AAISM Practice Questions

A.  

Enhancing the accuracy of predictions to desired levels

B.  

Increasing model training speed for an efficient launch

C.  

Protecting individual data contributions while allowing statistical analysis

D.  

Reducing computational resources required for the model training phase

A.  

Talking through a decision tree to better understand how the algorithm made each of its choices

B.  

Publishing AI mechanisms, data sources, and decision-making processes while making them openly available

C.  

Explaining the AI system in an understandable and logical way so reasons for decisions can be given

D.  

Persuading someone that the AI tool in use is beneficial and operates as expected

A.  

Risk exposure due to bias in AI outputs is kept within an acceptable range

B.  

Ethical standards are incorporated into security awareness programs

C.  

Management is prepared to disclose AI system architecture to stakeholders

D.  

Responsibility is defined for legal actions related to AI regulatory requirements

A.  

Model ensemble techniques

B.  

AI threat modeling

C.  

Differential privacy

D.  

Cybersecurity-oriented red teaming

A.  

Inputting encrypted data into the model

B.  

Adding noise to output predictions

C.  

Stealing model weights from a deployed API

D.  

Corrupting training data sets to manipulate outcomes

A.  

Bias minimization

B.  

Access controls and secure storage solutions

C.  

Transparent disclosure and informed consent

D.  

Data anonymization