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CSR: 10 ways to apply AI to social good

Topher White
Engineer Topher White from The Rainforest Connection, a nonprofit in the US, uses AI tools such as Google’s TensorFlow in conservation efforts
Artificial intelligence, while not a silver bullet, could contribute to the multi-pronged efforts to tackle some of the world’s most challenging social problems. Social impact domains used by social-sector organizations and CSR committees could benefit largely, according to a report by McKinsey Global Institute. Here are 10 ways to apply AI to social good.

1. Health and hunger

Addressing health and hunger challenges, including early-stage diagnosis and optimized food distribution.
How it can be done: AI-enabled wearable devices, which can already detect potential early signs of diabetes through heart rate sensor data with 85% accuracy, could potentially help more than 400 million people worldwide afflicted by the disease if the devices could be made sufficiently affordable. Other examples include combining various types of alternative data sources such as geospatial data, social media data, telecommunications data, online search data, and vaccination data to help predict virus and disease transmission patterns.

2. Educational challenges

These include maximizing student achievement and improving teacher productivity.
How it can be done: Adaptive learning technology could be used to recommend content to students based on past success and engagement with the material. AI could also be used to detect student distress early, before a teacher has noticed.

3. Economic empowerment

Opening access to economic resources and opportunities, including jobs, skills development, and market information, with an emphasis on currently vulnerable populations.
How it can be done: AI can be used for early detection of plant damage through low-altitude sensors, including smartphones and drones, to improve yield in small farms if farmers have access to technology; one Microsoft project called FarmBeats is building edge-computing technology that could one day make data-driven farming accessible for even the poorest farmers. Watch how:

4. Environmental challenges

These include sustaining biodiversity and combating natural resource depletion, pollution, and climate change.
How it can be done: Robots with AI capabilities can be used to sort recyclable material from waste. The Rainforest Connection, a nonprofit in the US, uses AI tools such as Google’s TensorFlow in conservation efforts across the world. Its platform can detect illegal logging in vulnerable forest areas through analysis of audio sensor data. Watch the video below to under how.
Other applications include using satellite imagery to predict routes and behaviour of illegal fishing vessels.

5. Equality and inclusion

Addressing equality, inclusion, and self-determination challenges, such as reducing or eliminating bias based on race, sexual orientation, religion, citizenship, and disabilities.
How it can be done: Affectiva, which was spun out of the MIT Media Lab, and Autism Glass, a Stanford research project, involves use of AI to automate emotion recognition and provide social cues to help individuals along the autism spectrum interact in social environments. Another example is the creation of an alternative identification verification system for individuals without traditional forms of ID, such as driver’s licenses.
Watch the video to see how Autism Glass helps kids with autism read facial expressions:

6. Crisis response

Specific crisis-related challenges, such as responding to natural and man-made disasters in search and rescue missions and at times of disease outbreak.
How it can be done: AI on satellite data to map and predict wildfire progression to optimize firefighter response. Drones with AI capabilities can also be used to find missing persons in wilderness areas.

7. Information verification and validation

This domain differs from the others in that it focuses on filtering or counteracting content that could mislead and distort, including false and polarizing information disseminated through the relatively new channels of the internet and social media. Such content can have severely negative consequences, including the manipulation of election results and the mob killings in India that have been triggered by false news dissemination via messaging applications.
How it can be done: Actively presenting opposing views to ideologically isolated pockets in social media.

8. Infrastructure management

Infrastructure challenges that could provide public good in the categories of energy, water and waste management, transportation, real estate, and urban planning.
How it can be done: Traffic light networks can be optimized using real-time traffic camera data and Internet of Things sensors to maximize vehicle throughput. AI can also be used for predictive maintenance of public transportation systems such as trains and public infrastructure, including bridges, to identify potentially malfunctioning components.

9. Public and social sector management

Initiatives that are related to the efficiency and effective management of public- and social-sector entities, including strong institutions, transparency, and financial management.
How it can be done: AI can be used to identify tax fraud using alternative data such as browsing data, retail data, and payments history.

10. Security and justice

Challenges in society that include harm prevention—both from crime and other physical dangers—as well as tracking criminals and mitigating bias of police forces. This domain focuses on security, policing, and criminal justice issues as a unique category adjacent to public-sector management.
How it can be done: An example is using AI to create solutions that help firefighters determine safe paths through burning buildings using data from IoT devices.
This article is part of a series on applying AI to social good.