Hidden Ethical Dilemmas of Ai

What is bias in AI algorithms?

• A) A way to make predictions

• B) A reflection of existing societal biases

• C) A method to improve fairness

• D) A tool to collect data

2. How can algorithm design lead to bias?

• A) By ignoring past data

• B) By using random data sets

• C) By making algorithms too simple

• D) By using biased data for training

3. What is a potential effect of bias in AI systems?

• A) Faster computation

• B) More accurate predictions

• C) Unfair or discriminatory outcomes

• D) Better data collection

4. How does Machine Learning (ML) help AI predict the future?

• A) By analyzing historical data for patterns

• B) By randomly guessing outcomes

• C) By avoiding data processing

• D) By using facial recognition software

5. What is one method used in Deep Learning (DL)?

• A) Random number generation

• B) Using neural networks to process data

• C) Ignoring data layers

• D) Direct analysis without patterns

6. What is a solution to reduce bias in AI systems?

• A) Using random data

• B) Designing algorithms without fairness in mind

• C) Making training data more diverse

• D) Ignoring the data completely

7. Which of the following is an advanced form of Machine Learning used to predict future events?

• A) Deep Learning (DL)

• B) Data Preprocessing

• C) Manual coding

• D) Random sampling