Marketers can mitigate AI biases by relying on different, complementary models for richer insights.
This article states that AI biases can be mitigated by maintaining the right level of human interaction across the marketing chain while carefully examining the data sources. The author argues that marketers often assume their data represents the whole industry, thereby resulting in AI algorithms that are heavily biased to the past.
Likewise, early-phase box-office models rely on how similar films have fared. Historically, Hollywood has favoured “white, male films” and not been truly representative of minorities. Such in-built biases prevent algorithms from accurately assessing the value of films.
Analysts must gather industry-standard survey panel reports to track audience awareness and intent to train algorithms to predict box-office success. Further, marketers must maintain consistent human involvement to mitigate AI biases.
[3 minute read]