Artificial Intelligence (AI) MCQs – Part 5

Timer: Off
Random: Off

1. Which approach can help mitigate bias in AI algorithms by involving diverse stakeholders in the development process?
ⓐ. Excluding stakeholders with conflicting interests
ⓑ. Conducting bias detection after deployment
ⓒ. Implementing automated bias mitigation techniques
ⓓ. Engaging in inclusive and participatory design practices
2. What is one of the risks associated with bias in AI algorithms in criminal justice systems?
ⓐ. Increased efficiency in sentencing decisions
ⓑ. Reduced disparities in incarceration rates
ⓒ. Reinforcement of racial or socioeconomic biases
ⓓ. Enhanced rehabilitation and recidivism prevention
3. Which step is essential in addressing bias in AI algorithms in healthcare applications?
ⓐ. Using demographic information as a primary input for decision-making
ⓑ. Ensuring representation of diverse populations in training data
ⓒ. Ignoring potential biases to prioritize efficiency
ⓓ. Limiting access to AI-generated healthcare recommendations
4. What is one of the potential consequences of bias in AI algorithms in financial services?
ⓐ. Increased financial inclusion and access to credit
ⓑ. Enhanced accuracy in risk assessment
ⓒ. Reinforcement of socioeconomic disparities and exclusion
ⓓ. Improved transparency and fairness in lending decisions
5. Which approach can help mitigate bias in AI algorithms by incorporating fairness constraints into the model development process?
ⓐ. Ignoring fairness concerns to prioritize accuracy
ⓑ. Applying post-hoc bias detection techniques
ⓒ. Implementing diversity and inclusion training programs
ⓓ. Designing algorithms with fairness-aware objectives and metrics
6. What is one of the challenges in addressing bias in AI algorithms in social media platforms?
ⓐ. Limited availability of user data for bias detection
ⓑ. Lack of transparency in algorithmic decision-making processes
ⓒ. Resistance from platform users to address bias concerns
ⓓ. Inability to measure the impact of biased algorithms on user behavior
7. What is one of the primary concerns regarding data privacy when using AI?
ⓐ. Ensuring the accuracy of AI predictions
ⓑ. Protecting sensitive personal information from unauthorized access
ⓒ. Optimizing AI algorithms for efficiency
ⓓ. Increasing transparency in AI decision-making processes
8. Which approach can help address data privacy concerns when collecting and storing personal data for AI applications?
ⓐ. Sharing personal data with third-party vendors for analysis
ⓑ. Implementing strong encryption techniques to protect data in transit and at rest
ⓒ. Selling personal data to advertisers for targeted marketing
ⓓ. Storing personal data in unsecured databases to improve accessibility
9. What is one of the risks associated with data privacy concerns in AI applications?
ⓐ. Enhanced user trust and confidence in AI systems
ⓑ. Increased vulnerability to identity theft and fraud
ⓒ. Improved accuracy and effectiveness of AI predictions
ⓓ. Greater transparency in AI decision-making processes
10. Which step is essential in addressing data privacy concerns when deploying AI systems that handle personal data?
ⓐ. Collecting and storing as much personal data as possible for future use
ⓑ. Obtaining explicit consent from individuals before collecting their personal data
ⓒ. Sharing personal data with external partners and vendors without restrictions
ⓓ. Using personal data for purposes unrelated to the original consent
Subscribe
Notify of
guest
1000


0 Comments
Inline Feedbacks
View all comments
0
Join Discussionsx
()
x