The Bias in AI

TOGETHER FOR A BETTER FUTURE FOR OUR CHILDREN

/LISUAE

Lesson Objectives:
Students will be able to:

●By the end of the lesson, students will
be able to discuss the concept of bias
and fairness in AI and identify
examples of bias in AI systems.

Key Points:

- Bias refers to the unfair or unequal
treatment of individuals or groups based on
certain characteristics.
- AI systems can exhibit bias if they are
trained on biased data or programmed with
biased algorithms.
- Bias in AI can lead to unfair outcomes and
perpetuate societal inequalities.
- Fairness in AI involves designing and
developing AI systems that minimize bias
and ensure equitable treatment.
- It is important to critically analyze and
evaluate AI systems for potential biases.
Subject Competencies
1.1 Analyze the ethical and social implications of AI

a Bias and fairness in AI

Grade 12 - IT

Understanding Bias and Fairness in AI.

TOGETHER FOR A BETTER FUTURE FOR OUR CHILDREN

/LISUAE

Lesson Objectives:
Students will be able to:

●By the end of the lesson, students will
be able to discuss the concept of bias
and fairness in AI and identify
examples of bias in AI systems.

Key Points:

- Bias refers to the unfair or unequal
treatment of individuals or groups based on
certain characteristics.
- AI systems can exhibit bias if they are
trained on biased data or programmed with
biased algorithms.
- Bias in AI can lead to unfair outcomes and
perpetuate societal inequalities.
- Fairness in AI involves designing and
developing AI systems that minimize bias
and ensure equitable treatment.
- It is important to critically analyze and
evaluate AI systems for potential biases.
Subject Competencies
1.1 Analyze the ethical and social implications of AI

a Bias and fairness in AI

Watch this Video and answer the questions

AI in Our life

Multiple Choice

Starter: 1. According to the video, what is one way artificial intelligence can develop bias?

• a) From its creators and programmers

• b) From the data fed into it

• c) From its learning experiences

• d) From the language itself

Multiple Choice

Starter: How does the AI translation program show bias?

• By translating genderless terms differently based on gender

• By associating female names with career terms

• By accurately reporting gender distribution in jobs

• By learning prejudices from society

TOGETHER FOR A BETTER FUTURE FOR OUR CHILDREN

/LISUAE

Lesson Objectives:
Students will be able to:

●By the end of the lesson, students will
be able to discuss the concept of bias
and fairness in AI and identify
examples of bias in AI systems.

Key Points:

- Bias refers to the unfair or unequal
treatment of individuals or groups based on
certain characteristics.
- AI systems can exhibit bias if they are
trained on biased data or programmed with
biased algorithms.
- Bias in AI can lead to unfair outcomes and
perpetuate societal inequalities.
- Fairness in AI involves designing and
developing AI systems that minimize bias
and ensure equitable treatment.
- It is important to critically analyze and
evaluate AI systems for potential biases.
Subject Competencies
1.1 Analyze the ethical and social implications of AI

a Bias and fairness in AI

Key Points

●

Bias refers to unfair treatment
based on certain characteristics.

●

AI systems can exhibit bias if
trained on biased data or
programmed with biased
algorithms

●

Bias in AI can lead to unfair
outcomes and perpetuate
societal inequalities.

TOGETHER FOR A BETTER FUTURE FOR OUR CHILDREN

/LISUAE

Lesson Objectives:
Students will be able to:

●By the end of the lesson, students will
be able to discuss the concept of bias
and fairness in AI and identify
examples of bias in AI systems.

Key Points:

- Bias refers to the unfair or unequal
treatment of individuals or groups based on
certain characteristics.
- AI systems can exhibit bias if they are
trained on biased data or programmed with
biased algorithms.
- Bias in AI can lead to unfair outcomes and
perpetuate societal inequalities.
- Fairness in AI involves designing and
developing AI systems that minimize bias
and ensure equitable treatment.
- It is important to critically analyze and
evaluate AI systems for potential biases.
Subject Competencies
1.1 Analyze the ethical and social implications of AI

a Bias and fairness in AI

Fairness in AI

●

Fairness involves designing AI systems
that minimize bias and ensure equitable
treatment.

●

It is essential to critically analyze and
evaluate AI systems for potential
biases.

TOGETHER FOR A BETTER FUTURE FOR OUR CHILDREN

/LISUAE

Lesson Objectives:
Students will be able to:

●By the end of the lesson, students will
be able to discuss the concept of bias
and fairness in AI and identify
examples of bias in AI systems.

Key Points:

- Bias refers to the unfair or unequal
treatment of individuals or groups based on
certain characteristics.
- AI systems can exhibit bias if they are
trained on biased data or programmed with
biased algorithms.
- Bias in AI can lead to unfair outcomes and
perpetuate societal inequalities.
- Fairness in AI involves designing and
developing AI systems that minimize bias
and ensure equitable treatment.
- It is important to critically analyze and
evaluate AI systems for potential biases.
Subject Competencies
1.1 Analyze the ethical and social implications of AI

a Bias and fairness in AI

Examples of bias in AI systems

Bias in Natural Language Processing:

Some natural language processing models may be susceptible to bias in
interpretation and analysis because they may have been trained on text data
that contains specific biases or concepts.

Bias in Online Recruitment:

In online job recruitment platforms, artificial intelligence algorithms may filter
resumes and select candidates. If these algorithms are trained on data
containing past hiring biases, candidates may be chosen unfairly.

Bias in Search Engines:
●Occasionally, biases may appear in search engine results due to how
algorithms classify web content. This can lead to the promotion of certain
sources or the disregard of others.

Multiple Choice

In the context of AI, fairness refers to:

• Promoting the use of biased training data

• Designing AI systems to minimize bias and provide equitable treatment

• Ensuring that AI systems prioritize certain groups

• Treating everyone the same way regardless of their background

Multiple Choice

What is bias in the context of AI?

•    a. A technical glitch in AI algorithms

    

•  b. A preference for certain groups over others based on characteristics

     

• c. An AI's ability to make objective decisions

•    d. The speed at which AI processes data

Multiple Choice

Which of the following is an example of algorithmic bias in AI?

 

• An AI system that accurately identifies fraudulent transaction

• An AI system that improves its performance over time

• An AI system that prefers job applicants from certain universities

• An AI system that operates at a high speed

Multiple Choice

How can bias enter AI systems?

•    a. Through the use of objective data sources

•    b. Through the diverse backgrounds of AI developers

•   c. Through biased training data or algorithms

•    d. Through regular audits of AI systems

Multiple Choice

How can AI developers mitigate bias in their systems?

• By rushing the development process

• By promoting the use of biased training data

• By regularly evaluating and addressing bias in their algorithms

• By ignoring the diversity of data sources

TOGETHER FOR A BETTER FUTURE FOR OUR CHILDREN

/LISUAE

Lesson Objectives:
Students will be able to:

●By the end of the lesson, students will
be able to discuss the concept of bias
and fairness in AI and identify
examples of bias in AI systems.

Key Points:

- Bias refers to the unfair or unequal
treatment of individuals or groups based on
certain characteristics.
- AI systems can exhibit bias if they are
trained on biased data or programmed with
biased algorithms.
- Bias in AI can lead to unfair outcomes and
perpetuate societal inequalities.
- Fairness in AI involves designing and
developing AI systems that minimize bias
and ensure equitable treatment.
- It is important to critically analyze and
evaluate AI systems for potential biases.
Subject Competencies
1.1 Analyze the ethical and social implications of AI

a Bias and fairness in AI

Plenary: Check your understanding

Question : In the context of AI in healthcare diagnostics, what ethical
consideration is of utmost importance?

Open Ended

Plenary: In the context of AI in healthcare diagnostics,
What ethical consideration is of utmost importance?

Poll

Did you understand the lesson?

• Yes

• No