Technology has helped societies all over the world to battle the most pressing issues and solve social problems. By promising faster technological advancement, artificial intelligence (AI) promises to provide answers to questions relating to the environment, security, and society that we are all exploring today. There’s no denying that AI is on its way to change the world as we know it.
Are you curious about the impact AI solutions are already having and will have on our societies? Here are 5 social issues and examples of projects that use AI to address them.
Mitigating the risks of climate change, battling pollution and depletion of natural resources while sustaining biodiversity – these are some of the most critical challenges humanity faces today. Fortunately, AI comes to rescue in many different ways.
Wildlife conservation is essential to maintaining the most fragile ecosystems on Earth. An American nonprofit organization, The Rainforest Connection, developed an AI-powered platform that uses tools such as Google’s TensorFlow to battle wildlife poaching by analyzing audio-sensor data to detect illegal logging in vulnerable areas. AI is also helping us to track animal movements and learn which habitats we need to protect at all cost. For example, the state of Montana uses AI algorithms to come up with the best places to create wildlife corridors for wolverines and grizzly bears.
Depending on the energy source, high-energy requirements of organizations, institutions, or even entire societies may have a significant impact on adding to global warming. The tech industry is a culprit here – tech giants usually operate massive data centers that require a considerable amount of energy to run the servers and cool them. Google employed its AI platform DeepMind to optimize energy use with great success. The tool predicts when its data centers will get too hot and activates cooling systems only when necessary, saving Google 40% in energy expenses at its server farms
2. Crisis response
Responses to natural and human-made disasters, disease outbreaks, search and rescue missions – AI is transforming these areas as well. For example, we can use AI-powered drones to find missing persons in wilderness areas or combine satellite data with AI to predict wildfire progression and optimize the response of firefighters.
An example of implementing AI for emergency management is the BlueLine Grid, a mobile communications platform created to assist rescue efforts during disasters. Using AI, the tool connects users to an established network of security teams, first responders, and law enforcement through a range of services (voice, text, location, and group). Users can quickly find relevant public employees by geographic proximity, specific area, or agency.
3. Information verification
One of the most serious social issues we are all experiencing today is misleading information and distorted content disseminated through social media and the internet. Such content can bring about adverse effects such as manipulation of election results or even mob killings triggered by the spread of fake news – for example, the use of Facebook to incite violence in Myanmar.
Fortunately, AI technologies can help us to counteract this issue. The University of Washington and Allen Institute for AI created Grover, a system which is well-versed in generating fake news – as well as identifying it! A research group from Harvard University and the MIT-IBM Watson AI Lab has also built a tool that allows identifying text that has been generated with the help of AI.
When incorporated into education, AI technologies stand to maximize student achievement and improve teacher productivity by automating tasks such as grading. For example, Georgia Tech University in the US has recently implemented a helpful teaching assistant for students which answered their questions with incredibly high accuracy of 97%. The university decided to implement an AI-powered chatbot after their research revealed that lack of support was a key reason behind student drop out.
AI can support students in many different ways, helping to personalize learning and accommodate differences in learning speed and starting points. Since schools can’t afford an individual tutor for every child, they instead turn to AI-based tutors who deliver personalized education to help learners achieve the best results.
AI will find multiple uses in healthcare, supporting not only administrative but also clinical functions in areas like disease prevention and diagnosis, optimizing treatment plans, medication management, drug creation, and precision medicine. Naturally, AI-powered software can also optimize workflows to reduce costs, accelerate claim processing, improve supply cost management, and train physicians.
An excellent example of a clinical application of AI is the role of software in assisting oncology diagnostic. Researchers at Stanford created a program based on a deep convolutional neural network for diagnosing skin cancer from visual samples. The tool has been tested in trials and revealed to match the performance of a human dermatologist in skin cancer detection.
Why is implementing AI for social good so challenging?
Developing AI solutions for the public good is challenging because of two reasons: 1) shortage of skilled machine learning engineers and data scientists, and 2) data accessibility.
To resolve the latter, private- and public-sector organizations will have to become open to making data available. A large chunk of the data required for building social-good applications are owned privately or by public institutions that might not be willing to share it – think telecommunications companies, social media platforms, financial institutions, health providers, and governments. Because of regulations on data use and privacy concerns, entrepreneurs and non-governmental organizations find accessing data sets difficult.
The other reason is related to the shortage of available expertise in AI. Many of the use cases presented above are complex and require combining several AI capabilities that will work together seamlessly. That creates a demand for high-level AI expertise from engineers who have a lot of experience and possibly higher education degrees such as Ph.D. in Computer Science. As you can imagine, the competition for such expertise is very high.
The future of AI for social good
Despite the promising use cases of AI for social good, societies, tech companies, governments will have to address several problems before AI becomes a reliable tool for solving social issues. Most importantly, they need to address the problem of bias that often creeps into the algorithms we design. Another critical action would be focusing on the transparency of AI tools, ensuring that the decision-making process is no longer enclosed in the “AI black box.”
Are you looking for AI experts who could help you build a tool that addresses a key social issue? Get in touch with us; we help organizations solve their most pressing problems using AI and other innovative technologies.