A data-driven visual identy
The Krino concept originated at the beginning of the COVID-19 pandemic, when many of our data scientists were developing predictive and prescriptive models to help governments, institutions, and media better grasp the dynamics of the infection and understand how to cope with it.
I thought to experiment with new ways to convey our data scientists' AI models to a broader audience who was not versed in data science but might still want to understand how COVID-19 was impacting their lives.
I created a hub that could host important AI-driven stories and make them more accessible through visuals. I called the platform Krino
Explaining the AI
The main objective of Krino was to use storytelling to unlock the science and the math behind AI and ML models and to translate their outcomes into meaningful narratives easily accessible by a wide audience without technical experience.
Krino could provide an AI framework to help people develop a clearer understanding of how the impact of COVID-19 on cities, services, and job markets might affect their habits and behaviors. It was built as a platform to publish stories with visuals, data-viz, audio, and other compelling media, that would drive people’s attention to the AI outcomes produced by the IBM data scientists.
Storytelling is the most powerful tool to explain the real value provided by AI models: how they work, how much uncertainty lies underneath lines of code, and why specific solutions and techniques have been adopted (such as Machine Learning or Decision Optimization.)