AI-Based Recommendation Systems Can Find New Link Between Unexplored Threats

The University of Texas as Dallas researchers have recently uncovered a strong link between examining the role of economic impacts between products that are designed and structured by AI-based recommendation systems. Furthermore, the team notes that the study revolves around the affected consumer’s decisions after the recommended product is undertaken. The team notes that millions and millions of pages are being indexed every time a user flips through recommendation based applications that are often auto-generated to begin with. These recommender systems are extensively used in the sector of retail, entertainment, social networking and more as the team quotes.

So far, the current format of research study is extensively based on the technical aspects of the algorithm that go behind suggesting recommendations. The research team essentially focuses on how consumer’s decisions are affected by the inner working of the algorithms that they are being manipulated with. These systems are often deemed attractive because of the huge impact they carry on the consumer and the incredibly helpful nature they are often associated with. The research team quote studies that verify more than 35% of Amazon users and 60% of Netflix users are generally in agreement with the recommendations that they are generally placed with.

These systems are generally functional on the user’s past purchase history, search pattern behaviors, surrounding demographics, and product ratings to pinpoint the user’s preferences and recommend a product or service that a user might buy or purchase. The team quotes that the concept of free exposure behind these recommendation systems are highly exploitable as new market spaces are being fed to the timeline of new incoming consumers. The team warns that consumers should choose their advertising approach and adopt a strict uniform pattern in order to not let the recommendation algorithms to actively target them in order to not overshadow the positive effect of the latter.

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