Chief Marketer: Don’t Let AI Bias Derail Your Marketing Efforts
More and more marketers are adding artificial intelligence (AI) to their toolbox of late, and with good reason. AI promises significant automation of workflows and intellectual processes, and to a great extent, it delivers on that promise. However, it’s crucial that marketers not lose sight of the fact that AI is not magical or omnipotent.
The algorithms behind AI are beholden to the integrity—or lack thereof—in the measurements and datasets used to train them. If a model is trained to predict future states of the market, the data it is built with must be representative of that market. Unfortunately, this is often not the case. As a result, algorithms risk becoming as biased as their constituent data sets. Left unaddressed, such errors and inconsistencies can cascade through an entire marketing strategy and severely hobble its performance. Among the numerous potential pitfalls to monitor, AI bias often remains the most undetectable, and therefore, dangerous. The best way to mitigate this bias is by maintaining the right level of human interaction throughout the marketing chain while applying healthy scrutiny to data sources.
The Danger of Relying on Internal Data
Bias issues increase exponentially when marketers rely primarily on their own data to train their algorithms. This is increasingly common across many industries (due at least in part to growing privacy restrictions) and is particularly evident in the movie industry.
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