Technological advancements have enabled organisations across industries to weather the economic storm caused by the pandemic. The rapid advancement of technology, particularly the use of machine learning (ML) and artificial intelligence (AI), has enabled organizations to survive and, in some cases, thrive in today's economic landscape.
According to a recent PwC study, investment in AI has skyrocketed in the last year. Almost 86 percent of survey respondents said AI has become a standard technology in their company. While AI's growing list of applications is undeniable – from enabling organizations to effectively deal with complex and time-consuming repetitive tasks to identifying future growth opportunities – it is far from perfect. The perfect example of AI's disadvantage is 'ethics and bias.'
These two factors have drawn negative attention to AI from the general public. Face recognition technology, for example, appears to be biassed against dark-skinned and female individuals; racial and gender biases appear to be common. Other examples include AI recruiting tools that demonstrated bias against non-white candidates, candidates of a particular ethnicity, race, or language, and women, among many others.
Despite this criticism, many organizations are unable to address this issue. According to a recent FICO report, only 20% of businesses actively monitor their production models for fairness and ethics. Furthermore, 73 percent of survey respondents found it difficult to gain the support of their executive board for prioritizing AI ethics and tackling bias associated with it.