What is the impact of bias in training data on applicants?

• Privacy rights

• Unfair discrimination

• Mistrust among employees

• Inaccurate hiring decisions

What does the risk management framework aim to address?

• Unintended consequences

• Stakeholder engagement

• Project timelines

• Budget constraints

What is a part of the data and risk management framework that involves checking and verifying processes?

• Audit

• Ignoring incidents

• Reducing transparency

• Increasing production

What is a response to incorrect outputs due to an inaccurate or biased model?

• Implement differential privacy

• Identify sources of bias with stakeholders

• Data anonymisation

• Legal compliance

What is a key consideration when developing AI models to prevent bias?

• Maximizing processing speed

• Reducing model complexity

• Focusing solely on accuracy

• Ensuring diverse data representation

Which method can be used to detect bias in AI systems?

• Increasing data volume

• Ignoring data anomalies

• Focusing on user feedback

• Conducting regular audits

What is a potential risk of using biased data in AI models?

• Enhanced user satisfaction

• Increased model accuracy

• Perpetuation of existing inequalities

• Improved decision-making

What is an effective strategy to mitigate bias in AI decision-making?

• Prioritizing speed over accuracy

• Reducing stakeholder involvement

• Implementing transparency measures

• Relying on historical data

What is a key practice to promote ethical AI development?

• Disregarding ethical guidelines

• Implementing transparency measures

• Prioritizing profit over ethics

• Relying solely on automation

What is a key practice for maintaining transparency in AI systems?

• Withholding performance metrics

• Disregarding ethical guidelines

• Providing comprehensive documentation

• Obscuring decision-making criteria