Can AI Help Prevent Natural Disasters?

By Kathleen Walch, Contributor

Advanced analytics and other AI-driven tools and technologies have been transforming the way organizations function by harnessing valuable information from the largest datasets and providing important insights. With the continued growth of cognitive technologies and increasingly widespread adoption by many industries, what will the future of advanced analytics and AI adoption look like? 

Antonio Cotroneo, Director of Technical Content Strategy at OmniSci Antonio Cotroneo

With the evolution of big data analytics over the past few years, the opportunities to apply this knowledge and to see how different industries are embracing AI and ML has shown tremendous value. However, the evolution and future of analytics doesn’t come without challenges. In a recent AI Today podcast interview with Antonio Cotroneo, Director of Technical Content Strategy at OmniSci, spoke about these potential challenges as well as opportunities for industries. Antonio’s background is in helping organizations maximize their geospatial data, mapping technology, and spatial analyses for decision-making, so it would only make sense that he provide comprehensive details on how advanced analytics and AI are changing the game when applied to helping prevent natural disasters. Anthony will be presenting at an upcoming Data for AI community virtual event on October 28, 2021 where he will explore how geospatial companies like OmniSci can play an important role in understanding the factors, risks, and impacts of wildfires.

Evolving Big Data and Data Analytics

As new developments in cognitive technologies continue to be introduced, the role of data and data analytics, especially in big data, has been evolving as well. The biggest shift, Antonio notes, is in how the collective idea of AI, ML, big data, analytics, and visualization is moving towards a broader audience. Technologies that were traditionally used or understood only by hardcore practitioners such as data scientists or other AI practitioners are now moving to knowledge workers. As a result of this transition, people are beginning to see the impact of AI on their day-to-day activities, both in their work and home lives. Whether it be through new tools or downstream analytics services, individuals are able to use these advancements to inform their decisions in ways that were not possible or common before. 

Antonio explains that a decade ago in the industry of Geographic Information Systems (GIS), the focus was mostly on making observations about what had happened or mapping out current states and creating visuals. This is still an important aspect, but the newer focus is now on taking additional steps to not only observe or orient, but being able to track and predict the trajectory of any phenomenon. In terms of the larger trends, the commodification or consumerization of AI and ML is beginning to impact a broader audience, which is when these technologies will really penetrate the marketplace even more, says Antonio. 

AI Adoption and Usage across Industries

Artificial intelligence has become a frequent topic of conversation in almost every industry worldwide, but which industries are truly leading the adoption of these advancements? The industries that are embracing these technologies the most seem to be those that have embraced the waves of technological advancements in the past. The U federal government and specifically the military, for instance, are taking a large role in the research, development, and use of AI, and other industries such as the FinTech market are key drivers as well. The industries that have traditionally pushed the boundaries of our current understanding of these concepts are the ones that are building the initial practical examples of how they can be used and pushing us into the new emerging spaces. The automotive and manufacturing industries are other key examples, with the automation of factories and transportation leading to the ideas of connected cities and services. In some industries, however, the privacy or security of organizations keep these technologies and concepts behind closed doors, but the overall trend across markets is towards widespread adoption and shared knowledge. 

The Growth of Advanced Analytics

Artificial intelligence and machine learning are part of the overall trend of deriving more insights from data and finding the patterns and applying tools that lessen the cognitive load on the human. Antonio believes the future of these advanced analytics is again in how we are going to be using AI and ML products in our daily lives, from a more personal or human perspective. Analytics are already being used in financial services for tasks such as predicting whether an individual will default or qualify for a loan. Virtual assistants are another example of how analytics are becoming more and more incorporated into our personal lives. As advanced analytics become more and more present in our routines, the future is less about the deep technical worker being the individual interfacing or building solutions, services, and applications, and more about the users being impacted and using AI, ML, and analytics to accomplish even ordinary tasks.  

Impacts of AI, Ethical Frameworks, and the General Future of AI 

In today’s world, there are many ethical AI frameworks issued by corporations, non-profits, governments, and industry groups. More often than not, however, these various frameworks exhibit little overlap and are each focused on only a small subset of the aspects of using AI in ethical ways. While most frameworks mention fairness, bias, and dignity to some degree, there are many other areas such as consent, disclosure, contestability, interpretability and explainability, governance, and ownership that are important aspects of responsible AI. These aspects contribute to why there can sometimes be discomfort in performing the kinds of analytics that are in demand today. Antonio explains that at OmniSci, teams are careful to choose data partners that are curating datasets in ethical ways and critically considering these types of frameworks. There have been situations where he and his teams have had to walk away from certain uncomfortable situations where harvesting data can cause sticky situations related to privacy and security. This is why working with data providers that strive for both quality and equitability simultaneously in generating datasets is important for presenting an accurate picture of the world and ultimately for producing good analytics. 

The general future of AI, says Antonio, is when we will not even realize that it is there, when systems, governments, and organizations – all the different components of our culture – are going to be in some ways functioning off of AI and ML through means we will not even notice. In fact, we are already entering that stage, as many individuals may not even be aware of how AI and ML is affecting their lives today. As this growth continues, one important area of focus as a culture, as technologists, and as people in this space, is the continued push for broader research and critical thought around AI and ethics. There are already plenty of people working on the technical problems, building more efficient algorithms, better models; there is no absence of data. However, in order to properly use the data to produce valuable information, the focus should be placed on how to leverage AI responsibly and inclusively. For additional insights on this Anthony will be presenting at an upcoming Data for AI community virtual event on October 28, 2021 where he will explore how geospatial companies can play an important role in understanding the factors, risks, and impacts of wildfires and how data, advanced analytics, and AI are making an impact.

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