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Designing a Machine Learning Model to Enhance Human Interactions and Reduce the Influence of Cognitive Biases
  • Giacomo M. Scudiero
Giacomo M. Scudiero
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Abstract

Humans are an intensely social species and therefore, it is essential for our interpersonal judgments to be valid enough to help us avoid enemies, form useful alliances and find suitable mates;\({}^{[1]}\) when we interact with a new individual, our judgments are affected by our own past experiences, projections, and expectations. In essence, we are imposing the correlation of our past relationship experiences on the new person. This event can also lead to a prediction that entirely overlaps with one’s own choice. Knowledge used in predictions can be wrong, and it does not necessarily have to do anything with oneself.\({}^{[2]}\) This paper will present a method to enhance human interactions using models such as word embedding and convolutional neural network, along with specific linguistic markers, to extract meaningful insights from data. This architecture will ultimately offer a possible approach to fill the current gap between individuals, which often leads to a biased decision-making.