Artificial intelligence is present and growing in adoption in workflows that require the processing of large imagery datasets. Algorithms that are trained for pattern recognition are counting and classifying objects that are then processed for dashboards, reports and other insights. This kind of information extraction drives business and other critical decisions on a daily basis, and there are very few humans involved.
The machines, and the infinite computing capacity of the cloud, have taken over. This change toward automation is an answer to derive intelligence from today’s explosion of data, but it’s scary to think that there’s no going back. This transformation and machine takeover is not only attacking the geospatial marketplace, it’s everywhere you turn from automated telephone call centers and even algorithms that could probably do a better job of writing this column. Are you hiding under your desk yet, or are you ready for the shift toward a data-driven society?
There’s a certain feeling of powerlessness that comes with automation that takes workflows that had once been a valued and even lucrative occupation and gives them to algorithms and monolithic dark and humming computing centers. We protest in the face of such soulless automation, and yet the market demands faster answers that only machines can provide.
Of late, there have been some high-profile cautionary and even alarmist statements from thought leaders such as Bill Gates, Elon Musk and Stephen Hawking about the threat posed by artificial intelligence. Before you get too concerned, consider that Alan Turing, one of computing’s pioneers, had predicted artificial intelligence back in the 1950s and we’re still a ways off to realizing the level of functionality he posited. Yes, we do have a computer that wins at chess and more recently at the trivia game Jeopardy, but there’s just one of them so far. It may be some time before these machines turn to the mapping, data handling and analytical services that geospatial professionals provide
Instead of focusing on how the computers will take our jobs, or to think that they might take away the aspects that we enjoy the most, perhaps it’s best to plan and prepare to harness this power. Ray Kurzweil, the inventor best known for his focus on the singularity where man and machine will meld, is of the mind that our machines will assist our memories and our workflows to make us smarter and more efficient.
The augmented intelligence idea is a parallel splinter to artificial intelligence thinking, and poses a more benign, although certainly still disruptive, view on smarter machines and data processing. The idea that we’ll each have a computer assistant that melds easily with our consciousness to assist in memory, to catalog our ideas and interests and keep tabs on reference materials to make sure that we’re up to date, is a more friendly idea. In this scenario the maps that we could generate with the help of computers would consider more inputs and more real-time information thanks to assistance that could keep watch and catalog and classify the data that would make our maps the most current and complete.
Today’s tools for processing large imagery datasets are an impressive leap forward in making sense of the big data volumes. To date, the pioneers in this field such as the military and companies like Orbital Insight are selling the resulting insight as a service. It’s not a stretch to imagine that a company might stand up a similar capacity that would allow you to add your own data and problem sets to an online platform so that you might explore a deep set of historical imagery and other data for better insights of your own.
There are a great many disruptive technological innovations today that are putting added pressure on business as usual. Some see the tools and processes as a threat to the way they’ve always done things, while others are embracing each added capability and are enhancing the way that they work. Machines are becoming more capable through a series of advancements that is not slowing down.
Now would be the time to acknowledge the rise of smarter machines, and to adapt and embrace the opportunity for added insight. We’ve had a crack at greater understanding of the complexity around us, and we’ve made inroads, but with the clearer logical capacity of machines there’s no telling what our assisted intelligence might reveal.