EMERGENT ALLIANCE COVID-19
At IBM we believe in the power of collaboration and co-creation. Therefore, when in April a not-for-profit organization called Emergent Alliance was born, IBM joined the cause. The. Emergent Alliance is a community that aims to better inform the future economic decision-making of corporations, small businesses, and nation-states. The Alliance's scope is to create a safe environment in which members and volunteers could share data, expertise and merge it to provide new insights and practical applications to the global Covid-19 response: "Recover, Together, Stronger".
As part of the collaboration between Rolls Royce R2 Lab and the IBM Data Science & AI Elite team, I had the honor to run a design thinking workshop that set the strategy for the entire project and design and built three dashboards to communicate the results of the AI models. The mission was to create a risk index to communicate AI predictions to governments to help them track the impact of COVID-19 on several aspects of the economy.
AI driven Stories,
my role in the project:
Ran a design thinking workshop to surface information and design the data visualizations
Crafted storytelling by working with data scientists based on their ML models' outcome
Built dashboards with Cognos Analytics
EMERGENT ALLIANCE COVID-19
We started our collaboration with Rolls Royce with a design thinking workshop that helped the team producing a challenge statement. The challenge statement served as a starting point to divide the project into 3 different workstreams: An Emergent Risk Index, aimed to create a localised risk index that would include different aspects related to the COVID-19 impact; an Emergent Pulse, directed toward the sentiment and behaviour analysis of the population in response to the government countermeasures; and lastly, the Emergent Simulation focused on the creation of what-if scenarios to help understand the deep economic impact of the Virus.
Based on these challenge statements I then designed and built three dashboards translating the results of the ML models developed by the data scientists into visual stories that could be publicity consumed.
"Explainable AI (XAI) was imperative because explainable outcomes help users build trust and confidence in AI. Data visualizations powered by Cognos Analytics bridged the three workstreams together, illuminating the logic hidden behind algorithms, transforming the AI-generated outcomes into actionable results and generating enlightening data narratives."
This project has been extensively explained in the story below, published on the IBM Journey to AI blog: