Digital Algorithmic Nudging

Digital algorithmic nudging uses computational methods to subtly influence human behavior towards desired outcomes, primarily focusing on improving decision-making and promoting positive actions in areas like health and cooperation. Current research explores various model architectures, including reinforcement learning, graph neural networks, and deep learning approaches, to personalize and optimize nudges for effectiveness and user acceptance. This field holds significant promise for improving public health initiatives, enhancing user engagement with technology, and addressing societal challenges by leveraging AI to guide behavior change in a more ethical and efficient manner than traditional methods.