What do forecasting floats, speech recognition, and self-driving cars have in common? Well, they are all put into life using AI.
Machine learning (ML) and artificial intelligence (AI) are great opportunities for us to build tools that will help the world’s most pressing challenges and deliver positive social impact. The problems that we are facing today are becoming more and more complex, so we need better mechanisms and even better communication between all involved parties to make the required difference.
Due to a series of high-profile successes with ML and AI projects, the interest in these technologies has spread worldwide. But next to games & simulations and talking robots, how can we use AI for the good of humanity?
The commercial applications often have an indirect positive social impact by increasing the availability of information through better search and language-translation tools, providing improved communication services, enabling more efficient transportation, or supporting more personalized healthcare.
Also, the idea of applying AI for solving problems in society has already started to be a focal point of some of the greatest NGOs in the world, academic institutions, and the tech giants Google and Microsoft.
Some of the great examples of projects done with the help of AI are the automated monitoring of viral cassava disease, electronic agricultural marketplace in Uganda, satellite imagery to help predict poverty and identify burned-down villages in conflict zones in Darfur.
Despite the optimism, technical and organizational challenges remain that make successful applications of AI/ML hard to deliver within the field and make it difficult to achieve lasting impact. Some of the issues are deeply ingrained in the tech culture that involves moving fast and breaking things while iterating towards solutions and a lack of familiarity with the non-technical aspects of the problems. Not all applications of technology aimed at delivering positive social impact manage to achieve their goals, leaving us with essential experiences from which we must learn. Importantly, technology should not be imagined as a solution on its own, outside of the context of its application: it merely aligns with human intent and magnifies human capacity. Therefore, it is critical to put it in the service of application-domain experts early, through deep partnerships with technical experts.
To achieve a positive impact, AI solutions need to adhere to ethical principles. AI needs to be lawful, ethical and robust, to avoid causing unintended harm. It should be driving inclusive growth and sustainable development, designed to respect the rule of law, human rights, democratic values, and diversity, transparent so that people can understand AI outcomes.
Also, proper ethical design and governance of AI systems are important and broad research topics of fundamental importance.
AI can provide new ways of approaching problems and meaningfully improve people’s lives. The many successful projects just prove the fact that we can use technology for good, and in this case, teach the machines how to guide and support us to be better human beings!
Sources of inspiration:
https://eirinimalliaraki.medium.com/what-is-this-ai-for-social-good-f37ad7ad7e91
https://apru.org/aiforsocialgood/
https://www.turing.ac.uk/events/ai-social-good
https://www.intel.com/content/www/us/en/artificial-intelligence/ai4socialgood.html
https://ai.google/education/social-good-guide/
