Developing personalized persuasive technologies using an adaptive and data-driven approach

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Persuasive technologies (PT) are interactive systems that motivate and help people adopt new behaviours through platforms such as mobile games, mobile applications, and social media. Existing PT are developed using personalization models that are not adaptive to the user's current situation while engaging with the system. My recent research indicates that PT developed with personalized models of persuasion have a greater efficacy than non-personalized ones. Understanding how technology can influence behaviour is at the forefront of human-computer interaction. Accurately reflecting individual human behaviour through machine learning algorithms remains an open challenge. My long-term vision is to develop data-driven trusted PT that can empower users and motivate them to achieve goals that are important to them and society. Underpinning effective PT are complex algorithms, and currently, there are no methodologies to incorporate individualized user personalization that are adaptive to changes in user preferences. The short-term objectives of this Discovery Grant research program include: 1) to develop novel adaptive data-driven personalization models for PT, 2) to design, develop and evaluate personalized persuasive systems using the novel personalization models in the domains of e-learning and serious games, and 3) to model trust and ethics in the design and development of persuasive systems. For the first objective, I will develop novel personalization models using Bayesian machine learning algorithms to compute the probability of success of a persuasive message or visualization when presented to a user. For the second objective, I will apply this novel personalization model in the design and development of an adaptive e-learning platform to overcome the non-adaptive setback of current e-learning PT. I will also use the novel personalization model to develop serious games for healthy nutrition. To achieve the third objective, I will develop an ethical framework to increase people's trust in PT. There is currently no PT design framework for designing ethical and trustworthy PT to enhance their use. To create the framework, I will develop multiple prototype systems to simulate various ethical scenarios to identify users' trustworthiness. Through developing state-of-the-art algorithms that can characterize complex human-computer interactions in a dynamic personalized manner, my research will be among the first globally to advance personalized PT in a manner that dynamically incorporates a user's current situation, which has far-reaching applications across numerous domains such as e-learning and healthy nutrition. My research will result in the first framework for ethical PT design which can guide future development in this area. HQP will gain experience from research design to evaluation and implementation and will enhance their data mining and software development skills which are beneficial to their future careers in academia or industry.