Over the years, Deep Learning has become the most popular approach to developing Artificial Intelligence (AI) – machines that perceive and understand the world. It empowers geospatial ecosystem by providing real-time near-human level perception; integrates into analytical workflows and driving data exploration and visualisation – automating the entire process of creating scalable insights from large amounts of data. Such machines will be able to ‘understand’ geospatial information themselves and with deep learning, able to self-obtain geospatial information from their surroundings as per required to do their jobs, processing it in real time. This is truly an extraordinary time.
AI and Deep Learning have been applied to a vast range of industries, from healthcare, to finance, advertising and retail, to manufacturing and transport. As these frontier technologies continue to transform industries, we wonder what’s in it for geospatial community. Which sectors can bring most impacts to world’s economy with geospatial & deep learning? Is automation a threat to human resource?
An interactive workshop at Geospatial World Forum 2017 held in Hyderabad was a platform for geospatial players to meet and share ideas with experts from various industries on geospatial opportunities in the up-rise of Artificial Intelligence and Deep Learning.
Drawing attention to the sectors which can bring most impacts to world’s economy with geospatial and deep learning, Budhendra Bhaduri, Director, Oak Ridge National Laboratory, USA, said, “There is a tremendous impact waiting to happen on the global economy from various sectors. I believe defense and intelligence is leading the way so is the commercial business sector. But, there is an overall impact on society and humanity and we need to make sure the societal services reach population. Thinking at large – about anything from agriculture to climate change science all the way to security applications to enabling e-commerce and even the future of society in interconnected infrastructure, are going to be deeply impacted by AI and Deep Learning.”
Dittoes Sundara Ramalingam Nagalingam, Head – Deep Learning Practice, NVIDIA, India: “Deep Learning as a domain is touching every aspect of human life and what is the economic impact of it – it is really huge, for example, autonomous vehicles that itself is expected to be multiple billions over the next few years and in fact almost every car manufacturer in the world is setting up R&D centers and trying to move their solutions to be more software driven then hardware driven. So, it is a major economic impact segment that we are talking about.”
There are multiple social innovations possible and these will impact the life led by human beings today. Nagalingam explains further, “For example, if we talk about poverty and epidemic – how is the poverty spread over a particular area, what is the prediction of the direction in which the epidemic will spread, what preventive measures are required. All this can be done through prediction using deep learning methods; and the ‘where’ factor definitely comes through geospatial data. So, a major socio-economic change and impact can be brought by using deep learning and geospatial data.”
Conversing about the opportunities for geospatial industry following the rise of artificial intelligence and deep learning in various business and social innovations, Aswani Kumar Akella, Founder, Latgeo Consulting, India highlighted, “The biggest opportunity for geospatial industry is its core asset which is geospatial data. Most of data-sets that we generate and deal with are geospatial in nature so exploiting that data using automation through AI and deep learning comes naturally to creating solutions for rest of the basic sectors.”
The application phase is deeply tied with the geospatial world, even if we think about agriculture, climate, connected autonomous vehicles, defence and intelligence, all the data that are been collected as part of these sectors are essentially geospatial in nature. “If there is any community that is poised to make a deep impact on AI and deep learning based solutions – geospatial industry is going to be the leading one,” emphasize Bhaduri.
Data today comes to us in many different forms and resources. Geospatial is a key platform which uses geographic coordinates in bringing different data together. The most important part looking through AI and deep learning is to understand the context and not just the objects.
“Here we are talking about a very interesting technology – sensor fusion technology. Again talking about autonomous vehicles – they have input from multiple sensors, like – camera, radar, LiDAR. But for an intelligent decision, it has to be an amalgamation of all these data,” said Nagalingam.
Amidst all these discussion the grey area: “Is automation a threat to human resource?” was also addressed. Dr Bhaduri was assured that automation is not necessarily a threat. He said, “It is well recognized that the rate of automation could perceivably dwarf the rate human beings can be retrained for particular trade. So, automation could be disruptive to society in terms of making some of these functionalities obsolete or not so much effective but at the same time automation also opens up opportunities for creating new ways of analyzing our environment, creating solutions for every possible sector which in turn require new sets of skills and diverse sets of talent.”
Overall it may be a threat to part of the society who will have the challenge to keep up with their occupations but at the same time there would be different kinds of challenges that would create different kinds of career options and opportunities for people to continuously innovate. The society is likely to benefit from it.
“I expect that after an initial downward trend in terms of human skills, there will be a change in what all people are skilled at, like today people are skilled more on programming side may be people will be skilled more on writing algorithms for deep learning or AI. So, after an initial period of lull I think it will pick up,” Nagalingam added.
Mansour Raad, Senior Software Architect, Esri, USA underlined, “The pace at which automation is happening, the human skills can face some sort of threat for a short period of time, but then technology watches up with human beings and vice-versa. AI and deep learning has enhanced our capabilities. AI makes GIS more affluent which in turn makes our life easy.”
Pankaj Dahiya, Executive Director, Hypothizer, sums up, “Geospatial industry as a whole has a vast amount of data and deep learning can help automate extraction of information from these visual data-sets which was not possible before. Humans have a limited capacity for focus and efficiency. AI and deep learning defiantly increases work efficiency. Automation as such is not a threat but pace of automation is crucial. All we need to do is to adapt and re-skill ourselves.”
It’s almost impossible to escape the impact frontier technologies are having on everyday life. AI and Deep Learning can solve problems that seemed well beyond our reach just a few years back. These will also usher in the 4th industrial revolution. AI and Deep Learning are beginning to reshape our world — so it’s incumbent upon us to understand the connection between geospatial ecosystems and machine deep learning, and how the integration of both can produce ultimate knowledge for shaping a smarter world.