People believe that data is fair and accurate; bias only enters the equation when humans interpret it. However, the reality is more convoluted, since data itself is always biased.

Interestingly, datasets always bear the marks of history, the history carved by humans with humanly frailties and biases. The danger is not necessarily bias itself; it is disregarding bias and not minimizing it. It is essential to analyze how bias gets into datasets. Bias exists because humans, who are the decision-makers around who or what that data represents, generate data.

Many instances of artificial intelligence bias have brought humans to realize the critical nature of ethics in AI. For AI to aid technological development, it must be grounded in empathy, aligning with morals and ethics. It is recommended to have diversity in the set of researchers to mitigate the risk of bias creation.

AI needs to be built up in a way to earn trust, designed with protections for inclusiveness, fairness, transparency, accountability, reliability and safety, and privacy. People must remain vigilant about assessing and continuing to address potential risks. This applies to marketers and marketing leaders as well, who need to understand the bias that lives within the datasets and to recognize that they might taint the outcomes from the machine learning models. It is impossible to remove bias from data entirely, but marketers must take steps to minimize and control it.

Marketers need to check for enough diversity in the data sets and in the individual researchers creating the data set. There should be enough diversity in the customer base as well. From a digital marketer’s standpoint, most search campaigns are biased. In case search campaigns are hyper created, there can be a potential loss of more diverse audiences.

In case marketers focus on bottom-of-funnel (BOFU) or top-of-funnel (TOFU) activity, then the search data becomes increasingly biased. A healthy search campaign constitutes the right mix of TOFU and BOFU activity to reach out to consumers throughout the multiple stages of the consumer decision journey.

Most of the search marketers concentrate on BOFU campaigns for good reasons like – remarketing and brand terms/phrases often deliver higher conversation rates and click-through rates. But there is a cost to biased data –possibly missing out on potential new customers who are unaware of the product or brand at the beginning of their search. Including broader, top-of-funnel keywords marketers can attract net-new customers and create a stronger overall customer portfolio by minimizing bias.

It is time for marketers to challenge their assumptions, redefine their strategies, and embrace empathy. Ultimately, all must be willing to accept the presence of biases and actively work towards minimizing it. Most importantly, marketers must create diverse, inclusive environments where team members are free to share their unique perspectives to drive a digital marketing campaign.