Context
To solve the issues the Comptroller and Auditor General (CAG) encounters, ethical AI must be applied in auditing.
 
Integrity and Diversity in AI for Trustworthy Auditing 
• Ethical AI Foundation: The Comptroller and Auditor General's (CAG) audits must be scalable, trustworthy, and credible.
• Data Quality Assurance: Accurate, timely, thorough, and relevant data are necessary to prevent incorrect audit conclusions.
When using data from unreliable sources, such as social media, which is prone to both bias and data manipulation, caution must be exercised.

Regulation of AI Is Needed, and International Examples  
• EU AI Act: According to the EU's AI laws, social scoring and biometric tracking are prohibited, and developers must acquire permission before putting AI goods on the market.
• Intellectual property issues: AI-generated content raises questions regarding infringement of copyright and other intellectual property rights.
• Global AI safety initiatives: Elon Musk's "Truth GPT" and the UK Prime Minister's AI safety regulation emphasise the challenges and importance of ethical AI.
 
Challenges in AI Auditing 
• Data standardisation: Due to issues with data integration, CAG must synchronise with other government organisations.
• It's crucial to increase capacity since auditors must be familiar with AI technology and collaborate closely with data specialists.
• Examples of compliance and risk management include adopting frameworks for AI auditing, addressing hazards specific to the AI domain, and ensuring data security and privacy.
 
LTX Mains Question
Q. Talk about the role moral AI plays in auditing processes and the challenges auditors must overcome to adopt this technology.