In recent years, there has been a significant change in how we connect with technology. A big part of the internet experience includes prediction models. They offer suggestions for what to watch, read, buy, or listen to next. We are constantly being bombarded with recommendations from what to watch on Netflix or YouTube to what products we should buy on Amazon or Walmart — all generated by algorithms that have been trained on vast data sets of user behavior patterns.

The power over our decisions is not without consequence. Algorithmic Anxiety is a phenomenon in which people worry about how AI will affect our interactions with technology in the future. It is a fear that the algorithms that control our lives will eventually take over and make decisions for us. Many people believe that these algorithms can be biased and can also be hacked, causing them to malfunction or make bad decisions. 

What Does an Algorithm Do?

An algorithm finds patterns in data, and it uses those patterns to make decisions about things. Algorithms use heuristics and rules of thumb; they work well for some things but can also make bad decisions.

Causes of Algorithmic Anxiety

Algorithmic Anxiety is the feeling of unease or discomfort when interacting with an AI system. People frequently experience this when a machine-learning system is being used to make decisions. Algorithms are not only used in online services but also everyday life and people are increasingly more dependent on them to make decisions for them. If you’re unaware, the concept of the “Quantified Self,” which involves recording health data for self-awareness, is now a dominant contributor to algorithmic anxiety. The data acquired by this self-tracking activity is typically accessible to commercial, governmental, research, and marketing organizations.

Algorithmic Anxiety Impacting Customer Purchase Behavior

Algorithms have a huge impact on customer purchase behavior. In the past, these algorithms were used to analyze their purchasing habits. Nowadays, they are used to track and predict their future behavior. This is done by analyzing their browsing and buying history. As a result of this, customers feel insecure and disempowered as algorithms make decisions for them. Online marketplaces use algorithms to determine the best offers. What they know is that some products sell better during certain seasons or periods, and have certain costs. For example, it is easier to sell dresses during the springtime because people are more likely to be getting married or buying them for a debutante ball. As a result, in-season items are often offered at a lower price. Conscious consumers are actively avoiding marketplace or stores that employ algorithm recommender systems to stay safe from the related anxiety. Consumers are trying to find ways how to avoid the algorithm recommender system impact. As a result, they are shifting their shopping behaviors to minimize the likelihood of being affected by the algorithm.

How Marketers Should Respond to Algorithmic Anxiety?

Marketers should understand that Algorithmic anxiety is a result of the lack of transparency and control over the information. Marketers can help customers overcome this anxiety by providing them with more transparency in the form of access to their data. It is a better idea for businesses to work with consumers to come up with personalized product recommendations, rather than relying on algorithms alone.

Through intelligent technologies that learn from previous interactions and individual needs, customer services would be able to provide customers with more personalized content. However, a human touch will foster trust more so than a chatbot.

One of the ways marketers can respond is by creating a ‘product bundle.’ Product bundling is a marketing tactic in which several products are packaged together and offered for sale as a single item. This way, people are not just buying a product but also getting some other items with it. Purchasing a bundle is one of the ways customers most often try to circumvent the algorithm. Customers appear to have a lower chance of being tracked when they buy a set of pre-selected products.

Computer programmers and the public in general have divergent views on the kinds of values that algorithms should provide. While some argue that algorithms ought to be objective, others believe they are by nature subjective. A 2020 McKinsey & Company research makes the case that businesses should place a higher value on people than revenue. The new digital divide in that context is between those who oppose algorithms and those who do not.

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