The first few decades of the information age have been marked by a significant increase in data storage and processing capabilities. In conjunction with this increase, the quantity of data has increased as well. The result is that most industries are now buried under mountains of data. Companies have come to recognize that there is value in analyzing this data.
Up until this decade, it has been difficult for companies to find and exploit this value because the analytical tools were too primitive or expensive. Breakthroughs in machine learning algorithms and increases in parallelism in processing have come together to offer an affordable solution. Today artificial intelligence (AI) is being used in many different industries.
Industries are turning to AI to derive value from their dataOne example of an industry with a tremendous amount of data in need of analysis is medical diagnostics. The Institute of Medicine at the National Academies of Science, Engineering, and Medicine reports that “diagnostic errors contribute to approximately 10 percent of patient deaths”.
With an aging population suffering from a multitude of chronic diseases, combined with the nascent field of personalized medicine via genetic dispositions, the stage is set for AI to become a significant part of the diagnostic process.
Already AI is being incorporated into diagnostics. For instance, deep learning algorithms are learning to spot cancer tissue. Machine vision systems are being incorporated in the analysis of blood and urine, spotting potential problems that previously could only be identified by a pathologist with a microscope. Facial recognition programs are being used to look for facial patterns associated with rare diseases.
Another industry that is benefiting from AI is the automotive industry. In the past few years alone there has been a steady increase in offerings related to driver assistance. Adaptive cruise control, lane keep assistance with drift warnings and automatic emergency braking has become standard on high-end models. Enhanced cruise controls such as Super Cruise by GM, Distronic Plus by Mercedes-Benz, ProPilot Assist by Nissan and of course Autopilot by Tesla offer semi-autonomous driving.
An interesting consequence of the automobile industry’s rapid AI development has been getting drivers to adjust. Where the automotive companies need drivers to trust the systems and only intervene in emergency situations, what they are finding is that drivers go from not trusting the systems at all to trusting them too much. There have been incidents where drivers have slept as their car drove autonomously on the highway. Automotive companies are not in a race to achieve fully autonomous cars for full-scale production, but within the next decade, there likely will be cars that need only be told a destination.
The introduction of AI will likely also result in job loss in many industries. The real estate industry is an example of one such industry where brokers may eventually find they’ve been replaced by machines. The process of buying a home is expensive and time-consuming. Both buyers and sellers depend upon brokers to know the comparable sales in a neighborhood in order correctly price a home. Details such as home type, neighborhood, schools and house features play a large role in this pricing strategy. Most of these details can be found in databases and analyzed by AI.
Typically brokers will require 5% to 6% of the sales price of the house, which is then split between the buyer’s and seller’s brokers at closing. A company called REX offers to act as both the buyer’s and seller’s broker for 2% and is a licensed real estate broker in California, Colorado, New York and Texas. REX is able to charge such a low fee because it uses AI in place of the brokers.
The AI takes the seller information and posts it to real estate websites such as Zillow, Trulia and Realtor.com. It then analyzes historical buyer and seller data to identify likely buyers for the house. Then REX purchases ads on websites and social media that target those potential buyers. Since 2016 REX has closed 200-plus transactions, so the technology is still relatively new. Still, the user experience has been positive and REX has ambitious plans to grow.
These are but a handful of the industries that are turning to AI to improve products and profits. Other notable industries include education, where everything from career paths to college acceptance can be done by AI. Human resource departments often use AI to vet candidates and make evaluation more manageable. Researchers in fields ranging from the social sciences to chemistry are using AI to better understand their data and develop models. Civil engineers are starting to use AI to develop non-intuitive infrastructure layouts that are more efficient. The law industry is finding AI helps reduce workload, and in some simpler cases even can serve as the lawyer itself.
The information age is a time of increasing bandwidth, storage and processing power. Cloud computing, edge computing, mobile devices and the IoT are offering more data. With all this data and analysis comes the opportunity for improvements and increased efficiency. It is not surprising then that many industries are turning to AI in order to improve performance and better understand customers. As AI algorithms become more sophisticated and data more prevalent, reliance on AI will only grow. A future of self-driving cars, chat-box lawyers and computer pathologists may be right around the corner.
