INTRODUCTION TO AI.
Quick
Revision Notes
1. Intelligence is "the ability to perceive or infer information and
retain it as knowledge, which is then applied to adaptive behaviour in an
environment or contest."
2. humans have 9 types of intelligences-Spatial Visual Intelligence, Kinesthetic
Intelligence, Musical Intelligence, personal Intelligence, Existential
Intelligence, Naturalist Intelligence and Interpersonal intelligence.
3. All around us there are machines that work with artificial
intelligence. They are becoming an important part of our daily lives, allowing
us to easily complete some of the most complex and time-consuming tasks, simply
by pressing a button or simply by using a sensor.
4. Artificial intelligence is Intelligence displayed by machines, in
contrast to the natural intelligence displayed by humans or animals
5. The Al-enabled machines think algorithmically and execute what they
have been asked for intelligently.
6. Machine learning is the study of computer algorithms that can be
automatically improved using experience and data.
7. Al models can be broadly categorized into three domains: Data Science,
Computer Vision, Natural Language Processing.
8. Data sciences is a domain of Al related to data systems and processes,
in which the system collects numerous data, maintains data sets and derives
meaning/sense out of them.
9. Computer Vision is a domain of Al that depicts the capability of a
machine to get and analyze visual information. The entire process involves
image acquiring screening, analysing, identifying and extracting information
10. Natural
Language Processing is a branch of artificial intelligence that deals with the
interaction between computers and humans using the natural language.
11. Any bias
can transfer from the developer to the machine while the algorithm is being developed.
-Objective Questions-
Multiple Choice Questions (MCQs),
1. One of the biggest sources of data nowadays for
many big companies is…………………….
a. Cortana b.
Smartphones
c. Smartwatches d.
Computer Vision
2. One application of Computer Vision is
…………………………………..
a. Chatbot b.
Recommender System
c. Price Prediction d.
Facial Recognition
3. …………………… is a sub-field of Al that is enables
computers to understand and process human languages.
a. Machine Learning b.
Furry Lege
c. NLP d.
Expert Systems
4. The prejudiced assumptions made during the Al
algorithm development process or prejudices in the AI training
data is called
a. Al Bias b.
AI Prejudice
c. Al Preconception d.
AI Impairment
5. Siri and Alexa are examples of…………………………………..
a. Real time Assistants b.
Neural Networks
c. Virtual Assistants d.
Computer Vision
6. These autonomous vehicles combine Al software,
sensors, real-time cameras to ensure sale decisions on the road.
a. Computer Vision b.
Recommender System
c. Self Driving cars d.
Expert System
7. The very first humanoid robot sophisticated enough
to get citizenship by Saudi Arabia is……………..
a. KURI b. EVA
c. AIBO d.
SOPHIA
8. ………….. is the ability to perceive or infer
information, and to retain it as knowledge to be applied towards adaptive
behaviours within an environment or context.
a. NLP b.
Computer Vision
c. Data Science d. Intelligence
9. ………………………………is a domain of Al in which the system
collects numerous data, maintains data sets and derives
meaning/sense out of them.
a. Data Science b. Computer Vision
c. NLP d.
Expert Systems
10. Which of the following are types of human
intelligence?
a. Musical intelligence b. Existential Intelligence d. All
of these
c. Naturalist intelligence c. All of these
11. Al bias is due to bias of the………………………
a. Programmer b. Machine
c. Company building the model d.
None of these
12. What is NOT AIT
a. Siri b.
Google Maps
c. Semi-Automatic Washing Machine d. Face
recognition
13. Intelligence is defined as
a. Ability to interact with the real world b. Reasoning and planning
c. Learning and adaptation d. All of these
14. Unscramble the letters and find the correct answer
DATA+ ……………………. = AI MACHINE
a.
SAEGSEA b.
IMLHOMRGAT
d. RROER d.
TSMMCOE
15. Assertion(A): Neural networks are the
backbone of deep learning algorithms
Reason(R): Neural networks use vast amounts of data. [CBSE
Sample Paper, 2022]
a. Both A
and R are correct and R is the correct explanation of A
b. Both A
and R are correct but R is NOT the correct explanation of A
c. A is
correct but R is not correct
d. A is
not correct but R is correct.
16. Tom is a student of grade five. He likes to move
constantly at his desk. He plays with pencils and taps his fingers, stands up
in his place any time he gets a chance. He enjoys playing basketball, and likes
to play in the classroom Which of the following intelligence does he
demonstrate? (CBSE Sample Paper, 2022)
a.
Linguistic b. Logical-Mathematical
c. Musical d.
Kinesthetic
17. The basis of decision making depends upon (CBSE
Sample Paper, 2022)
i. availability
of information ii.
past experience
iii.
positive attitude iv.
self-awareness
a. i) and ii) b.
ii) and iv)
c. i), ii)
and Iv) d. i), ii) and ii)
18. When a machine possesses the ability to mimic the
following human traits, it is said to have artificial intelligence. Identify the positive traits that an Al machine
should possess. [CBSE
Sample Paper, 2022]
i. make
decisions ii.
bias
iii.
predict iv.
learn and improve on its own
a. i), and
iii) only b.
i), ii) and iv) only
c. ii) and
iv) only d.
i),ii), and iv) only
19. Infrared sensors detect infrared energy that is
emitted by one's body heat. When hands are placed in the proximity
of the sensor, the infrared energy quickly fluctuates.
This fluctuation triggers the pump to activate and dispense
the designated amount of sanitizer. This is an example
of (CBSE Sample
Paper, 2022)
a.
Automated machine b.
Al machine
c.
Semi-automatic machine d. Deep Learning machine
20. Match Column A with Column B: [CBSE
Sample Paper, 2022]
Column A Column
B
1. Face
recognition machine i. Not AI
2.
Automatic door ii.
AI
3. Gesture
recognition
4.
Automatic toy car
a. 1->(i):2->(ii);
3->(i):4->(ii) b. 1-> (ii): 2->
(i):3-> (ii): 4-> (i)
c. 1->
(i): 2-> (i):3-> (ii): 4-> (i) d. 1-> (ii): 2->
(i):3-> (i): 4-> (ii)
21. Assertion(A): Anyone can kick an artificially intelligent
machine Reason (R): They have no pain receptors
a. Both A
and Rare correct and R is the correct explanation of A
b. Both A
and R are correct but R is NOT the correct explanation of A
c. A is
correct but R is not correct
d. A is
not correct but R is correct
22. if Data is represented as "Answer, Processing
is represented as "Data" and Answer is represented as
"Processing". which of
the following can be related to the description of layers in a neural network?
Choose the correct options [CBSE
Sample Paper, 2022]
a. Input
Layer-> Data; Output layer-> Processing; Hidden Layer-> Answer
b. Input
Layer-> Processing: Output layer-> Data; Hidden Layer-> Answer
c. Input
Layer Answer: Output layer->Processing: Hidden Layer-> Data
d. Input
Layer->Answer: Output layer->Data; Hidden Layer-> Processing
23. Which of the following is true about neural
networks? [CBSE
Sample Paper, 2022]
a. Neural
Networks tend to perform better with larger amounts of data.
b. Neural
Networks tend to perform poorer with larger amounts of data.
c. Neural
Networks tend to perform better with smaller amounts of data.
d. Neural
Networks need no data
24. Choose the correct option
a.
Unsupervised learning->labelled dataset, Regression
b.
Supervised learning labelled data set, Regression
c.
Unsupervised learning ->unlabelled dataset, Classification
d.
Supervised learning unlabelled data set, Regression
25. Google Translate is Google's free service that
instantly translates words, phrases, and web pages between English
and over 100 other languages. Google translate uses………………………………….
a. 4w
problem canvas b. Neural Networks
c. KWLH
chart d. System maps
26. Email Filters are the application of: [CBSE,
2022]
a.
Computer Vision b.
Data Science
c. Natural
Language Processing d. Neural
Network
27. Computer vision acquires, screens, ……………………. identifies
and extracts information. [CBSE,
2022]
a. does
price comparison b.
analyses
c.
collects d.
labels (CBSE,
2022)
28 Self-Driving Car is an example of…………………
a. Data
Science b. Computer
Vision
c. NLP d. Augmented
Reality
Answers
|
1.b |
2. d |
3. c |
4. a |
5. c |
6.c |
7. d |
8. d |
9. a |
|
10. d |
11. a |
12. c |
13. d |
14. b |
15. a |
16. d |
17. c |
18. b |
|
19. a |
20. b |
21. d |
23. a |
24. b |
25. b |
26. c |
27. b |
28. 6 |
|
1. Al Bias |
2. data |
3. Computer vision |
4. Fraud and Risk Detection |
5. patterns |
|
6. Data Science |
7. Computer Vision |
8. bias |
9. nine |
10. Al bias |
|
|
Domain |
Purpose |
|
Price Comparison Website |
Data Science |
These allow consumers to compare the price of a
product from multiple vendors at one place. This enables the consumers to
make better informed choices. |
|
Email Filters |
NLP |
These analyse incoming emails for red flags that
signal spam/phishing content and automatically move those emails to a
separate folder. Most major email providers have built in spam filters. |
|
Face lock in smartphones |
Computer Vision |
The feature of face lock allows the smartphone's
owner to set up his/her face as an unlocking mechanism for it. This provides
better security for the data in the phone. |
|
Smart Assistance |
NLP |
By accessing our data, they can help us in keeping
notes of our tasks, make calls for us, send messages and a lot more. |
|
Machine Learning |
Deep Learning |
|
Requires large amount of training data. |
Requires very large amount of training data. |
|
Focus is on solving a problem. |
Focus is on identifying patterns from the training data. |
|
It does not need high processing powers. |
It needs high processing powers. |
|
The output result is easy to understand. |
The output result is often not easy to understand. |
|
Programmer has to manually enter the features. |
Machine identifies the features itself based on the
training data. |
-Subjective Questions-
Very Short/Short Answer Questions
A. Fill in the blanks.
1. Majorly, all the virtual assistants have a female voice. This shows…………….
2. A machine can also become intelligent if it is trained with………………………….
3. A self-driving car identifies objects in front of it using………………………………..
4. One of the key applications of Data Science is……………………………………………domain
of Al
5. A machine learns by finding………………………………………. in data.
6. Airline route planning is an application of ……………………………
7. Lenskart.com allows you to try out its frames virtually by switching on
your camera. This is an application of……………….
8. Any……………………..can transfer from the developer to the machine while the
algorithm is being developed.
9. Every human being has…………………….types of intelligences.
10. In 2014, Amazon developed an Al model to recruit software engineers.
It was found that the model discriminates against women. This is an example of………………………
Answers
B. State whether the statement is True or False.
1. An Al Model can have minimum bias if Training set is diverse and
includes all representation.
2. The term Artificial Intelligence was given by John Darmouth.
3. Google Translate is based on NLP
4. Smart assistants like Apple's Siri and Amazon's Alexa recognize
patterns in images, then infer meaning and provide a useful response.
5. Al bias is used to deal with all ethical issues surrounding Al systems.
-Answers
1. True 2.
False 3. True 4.
False 5. False
Very Short Answer Type Questions
1. Define Artificial Intelligence.
Ans.
Artificial Intelligence is the science and engineering of making intelligent
machines. It is a technique of getting machines to work and behave like humans.
The machines that are incorporated with human-like intelligence to perform
tasks as we do. This intelligence is built using complex algorithms and
mathematical functions.
2. What is Al bias?
Ans.
Artificial intelligence bias includes bases that are passed to the artificial
intelligence systems created by humans. These biases can be passed into the Al
systems when they are trained on data based on gender, race, nationality etc.
3. Give two examples of each of the following:
a. Tields where Computer Vision is used
b. Applications of NLP
Ans. a.
Fields where Computer Vision is used Virtual try on feature for any product
like lens, dress, jewellery (e.g. lenskart.com), theft detection
b. Applications of NLP-Language Translator, Virtual
Assistants like Alexa, Siri
4. List any four types of Intelligences and briefly
explain any two.
Ans. Types
of Intelligence
a. Musical Intelligence
b. Interpersonal intelligence
c. Linguistic Intelligence: Language processing skills
both in terms of understanding or implementation in writing or verbally
d. Existential Intelligence: Intelligence relating to
religious and spiritual awareness.
5. How is Deep Learning related to Machine Learning?
Ans. The
intention of Machine Learning is to enable machines to learn by themselves
using the provided data and make accurate predictions. Deep learning is a
subfield of machine learning. In Deep Learning, the machine is trained with
huge amounts of data which helps it in training itself around the data. Such
machines are intelligent enough to develop algorithms for themselves Deep
Learning is the most advanced form of Artificial Intelligence.
6. How does a machine become Artificially Intelligent?
Ans. By
using data and algorithms for training, the machine becomes intelligent
Artificial intelligence machines
constantly update their knowledge to optimize the
performance.
7. Define Machine Learning.
Ans. Machine
learning is the study of computer algorithms that can be automatically improved
using experience and data.
8. Briefly explain what Al can and cannot do.
Ans. What Al
can do
a. Prediction b.
Face Tagging on social media sites
c. Product recommendations
What Al cannot do:
a. Learn on small amounts of data b.
Become effective fast
9. What are Price Comparison Websites?
Ans. These
websites are driven by large amounts of data. Using these sites, it is easy to
compare the prices of products from multiple suppliers in one place
PriceGrabber, PriceRunnet Junglee, Shopita, DealTime are some examples of price
comparison websites. Today, price comparison websites can be found in almost
every field such as technology, hotels, automobiles, durable goods, clothing,
etc.
10. What is an email filter? To which Al domain does
it belong?
Ans. Email
Filter is one of the first and most base applications of online NLP. It started
with a spam filter that looked for certain words or phrases that represent
spam.
D. Answer the following questions.
1. List few applications of Al
Ans. a. Virtual
Assistants: Alexa, Sirt, OK Google b.
Music and media streaming services
c. Video Games d.
Healthcare: early disease detection
e. Online Ads network f.
Navigation and travel
g. smart cars and drones
2. Briefly explain the three domains of Al
Ans. a.
Data Sciences: is a domain of Al related to data systems and processes,
in which the system collects numerous data, maintains data sets and derives
meaning/sense out of them. The information extracted through data science can
be used to make a decision about it.
b. Computer
Vision: is a domain of Al that depicts the capability of a machine to get
and analyse visual information and afterwards predict some decisions about it.
The entire process involves image acquiring, screening, analysing, identifying
and extracting information.
c. Natural
Language Processing: is a branch of artificial intelligence that deals with
the interaction between computers and humans using the natural language.
3. Why do we need Al Ethics? Explain with an example.
Ans.
Artificial intelligence is ultimately an advanced calculation and analysis
tool. When developed with malicious Intent or trained with conflicting data, it
is prone to errors and biases. Artificial intelligence has great potential to
be used as a weapon in a way that threatens public safety, security and quality
of life, which is why the ethics of artificial intelligence is so important.
Example Deepfakes are video or audio content generated by Al for deception.
Such Machine-generated videos have great potential to harm society by promoting
the spread of misinformation and cyber-attacks.
4. Al certainly has changed our lives but there are
certain risks involved too. Explain two risk areas of Al.
Ans. a.
Relying too heavily on Al systems for diagnosis of a medical condition poses a
risk, as some prototype Al Ans. systems have been known to misdiagnose.
b. AI can also pose a risk to the environment due to
the massive amount of energy required to train its deep learning models. The
machines emit large amounts of carbon dioxide which adds to the green-house
effect.
5. What is data privacy and why is it important?
Ans. Data
privacy generally refers to an individual's ability to decide when, how and to
what extent to share or communicate their personal information with others.
This personal information can be a person's name, location, contact
information, or their behaviour online or in the real world. Ad Internet use
increases year after year, so does the importance of data privacy. Social media
platforms, apps and websites generally need to collect and store personal data
about users to provide services. However, certain applications and platforms
can exceed user expectations for data collection and use, making users less
private than they might think. Other applications and platforms may not take
adequate protection measures for the data they collect, which can lead to data
leakage, thus compromising user privacy.
6. List 3 ways in which AI can be misused.
Ans. a. Deepfakes:
using artificial intelligence to produce or manipulate audio and visual content
to make it appear real. Combining "deep learning" and "fake
media", deepfakes are very suitable for future false propaganda
activities, because even with technical solutions, they are difficult to
immediately distinguish from legal content.
b. Cybercriminals are using machine learning for
guessing users' passwords.
c. Cybercriminals also abuse artificial intelligence
to mimic human behaviour. For example, they can successfully fool bot detection
systems on social media platforms like Spotify by mimicking human usage
patterns. Cybercriminals can profit from malicious systems and generate
fraudulent streams and traffic for specific artists.
7. Will Al lead to unemployment?
Ans. With
the advancement of artificial intelligence, some people believe that it will
steadily and inevitably take over most of the labour force and bring about
massive unemployment and social unrest. However, Artificial intelligence and
other innovations are designed to excel at a very specific set of tasks. They
will not easily be able to substitute an entire occupation, which, in most
cases, requires much more versatility and adaptability. Artificial intelligence
will also create new jobs on the ground. Self-driving cars may require the
driver to make emergency trips. More technical developers will be needed to
create chatbots for all industries, and most importantly, to act like humans.
No matter how advanced and super-efficient artificial intelligence becomes,
some tasks are always done by humans, including doctors, therapists,
hairdressers, and personal trainers.
8. Briefly explain the moral issues surrounding
Self-Driving cars.
Ans. A
self-driving car is an automated vehicle. Its response in any situation is a
coded, pre-meditated decision to take the ‘least bad' course of action.
However, the issue of ethics-exactly who should take responsibility for
accidents happening on the road-remains an area that's up for discussion. In
case of an accident, who should be made responsible:
a. The person who bought this car
b. The Manufacturing Company
c. The developer who developed the car's algorithm
d. The person who came in front of the car and got severely injured
These are some of the moral issues surrounding Self-driving
cars.
9. List any 6 applications of Computer Vision.
Ans. a. Ball
tracking in games like Tennis, cricket b.
Athlete pose tracking
c. Cancer detection d.
Cell Classification
e. Medical Skill Training f. Crop
monitoring
10. How many intelligences does a human being possess?
Define Mathematical logical reasoning, Naturalist
Intelligence, Interpersonal Intelligence and
linguistic Intelligence.
Ans. A human
being possesses all nine types of intelligences, only at a different level.
a. Mathematical logical reasoning: A person's
ability to regulate, measure, and understand numerical symbols,
abstraction and logic.
b. Linguistic Intelligence: Language processing
skills both in terms of understanding or Implementation in writing or verbally.
c. Interpersonal Intelligence: Interpersonal
intelligence is the ability to communicate with others by understanding other
people's feelings & influence of the person.
d. Naturalist Intelligence: An additional
category of intelligence relating to the ability to process information on the
environment around us.
Long Answer Questions
1. Identify the Al domains to which the following
belong to and list their purpose.
a. Price
Comparison websites b.
Email filters
c. Face
lock in smartphones d.
Smart Assistants
Ans.
2. Define Al, ML and DL. How are they interlinked?
Ans. Artificial
Intelligence: When a machine possesses the ability to imitate human
traits, make decisions, predict the future, and improve on its own, it is said
to have artificial intelligence.
• Machine Learning: Machine learning
(ML) is often used in conjunction with Al, but it is a subset of Al ML refers
to an artificial intelligence system that can teach itself based on algorithms.
The system that becomes smarter over time without human intervention.
Deep Learning:
This subset of ML is a technology inspired by the way the human brain filters
information. It's about learning from the examples. The DL system helps
computer models filter input data through layers to predict and classify
information. Deep learning processes information in the same way as the human
brain
Machine learning is a subset of artificial
intelligence, consisting of technologies that allow computers to find patterns
in data. Deep learning is a subset of machine learning, which enables computers
to solve more complex problems. Such machines are intelligent enough to develop
algorithms for themselves. Deep Learning is the most advanced form of
Artificial Intelligence.
3. Explain any 4 areas where Computer Vision is being
used.
Ans. a.
Facial Recognition: Various security applications involve use of Computer
Vision for facial recognition. It can be either guest recognition or
recognition of regular employees, students in school etc.
b. Google's Search by Image: This uses Computer Vision as it compares different
features of the input image to the database of images and give us the search
result while at the same time analysing various features of the image.
Self-Driving Cars: This involves the process of identifying the objects, getting
navigational routes and also at
the same time environment monitoring.
d. Medical Imaging: The application is used to read and convert 2D scan images into
interactive 3D models that enable medical professionals to gain a detailed
understanding of a patient's health condition.
4. Explain any 4 popular real-life applications of Al.
Ans. a. Virtual Assistants: Alexa, Siri, OK Google. They set reminders, make
calls, launch Games, open Websites, tell you about the weather, date and time,
greetings, news, etc.
b. Self-Driving Cars: These autonomous vehicles combine Al software,
sensors, real-time cameras to ensure safe decisions on the road.
c. Spam filters: These use Al to detect unwanted, and virus-infested email (called
spam) and stop it from getting into email inboxes.
d. Facial Recognition: Social media apps like Facebook and Snapchat use Al
for tagging people and face filters.
5. Differentiate between machine learning and deep
learning
Аns.
Competency Based Questions
1. A leading multinational company operates on a chain
of hypermarkets and grocery stores deployed an Al application to make it easier
for employees to keep their stores running smoothly. They used thousands of
video cameras, weighted sensors on shelves, and other technologies that can
tell employees when certain products is starting to go bad. One of the task of
the application is to identify bananas that had started to turn brown,
eliminating the need for employees to manually inspect fruit. Which of the
following domain is used to achieve this?
a. Data sciences b.
Computer vision
c. Natural Language Processing d. Fuzzy logic
2. An Al system uses two broad classes of data namely
content data which includes the raw video streams title, description, etc, and
user activity data that includes rating a video, favoriting/liking a video, or
subscribing to an uploader, and watch time. Based on this, the Al system
measures a user's engagement and happiness. It then starts computing
personalized recommendations to the user. Which of the following applications
can you relate to this?
a. self-driving car b. Siri
c. email filters d. YouTube
3. Amazon had been working on a secret Al recruiting
tool. The machine-learning specialists uncovered a big problem: their new
recruiting engine did not like women. The system taught itself that male
candidates were preferable. It penalized resumes that included the word
"women". This led to the failure of the tool. This is an example of
a. Data Privacy b.
Al access
c. Al Bias d.
Data Exploration
4. Choose the correct statement related to Machine
Learning: [CBSE,
2022]
Statement : It is a subset of Artificial Intelligence which
enables machines to improve at tasks with experience. Statement : It
enables machines to learn by themselves using the provided data and make
accurate Predictions/Decisions.
a. Only
Statement i is correct b.
Both the Statements i and ii are correct
c. Both
the Statements i and ii are incorrect d.
Only Statement il is correct
5. Statement i:
in Deep Learning the machine is trained with huge amounts of data which helps
it in training itself around the data [CBSE,
2022]
Statement : Everything which is Machine Learning is also Deep
Learning.
a. Both the Statements i and ii are correct b. Only Statement i is
correct
c. Only Statement is correct d. Both the
Statements i and ii are incorrect
6. Jhanvi loves travelling and makes wonderful travel
logs, she was planning to take this as a profession and wanted to buy a good
camera with ether accessories for her vlogs. Her friend had suggested her to
look for various options online which is giving her comparison from various vendors.
She was happy to purchase the camera at a best price Which domain of Al is
working behind that has helped her to take decision on this? [CBSE, 2022]
a. Computer Vision b.
Data Science
c. Natural Language Processing d. Neural Network
7. Ananya has recently bought a robot to do cleaning
including mopping. The robot senses the dirty floor, calculates the average
time takes to moo, senses the obstacle and changes the direction, also goes for
auto charging. Her housemaid was feeling insecure as if she would not be
required in the near future. This is a problem related to: [CBSE, 2022]
a. Al Bias b.
Al Ethics
c. Al Creating Unemployment d. Data Privacy
8. Read the test given below and categorize the
following under Data Sciences, Machine Learning, Computer Vision and NLP The
latest technological advances have made our lives more comfortable. Google
Home, Alexa and Se are of great help for people who do not understand
technology. Features like face recognition and face lock add additional
security to our devices. These advancements also help make our needs more
accessible and convenient Now you can even use price comparison sites to check
prices and use chatbots to order groceries online.
a. Did you know that you can even find how you look
when you get older? FaceApp and Snapchat filters make it possible!
b. Facial Recognition and Face lock- Computer Vision
c. Price comparison websites - Data Science
d. FaceApp and Snapchat Filters (tis check how you
look when older)- Machine Learning and Computer Vision
Read the test given below and answer the given
questions
A team from the University of California at Berkeley
discovered a problem in their Al system, that was used to assign care to 200
million patients in the United States. In general, blacks were assigned lower
risk scores than whites, even though black patients were also statistically
more likely to have comorbidities and therefore experience higher levels of
risk. This, in turn, meant that black patients were less likely to receive
necessary standards of care and more likely to be adversely affected by denial
of adequate care. The problem arose from the fact that the system used
predicted health care costs as a determining variable to assign risk values,
and because black patients are generally less able to pay or ‘considered’ less
able to pay, the system ‘decided’ that they were not entitied to a higher
standard of medical care.
a. What ethical issue is the author talking about?
b. What were the reasons of this ethical issue
entering the Al system?
c. Give two reasons How can this problem be solved?
d. Which other factor(s) besides heath care cost
should be used to determine risk values?
10. MIT grad student Joy Buolamwini was working with
facial analysis software when she noticed a problem: the software didn't detect
her face- because the people who coded the algorithm hadn't taught it to
identify a broad range of skin tones and facial structures. This is an example
of
a. Computer Vision b.
Al Bias
c. NLP d.
Data Mining
11. Radha is good at singing since childhood, she
understands key notes and is composing a song for her college festival but her
father wants her to focus on science exam. She possesses ………………… skill but her father
is not finding it lucrative. [CBSE, 2022]
a.
Naturalist Intelligence b.
Interpersonal Intelligence
c. Musical
Intelligence d.
Spatial Visual Intelligence
12. Radha was searching for new shoes online. Now, she
is fed up with mails, popups, advertisements related to shoes on her social
media accounts, email inbox and SMS on her phone. This is an issue related to:
[CBSE, 2022]
a. Data privacy b.
Data Acquisition
c. Poor training d.
Lack of access
--Answers
1. b 2. d 3. c 4.
b 5. b 6. b 7. C
8. a. Alexa, Siri, Chatbots-NLP
b. Facial Recognition and Face lock-Computer Vision
c. Price comparison websites-Data Science
d. FaceApp and Snapchat Filters (to check how you look
when older)- Machine Learning and Computer Vision
9. a. Al Blas
b. i. The Al machine was trained on limited data-only
white people.
ii. It used
only health care costs to determine risk values
c. By training the machine on data involving people of
all genders, races, communities etc.
d. Insurance, patient age.
10. b 11. c 12. b
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