The ‘Ora’ platform was developed along-side clinicians in a collaborative effort, winning the Microsoft ‘Artificial Intelligence (AI) for Good’ challenge with an AI powered tool for humanitarian crises. Geographically-tagged social media sentiment analysis is proposed as an increasingly validated metric for rapidly modelling disease incidence – supported by emerging literature marking a change in how the digital footprints of ‘modern migrants’ might be conceptualised. ‘Ora’ incorporates AI driven meta data with real time immigration statistics and regional infectious disease prevalence, providing an early warning system for communicable diseases in transient populations.
The UN High Commission for Refugees now estimates that 70.8 million people are forcibly displaced around the world, the highest in recorded history with nearly one person displaced every two seconds. The growing social, humanitarian and economic costs signal a pressing need for collaborative innovation.
This multi-disciplinary approach highlights the benefits of cross-agency partnership in addressing the needs of a mobile and digitally connected global population. Agile development, prototyping and the clinical training of ‘Ora’ algorithms, were achieved through integration of workflows across clinicians, data scientists and technologists. Diversity in training, design approaches and backgrounds of the team yielded debate on the ethical and societal consequences of scraping meta data from vulnerable populations. Anecdotal evidence of European agencies using migrant smartphone data (social media, geolocation, messages) for deportation purposes led to the formation of ‘Ora’ operating values, and the emphasis of embedded bio-ethical principles in its deployment.
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