How AI could address the world's most challenging issues
1. Focusing on renewable energy and sustainability: No longer will a citywide or country level suffice for complying with reduction mandates. Neighbourhoods, local businesses and even households will need to get prudent about energy consumption. We will see products and services within these areas move to the forefront. AI will be a key tool in enabling this by providing better automation, wherever required. A great example of how AI can help was highlighted in PwC and Microsoft’s joint report: “For example, in the energy sector, AI-enabled distributed energy grids will reach their maximum potential with the adoption of related innovations in distributed grid infrastructure including distributed generation, distributed storage, Industrial IoT, electric vehicle charging, dynamic pricing, and smart meters. Likewise, in transport, AI-enabled autonomous vehicles must offer more than energy efficiency gains through smart navigation and eco-driving, but also ultimately be electric vehicles and incentivize ride-shares, to counter a potential rebound effect of increased vehicle miles.”
2. Data transparency and better governance: A big challenge that citizens in many countries currently face is the lack of transparency in financial systems and lack of governance particularly when it comes to data. Governments often announce benefit schemes for those who need it the most but the money and benefits rarely reach them. Using cutting edge technology such as AI and using quantum processing to handle the huge volume of transactions on the blockchain, governments can help take their benefits directly to the people and keep the process transparent, thus avoiding any red tape or loss of resources.
3. Access to better healthcare: Developing countries in Asia will have better access to healthcare through AI-powered innovations. "AI and predictive analytics help us to understand more about the different factors in our lives that influence our health, not just when we might get the flu or what medical conditions we’ve inherited, but things relating to where we are born, what we eat, where we work, what our local air pollution levels are or whether we have access to safe housing and a stable income. These are some of the factors that the World Health Organization calls the ‘social determinants of health’. In 2030, this means healthcare systems can anticipate when a person is at risk of developing a chronic disease, for example, and suggest preventative measures before they get worse. This development has been so successful that rates of diabetes, congestive heart failure and COPD (chronic obstructive heart disease), which are all strongly influenced by SDOH, are finally on the decline,” explains Carla Kriwet of Philips in her commentary piece for UPS.
4. Generational transformation: A combination of widespread aging, falling fertility, and urbanization will lead to a dramatically different world in 2030. With an expected 8.3 billion people, human civilization will be both older and much more city life based. Our infrastructure may improve, but our level of innovation and output will slow down without younger workers. This is where AI-powered innovations will help us keep up the pace of progress.
5. Growing demand for food, water, and energy: A growing middle class and gains in empowerment will lead the demand for food to rise by 35%, water by 40%, and energy by 50%, government research suggests. Regions with extreme weather patterns — like rain-soaked Singapore or muggy Mumbai — will get more extreme due to the effects of climate change. Dry areas such as Northern Africa and the US Southwest will feel the effects of diminished precipitation especially hard. We will still have enough resources to avoid energy scarcity by 2030; however, whether those resources include fracking or renewable forms like solar and wind is yet to be seen. Satellite image data along with predictive analytical tools could potentially help farmers foresee disease onset and give governments a heads up on an approaching season of drought. AI and machine learning can thus reduce the burden for the farmer in the fields and help governments better handle the global food crisis.