Fred Rogers of Mister Rogers’ Neighborhood shared that his mother would say, in times of crisis, “Look for the helpers. You will always find people who are helping.”
This advice holds true when looking at the potential for artificial intelligence to change the world. People are using technological advances to create and experiment with innovative approaches to global issues that have affected humanity for generations.
The plight of displaced persons, the global food crisis and natural disasters are real challenges people face every day. With the expansion of violent extremist groups and civil unrest around the world, the need for providing safety and security is as important as ever.
While these issues aren’t new, the application of artificial intelligence to augment our ability to solve them is. What if artificial intelligence is the change agent we need to significantly accelerate our ability to have positive, lasting impact in these areas in a globally sustainable way?
Addressing privacy with AI and blockchain
The World Food Programme uses blockchain technology to distribute food to Syrian refugees in Jordan. Beyond this, blockchain holds potential for re-establishing government identities for displaced persons by creating digital records that are unique, accessible from anywhere and encrypted for privacy. The ability to formally validate one’s identity is critical for securing a new life when transitioning from a refugee camp.
Consider blockchain as a data source to feed artificial intelligence algorithms. AI could analyze blockchain data to help with forecasting resource demands, understanding overall program effectiveness and perhaps eventually gaining insight on challenges and successes of refugee transition. The ability for blockchain to provide an official identity to those who have lost everything is a new solution to a problem experienced across the globe. It holds the potential, when combined with artificial intelligence capabilities, to guide data-driven policies and programs that address needs in a meaningful, high-impact way.
Read more stories about humans and AI working together
Hear from real people powering real AI, and learn where conversations should start about AI. When you believe in humans and AI working together, the possibilities are exponential.
IoT and AI contribute to disaster relief
The investment to combine sensors and connected devices, or the Internet of Things, with AI has profoundly influenced disaster relief operations. Drones provide real-time images of land, port and building damage in affected areas that AI systems can rapidly evaluate for input into damage assessments.
When an earthquake devastated Nepal in 2015, AI identified and categorized resource needs from tagged tweets to triage response efforts based on urgency, building damage and resource deployment.
Perhaps the most transformative way that AI can aid in disaster relief operations is incorporating the analytic power of machine intelligence throughout emergency command centers. Consider these scenarios:
- Smarter systems can distribute and monitor resource deployment effectively.
- Streaming image analysis of the environment can provide alerts to emerging dangers.
- Digitizing victim information and establishing identity at the point of contact provides more robust data for medical treatment and continued care efforts.
These capabilities support more robust data collection and analysis, leading to better-informed decisions and faster response times.
AI for safety and security
In times of civil unrest and humanitarian crisis, safety and security remains a top concern. How do you protect those fleeing from or living in an area rife with violence and instability?
Military and law enforcement organizations around the world are looking at how artificial intelligence can help sift through a variety of data sources and formats to detect and assess emerging threats. AI is analyzing pattern of life connections throughout criminal networks at an unprecedented speed, helping those on the front lines gain better situational awareness and improving the ability to preemptively target and address acts of violence.
For those living in areas plagued with instability, the global food crisis is front and center. In areas of extreme poverty, a good harvest can be the difference between life and death. AI is helping farmers in the developing world understand the ideal time to sow crops by analyzing decades of weather data and monitoring daily rainfall reports. AI algorithms have successfully determined the optimal sowing time and predicted the best timelines for producing a good harvest season in different regions by finding key patterns in past and present weather data.
This affordable approach demonstrates how, without the need for expensive sensors or investment in additional equipment, AI legitimately helps farmers around the world.
The ethical use of AI remains a top priority
In each of these examples, the same concerns that surround AI in the business market are relevant. Is the data being collected and used in an ethical manner? Is there transparency and interpretability built into the AI models being deployed? Is there due diligence in managing bias?
These should always be guidelines for implementation. But when it comes to improving quality of life issues around the world, it is important not to let a quest for perfection become a barrier to progress.
AI is not the single answer to solve all these problems, but it is a catalyst for new approaches to significant issues. In a moment of crisis, look for the helpers. And don’t overlook those who are creating powerful technology and innovative approaches to help people in need and make a difference in this world. Contrary to what some may think, there is no magic in AI. But there is certainly humanity.
About the Author
Mary Beth Moore is an Artificial Intelligence and Language Analytics Strategist at SAS. She is responsible for providing strategic marketing direction for artificial intelligence and text analytics. She frequently presents and writes on a wide range of technology topics, including AI, NLP and data for good. Prior to SAS, Moore served in the United States Marine Corps and spent several years as an intelligence analyst and senior instructor in the US Department of Defense and Intelligence Community, primarily supporting expeditionary units and special operations. She is also a special education advocate, a disability rights consultant and a believer in community inclusion for people of all abilities.
- Know your blind spots in tax fraud preventionTax agencies sometimes miss fraud that's happening right under their noses – despite robust external fraud prevention efforts. Find out where traditional tax fraud prevention and detection efforts fall short, and how analytics can change that.
- Understanding capital requirements in light of Basel IVMany financial firms are already using a popular 2012 PIT-ness methodology for internal ratings-based models. This article examines eight ways the industry is successfully using the methodology – and why this approach can bring synergies for banks, value for regulators, and major competitive advantages.
- Understanding capital requirementsCredit risk classification systems have been in use for a long time, and with the advent of Basel II, those systems became the basis for banks’ capital adequacy calculations. What is needed going forward is an efficient and honest dialogue between regulators and investors on capitalization.