More than two-thirds (68%) of organizations in Singapore are aware of the problem about data bias, but addressing the problem still proves elusive, according to research findings from Progress.
The application development and infrastructure software tapped independent research firm Insight Avenue to survey 640 business and IT professionals, 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.
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.
Findings show that 74% of Singaporean business and IT decision makers believe data bias will become a bigger concern as AI/ML use increases, but only 16% 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 also found that 58% of organisations anticipate becoming more reliant on AI/ML decision-making, in the coming years, and 68% believe there is currently data bias in their organisation.
Also, 74% believe they need to be doing more to address data bias, and 48% consider lack of awareness and understating of biases as a barrier to addressing it.
“Bias can be a serious detriment to growth,” said John Yang, VP for Asia Pacific and Japan at Progress. “Indeed, one in two Singaporean businesses cite eroding customer trust as the biggest implication of unchecked data bias.”
“Local organisations are also worried about lost financial opportunities (48%) as well as security and governance risks (38%),” said Yang.
Results are also based on interviews with business and IT professionals located across the Americas, Europe and Asia, focused on the use of data in decision making.
These professionals come from organisations with over 500 employees to better understand the overall awareness of data bias, how it was impacting businesses and what companies were doing to address it.
