AI Ethics Framework

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Match the type of AI system with its corresponding risk level:

Spam filters = Little or no risk Technical programs = Limited risk Social profiling systems = Unacceptable risk AI systems affecting basic rights = High risk

Match the type of AI system with its corresponding assessment requirement:

AI systems with little or no risk = No assessment required AI systems with limited risk = Application of ethics principles AI systems with high risk = Pre- and post-conformity assessments AI systems with unacceptable risk = No development or use allowed

Match the AI stakeholder with its corresponding scope:

Public entities = Within KSA Private entities = Within KSA Non-profit entities = Within KSA Consumers = Within KSA

Match the AI ethics principle with its corresponding application:

AI ethics principles = Limited risk AI systems Statutory requirements = High risk AI systems Ethical compliance = Little or no risk AI systems Pre-conformity assessments = Unacceptable risk AI systems Signup and view all the answers

Match the AI principles with their corresponding descriptions:

Principle 1 = Requires AI systems to be built in a safe way that respects the privacy of the data collected and upholds the highest levels of data security processes and procedures. Principle 2 = Requires AI systems to be trained on data that are cleansed from bias and is representative of affected minority groups. Signup and view all the answers

Match the type of AI system with its corresponding consideration:

AI systems with little or no risk = Recommended ethical compliance AI systems with limited risk = Application of ethics principles AI systems with high risk = Consideration of statutory requirements AI systems with unacceptable risk = No development or use allowed Signup and view all the answers

Match the biases that may occur with their corresponding reasons:

Data bias = Due to data, representation or algorithms Representation bias = Due to data limitations Algorithm bias = Due to the composition of algorithms Signup and view all the answers

Match the principles with their corresponding goals:

Principle 1 = To ensure AI systems that are private and secure Principle 2 = To ensure AI systems that are fair and unbiased Signup and view all the answers

Match the consequences of not following the principles with their corresponding outcomes:

Discrimination against historically disadvantaged groups = Not following Principle 1 Data and system breaches = Not following Principle 2 Reputational harm = Not following Principle 1 Psychological harm = Not following Principle 2 Signup and view all the answers

Match the actions required with their corresponding principles:

Ensuring just, fair, non-biased, non-discriminatory and objective standards = Principle 1 Building AI systems in a safe way that respects the privacy of the data collected = Principle 2 Training AI systems on data that are cleansed from bias = Principle 1 Designing AI systems with mechanisms and controls to govern and monitor their outcomes = Principle 2 Signup and view all the answers