Worksheet Solutions: Basics of AI | Artificial Intelligence for Class 10 PDF Download

Multiple Choice Questions (MCQs)

Q.1: What is the primary goal of developing machines as per the concept of AI?

a) To replace human intelligence completely
b) To perform cognitive tasks like thinking and decision-making
c) To operate without any data
d) To limit technological advancements

Ans: b) To perform cognitive tasks like thinking and decision-making

The primary goal of AI is to enable machines to perform cognitive tasks such as thinking and decision-making, enhancing efficiency. Options a, c, and d misinterpret AI’s purpose.

Q.2: How is AI described in the context of the Fourth Industrial Revolution?

a) A hardware component for robots
b) The software engine driving technological advancements
c) A manual system for data collection
d) A non-evolving technology

Ans: b) The software engine driving technological advancements

AI is often regarded as the software engine propelling innovation during the Fourth Industrial Revolution, unlike the other options, which misrepresent its role.

Q.3: Which of the following is a challenge associated with AI?

a) Increased manual labor
b) Inscrutable 'black box' algorithms
c) Reduced data collection
d) Limited use in households

Ans: b) Inscrutable 'black box' algorithms

One major challenge of AI is the 'black box' nature of certain algorithms, making their decision processes unclear. The other options do not accurately reflect current AI challenges.

Q.4: What is a characteristic of AI systems?

a) Performing tasks requiring physical strength
b) Reasoning and learning from past experience
c) Operating without algorithms
d) Avoiding human-like processes

Ans: b) Reasoning and learning from past experience

AI systems are designed to reason and learn from experience, making option b correct. The other options mischaracterize AI capabilities.

Q.5: Which AI domain involves analyzing visual information to make decisions?

a) Data Sciences
b) Natural Language Processing
c) Computer Vision
d) Machine Learning

Ans: c) Computer Vision

Computer Vision is the AI domain focused on analyzing visual information for decision-making, distinguishing it from the other domains listed.

Q.6: What is the primary goal of Natural Language Processing (NLP)?

a) To process numerical data
b) To understand and interact using human language
c) To enhance physical movements
d) To replace human communication

Ans: b) To understand and interact using human language

The main goal of NLP is to enable machines to understand and engage in human language, which is accurately described in option b, while others misrepresent its purpose.

Q.7: Which of the following is an example of a Data Science application?

a) Face lock in smartphones
b) Price comparison websites
c) Voice-activated assistants
d) Self-driving car navigation

Ans: b) Price comparison websites

Price comparison websites utilize data science principles to analyze and present information, differentiating them from the other options that do not primarily focus on data science.

Q.8: Which intelligence trait involves understanding and responding to conversations?

a) Mathematical Logical Reasoning
b) Linguistic Intelligence
c) Spatial Visual Intelligence
d) Kinesthetic Intelligence

Ans: b) Linguistic Intelligence

Linguistic Intelligence specifically relates to the ability to understand and engage in verbal communication, while the other options pertain to different types of intelligence.

Q.9: What is a potential ethical concern with self-driving cars?

a) Inability to process data
b) Moral dilemmas in decision-making algorithms
c) Lack of connectivity
d) Inability to use sensors

Ans: b) Moral dilemmas in decision-making algorithms

Self-driving cars face ethical concerns primarily due to the moral dilemmas that arise in their decision-making algorithms, unlike the other listed issues.

Q.10: What is a source of AI bias?

a) Machines developing their own biases
b) Transfer of developer’s biases into algorithms
c) Lack of data collection
d) Absence of human interaction

Ans: b) Transfer of developer’s biases into algorithms

AI bias often arises from the biases of the developers being embedded in algorithms, which is accurately captured in option b, while the others do not directly address the source of bias.

Fill in the Blanks

Ans: intelligence

Artificial Intelligence (AI) is defined as a form of intelligence that allows machines to mimic human cognitive functions, such as learning and problem-solving.

Q2: Machine Learning is a subset of AI that enables machines to improve at tasks with __________ data.

Ans: training

Machine Learning relies on training data, which helps algorithms learn from past experiences and enhance their performance over time.

Q3: __________ is a domain of AI that involves analyzing visual information like images or videos.

Ans: Computer Vision

Computer Vision is a key area within AI focused on enabling computers to interpret and process visual data, such as images and videos.

Q4: Smart assistants like Siri use __________ to understand and respond to voice commands.

Ans: Natural Language Processing

Natural Language Processing (NLP) allows smart assistants to comprehend and generate human language, improving interaction and functionality.

Q5: AI __________ refers to the unequal access to AI-enabled devices due to affordability issues.

Ans: access

AI access highlights the disparities in the availability of AI technologies, often influenced by economic factors that limit affordability.

True or False

Ans: True

Deep Learning is indeed considered the most advanced subset of Artificial Intelligence, distinguishing itself from traditional Machine Learning through its use of neural networks and large data sets.

Q.2: All smart devices are powered by Artificial Intelligence.

Ans: False

Not all smart devices utilize Artificial Intelligence; some operate on basic programming and do not have the capability to learn or adapt.

Q.3: Data privacy concerns arise because smartphones collect data through apps with user permissions.

Ans: True

Data privacy issues are indeed a concern, as smartphones gather personal information through apps that require user permissions, often leading to unintentional data sharing.

Q.4: AI bias can only be introduced intentionally by developers.

Ans: False

AI bias can occur unintentionally due to biased training data or flawed algorithms, not solely from intentional actions by developers.

Q.5: AI can help solve societal issues but also poses challenges like job displacement.

Ans: True

While AI has the potential to address various societal challenges, it also raises significant concerns regarding job displacement and changes in the workforce.

Short Answer Questions

Q.1: What is the role of data in enabling Artificial Intelligence?
Ans: Data is essential in AI as it is used to train machines, enabling them to learn, analyze patterns, and make decisions by processing and deriving insights from large datasets.

Q.2: What is the difference between Machine Learning and Deep Learning?
Ans: Machine Learning enables machines to learn from data and improve with experience, while Deep Learning, a subset of ML, uses vast data and neural networks to train itself and develop algorithms autonomously.  

Q.3: How does Computer Vision contribute to AI applications?
Ans: Computer Vision enables machines to analyze and interpret visual data, such as images or videos, to make decisions, as seen in self-driving cars and face lock systems in smartphones.  

Q.4: Why is data privacy a concern in AI-enabled smartphones?
Ans: Smartphones collect data through app permissions, using sensors to track user behavior, which raises privacy concerns when apps access and share this data without full user awareness.  

Q.5: What is AI bias, and how does it occur?
Ans: AI bias occurs when algorithms produce prejudiced results due to biases in training data or developer assumptions, such as virtual assistants defaulting to female voices.  

Long Answer Questions

Q.1: Explain the three main domains of AI and provide one example for each.
Ans: The three main domains of AI are Data Sciences, Computer Vision, and Natural Language Processing. Data Sciences involves collecting and analyzing data to derive insights, like price comparison websites (e.g., PriceGrabber). Computer Vision enables machines to interpret visual data, such as self-driving cars analyzing road objects. Natural Language Processing allows machines to understand and respond to human language, as seen in smart assistants like Siri processing voice commands.  

Q.2: Discuss the ethical concerns related to self-driving cars.
Ans: Self-driving cars raise ethical concerns about decision-making in critical situations, such as choosing between hitting a pedestrian or crashing to protect the passenger, challenging the developer’s moral priorities. Additionally, determining responsibility in accidents—whether the car owner, manufacturer, or algorithm developer—is complex, as perspectives vary, requiring careful consideration of accountability and safety in AI design.  

Q.3: Describe how data privacy issues arise in AI-enabled smartphones with examples.
Ans: Data privacy issues in AI-enabled smartphones arise because apps collect data through permissions, accessing sensors to track user behavior. For example, discussing shoes with a friend may trigger shoe purchase notifications, or searching for a trip may prompt travel ads. These occur as apps use data from conversations or searches, often without full user awareness, raising concerns about unauthorized data sharing.  

Q.4: Analyze the concept of AI bias with examples and suggest ways to mitigate it.
Ans: AI bias occurs when algorithms reflect developer or data biases, leading to prejudiced outcomes. Examples include virtual assistants using female voices due to assumed user preference or search results prioritizing female salons. To mitigate, developers should use diverse, representative datasets, ensure transparency in algorithm design, and regularly audit systems to identify and correct biases, promoting fairness.  

Q.5: Evaluate the impact of AI access disparities and their potential consequences for society.
Ans: AI access disparities create a gap between those who can afford AI-enabled devices and those who cannot, leading to unequal opportunities. This may cause unemployment for low-skilled laborers as AI automates tasks, while skilled individuals benefit. Adapting to technology through skill development is crucial to bridge this gap, ensuring equitable societal progress and minimizing economic divides.