A recent United Nations (UN) supported summit in Geneva, “AI for Good”, focused on the potential of using AI technologies for achieving the Sustainable Development Goals (SDGs) by 2030.
The speakers talked about the potential use of AI in agriculture, nutrition, education, health, poverty alleviation, climate change, disaster management, etc.
What is Artificial Intelligence?
AI is a set of computational tools that can be used to improve decision-making.
It is the theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.
AI can play a transformative role in following sectors:
Health and nutrition:
The level of malnutrition and stunted growth in pre-school children in India is alarming. AI can help in following ways-
Tracking the progress of individuals- In a project in Karnataka AI-based systems is being used to improve delivery of child nutrition programmes. While existing systems capture data about children, the Anganwadi worker gets overwhelmed with the quantum of data produced. AI-based systems can sift through this data and track the progress of an individual child at various Anganwadi centres in terms of their cognitive development and health. In addition, image-recognition techniques can help in early identification of stunted growth, epidemics and other health issues. This information can then be used by the programme officers to recommend corrective solutions.
Integrating information from other sources, the AI systems can assist in the diagnosis of problems being faced—from drought to poor sanitation and inadequate supplies.
Agriculture:
Issues in agriculture like low yields, dependence on rains, high costs of fertilizers and pesticides, inefficient use of water, often depleting the water table can be resolved using AI.
Precision farming using AI- Several start-ups in the US have used AI to develop “precision farming” practices, which lead to a more efficient use of inputs and higher yields. Sensors gather information about the condition and colour of foliage and soil moisture content. This information is fed to the system, which determines the amount of water, and fertilizer to be provided. It also specifies which part of the plant needs to be provided with these inputs. These systems have reported higher yields and reduction in agricultural inputs.
Education:
AI-based systems can assist students with their learning experience, especially in changing the form and nature of content to suit the student. “Smart content” is generated with text summaries, supported with related videos and simulations.
AI can also help connect with students who are working on similar problems worldwide. The systems can ensure that learning takes place through frequent testing which can be used as feedback to alter the course content and trajectory.
AI cannot entirely replace the human teacher, but an AI system can play an intermediate role by providing timely feedback to students and teachers.
Smart energy:
Artificial intelligence could help us be smarter about our energy consumption. Google and other tech giants have enormous data centres that require a massive amount of energy to run the servers and keep them cool. Google has used its artificial intelligence platform Deep Mind to predict when its data centres will get too hot. Cooling systems are only activated when required. AI has saved Google around 40% in energy costs at its server farms.
Helping wildlife:
As in the case of healthcare, being able to analyse massive amounts of data can transform wildlife conservation. For instance, by tracking animal movements, we can see where they go, and what habitats we need to protect. This study uses computing power to figure out the best places to create wildlife corridors for wolverines and grizzly bears in Montana. Wildlife corridors are continuous areas of protected land that link zones of biological significance that the animals can use to move safely through the wilderness.
Challenges:
As in case of agriculture, the use of such AI technologies in Indian conditions will need to consider much smaller land-holding sizes and the socioeconomic conditions of farmers.
Some of the available AI technologies are expensive today.
There are also ethical issues of privacy of data, equity and liability of actions.
One of the biggest of challenge is – how do we keep the systems safe? Algorithms are based on data, so any change to that data will change the behaviour and outcomes.
Conclusion:
AI is in the middle of exponential growth and it has the potential to make game-changing transformations. The developmental challenges faced by India are also too big to be solved by the conventional linear approach. AI provides an opportunity for transformative solutions and India’s scale provides the possibility of rapid cost reduction of these technologies.
