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7. What is the necessity for Ethical Frameworks in AI development?

Ans: An ethical framework for AI is vital to address the complexities and challenges that arise from the use of
AI systems.

F. Long answer type questions.

1. What are the key steps involved in the AI Project Cycle, and why is it necessary to follow a systematic
approach?

Ans: The AI Project Cycle comprises stages such as Problem Scoping, Data Acquisition, Data Exploration,
Modelling, Evaluation, and Deployment. Following a systematic approach ensures planning, organization,
and effective implementation of AI projects. Problem Scoping defines the problem, Data Acquisition
gathers necessary data, and Modelling analyses and trains the model, while Evaluation ensures
its efficiency before deployment. It is important to follow a systematic approach to ensure that the
developed AI model provides an efficient solution to benefit all stakeholders and avoids any pitfalls that
arise due to biased data.
2. How does Data Exploration contribute to the effectiveness of an AI project? What are the characteristics
of good quality data?
Ans: Data Exploration enhances project understanding by interpreting data characteristics. Good quality data is
crucial for effective outcomes. Characteristics of good data include accuracy, completeness, consistency,
and reliability. Exploring these ensures meaningful insights for building a successful AI model.

3. What is Natural Language Processing? Name any two real-life applications of NLP.
Ans: Natural Language Processing (NLP) deals with the interaction between computers and humans using the
natural language. The main objective of NLP is to read, interpret, understand natural language. Always
remember that the input and output data of an NLP system can be either voice or written text. For two
real life applications of NLP are, Google Translate and Email spam filters.

4. Write a short note on sector-based frameworks.
Ans: Sector-based frameworks are customised ethical guidelines and principles specifically designed to address
the unique challenges and considerations within particular industries or fields. These frameworks are
designed for specific sectors or industries.

5. Explain the principles of an AI ethical framework in brief.
Ans: The four main principles of an AI ethical framework are as follows:
a. Respect for autonomy: Respect for autonomy is a critical ethical principle that emphasises the importance
of allowing individuals to make informed decisions about their involvement in processes that affect
them.
b. Do not Harm: The Do not Harm principle depicts the importance of preventing harm to individuals and
society from the AI model in such a way that no negative consequences affect the various stakeholders
and the broader social context.
c. Maximum Benefit: Maximising the benefits of an AI-based tool involves a thoughtful approach that
prioritizes efficiency, personal experience, bias mitigation, and data-driven insights that may be in the
interest of all the stakeholders.
d. Justice: The principle of Justice in AI based model focuses on fairness, equity, and impartiality in the
model’s actions. It aims to ensure that all stakeholders have an equal opportunity share resources and
opportunities and decisions made by the AI system do not discriminate against individuals or groups
based on attributes such as race, gender, age, or disability.

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