What do you understand by transparency in AI? Explain with the help of an example.

Transparency in AI refers to the transparency and openness for the decision-making processes of AI systems. Users and stakeholders should understand how AI systems work, make choices, and what data they utilise. Transparent AI systems allow for inspection, the identification and correction of biases, and the development of user trust.

Example: An example of transparency in AI may be reviewing loan applications and deciding eligibility. Transparency in this sense means providing explicit information about how the AI system reviews loan applications and decides creditworthiness. This involves revealing the elements and criteria taken into account, such as credit history, income, debt-to-income ratio, and other important characteristics. Transparent AI solutions also improve applicants' access to the decision-making process. If a loan application is declined, the AI system may deliver an explanation to the applicant, outlining the particular reasons for the decision and the elements that led to it.