Our world’s challenges — incurable illness, climate change, food insecurity, and inequality — often seem insurmountable. Yet our shared humanity inspires us to not accept these challenges as fate, but rather to strive for solutions. Artificial Intelligence (AI) can help.
Where insufficient data once limited our ability to understand the root causes and nuances of society’s biggest challenges, now we have the opposite problem: more data than we could ever hope to manually analyze. Untapped, data is useless, but through analysis it may reveal hidden insights to help shape solutions. When applied with a disciplined approach using guidance from experts, AI has the potential to enable the development of revolutionary solutions for our toughest challenges.
AI has the power to analyze larger amounts of data than any human could previously imagine. Consider water quality. Many waterways, like the Chesapeake Bay, face threats to their continued existence. Without the bay, we would lose not only a cherished ecosystem and a natural safeguard from floods and erosion, but also tourism and agricultural business.
For seven weeks in 2020, data scientists, developers, designers, and AI practitioners partnered with the Chesapeake Monitoring Cooperative in the first federally supported citizen science water quality data initiative. Data scientists explored previously unanalyzed, nontraditional water quality data and geospatial information. Building on the cooperative’s expertise, AI engineers used machine learning to analyze potential causes of pollution and build models to predict water health. By shedding new light on one of the most studied watersheds in the world, AI provided insight into the health and well-being of the Chesapeake Bay, and demonstrated the ability to support a wide range of environmental and conservation efforts.
Advantages in speed and accuracy
AI can diagnose anomalies in complex data much more quickly – and accurately – than even a human expert in their field. Each day, 1,500 people in the United States alone are diagnosed with heart failure. Doctors aim to identify declining heart function early, using gold-standard magnetic resonance imaging technology. But this process is time-consuming. Skilled cardiologists require up to twenty minutes per patient to read these images, sometimes days after the radiologist submits the imaging for analysis.
In 2015, the Data Science Bowl® challenged data scientists to create an algorithm to automate this assessment. Using data from the National Institutes of Health and Children’s National Medical Center, analysts developed solutions in just three months, which is an incredibly quick timeframe in the health industry. These algorithms have the potential to allow doctors to diagnose heart conditions faster and earlier, providing doctors more time with their patients to proactively create robust treatment plans when a heart problem is found. At the close of the competition, the winning algorithm was released publicly to allow cardiologists and researchers to explore its integration with diagnostic technologies. This is but one example of how AI can empower doctors to help people live longer, healthier lives.
Supporting human minds
Collaboration between subject matter, data, and AI experts can build AI solutions to empower better human decision-making. In 2019, there were more than 34 million activations of Emergency Medical Services in the United States. That’s one emergency response every second. The emergency medical technicians answering those calls know slow response times can have life-threatening outcomes. In Fairfax County, Virginia, medical technicians aimed to respond in under four minutes. But reducing response time can be challenging. How do you improve performance with immovable stations, a growing population, and calls coming from anywhere, anytime?
Booz Allen donated time and expertise to the Fairfax County Fire and Rescue Department in a collaborated effort to tackle this challenge. Emergency medical technicians walked the AI team through their dispatch center, explaining how 9-1-1 calls are answered and EMS crews are deployed. Using what they learned, machine learning engineers trained an AI model to optimize allocation of the department’s resources. This AI solution provides insights to aid in the redeployment optimization of fire station assets, thereby improving response times.
AI enables us to innovate across a wide variety of disciplines using previously untapped data, providing insights to help shape advanced solutions. In a world increasingly awash in data, AI can empower researchers, innovators, and leaders to develop revolutionary solutions for our toughest challenges. What was once insurmountable can now be overcome with AI guiding our way.