Positive social impact has also advanced through the emergence of AI. Being surrounded by overwhelming amounts of information, AI models have allowed us to identify and prevent content that is discriminatory, biased and/or nudging. With these models, we are able to identify fake news and false content, created with the sole aim of growing inequalities and polarization. However, the way these technologies are used is highly dependenton the country and its values.

For example, we have experienced misuse of AI and big data in many recent events associated with elections, nationalism, and discrimination. In addition, it is crucial to ensure proper data collection and validation processes to avoid data- and output biases. In other words, we need to define data compilation and annotation standards to ensure both non-biased data and trustworthy AI models.

AI systems have also been used for environmental sustainable development. >For example, detecting failure in management systems and smart production processes have helped us optimize the use of resources such as water, energy and materials for sustainable consumption and production. In addition, AI can be leveraged to develop models for protecting and preserving the natural environment, biodiversity and land ecosystems.

For example, deep learning models, using satellite images as input, have been used to identify fire risk areas, desertification trends, ocean deterioration and deforestation regions. Now, using AI for advancing sustainable development has another side to it as well. The carbon footprint of AI applications is very high due to the amount of energy required to run these systems. Even more so if non-renewable energy sources are used. For example, research states that data centers account for around 1-8% of global energy consumption.

There are two key points to be made from this post.

Firstly, this post is written to give examples of possibilities and challenges brought by implementing AI applications for sustainable development, and therefore this list is by no means exhaustive.

Secondly, you may have noticed that these examples are not mapped to the SDGs. Research articles like to classify the 17 SGDGs into either environment, social or economic themes. Yes, it is true that some SDGs have targets and indicators that clearly focus on one of the three. However, each SDG consists of economic, social and environmental aspects.

For example, when considering SDG 7 (renewable energy) the social part includes making energy affordable and available for all, but at the same time the goal consists of making a transition towards renewable energy resources with the environment in focus. Or from the economic perspective, investments in innovation and AI for making this transition is an action that can be taken for advancing SDG 7. So, whichever aspect you choose is up to you.