Financial Crime World

Dependence on Technology May Lead to Blind Acceptance of AI Outcomes

The increasing reliance on artificial intelligence (AI) in various industries has raised concerns about the potential risks associated with its use. A recent report highlights the importance of understanding technology and data to avoid these risks.

The Risks of Blind Acceptance

Organizations that deploy AI systems without a comprehensive understanding of the technology and data they are using may be more likely to accept whatever outcomes their systems produce, potentially overlooking inaccurate or discriminatory decisions. This is because they may not have the ability or know-how to challenge the outputs generated by these machines.

Establishing Good Governance Frameworks

To mitigate this risk, organizations must establish good governance frameworks that set organization-wide guidelines for data management. This includes:

  • Ensuring employees across all business functions understand their data-related responsibilities and obligations around data privacy and security
  • Implementing robust data quality and protection measures
  • Developing strong controls to monitor AI systems and ensure data integrity

The Importance of Data Mapping and Sharing

Data mapping plays a crucial role in modern business operations, providing organizations with a deep understanding of how their data is being used, what it is being used for, and how data flows throughout the organization. Data sharing can also enhance transparency by allowing organizations to benefit from external input and highlighting data gaps.

Education is Key

Education is another critical aspect of an organization’s understanding of AI and data. A commitment to widespread education throughout the organization is essential to ensure that humans continue to play a crucial role in managing the data that feeds into AI and ensuring its meaningful use.

Integrating AI Requires Strategic Approach

The integration of AI requires more than just picking an AI solution. Organizations need to take a strategic approach, understanding business and financial crime risk exposure, and ensuring data integrity. This includes:

  • Implementing ongoing monitoring and testing
  • Investing in education and resources
  • Ensuring strong controls and robust data quality and protection

Conclusion

Dependence on technology may lead to blind acceptance of AI outcomes if organizations do not take the necessary steps to understand the technology and data they are using. Establishing good governance frameworks, implementing data mapping and sharing, and committing to education and training can help mitigate this risk and ensure that organizations harness the full potential of AI.

Sources:

  • European Parliament’s Artificial Intelligence Act
  • Kroll’s 2023 Fraud and Financial Crime Report