Thinking beyond bots: How AI can drive social impact

What do artificial intelligence (AI), invention, and social good have in common? While on the surface they serve very different purposes, at their core, they all require you to do one thing in order to be successful at them: think differently.

Take the act of inventing—in order to develop a great patent, trade secret, or other intellectual property, you need to think outside of the box. Similarly, at the heart of AI is the act of unlocking new capabilities, whether that’s making virtual personal assistants like Alexa more useful, or creating a chatbot that provides a personalized experience to customers. And because of the constantly changing economic and social landscapes, coming up with impactful social good initiatives requires you to constantly approach things through a new lens.

Individually, these fields have seen notable advancements over the past year, including new technologies that are bringing improvements to AI and large companies that are prioritizing giving back. But even more exciting is that we’re seeing more and more business leaders and nonprofits combining AI, innovation, and social good to reach communities in innovative ways, at a scale we’ve never before seen.

There’s no better time than now to explore how your organization approaches your social good efforts. Here are a few ways you can think differently and integrate innovation and AI into your company’s altruistic pursuits.

Approach social good through the mind of an inventor

As a master inventor at IBM, I’m part of the team responsible for helping the company become the leading recipient of U.S. patents for the last quarter century. While developing patents and intellectual properties might not be what you’re setting out to do as part of your humanitarian efforts, the way we approach our jobs as inventors is something that can be applied across all aspects of giving back. Consider the United Nations’ 17 Sustainable Development Goals, which aim to eradicate things like poverty, hunger, disease, and more. These are game-changing initiatives that definitely require new ideas. What’s more, the United Nations estimates that we’re $5 trillion short on resources needed to accomplish these goals. How do we bridge this gap? Well, we need to start thinking differently.

Foundationally, coming up with a great invention is identifying a problem that needs to be solved and coming up with an out-of-the-box idea that’s smart, has the biggest impact, and the lowest risk. To do this, we look around us to see which relevant technologies we can use that are already at our disposal so we don’t have to completely reinvent the wheel if we don’t have to. We also identify which parts of the solution need a completely new idea to be created from scratch. Additionally, we look at the issue we’re trying to solve and the current landscape as a whole so we can predict any issues or future problems that may arise, and we try to address them ahead of time in our invention.

The same approach should be applied to social good—identify the problem you want to solve, the tools that already exist that can help you solve this dilemma, and the resources that need to be created or brought in from outside properties in order to execute your plan. At the heart of social good, similar to most inventions, are the people you’re trying to help. You need to make sure you’re maximizing the reach of your project while also minimizing any risks that may unintentionally create additional problems for the people you’re trying to help. To do this, you need to be creative in your approach.

As an example, this is exactly the approach InvestEd is taking (full disclosure: I am an advisor for InvestEd). They started off by realizing they could commercialize and create social good at the same time by enabling financial education and facilitating microloans for small businesses in emerging markets. Helping these small businesses grow added more value to the small, local communities. And to make their product even better, InvestEd is adding AI capabilities to widen their offerings and provide a more innovative user experience.

AI: Unlocking new capabilities

To grab the value and create disruptive AI technology for social good ideas, we have to think beyond the typical automation activities of a machine. Take Guiding Eyes, for example, which is using AI to discover the secrets behind successful guide dogs. By taking advantage of natural language processing (NLP) on structured and unstructured data, the system they’re using is trained to find correlations to successful dogs among genetic, health, temperament, and environmental factors—and the technology continues to learn and get better. By using AI, Guiding Eyes has seen a 10% increase in guide dog graduation rates, helping the organization meet the growing demand for guide dogs.

There are many other examples of AI being used for the betterment of society. For example, PAWS is an organization that uses machine learning to predict where poachers may strike, or Dr. Eric Elster, who worked with the Walter Reed National Military Medical Center to apply machine learning techniques to improve the treatment of U.S. service members injured in combat.

Best practices for getting started

These are a just a few ideas for how AI can be used for social good— there are still plenty of opportunities out there. The challenge is how to get started, so here are three best practices I’d like to share to help people who want to embark on this journey.

1. First, build your understanding of what AI is and is not through great online learning, such as Intro to Artificial Intelligence, led by Peter Norvig and Sebastian Thrun, on Udacity.
2. Second, think differently. AI is a different computing model. Instead of thinking about use cases and scenarios, really focus on the problem you want to solve. Think more “ideal scenario” on how to best develop a solution, and then see if a machine can be trained to do this work. Let’s consider personalized education, particularly reading comprehension (which has shown to have a tremendous impact on a child’s long-term educational performance across all subjects). With a traditional use case approach, we would probably try to develop a general framework that would help in a handful of scenarios. Now, Learning Ovations has thought about the more ideal scenario. They have realized there are too many possible scenarios to program or for a general framework to even cover. Instead, they’re training AI to assess each child’s performance (across traditional metrics and some new ones) as a tool for educators and parents. In addition, they’re creating an AI-powered recommendation engine based on each individual school’s curriculum to provide another tool for educators to create a customized reading program for each student. Thus, Learning Ovations thought differently on how to personalized education.
3. Third, set aside preconceived notions. There are things that people are better than machines at doing, but there are things machines are better than people at doing—some of which may be surprising. For example, people seem to be more honest in sharing health or financial information with a machine than a person because they don’t worry about being judged. This typically means the machine gets more accurate data to provide recommendations. Thus, recognizing that a machine might be as capable in some areas could unlock whole new capabilities.

When it comes to AI, invention, and social good, the possibilities are endless. Technology will only continue to become more advanced, creating new opportunities to fix societal problems related to health, sustainability, conservation, accessibility, and much more. If you’re thinking of jumping into AI for good, just remember the most important rule: think differently.