APCSP Active Reading on Data Bias

Last updated 5 months ago

15 questions

Note from the author:

This is an quiz will be based on the web page link that has been attached, please answer these question using full and well structured sentences. Attempt it at a time that is convenient for you.

IBM AI BIAS

Instructions

This is an quiz will be based on the web page link that has been attached, please answer these question using full and well structured sentences. Attempt it at a time that is convenient for you.

IBM AI BIAS

APCSP Active Reading on Data Bias

Last updated 5 months ago

15 questions

Note from the author:

This is an quiz will be based on the web page link that has been attached, please answer these question using full and well structured sentences. Attempt it at a time that is convenient for you.

IBM AI BIAS

Instructions

This is an quiz will be based on the web page link that has been attached, please answer these question using full and well structured sentences. Attempt it at a time that is convenient for you.

IBM AI BIAS

What is AI bias, and how does it typically occur?

APCSP Active Reading on Data Bias

APCSP Active Reading on Data Bias

What is AI bias, and how does it typically occur?

Why is it important for organizations to address AI bias?

How can AI bias affect businesses and their reputation?

What are some of the social impacts of AI bias on marginalized groups?

Describe one example of AI bias in healthcare mentioned in the reading.

What did the Bloomberg study reveal about AI-generated images, and what biases were identified?

How can AI-powered predictive policing tools perpetuate existing biases in the criminal justice system?

Explain what is meant by “algorithm bias” and how it can occur.

What is “exclusion bias,” and how might it affect AI outcomes?

List two principles for avoiding AI bias and explain their significance.

Why is it crucial to train AI systems with the right data, and what should this data include?

Why should a diverse team be involved in the AI development process, and what perspectives should be considered?

Discuss how historical data can embed societal biases into AI systems.

Why is it not always effective to simply remove protected classes (such as race or gender) from AI training data?

Final question, is it possible to completely prevent data bias in your data collection, analysis, or Ai models. Why or Why not?

What is AI bias, and how does it typically occur?

Why is it important for organizations to address AI bias?

How can AI bias affect businesses and their reputation?

What are some of the social impacts of AI bias on marginalized groups?

Describe one example of AI bias in healthcare mentioned in the reading.

What did the Bloomberg study reveal about AI-generated images, and what biases were identified?

How can AI-powered predictive policing tools perpetuate existing biases in the criminal justice system?

Explain what is meant by “algorithm bias” and how it can occur.

What is “exclusion bias,” and how might it affect AI outcomes?

List two principles for avoiding AI bias and explain their significance.

Why is it crucial to train AI systems with the right data, and what should this data include?

Why should a diverse team be involved in the AI development process, and what perspectives should be considered?

Discuss how historical data can embed societal biases into AI systems.

Why is it not always effective to simply remove protected classes (such as race or gender) from AI training data?

Final question, is it possible to completely prevent data bias in your data collection, analysis, or Ai models. Why or Why not?