Explainable AI Can Assist Internet of Behavior Efforts

#Discussion(General) [ via IoTGroup ]

U.K.-based researcher Haya Elayan delved into the concept of Internet of Behaviors (IoB) and its integration with explainable artificial intelligence (XAI) algorithms to observe the impact of changing Internet of Things-related behavior. IoB is the confluence of Internet of Things (IoT) devices combined with advanced sensors, computer vision, facial recognition, other biometric indicators or location tracking, which, when added to insights from human psychology and data analysis, can influence, prompt or change human behavior—a powerful method.

The explainable approach also helps to overcome a common challenge in the use of IoB referred to as the ostrich effect. “There is a challenge for Internet of Behaviors called the ostrich effect, with people essentially being afraid,” she says. “And you may encounter resistance when you are trying to influence and change people’s behavior because it’s a sensitive area. You are dealing with sensitive data, and you are dealing with their behaviors. In order not to encounter this, or to manage this resistance and other psychological factors related to comfort and stress, XAI helps us provide the user with the required understanding and trust for the system that uses an AI model.” 

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