CBSE Grade 8 Computer Science Artificial Intelligence Mind Map

Artificial
Intelligence
Mind Map
SRITOMA MAJUMDER
Class 8 (The Newtown School)

Artificial Intelligence(AI)
✓Artificial Intelligence (AI) is a fast-evolving field in Computer Science that enables
development of smart machines which can think and take decisions like a human being.
✓AI encompasses a vast variety of areas like machine learning, computer vision, robotics,
natural language processing, which are needed to build smart machines capable of executing
tasks that are believed to require human intelligence.

Artificial
Intelligence
Evolution Application Areas
Email Services
Online Shopping
Smartphones and
Personal Assistants
Social Networking
Education
Banks
Healthcare
Agriculture
Domain Areas
Machine Learning
Computer Vision
Natural Language
Processing
Advantages and
Disadvantages
Advantages
Disadvantages
Impact of AI on
SDGs
AI Ethics
AI Bias and AI
Access
Future of AI

Evolution of AI
✓ The focused work in the field of AI is considered to be Alan Turing's important work in 1950. He
was the first to propose that machines can 'learn' and become artificially intelligent.
✓ In 1952, Arthur Samuel of IBM laboratory started working on AI programs that could play
Checkers.
✓ In the summer of 1956, John McCarthy, a prominent figure in AI and an instructor in Dartmouth
College, organised a 2-month workshop at Dartmouth. The workshop was to discuss the possibility
of machines simulating aspects of human learning and intelligence. This was the first time when
McCarthy used the term 'Artificial Intelligence’ officially to describe the theme of the workshop.
✓ In 1957, Frank Rosenblatt designed the first neural network program simulating the human brain.
✓In 1958, McCarthy developed the LISP language-the first AI programming language.
✓From then on for the next 50 years, the journey of Artificial Intelligence has been fascinating.

1943
• Warren McCulloch and
Walter Pitt comes up with a
model for artificial neurons
inspired by biological
neurons
1950
• - Alan Turing proposes
'learning machine’
• - Marvin Minsky and Dean
Edmonds build the first
neural network computer
1952
• Arthur Samuel develops an
Al program that could play
Checkers
1956
• Famous Dartmouth
conference organised by
John McCarthy where the
term Artificial Intelligence is
used officially for the first
time.
1958
• McCarthy defines first
Al programming
language LISP
1962
• Frank Rosenblatt
designs the popular
neuron model termed
perceptron
1964
• Al program developed
which can understand
natural language
1965
• First Al-based chatbot
ELIZA developed
1974
• Stanford Al lab
develops first self-
driving cart
• Beginning of use of Al
for medical diagnostics
1982
• First commercial Al
system developed by
Digital Equipment
Corporation
1997
• IBM Deep Blue beats
world chess champion
Gary Kasparov
1999
• Sony introduces first
domestic robot AIBO
2005
• Beginning of AI-based
recommendation engine
2011
• IBM's Watson beats
two human champions
in Jeopardy
2016
• Google's AlphaGo
program beats
professional Go player
Evolution of AI

Application Areas of AI
✓ AI finds its applications in almost all walks of life whether it is school, banks or hospitals. It
is quite possible that you are not aware of all of them. Let's take a quick look at different
applications of Al.

Email Services
✓ Spam filters use AI to regularly update the list of rules for removing spam emails and
keeping the inbox clean. Simple rule driven filters are applied to sweep out emails with specific
words such as 'cash reward' and 'loan approval' as well as emails coming from unknown
addresses.
✓ AI helps in composing emails and drafting reply messages by suggesting short and context-
specific words.
✓ AI is also used for implementing utility functions like reminders for taking actions on specific
emails.

Online Shopping
✓ Sites such as Amazon use AI to analyse the search pattern of the customer and show the
relevant products.
✓ AI is also used for fraud prevention in online transactions while shopping.

Smartphones and Personal Assistants
✓ Smartphones are the most adopted gadgets used to do a multitude of tasks. While using a
smartphone, the user interacts with AI consciously or sub-consciously.
✓ In an AI driven home set-up, there can be multiple gadgets like air-conditioner, microwave,
surveillance camera, etc. which can have sensors through which connectivity can be established
between the devices and a smartphone. This helps to connect to the devices remotely using the mobile
phone.
✓ Another standard functionality provided by smartphones is voice-to-text. By pressing a button or
saying a particular phrase like 'Ok Google', voice-based searches can be made through Google Assistant.
✓ Amazon's Alexa is an Al-powered personal assistant that accepts voice commands to do a wide range
of activities like creating task lists, ordering items online, setting reminders, playing songs, answering
questions and so on.

Education
✓ Different students have different learning needs. AI systems are used to customise and give
personalised teaching to individual students.
✓ Students can also use interactive voice assistants such as Amazon Alexa, Apple Siri, etc. to
find relevant learning materials. AI also helps the teachers to do their administrative tasks
efficiently so that more time can be given to the students.
✓ Language translation is another blessing of AI which is used by many students, especially
when learning a new foreign language.

Banks
✓ In the banks, fraudulent transactions, especially the ones related to credit cards, are
extremely common. Since the volume of these transactions is extremely high, it is not possible
for human beings to monitor and identify such transactions. In such situations, AI comes to
the rescue and can help detect such fraudulent transactions.

Healthcare
✓ Data from wearable devices, e.g., FitBit and Apple, are Garmin forms a rich source for applying artificial
intelligence and predicting the health conditions of a person in real time.
✓ In case, some health issue is predicted by AI, the person is immediately alerted to take preventive action.
✓ In case of some extreme problem, doctors or healthcare providers in the vicinity of the person can also be alerted.
✓ Suppose an elderly person goes for morning walk in a park close to his house. Suddenly, while walking, his blood
pressure shoots up beyond a certain limit, which is tracked by the wearable device and analysed by an AI system.
Alert is sent to the person to immediately stop walking and take rest. Also, doctors and healthcare providers can be
alerted to be on standby.
✓ AI or more specifically Computer Vision plays a crucial role in disease diagnosis from medical imaging.
✓ AI is also used to manufacture medicines in a faster time and at a reduced cost. During the Covid-19 pandemic,
AI was used for fast discovery and trial of the vaccine.

Agriculture
✓ Just like driverless cars, driverless tractors are also being developed.
✓ Robotics and drones have started playing a big role in agriculture. Robots are used in diverse
activities like harvesting crops and removing weeds. On the other hand, drones are used to
monitor the field, check crop quality, etc.
✓ Precision farming is another trending way of agriculture in which AI plays a big role. Precision
farming uses AI to do controlled farming by proper watering, protecting from pest attack,
providing the right amount of nutrients and timely harvesting.

Domain Areas of AI
✓ AI is built on pools of data. Data growth
is a key reason for the huge success of Al.
✓ Data used in Al are grouped into two
types-structured and unstructured.
✓ As depicted in the following figure,
structured data are highly organised and
operations related to structured data are
easy to do.
✓When we think of a student's data
containing information like student name,
student address, age, gender and weight, it
is structured in nature.

Domain Areas of AI
✓ Unstructured data have just the
opposite nature. It is highly disorganised,
doesn't follow any specific format and is
difficult to analyse.
✓ Examples of unstructured data include
text files, email messages, social media
posts, images, video and audio files,
surveillance imagery, etc.

Domains of AI
✓ Structured data can be analysed using traditional tools and techniques of AI. However, at the
moment, a lot of developments are taking place in the area of unstructured data.
✓ Computer Vision is a fast-evolving domain of AI that is playing a critical role in the analysis and
interpretation of image and video data.
✓ Natural Language Processing, which is another domain of AI, is playing a crucial role in analysing text
and speech data efficiently.

Domains of AI
✓Following domains of AI:
❖ Ability to learn to take decisions based on past information regarding similar situations-also called
Machine Learning.
❖ Ability to communicate in a language used by human beings, e.g., English-also called Natural
Language Processing.
❖ Ability to view objects and interpret the information they convey-also known as Computer Vision.

Machine Learning
✓Machine Learning (ML) is the most important area of Artificial Intelligence. It refers to the
ability of machines to learn to take decisions based on past information regarding similar
situations. In other words, it can be defined as the process by which a computer program
learns to do a task T based on past experience E in such a way that its performance P
improves with experience E.
✓ Search Engines and personal assistants use Machine Learning to refine and improve results
based on the data collected from our previous interactions with them.
✓ For example, based on our past searches, a search engine or a personal digital assistant
might analyse and conclude that when we search for bedtime stories, we always prefer
listening to stories in English from a particular channel. Next time, when we search for
bedtime stories, the top search results will be based on this preference.

Computer Vision
✓ Computer Vision (CV) is the domain of
Al which enables computer to see things
like human beings.
✓ However, to start with, let's try to
understand how computer sees the
world. In context of Computer Vision, the
image is not a picture but a set of pixel
values. Each pixel value represents color
intensity. A set of a few hundred (or may
be a few thousand) pixels constitute a
picture as shown in Figure.

Computer Vision
✓ There are many ways in which Computer Vision touches our life.
✓ Diagnosing diseases from images like X-ray, CT scan and ECG is one area where Computer
Vision plays a very important role.
✓ In agriculture, right from planting seeds to monitoring the crop growth to grading and
sorting of the crops produced, Computer Vision plays a big role.
✓ It is used for critical tasks like security camera-based surveillance as well as for simple tasks
like automatic tagging of photos on a social networking site.
✓ Future fantasies like self-driven cars or flying drones delivering package to doorstep may all
be possible one day by virtue of Computer Vision.

Natural Language Processing
✓ Natural Language Processing (NLP) is another key domain area of Al which enables a
conversation between human beings and computer.
✓ Human language unlike a computer programming language such as C, Java and Python is
complex, diverse and difficult to understand.
✓ NLP makes it possible for computers to understand human language. It helps in translating a
sentence like 'Where is the nearest Oriental cuisine restaurant?' into numbers so that the
machines can understand it.

Natural Language Processing
✓ Some common applications of NLP are seen in:
❖ Text-to-speech and speech-to-text conversion: Given a piece of text, computer is able to
convert it to audio clippings as if some human being has read through the text. Also,
computer is able to extract the text corresponding to an audio clip.
❖ Language translation: Computer is able to translate a piece of text written in one language,
say German, to another language, say French.
❖ Text summarisation: Computers are able to understand and summarise the content of a
piece of text.
❖ Question answering (chatbots): Computers are able to understand and answer the questions
given in languages used by humans.

Advantages of AI
✓ The advantages of AI are as follows:
❖ AI helps in taking faster and more precise decisions. Also, if the same task is done by human
beings over and over again, there is a possibility of human error due to fatigue, carelessness,
etc. However, the possibility of such 'human error' is eliminated if Al is used.
❖ AI has a critical role to play in weather forecasting, disaster prediction, etc. which helps in
averting large-scale calamities.
❖ In situations where there is a high possibility of health hazard for human beings, Al-based
robots can be used. Examples of such hazardous situations are widespread fires, nuclear plant
explosion, poisonous gas leakage in mines, etc.
❖ AI systems are available at all times. Like human beings have working shifts, Al systems have
no such shift and can work 24 x 7.

Disadvantages of AI
✓ The disadvantages of AI are as follows:
❖ Developing an AI solution is not very easy. It is often pretty expensive based on the
complexity of the solution.
❖ Automating too many activities using AI is making human idle. Slowly, the capacity of
humans to do the work is also coming down.
❖ There is a growing concern that too much of automation using AI is responsible for taking
away a number of jobs.

Impact of AI on SDGs to Develop Responsible
Citizenship
✓ AI is emerging as the top enabler in terms of achieving the 17 Sustainable Development
Goals or SDGs defined by the United Nations.
✓ Some ways in which AI can help us achieve SDGs laid down by UN.
❖ SDG 1: No poverty: AI can provide a real-time view of resource allocation through satellite
mapping and data analysis.
❖ SDG 2: Zero hunger: AI helps in boosting agricultural productivity through automated crop
monitoring and harvesting.
❖ SDG 3: Good health and well-being: Healthcare wellness programs powered by AI help in
diagnosis and cure of a number of ailments including cancer, diabetes, heart diseases, etc.

Citizenship
❖ SDG 4: Quality education: AI is revolutionising education by helping to spread it far and
wide. Virtualised learning platforms like NPTEL and MIT Courseware has helped in delivering
top quality and affordable education at the doorstep.
❖ SDG 5: Gender equality: AI is instrumental in identifying and remediating gender bias.
❖ SDG 6: Clean water and sanitation: AI helps in predicting sanitation and consumption
patterns which forms critical input for improved water and sanitation provisioning.
❖ SDG 7: Affordable and clean energy: By unveiling patterns related to energy consumption at
in real time, AI helps to ensure affordable and green energy.
❖ SDG 8: Decent work and economic growth: AI helps to improve productivity thus boosting
up economic growth.

Citizenship
❖ SDG 9: Industry innovation and infrastructure: This is probably the most important area
influenced by AI.
❖ SDG 10: Reduced inequalities: AI-enabled devices helps in correcting disabilities resulting in
a more equal and inclusive society.
❖ SDG 11: Sustainable cities and communities: AI enables smart homes and smart cities and
helping to create sustainable communities.
❖ SDG 12: Responsible consumption and production: AI helps in optimising production and
consumption levels thus eliminating waste and improving production efficiency.
❖ SDG 13: Climate action: AI-based weather prediction helps in averting major disasters.

Citizenship
❖ SDG 14: Life below the water: AI helps in tracking underwater life thus enhancing
sustainable marine ecosystems.
❖ SDG 15: Life on land: Like marine ecosystems, AI helps to enhance sustainable land
ecosystems.
❖ SDG 16: Peace, justice and strong institutions: AI helps in reducing discrimination and
corruption.
❖ SDG 17: Partnerships for goals: Multi-discipline collaboration enabled by AI is responsible
for all-round development.

Ethical Considerations of AI
✓ Ethics or moral behaviour is an important quality of human beings which is needed for a
healthy personal or professional life.
✓ Ethical behaviour encompasses qualities such as honesty, integrity, fairness and
accountability.
✓ The norms of human ethical behaviour are expected to be followed by AI systems too.
✓ However, due to the rapid growth in the field of AI and the diverse laws and regulations in
different countries, ethical risks are perceived as one of the top concerns related to Al.

✓Some of the major ethical risks of AI are:
❖ 1. Privacy and surveillance: The biggest issue arising out of AI is related to access to private
data. Privacy or 'the right to be let alone' is a key democratic right in most countries. Hence any
technology which significantly interferes in the private zone is not acceptable. Since the primary
focus of AI is to analyse data and come up with decisions based on such data, these decisions may
have been taken by accessing data and facts which the person would prefer to keep confidential.
❖ 2. Unethical action based on classified information: Data captured by breaching privacy, as
mentioned above, is not the only problem that AI systems may indulge in. A bigger threat is to use
the information from the captured data to manipulate behaviour. Whether it is running a sales
campaign or an election campaign, customised messaging can be done for specific target groups
to manipulate their willingness to buy a particular product or to vote for a particular candidate.

❖3. Automation and job loss: There is a growing worry globally that AI systems will result in
job losses, more so in the work areas which involve repetitive work and can be automated.
According to a recent report, by 2030 about 800 million people will lose their jobs because
of robots and other AI deployments. Industrial robots will replace human workers in many
factories. However, the silver lining is new jobs requiring AI skills will be created.
❖ 4. Physical and cyber-physical security threats: Virtual wars or cyber wars may be launched
using AI systems and can lead to massive financial and intellectual damage beyond recovery.

✓ So, while implementing an AI system, proper human judgment should be exercised. Also,
regular assessment of risk should be done to determine violations in compliance with
regulations. In the organisations adopting AI, proper governance should be put in place to
identify ethical risks, manage those risks and ensure compliance with standards.

AI Bias and AI Access
✓ AI systems work on past data to make automated decisions. Since the decision is based on past data, if
there is a bias or an uneven representation of a particular element in the data, it will influence the
decision made by the Al system.
✓Let's take a few examples to understand the problem of bias of an AI system.
❖ The hiring of a large company used an AI system which preferred male candidates over female. This was
because the Al system was fed with data for the previous 10-year period that included male candidates
mostly.
❖ AI systems made by top global companies for facial recognition had biases in detecting people's gender.
These systems could detect the gender of white men more accurately than the gender of men with
darker skin.
❖ Another global company built an Al system to predict future criminals from photographs. The system
showed bias against black people.

AI Bias and AI Access
✓ AI has resulted in a productivity gain which has benefited a lot by compounding the financial
returns obtained from it. However, the problem is that not everybody is benefited by the
blessings of AI. Only a selected section of the population have the money to implement AI
systems and leverage the benefits from them. So, due to this access problem of AI, the rich
are getting richer and the poor are remaining stagnant.

Future of AI
✓Artificial intelligence is a technology which is evolving very fast. Though the general notion which
many people have is AI may soon replace human beings, the reality is AI can be a great blessing to
mankind by complementing things that human beings cannot do.
✓ At the moment a lot of research is going on to break new barriers. In near future, you may
expect things like pizza delivered to your doorstep by unmanned aerial vehicles or drones. Drones
are actually becoming adopted in many fields- the most prominent one being security surveillance.
✓ Medical diagnostics and new medicine discovery are the areas which are expected to get great
benefits in future by the application of AI.

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CBSE Grade 8 Computer Science Artificial Intelligence Mind Map

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