Advances in speech-to-text technology are the reason speech-impaired patients are able to speak in their own voice.

True

False Correct

AI-powered advances in speech synthesis (text-to-speech rather than speech-to-text) have made it possible for machines to re-create a specific human's voice. One of the applications of this technology is to help speech-impaired patients talk in their real voice in place of a computerized voice when they type what they want to say.

Which of the following aspects involved in converting the stethoscope into a digital device to support patient diagnoses involves the use of AI?

Inserting a digitizer into the stethoscope tube to convert the analog sound of the heart beat into a digital signal

Amplifying the sound of heart beats so the physician can detect patterns more easily

Using a machine learning model trained with previous diagnosis results to assist physicians with their current diagnosis Correct

Using a machine learning algorithm trained with previous diagnosis data to assist physicians with their findings is a use of AI technology.

Which of these is NOT an application of AI?

Precise disease diagnoses and prescribing treatments independently Correct

In Healthcare, while AI is being used to support doctors arrive at more accurate preliminary diagnoses, it is not yet being used to make precise disease diagnoses independently.

Precise disease diagnoses and prescribing treatments independently is selected.This is correct.

In Healthcare, while AI is being used to support doctors arrive at more accurate preliminary diagnoses, it is not yet being used to make precise disease diagnoses independently.

Classifying rock samples to identify best places to drill for oil

Collaborative Robots helping humans lift heavy containers

AI is being used in the recovery of patients who have suffered a neurological trauma by triggering new neural pathways to form in their brain using robotic devices to trigger corresponding movements in the body.

False

True Correct

Different movements of the human body correspond to specific parts of the brain that control these movements. By creating massive data sets of information of how people move and how that corresponds to different areas of the brain, AI-powered robots are able to trigger specific movements in the human body which in turn create new neural pathways in the brain.

In which of these applications did Watson analyse emotional themes and categorize them based on varied human emotions?

Watson collaborating with ESPN to share insights that help Fantasy App users make better decisions to win their weekly matchups

Watson teaming up with the Academy to analyze Grammy nominated song lyrics over a 60 year period and categorize them Correct

Watson analyzed Grammy nominated song lyrics over the last 60 years to identify the emotional themes in music and categorize them on the basis of emotions such as joy, sadness, and other emotions.

Watson teaming up with the Academy to analyze Grammy nominated song lyrics over a 60 year period and categorize them is selected.This is correct.

Watson analyzed Grammy nominated song lyrics over the last 60 years to identify the emotional themes in music and categorize them on the basis of emotions such as joy, sadness, and other emotions.

Watson playing Jeopardy to win against two of its greatest champions, Ken Jennings and Brad Rutter

Graded: What is AI? Applications and Examples of AI Total points 9

1.Question 1

Which of the following is NOT a good way to define AI? 1 point

AI is Augmented Intelligence and is not intended to replace human intelligence rather extend human capabilities

AI is the use of algorithms that enable computers to find patterns without humans having to hard code them manually

AI is all about machines replacing human intelligence.

AI is the application of computing to solve problems in an intelligent way using algorithms.

2.Question 2

Which of the following is an attribute of Strong or Generalized AI? 1 point

Operate with human-level consciousness

Can perform specific tasks, but cannot learn new ones

Cannot teach itself new strategies

Perform independent tasks

3.Question 3

AI is the fusion of many fields of study. Which of these fields, along with Computer Science, plays a role in the application of AI? 1 point

All responses are correct

Mathematics

Statistics

Philosophy

4.Question 4

Which of these is NOT a current application of AI? 1 point

Making precise patient diagnosis and prescribing independent treatment

Self-Driving vehicles utilizing Computer Vision to navigate around objects

Collaborative Robots helping humans lift heavy containers

Classifying rock samples to identify best places to drill for oil

5.Question 5

Natural Language AI algorithms that learn by example are the reason we can talk to machines and they can talk back to us. 1 point

True

False

6.Question 6

Advances in the field of Computer Vision make which of the following possible? 1 point

On-demand online tutors

Real-time transcription

Detecting fraudulent transactions

Detecting cancerous moles in skin images

7.Question 7

Which of these is currently NOT an application of Collaborative Robots or Cobots? 1 point

Robots helping humans lift heavy containers

Robots helping move items on shelves for stocking purposes

Robots assisting or replacing humans in jobs that may be dull, dangerous, ineffective or inefficient when done by humans

Personal use in the home such as doing the laundry and cooking for example

8.Question 8

Which of the following aspects involved in converting the stethoscope into a digital device to support patient diagnoses involves the use of AI? 1 point

Sending digital signals to a mobile device with a machine learning app via bluetooth

Graphing heart beat data on the mobile device allowing a physician to spot trends

An app on the mobile device that applies learnings from previous diagnosis data to assist the physicians in their current diagnoses

Inserting a digitizer into the stethoscope tube to convert the analog sound of the heart beat into a digital signal

9.Question 9

Which of the following are applications of Artificial Intelligence in action?

A. IBM Watson utilizing its information retrieval capabilities to provide technical information to oil and gas company workers.

B. Watson analyzing Grammy nominated song lyrics over a 60-year period and categorizing them based on their emotions.

C. Assisting patients with neurological damage by detecting patterns in massive movement related datasets and using robots to trigger specific movements in the human body to create new neural pathways in the brain.

D. Law enforcement authorities using facial recognition algorithms to identify suspects in multiple streams of video footage 1 point

Only options A, B, and C are correct

None of the options are correct

Only option A is correct

All of the options are correct I, Sai Maung Maung Zaw, understand that submitting work that isn’t my own may result in permanent failure of this course or deactivation of my Coursera account.

Week 2 Cognitive Systems can interpret data to generate hypotheses about what it means

True Correct

Cognitive systems use processes similar to the decision-making process of humans to interpret and generate hypotheses about the information they read.

True is selected.This is correct.

Cognitive systems use processes similar to the decision-making process of humans to interpret and generate hypotheses about the information they read.

False

Which of these statements is true?

Cognitive systems can derive mathematically precise answers following a rigid decision tree approach

Cognitive systems can understand the intent and context in which a word has been used Correct

Cognitive systems rely on natural language governed by rules of grammar, context, and culture, to understand the real intent and context of the user's language.

Cognitive systems can understand the intent and context in which a word has been used is selected.This is correct.

Cognitive systems rely on natural language governed by rules of grammar, context, and culture, to understand the real intent and context of the user's language.

Cognitive systems can only process neatly organized structured data

Cognitive systems require human intervention in order to to learn from their interactions with humans

Is the following an application of Machine Learning and AI: A machine that beats human in a game in which all rules and moves have been pre-programmed into the machine - true or false?

False Correct

Programming all rules and moves of a game is not a true application of AI, rather training the machine to learn from data and enabling it figure out the moves and strategies for winning is how Machine Learning works.

False is selected.This is correct.

Programming all rules and moves of a game is not a true application of AI, rather training the machine to learn from data and enabling it figure out the moves and strategies for winning is how Machine Learning works.

True

Data Science is a subset of AI that uses machine learning algorithms to extract meaning and draw inferences from data.

True

False Correct

Data Science is an interdisciplinary field encompassing the entire data processing methodology. While it uses AI techniques to derive insight from data, it is NOT a subset of AI.

Which of the following are attributes of Machine Learning?

Machine learning algorithms can be continuously trained and used in the future to predict values This should be selected

Machine learning algorithms can be continuously trained and used in the future to predict values is not selected.This is wrong. It should be selected.

In Machine Learning models, when we submit inputs, we get answers based on predefined rules Un-selected is correct

In Machine Learning models, when we submit inputs, we get answers based on predefined rules is not selected.This is correct.

Takes data and answers as input and use these inputs to create a set of rules that determine what the Machine Learning model will be This should be selected

Takes data and answers as input and use these inputs to create a set of rules that determine what the Machine Learning model will be is not selected.This is wrong. It should be selected.

Defines behavioral rules by comparing large data sets to find common patterns This should be selected

We can use reinforcement learning to teach a machine to play chess.

True Correct

Reinforcement learning relies on providing data and constraints and letting the model learn how to achieve desired results by trying different combinations of allowed actions, giving a reward or punishment depending on whether the decision was a good one. Reinforcement learning algorithms can teach a machine to play chess or even navigate an obstacle course.

True is selected.This is correct.

Reinforcement learning relies on providing data and constraints and letting the model learn how to achieve desired results by trying different combinations of allowed actions, giving a reward or punishment depending on whether the decision was a good one. Reinforcement learning algorithms can teach a machine to play chess or even navigate an obstacle course.

False

Which of the following are attributes of Classification?

Classification is the process of predicting the class of given data points Correct

Classification is the process of extracting features from data and classifying the results into one or more categories.

Classification is the process of predicting the class of given data points is selected.This is correct.

Classification is the process of extracting features from data and classifying the results into one or more categories.

Using classification models we extract features from data and classify results into multiple categories Correct

Classification is the process of extracting features from data and classifying the results into one or more categories.

Using classification models we extract features from data and classify results into multiple categories is selected.This is correct.

Classification is the process of extracting features from data and classifying the results into one or more categories.

Forms of classification include decision trees, support vector machines, logistic regression and random forests Correct

Classification is the process of extracting features from data and classifying the results into one or more categories.

Forms of classification include decision trees, support vector machines, logistic regression and random forests

is selected.This is correct.

Classification is the process of extracting features from data and classifying the results into one or more categories.

Classification models are built by looking at the relationships between features and results, where results are a continuous variable

Neural networks are the reason deep learning algorithms become more efficient as the datasets increase in volume.

True Correct

Neural networks are the reason deep learning algorithms can continuously learn on the job and improve the quality and accuracy of results as datasets increase in volume over time.

True is selected.This is correct.

Neural networks are the reason deep learning algorithms can continuously learn on the job and improve the quality and accuracy of results as datasets increase in volume over time.

False

Which of the following are attributes of Perceptrons?

An activation function determines how a node responds to its inputs Correct 

Perceptrons are single-layered neural networks consisting of input nodes connected directly to an output node. Input layers forward the input values to the next layer, by means of multiplying by a weight and summing the results. An activation function determines how a node responds to its inputs and is a critical component to the success of a neural network. An activation function determines how a node responds to its inputs is selected.This is correct. Perceptrons are single-layered neural networks consisting of input nodes connected directly to an output node. Input layers forward the input values to the next layer, by means of multiplying by a weight and summing the results. An activation function determines how a node responds to its inputs and is a critical component to the success of a neural network.

Each layer of neurons conducts a mathematical operation on the output of the previous layer Un-selected is correct  Each layer of neurons conducts a mathematical operation on the output of the previous layer is not selected.This is correct.

Perceptrons are single-layered neural networks consisting of input nodes connected directly to an output node Correct  Perceptrons are single-layered neural networks consisting of input nodes connected directly to an output node. Input layers forward the input values to the next layer, by means of multiplying by a weight and summing the results. An activation function determines how a node responds to its inputs and is a critical component to the success of a neural network. Perceptrons are single-layered neural networks consisting of input nodes connected directly to an output node is selected.This is correct. Perceptrons are single-layered neural networks consisting of input nodes connected directly to an output node. Input layers forward the input values to the next layer, by means of multiplying by a weight and summing the results. An activation function determines how a node responds to its inputs and is a critical component to the success of a neural network.

Input layers forward the input values to the next layer by means of multiplying by a weight and summing the results Correct  Perceptrons are single-layered neural networks consisting of input nodes connected directly to an output node. Input layers forward the input values to the next layer, by means of multiplying by a weight and summing the results. An activation function determines how a node responds to its inputs and is a critical component to the success of a neural network. This multi-layered neural network makes use of information in long sequences, and perform the same task on every element of the sequence.

Convolutional Neural Networks

Perceptrons

Recurrent Neural Networks Correct  Recurrent Neural Networks or RNNs are multi-layered neural networks that perform the same task for every element of a sequence, with prior outputs feeding subsequent stage inputs. RNNs make use of information in long sequences, each layer of the network representing the observation at a certain time. Which of the following are attributes of backpropagation in Neural Networks?

The process reduces errors over time by determining how far a given output is from the desired output Correct  Backpropagation uses an error function to determine how far the given output is from the desired output, and over time, it makes adjustments in order to reduce the errors.

The process reduces errors over time by determining how far a given output is from the desired output is selected.This is correct. Backpropagation uses an error function to determine how far the given output is from the desired output, and over time, it makes adjustments in order to reduce the errors.

The process works on the basis of reward and punishment depending on how close the given output is to the desired output Un-selected is correct  The process works on the basis of reward and punishment depending on how close the given output is to the desired output is not selected.This is correct.

An error function determines how far the given output is from the desired output Correct  Backpropagation uses training datasets to match known inputs to desired outputs. Using an error function, it then determines how far the given output is from the desired output. An error function determines how far the given output is from the desired output is selected.This is correct. Backpropagation uses training datasets to match known inputs to desired outputs. Using an error function, it then determines how far the given output is from the desired output.

Backpropagation uses training datasets to train neural networks to match known inputs to desired outputs Correct  Backpropagation uses a set of training data that match known inputs to desired outputs. The inputs are plugged into the network and outputs are determined.

Which of these statements is true? 1 point

Cognitive systems can learn from their successes and failures

Cognitive systems can only process neatly organized structured data

Cognitive systems can only translate small volumes of audio data into their literal text translations at massive speeds

Cognitive systems can derive mathematically precise answers following a rigid decision tree approach Incorrect Conventional computing systems process neatly organized structured data such as what is stored in a database while Cognitive systems can process structured and unstructured data to discern meaning from the semantics of the written material. 2.Question 2

Which of these statements is true? 1 point

Data Science is a subset of AI that uses machine learning algorithms to extract meaning and draw inferences from data

Deep Learning is a specialized subset of Machine Learning that uses layered neural networks to simulate human decision-making

AI is the subset of Data Science that uses Deep Learning algorithms on structured big data

Artificial Intelligence and Machine Learning refer to the same thing since both the terms are often used interchangeably

3.Question 3

Which of the following is NOT an attribute of Machine Learning? 1 point

Takes data and answers as input and uses these inputs to create a set of rules that determine what the Machine Learning model will be

Machine Learning defines behavioral rules by comparing large data sets to find common patterns

Machine Learning models can be continuously trained

Takes data and rules as input and uses these inputs to develop an algorithm that will give us an answer

4.Question 4

Which of the following is NOT an attribute of Unsupervised Learning? 1 point

It is useful for finding hidden patterns and or groupings in data and can be used to differentiate normal behavior with outliers such as fraudulent activity

It is useful for clustering data, where data is grouped according to how similar it is to its neighbors and dissimilar to everything else

Takes data and rules as input and uses these inputs to develop an algorithm that will give us an answer

The algorithm ingests unlabeled data, draws inferences, and finds patterns from unstructured data

5.Question 5

Which of the following is an attribute of Supervised Learning? 1 point

Tries its best to maximize its rewards by trying different combinations of allowed actions within the provided constraints

Relies on providing the machine learning algorithm human-labeled data - the more samples you provide, the more precise the algorithm becomes in classifying new data

Relies on providing the machine learning algorithm unlabeled data and letting the machine infer qualities

Relies on providing the machine learning algorithm with a set of rules and constraints and letting it learn how to achieve its goals

6.Question 6

Which of the following statements about datasets used in Machine Learning is NOT true? 1 point

Testing data is data the model has never seen before and is used to evaluate how good the model is

Validation data subset is used to validate results and fine-tune the algorithm's parameters

Training data is used to fine-tune algorithm’s parameters and evaluate how good the model is

Training subset is the data used to train the algorithm

7.Question 7

When creating deep learning algorithms, developers configure the number of layers and the type of functions that connect the outputs of each layer to the inputs of the next. 1 point

True

False

8.Question 8

Which of the following fields of application for AI can be used at the airport to flag weapons within luggage passing through the X-ray scanner? 1 point

Speech

Chatbots

Computer Vision

Natural Language

9.Question 9

Which of these activities is not required in order for a neural network to synthesize human voice? 1 point

Deconstruct sentences to decipher the context of use

Ingest numerous samples of a person’s voice until it can tell whether a new voice sample belongs to the same person

Generate audio data and run it through the network to see if it validates it as belonging to the subject

Continue to correct the sample and run it through the classifier, repetitively, till an accurate voice sample is created Incorrect

The process of generating natural voice starts with a neural network ingesting samples of a person’s voice until it can tell whether a new voice sample belongs to the same person. Then, a second neural network generates audio data and runs it through the first network to see if it validates it as belonging to the subject, which it does till such time that it generates an accurate voice sample.

10.Question 10

Which one of these ways is NOT how AI learns? 1 point

Supervised Learning

Proactive Learning

Reinforcement Learning

Unsupervised Learning I, Sai Maung Maung Zaw, understand that submitting work that isn’t my own may result in permanent failure of this course or deactivation of my Coursera account. Graded: AI Concepts, Terminology, and Application Areas Latest Submission Grade 70%

1.Question 1

Which of these statements is true? 0 / 1 point

Cognitive systems can learn from their successes and failures

Cognitive systems can only process neatly organized structured data

Cognitive systems can only translate small volumes of audio data into their literal text translations at massive speeds

Cognitive systems can derive mathematically precise answers following a rigid decision tree approach Incorrect

Conventional computing systems process neatly organized structured data such as what is stored in a database while Cognitive systems can process structured and unstructured data to discern meaning from the semantics of the written material.

2.Question 2

Which of these statements is true? 1 / 1 point

Data Science is a subset of AI that uses machine learning algorithms to extract meaning and draw inferences from data

Deep Learning is a specialized subset of Machine Learning that uses layered neural networks to simulate human decision-making

AI is the subset of Data Science that uses Deep Learning algorithms on structured big data

Artificial Intelligence and Machine Learning refer to the same thing since both the terms are often used interchangeably Correct

Deep Learning enables machines to continuously learn on the job and improve the quality and accuracy of results by determining whether decisions were correct.

3.Question 3

Which of the following is NOT an attribute of Machine Learning? 1 / 1 point

Takes data and answers as input and uses these inputs to create a set of rules that determine what the Machine Learning model will be

Machine Learning defines behavioral rules by comparing large data sets to find common patterns

Machine Learning models can be continuously trained

Takes data and rules as input and uses these inputs to develop an algorithm that will give us an answer Correct

Machine Learning algorithms are trained with large sets of datasets to determine the relationships between inputs and desired results to build the machine learning models.

4.Question 4

Which of the following is NOT an attribute of Unsupervised Learning? 1 / 1 point

It is useful for finding hidden patterns and or groupings in data and can be used to differentiate normal behavior with outliers such as fraudulent activity

It is useful for clustering data, where data is grouped according to how similar it is to its neighbors and dissimilar to everything else

Takes data and rules as input and uses these inputs to develop an algorithm that will give us an answer

The algorithm ingests unlabeled data, draws inferences, and finds patterns from unstructured data Correct

This statement is not an attribute of either Machine Learning or Unsupervised Learning. Machine Learning techniques such as unsupervised learning are not fed rules. Rather they determine the rules from data.

5.Question 5

Which of the following is an attribute of Supervised Learning? 0 / 1 point

Tries its best to maximize its rewards by trying different combinations of allowed actions within the provided constraints

Relies on providing the machine learning algorithm human-labeled data - the more samples you provide, the more precise the algorithm becomes in classifying new data

Relies on providing the machine learning algorithm unlabeled data and letting the machine infer qualities

Relies on providing the machine learning algorithm with a set of rules and constraints and letting it learn how to achieve its goals Incorrect

Unsupervised Learning provides the algorithm unlabeled data, letting it find patterns in the data by itself.

6.Question 6

Which of the following statements about datasets used in Machine Learning is NOT true? 1 / 1 point

Testing data is data the model has never seen before and is used to evaluate how good the model is

Validation data subset is used to validate results and fine-tune the algorithm's parameters

Training data is used to fine-tune algorithm’s parameters and evaluate how good the model is

Training subset is the data used to train the algorithm Correct

Training data is used to train the algorithm. It is the Validation data that is used to fine-tune algorithm’s parameters and evaluate how good the model is.

7.Question 7

When creating deep learning algorithms, developers configure the number of layers and the type of functions that connect the outputs of each layer to the inputs of the next. 1 / 1 point

True

False Correct

Deep Learning algorithms rely on several layers of processing units, or neurons, where each layer passes on its output to the next layer, which processes it and passes it onto the next. The number of layers and the types of functions that connect the outputs of each layer to the inputs of the next are configured by developers.

8.Question 8

Which of the following fields of application for AI can be used at the airport to flag weapons within luggage passing through the X-ray scanner? 1 / 1 point

Speech

Chatbots

Computer Vision

Natural Language

Correct

Computer Vision enables machines to interpret digital images and video sequences and perform tasks like object identification.

9.Question 9

Which of these activities is not required in order for a neural network to synthesize human voice? 0 / 1 point

Deconstruct sentences to decipher the context of use

Ingest numerous samples of a person’s voice until it can tell whether a new voice sample belongs to the same person

Generate audio data and run it through the network to see if it validates it as belonging to the subject

Continue to correct the sample and run it through the classifier, repetitively, till an accurate voice sample is created Incorrect

The process of generating natural voice starts with a neural network ingesting samples of a person’s voice until it can tell whether a new voice sample belongs to the same person. Then, a second neural network generates audio data and runs it through the first network to see if it validates it as belonging to the subject, which it does till such time that it generates an accurate voice sample.

10.Question 10

Which one of these ways is NOT how AI learns? 1 / 1 point

Supervised Learning

Proactive Learning

Reinforcement Learning

Unsupervised Learning Correct

AI learns in three different ways - Supervised, Unsupervised, and Reinforcement Learning.

What are four key aspects of AI that help people perceive it as trustworthy?

Usability, Accountability, Customization, and Lack of Bias.

Transparency, Accessibility, Privacy, and Lack of Bias.

Accuracy, Accountability, Privacy, and Policing.

Transparency, Accountability, Privacy, and Lack of Bias. Correct

Transparency, Accountability, Privacy, and Lack of Bias will help people trust AI systems. VSDC

Jobs most vulnerable to replacement by AI are likely to have which of the following characteristics?

Variety

Repeatability Correct  Jobs which have repeatable tasks, whether in office work or manual work, are good candidates for being replaced by AI systems. Repeatability is selected.This is correct. Jobs which have repeatable tasks, whether in office work or manual work, are good candidates for being replaced by AI systems.

Creativity

Complexity AI assistant bots can answer calls, answer questions on websites, perform tasks on mobile phones, and help workers at call centers.

True Correct  AI assistant bots can answer calls, answer questions on websites, perform tasks on mobile phones, and help workers at call centers. True is selected.This is correct. AI assistant bots can answer calls, answer questions on websites, perform tasks on mobile phones, and help workers at call centers.

False How many jobs does the World Economic Forum expect will be lost to AI, Robotics, and Automation in the next few years?

40 million

10 million

75 million Correct  The World Economic Forum expects that 75 million jobs will be lost to AI, Robotics, and Automation in the next few years. 75 million is selected.This is correct. The World Economic Forum expects that 75 million jobs will be lost to AI, Robotics, and Automation in the next few years.

165 million

Graded: AI Issues, Ethics and Bias Total points 10

1.Question 1

Ethics in artificial intelligence is: 1 point

Something that we need to apply today.(correct)

Something that is not an issue.

Something that is entirely solved in current AI systems.

Something that somebody else is going to do in the future. Incorrect There are many ethical issues arising from the use of AI, including privacy and trust concerns. Current AI systems do not solve all of these issues.

2.Question 2

One approach that helps developers avoid unintentionally creating bias in AI systems is: 1 point

Using a wide variety of appropriately diverse data for training.(correct)

Using highly specific training data from a narrow range. Not using any training data. None of the above. Incorrect Using highly specific training data from a narrow range could unintentionally create bias in an AI system.

3.Question 3

Which of the following statements about IBM’s views on AI are correct? 1 point

Data and insights belong to the people and businesses who created them. Organizations that collect, store, manage, or process data have an obligation to handle it responsibly.

Knowing how an AI system arrives at an outcome is key to trust. To improve transparency, we should define how we build, deploy, and manage AI systems through scientific research.

Unbiased models and a spirit of diversity and inclusion are necessary to create fair AI systems, which can mitigate, rather than magnify, our existing prejudices.

AI can be applied to solve some of humanity’s most pervasive problems and create opportunity for all.

All of the above.

4.Question 4

Which of the following are examples of bias in an AI system? 1 point

AI systems in call centers providing context sensitive assistance to staff. Customers not being aware that they are interacting with a chatbot on a company website. Image recognition systems associating images of kitchens, shops, and laundry with women rather than men. Facial recognition systems performing well for individuals of all skin tones. Incorrect

AI systems in call centers providing context sensitive assistance to staff is not an example of bias. In this situation, the AI system is freeing time for the staff to focus on more complex and difficult matters. Incorrect Customers not being aware that they are interacting with a chatbot on a company website is not an example of bias, although it may be a concern. If the customer discovers that the person they thought they were interacting with is actually a chatbot, they may find it more difficult to trust the what the bot is saying, and the company as a whole 5.Question 5

There is concern that some jobs will be replaced by AI systems. Which of the following characteristics make a job a good candidate for replacement? 1 point

Has very varied, unpredictable tasks.

Requires innovative problem solving.

Features highly creative tasks.

Rules-based decision-making.

6.Question 6

Ethical concerns with AI systems are: 1 point Short term and easily addressed when developing new AI systems. Not genuinely troubling, and the concern of very few AI experts. Something that should be the concern of every AI developer, so they can be mitigated for as AI systems are developed.(correct) Something that can’t be mitigated for. Incorrect

There are many ethical concerns that can be mitigated for. Examples include ensuring the use of effective training data for facial recognition systems, making users aware that they are interacting with a chatbot when using an online banking system, and regularly auditing and testing AI systems to ensure the expected results are produced. 7.Question 7

What are some of the ethical concerns around artificial intelligence?

A. Racial, gender or other types of bias.

B. Loss of jobs due to AI replacing workers performing repetitive tasks.

C. Concern about the trustworthiness of decision-making supported by AI systems.

D. Privacy, for example, as human faces are photographed and recognized in public spaces. 1 point

Only options A and B are correct

Only options A, B, and D are correct

None of the options are correct

All of the options are correct(correct) Incorrect There are ethical concerns around artificial intelligence listed

8.Question 8

Which of the following NOT a way AI is being used to benefit humanity?

1 point

In healthcare, AI is being used to interpret scans for early detection of cancer, eye disease, and other problems.

Crime: to identify criminals before they commit a crime.

In healthcare, AI is being used to predict where the next outbreak of a disease will occur.

In agriculture, AI is being used to identify and recommend treatment for plant diseases.

9.Question 9

How many new opportunities and job roles does the World Economic Forum expect that AI will create in the next few years? 1 point

48 million

133 million

7 million

165 million

10.Question 10

What is a significant way in which developers of AI systems can guard against introducing bias? 1 point

Providing effective training data and performing regular tests and audits.

Using less varied AI systems and datasets.

Using government approved algorithms.

Using only examples from their own environment as training data. I, Sai Maung Maung Zaw, understand that submitting work that isn’t my own may result in permanent failure of this course or deactivation of my Coursera account. Final Assignment Part One Total points 15

1.Question 1 How would YOU define AI?

Your definition of AI can be similar or different from the ones given in the course. 5 points Your answer cannot be more than 10000 characters.

2.Question 2 Explain an application or use-case of AI that fascinates YOU.

It may or may not be something that is mentioned in the course. 5 points Your answer cannot be more than 10000 characters.

3.Question 3

Pick a specific industry or an aspect of our lives or society and describe how YOU think it will be impacted by Artificial Intelligence in future.

What you discuss may or may not be something that is mentioned in the course. 5 points Your answer cannot be more than 10000 characters. I, Sai Maung Maung Zaw, understand that submitting work that isn’t my own may result in permanent failure of this course or deactivation of my Coursera account. States to the replication of human intelligence in machines that are programmed to think like humans and mimic their actions.

Artificial intelligence is based on the principle that human intelligence can be defined in a way that a machine can easily mimic it and execute tasks, from the most simple to those that are even more complex. The goals of artificial intelligence (cognitive systems) include learning, reasoning, and perception.