Noble Intelligence

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Artificial intelligence (AI) is emerging as one of the forces creating Change that Matters and opening new opportunities to shape our collective future. We see it as a potent instrument for social good. Drawing on our thinking and research in AI and analytics, Noble Intelligence, an initiative by McKinsey & Company, is engaging nongovernmental organizations, respected think tanks, and industry leaders as part of a global movement to responsibly use technology to benefit society and the environment.

Our diverse and passionate, cross-functional Noble Intelligence teams are using AI and analytics to develop and deploy innovative tools around the world to help organizations and communities achieve the United Nations’ Sustainable Development Goals. Organizations that help victims of natural disasters, diseases, and other humanitarian crises can use AI and analytics to act more quickly, nimbly, and effectively to save lives and rebuild communities around the world. From expanding access to education and easing unemployment to assisting survivors of human trafficking, AI and other 21st-century technologies—used knowledgeably and responsibly—can maximize the impact of humanitarian work.

Impact Story

Harnessing the power of AI to improve aftercare services for survivors of human trafficking

By applying analytics and AI algorithms to a database of anonymized survivor support journeys, we helped an anti-slavery organization understand how it could improve the likelihood of recovery for survivors.

Examples of our work

Noble Intelligence has extensive experience in helping organizations across sectors to develop and deploy unique algorithms and source codes for the benefit of society.

Identifying people at risk of long-term unemployment

Roughly half of one European nation's unemployed population in 2018 were jobless for 12 consecutive months or more. In collaboration with a training organization for data scientists, we advised and helped an agency develop a predictive model to assess people’s risk of long-term unemployment. With initial tools currently in implementation, discussions about wider use are underway to help officials match workers with job opportunities.

Improving disaster relief

We are working with an international aid organization to assess damage to schools from a devastating cyclone in Africa that displaced more than 160,000 people. Using satellite data, we developed a deep-learning image recognition and classification algorithm to assess building damage post-disaster. Using AI models on damage data, teams on the ground can optimize the distribution of temporary schools and rebuilding efforts to get more children back to school faster.

Helping to reduce outbreaks from vaccine-preventable diseases

When measles vaccination rates dropped precipitously among children, we collaborated with a training organization for data scientists to build a model that predicts a child’s risk of not receiving the vaccine. The AI-assisted solution allows doctors to identify children most at risk, allowing better follow-up and dialogue between physicians and parents.

Helping survivors of human trafficking

We helped an anti-slavery organization reshape how it provides services to women, men, and children rescued from modern-day slavery. By applying analytics and AI to a database of anonymized survivor support journeys, we developed multiple algorithms to help the organization improve post-rescue services and support. The analysis found that assistance in the first 30 days could improve a survivor’s chance of recovery by more than 50 percent. These algorithms were developed in the United States and will be deployed globally.

Featured capability

Deep-learning based damage assessment model

Assessing damage to buildings in the wake of a natural disaster is a key component of humanitarian relief. Until now, this has been done by physically scouting buildings, which can take weeks to months—creating a major bottleneck in relief efforts.

Noble Intelligence has developed a computer-vision algorithm that assesses damage to buildings using pre-and post-disaster satellite imagery. The algorithm classifies each building into one of four categories (from “no damage” to “destroyed”) within minutes of receiving the relevant satellite data, with no human input. This quick analysis can help relief workers and organizations deploy emergency aid and allocate scarce resources more quickly.

Featured Insights

A digitized image of the earth against a blue background

AI for social good: Improving lives and protecting the planet

May 10, 2024 -

As AI advances from predictive to generative capabilities, its potential to address social issues defined by the UN Sustainable Development Goals expands.

The state of AI in 2022—and a half decade in review

December 6, 2022 -

The results of this year’s McKinsey Global Survey on AI show the expansion of the technology’s use since we began tracking it five years ago, but with a nuanced picture underneath.

Executive’s guide to developing AI at scale

October 28, 2020 -

Developing artificial intelligence and analytics applications typically involves different processes, technology, and talent than those for traditional software solutions. Executives who possess a solid understanding of the basics can ensure they’re making the right investments in their tech stacks and teams to build reliable solutions at scale. We’ve created an interactive guide to help.