Artificial Intelligence
Risk Management

Artificial Intelligence is already here

Have you used Siri or Alexa to get directions, or asked your phone to find the nearest coffee shop? While shopping online, have you looked at the related products the merchant suggested? Or have you watched a recommended movie on a streaming video service? If you've done any of these things, you've experienced artificial intelligence in action.


What is Artificial Intelligence?

Artificial Intelligence (AI) is a concept that has been around as an academic computing principle since the mid 1950’s. It is divided into multiple sub-classifications that strive to mimic cognitive functions humans normally associate with neural activity – reasoning, problem solving, or learning. Two areas that define AI are machine learning and deep learning.

Machine Learning

Machine learning is based in the principles of identifying predictive models or patterns that are present within large datasets, and applying the learnings proactively. Areas where these concepts are being deployed include analyzing sensor data to better protect insured property and assets, or effectively managing fraudulent credit card or financial transactions to better mitigate risk. This functionality enables the timely issuing of alerts, and better monitoring of transaction decline thresholds. But its use isn’t limited to financial products. Within healthcare, for example, machine learning is being utilized to look for anomalies within images in x-ray analysis.

Deep Learning

Beyond machine learning are concepts related to deep learning. Deep learning looks to mimic the neural networks of the human brain, and to learn from the environment. A segment of deep learning includes the evolution and use of natural language processing – think of Alexa and Siri – and how these systems can understand, interpret and respond to conversation-based questions. Other areas where deep learning concepts are being applied include bioinformatics with the use of wearables to analyze sleep quality, or predict health complications based on electronic health record data. 

The most well-known use of deep learning is self-driving cars mapping their surroundings and detecting and anticipating hazards. Amazon’s physical store in Seattle is another example, using deep learning systems to transform the shopping experience with the elimination of cashiers.

IBM claims they are providing solutions that look to integrate with various analytic solutions that will consolidate healthcare data from disparate systems and risk stratify populations, helping healthcare teams quickly and effectively identify appropriate candidates for care management.

With the evolution of artificial intelligence, IDC forecasts worldwide spending on AI hardware, software, and services will increase from $19 billion in 2018 to $52 billion by 2021. Along with Google, Facebook, Apple, Microsoft, and (of course) Tesla, companies are heavily investing in this space to continue to find ways to tap into this technology. 

So why is AI having its day in the limelight now? Although these concepts and solutions have been talked about for fifty years, we are just now seeing the confluence of large amounts of data readily available, affordable access to powerful computing platforms (in the cloud), and better algorithms being developed. As these forces continue to converge, AI will be more heavily relied upon than ever before. Then the next wave will begin.


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