Humanitarian engineering programs bring together engineers, policy makers, non-profit organizations, and local communities to leverage technology for the greater good of humanity.
The intersection of technology, community, and sustainability offers a plethora of opportunities to innovate. We still live in an era where millions of people are under extreme poverty, lacking access to clean water, basic sanitation, electricity, internet, quality education, and healthcare.
Artificial Intelligence core capabilities like machine learning (ML), computer vision, NLU , and speech recognition offer new approaches to address humanitarian challenges and amplify the positive impact on underserved communities. ML enables machines to process massive amounts of data, interconnect underlying patterns, and derive meaningful insights for decision making. ML techniques like deep learning offer the powerful capability to create sophisticated AI models based on artificial neural networks.
To deliver high social impact, AI-driven humanitarian programs should follow a “bottom-up” approach. One should always work backwards from needs of the end-user, drive clarity on the targeted community/user, their major pain points, the opportunity to innovate, and expected user experience.