RESILIENT INFRASTRUCTURE
DIGITAL TRANSFORMATION WITH SUSTAINABLE STANDARDS BY RAY WALSH
How artificial intelligence and ICT Standards can contribute to the UN Sustainable Development Goals and achieve digital transformation in parallel with sustainability.
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rtificial intelligence is quite broad and is what’s known as a horizontal technology. In other words, it’s one of those foundational technologies that crosses across various sectors. There are lots of these types of technologies like 5G, big data, and IoT, which are multi-sectoral or multi-field oriented. By looking at where AI intersects with agriculture, automotive, manufacturing, finance, and health, we can get an idea of where these synergies would be with other horizontal technologies. Because with a lot of these technologies, it’s hard to draw a ring around where that ecosystem of AI ends and another begins. It tends to be a mesh of ICT technologies. The logistics end of it is also controlled by AI: prediction, analysis, and identification. AI is pervasive. We walk around with smart systems in our pockets with our mobile phones. We use predictor mechanisms on our websites to get better responses from vendors. We use social media AI for bringing content that’s of interest to us. So AI is everywhere. We use it all the time. So then we have the Sustainable Development Goals. And what I found is that AI can affect all of them. Social SDGs: Zero Hunger, Good Health & Well-Being, Quality Education, and Peace, Justice & Strong Institutions From a societal perspective, we have multiple uses for AI on a global scale. For example, AI can help with more efficient agricultural practices in terms of pesticides and fertilizer, reducing cost and waste and addressing scourges such as viruses. Technologies can also contribute to public
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health. For example, AI is very powerful and accurate when looking at radiography-type images and X-rays in terms of detecting particularly negative outcomes concerning those scans. To improve the quality of education, big changes have to happen in broadband deployment worldwide: Over 3 billion people don’t have access to online facilities. AI is also important for food, water, energy, health, education, climate, and the ocean, and all of these relate to the social SDGs. For example, AI is being used to control robots harvesting plastic from the ocean, and they are automatically or autonomously controlled. And they deposit their collected plastic to be disposed of from the ocean. Economic SDGs: No Poverty, Gender Equality, Economic Growth, Innovation & Infrastructure, and Reduced Inequalities We want to create environments where people can be more productive and there is better performance of economic tools being used. For AI in big data, we have to distribute ledger technology, which will create a more secure environment for transactions. The AI aspect would be the smart contracts, which are triggered at the delivery of the goal for the DLT technology. And these create faster and cheaper payment systems. The human-digital gender gap is a big thing: More males are digitally literate than females. So we can use education and AI tools to do online training. And we can use remote delivery systems once we have the infrastructure for that. Interoperability and standardization are big things for the economic SDGs. If you want
to have interoperable AI systems that impact SDGs, you need to have standards. And standards allow you to reduce barriers to entry when it comes to technologies, particularly global technologies like the internet and digital communication systems. Environmental SDGs: Clean Water, Clean Energy, Sustainable Cities, Climate Action, Life Below Water, Life on Land Next, we’re going to look at the environmental SDGs. Sensors with AI systems built into them can work in all sorts of environments on land, in the air, underwater, or in water. They’re constantly monitoring the state of our natural environment. And based on the data that’s being collected and aggregated, we can make decisions about what we want to achieve in terms of our environment. I mentioned we have AI harvesting plastics in our oceans, but you also do the same thing for smart water management, monitoring flow and control. We can also monitor the quality of water. We can look at water and air pollutants. And all of this can be used to improve the quality of life for citizens. For energy efficiency and renewable resources, we have AI systems that help not just to design and develop renewable resources but also to manage them and improve their performances. In terms of procurement and construction of performance indicators for smart, sustainable cities, you can have smart systems involved in those logistical parts as well. You can use AI with e-waste, recycling and managing the complete logistical pipeline associated with creating digital tools, technologies, and services, and then at the end
