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Data bias is an emerging risk but few organizations are currently addressing it

Progress has announced the results of a global study, ‘Data Bias: The Hidden Risk of AI’. Conducted by independent research firm, Insight Avenue, the report is based on interviews with more than 640 business and IT professionals at director level and above, who use data to make decisions and are using or plan to use artificial intelligence (AI) and machine learning (ML) to support their decision making. Respondents were based in the Americas, Europe, and Asia.

Biases are often inherited by cultural and personal experiences. When data is collected and used in the training of machine learning models, the models inherit the bias of the people building them, producing unexpected and potentially harmful outcomes. Yet, despite the potential legal and financial pitfalls associated with data bias, there is a lack of understanding around the training, processes and technology needed to tackle data bias successfully. 

The Progress survey indicated that 78 percent of business and IT decision makers believe data bias will become a bigger concern as AI/ML use increases, but only 13 percent are currently addressing it and have an ongoing evaluation process. The biggest barriers they see are lack of awareness of potential biases, understanding how to identify bias as well as the lack of available expert resources, such as having access to data scientists. 

The survey findings also show that:

  • 66 percent of organizations anticipate becoming more reliant on AI/ML decision making, in the coming years.
  • 65 percent believe there is currently data bias in their organization.
  • 77 percent believe they need to be doing more to address data bias.
  • 51 percent consider lack of awareness and understating of biases as a barrier to addressing it.

More details (PDF).



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