Data is becoming more and more accessible. The proliferation of Web platforms (e.g., social media and web fora) together with the increased affordance of smart sensing technologies allowed accessing data about a large and diverse set of users, as their activities in the digital world reflect their real-life desires, drives, and needs. In the last decade(s), several computational solutions - based on data science and machine learning -- have been developed to make sense and extract useful and meaningful insights from this large amount of data. However, in critical domains, such as health, fully data-driven approaches lead to solutions that favor the decision-makers rather than balancing the needs of all stakeholders, resulting in not inclusive solutions and a lack of trust among the individuals. In this talk, I’ll show how the concept of empathy can be embedded and integrated into the design of data-intensive systems to include different human perspectives at scale. This stems from the necessity - on one hand - of developing systems that are effective and efficient, and - on the other - understanding and acting on their impacts on society. I’ll discuss the current research/societal challenges and gaps, and show some works at the intersection of data science, HCI and design applied to different domains such as health, sustainability, and policy-making.
Biography: Andrea Mauri is a PostDoc at the Faculty of Industrial Design Engineering at TU Delft (Netherlands), and Research Fellow at the Amsterdam Institute for Advanced Metropolitan Solutions. He is interested in the design, implementation, and evaluation of novel computational methods and tools - focusing on hybrid human-AI methodologies - to support the design processes addressing societal problems by integrating human and societal needs and values.
