AI is a powerful tool in many industries. With increased public awareness of AI technology, some raised AI ethical problems. One of their concern is AI bias. While AI bias is considered harmful, marketers are actually benefited from it.
How is AI bias formed?
The origin of AI bias can be traced back to the training stage of AIs. Before AI systems can be used to make decisions, they needed to be trained using sets of data. Most AIs are trained with a machine learning method called supervised learning. In supervised learning, engineers feed the AI with labelled datasets. AI depends on the labels in the datasets to classify data. However, the training datasets may not be comprehensive. It may contain features that can lead the systems to specific results. As a result, the trained AI may perform excellently on certain types of data and poorly on other data. This phenomenon is called AI bias and it comes from the training datasets. In other words, the AI itself does not establish bias. It is man-made. AI face recognition system in western countries could be one of the typical examples. Those systems are often trained with the facial data of white people meaning that the AI is explicitly familiar with the facial characteristics of white people. In this case, the system may not work well on recognizing people in other races. So, how is AI bias helping marketing? While people are having concerns about the consequences of AI bias, some brilliant marketers are taking advantages from AI bias. enabling them to obtain useful information quicker compare with an absolutely neutral AI. In fact, marketers do not need an absolutely neutral AI which is different from the public's demand for neural AIs. An absolutely neutral AI needs more time to understand the preferences of an individual, leading to dissatisfactions due to inaccuracy of the AI performance. On the other hand, marketers may train the AI with data that is similar to the target customers. When the AI model is later used in serving the actual target customers, the model can provide excellent performance even from the start. The utilization of AI bias improves AI's performance for marketing purposes. Moreover, the use of AI bias can reduce the costs of deploying the AI since the collection of unbiased data is pricy. Still, it's inevitable that AI bias may cause bad effect on marketing... After all, marketers should still be aware of the AI bias being used. Unrecognized bias in AI systems may cause undesired impacts such as missing potential customer niches. The bias in the systems may also stop marketers from obtaining more applicable insights. One possible solution to optimize AI's performance is to refine the data collection. Marketers could optimize AI's performance by refining the data collection or the AI model. To refine the data collection, marketers can apply an A/B test on data sources allowing marketers to examine the impact of different data sources on AI. Hence, marketers can determine the suitable data source that can lead to better AI performance. References: AI bias is not always bad in marketing (campaignlive.co.uk) Don’t Let AI Bias Derail Your Marketing Efforts - Chief Marketer What is Supervised Learning? | IBM 
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