Today, insurance fraud is detected by a combination of claim analysis, computer programs and even private investigators. The FBI estimates the total cost of non-healthcare-related insurance fraud to be around $40 billion per year. But a maturing emerging technology called emotion artificial intelligence (AI) might make it possible to detect insurance fraud based on audio analysis of the caller.
Current versions link specific emotional states (i.e., happy, sad, insecure) to specific soundwaves. In the future, emotion AI could analyze the emotional state of a user via computer vision, audio/voice input or software logic.
Technology innovation is the key to competitive differentiation and is transforming many industries
In addition to catching fraud, this technology can improve the customer experience by tracking happiness, more accurately directing callers, enabling better diagnostics for dementia, detecting distracted drivers, and even adapting education to a student’s current emotional state.
Though still relatively new, several new commercial deployments and emotion AI vendors arose in the past two years. This makes emotional AI one of 21 new technologies added to the Gartner Hype Cycle for Emerging Technologies, 2019.
“The 2019 Hype Cycle highlights the emerging technologies with significant impact on business, society and people over the next five to 10 years,” says Brian Burke, Research Vice President, Gartner. “Technology innovation is the key to competitive differentiation and is transforming many industries.”
This year’s emerging technologies fall into five major trends: Sensing and mobility, augmented human, postclassical compute and comms, digital ecosystems, and advanced AI and analytics.
Sensing and mobility
As sensors and AI evolve, so will the situational awareness of autonomous robots. This means emerging technologies such as light cargo delivery drones (both flying and wheeled) will be better able to navigate the world around them. This technology is currently hampered by regulations, but its functionality is continuing to advance.
This trend features technologies with increasingly enabled mobility and ability to manipulate objects around them, including 3D sensing cameras and more advanced autonomous driving. As sensing technology continues to evolve, it will aid more advanced technologies like the Internet of Things (IoT). These sensors also collect a lot of data, which can lead to insights that are applicable across a range of scenarios and industries.
Other technologies in this trend include: AR cloud, autonomous driving levels 4 and 5, and flying autonomous vehicles.
Augmented human technologies improve both the cognitive and physical parts of the human body by including technologies such as biochips and emotion AI. Some will provide “superhuman capabilities” — for example, a prosthetic arm that exceeds the strength of a human arm — while others will create robotic skin that is as sensitive to touch as human skin. These technologies will also eventually provide a more seamless experience that improves the health, intelligence and strength of humans.
Other technologies in this trend include: Personification, augmented intelligence, immersive workspace and biotech (cultured or artificial tissue.)
Postclassical compute and comms
Some technologies within the postclassical compute and comms trends are totally new architectures, while others are small but impactful changes to existing designs. This is a change from traditional computational maturity, which mainly involved improvements to traditional architectures that resulted in faster CPUs, denser memory and increasing throughput.
Low-earth-orbit (LEO) satellites operate at much lower altitudes, around 1,200 miles or less, as compared to traditional geostationary systems at around 22,000 miles, enabling low-latency communications. These systems provide global broadband or narrowband voice and data network services, especially to places with little or no existing terrestrial or satcom coverage.
Other technologies in this trend include: Next-generation memory, nanoscale 3D printing and 5G.
Technological improvements are morphing traditional value chains into web-like digital ecosystems that connect a variety of agents and entities using digital platforms across geographies and industries. Digital ecosystems have emerged and are becoming increasingly automated. In the future these will include decentralized autonomous organizations (DAOs), which operate independently of humans and rely on smart contracts. These digital ecosystems are constantly evolving and connecting, resulting in new products and opportunities.
Other technologies in this trend include: DigitalOps, knowledge graphs, synthetic data and decentralized web.
Technological improvements are morphing traditional value chains into web-like digital ecosystem
Advanced AI and analytics
Advanced analytics is the autonomous or semi-autonomous examination of data or content using sophisticated tools beyond those of traditional business insights. This is the result of new classes of algorithms and data science that are leading to new capabilities, for example transfer learning, which uses previously trained machine learning models as advanced starting points for new technology. Advanced analytics enables deeper insights, predictions and recommendations.
Other technologies in this trend include: Adaptive machine learning, edge AI, edge analytics, explainable AI, AI PaaS, generative adversarial networks and graph analytics.
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