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3. Assertion (A): AI Ethics involves a set of rules and principles related to AI systems.

Reason (R): AI-enabled systems raise complex ethical issues, requiring evaluation of what is right or
wrong.

4. Assertion (A): The principle of Beneficence implies that no person should be hurt or harmed due to
actions or decisions taken by an AI system.

Reason (R): The principle of Beneficence aims to maximise the benefits of the AI system for the
stakeholders.

AI Fun Zone
21st
Century Project-based Learning
Skills
Skills
Skills
1. Draw the AI Project Cycle for an AI model for a streaming app to recommend movies and shows to its
subscribers. Illustrate each stage with a brief description.
2. Create a PowerPoint presentation on Ethical Frameworks for AI. The presentation should touch upon the
following topics:
a. Need for Ethical Frameworks for AI

b. Various principles of AI Ethical Frameworks, giving an example of each.
c. Types of AI Ethical Frameworks
d. Short description of each type of AI Ethical Framework

Competency Based Questions

1. According to The New Your Times, Facebook users who viewed a video of black males were asked, “Would
you like to keep viewing videos of primates (apes and monkeys)?” after seeing the video. As a result, the
company disabled AI function that made the recommendation, apologised for the “unacceptable error”
and began an investigation into what went wrong. What do you think the company found as the reason
of this incident?
a. Gender Bias b. Biased Data Fed into the machine

c. Data Privacy d. Data Availability
2. Data about houses such as area in square footage, number of rooms, features, whether a house has a
garden or not, and the prices of these houses are fed into an AI system, along with corresponding labels.
By leveraging data coming from thousands of houses, their features and prices, we can now train the
model to predict a new house’s price. Which type of AI modelling is shown here?

a. Reinforcement learning b. Supervised learning
c. Unsupervised learning d. None of the above

3. Read the steps for collecting data from a source.
Step 1: Understand and inspect the web page to find the HTML markers associated with the information
we want.
Step 2: Use Python libraries to pull out data from the HTML page.

Step 3: Manipulate the collected data to get it in the form we need.

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