What’s New in Gartner’s Hype Cycle for Emerging Technologies, 2020

Health Passports lead all technologies in their potential to make a transformational impact in two years or less, accelerated by early adopters in China (Health Code) and India (Aarogya Setu). Social distancing technologies first enter the hype cycle at the top of the peak of inflated expectations due to the extraordinary amount of media coverage and customer inquiries. Gartner continues to expand its coverage of AI’s potential in this year’s Hype Cycle, with several categories added this year, including Composite AI, Generative AI, Responsible AI, AI Augmented Development Embedded AI and AI Augmented Design.

These and many other new insights come from Gartner Hype Cycle For Emerging Technologies, 2020 published earlier this year and summarized in the recent Gartner blog post, 5 Trends Drive the Gartner Hype Cycle for Emerging Technologies, 2020. Gartner’s definition of Hype Cycles includes five phases in a technology’s life cycle and are explained here.

Of the many hype cycles that Gartner produces each year, this one is noteworthy as its methodology evaluated more than 1,700 emerging technologies into a concise set of the 30 most transformative in the next five to ten years. AI-specific technologies appearing for the first time in the Hype cycle are defined following the graphic. The Gartner Hype Cycle for Emerging Technologies, 2020 is shown below:

AI-specific details of what’s new in Gartner’s Hype Cycle for Emerging Technologies, 2020

Health passports are mobile applications that indicate the relative level of infection risk a person is and whether they can access buildings, supermarkets, restaurants, public spaces and transport. Early adopters in China and India are proving the combination of health passports and screening methodologies to be effective in stopping the spread of Covid-19, while also giving people the freedom to use public spaces and transport. China’s health code is widely used as a screening tool to reduce the risk of Covid-19 transmission. It provides the user with a color QR code based on their designated health status: Red is confirmed with Covid-19; Yellow must be quarantined and Green is free to travel. Health code checks are very common, making it difficult to move without having a green code. Early leaders in health passports include Alipay, Bizagi, Circle Pass Enterprises, Folio, Vottun and WeChat. Formative AI is a new category of technologies that Gartner predicts will be able to sense and dynamically respond to changing situational conditions. One of the primary use cases of formative AI would be to provide UI/UX designers with real-time interactive feedback to improve the usability of software and intelligent products. Gartner also predicts that formative AI will be used to streamline how mathematical and machine learning models are created and refined over time. Key technologies involving formative AI in the Hype Cycle include: AI-augmented design, AI-augmented development, ontologies and graphs, small data, composite AI, adaptive machine learning (ML), self-supervision learning, generative AI, and generative adversarial networks . Augmented AI Design is new to the Hype Cycle this year and has the potential to transform how digital and smart, connected products are designed, manufactured and sold. Gartner defines AI-augmented design as the use of artificial intelligence (AI), machine learning, and natural language processing technologies to automatically generate and evolve via machine learning, user flows, screen designs, content, and presentation layer code for digital products. AI-augmented design is already transforming the customer experience through decision support and personalization in CX products and site building platforms, including that of B12 which has added AI to curate content and best practices for your business type in less than a minute . Gartner expects to see AI at work in the digital product design platform market. Gartner predicts Adobe Xd, Figma and InVision will take the lead in this emerging technology category. New to the Hype Cycle this year, Composite AI refers to the aggregation or combination of different AI techniques to improve learning accuracy and efficiency. Gartner believes that composite AI will be an enabling technology for organizations that do not have access to large historical data sets or in-house AI expertise to complete complex analytics. Second, Gartner believes that composite AI will help expand the scope and quality of AI applications. Early leaders in this space include ACTICO, Beyond Limits, BlackSwan Technologies, Cognite, Exponential AI, FICO, IBM, Indico, Petuum and ReactiveCore. Embedded AI is one of the fascinating new technologies on the Hype Cycle, given its potential to increase the accuracy, insights and intelligence gained from current and next-generation sensors. Gartner defines Embedded AI refers to the use of AI/ML techniques within embedded systems to enable an analysis of locally captured data. Reducing the time it takes to analyze sensor data while improving the insights can transform sensor-based intelligence and the data captured using IoT and smart sensors. From consumer electronic products to production machinery and long-life assets, embedded AI can provide insights needed to improve customer experiences, increase production efficiency and learn more about Maintenance, Repair and Overhaul (MRO) cycles. Early leaders in this area include Arm, Cartesiam, NXP Semiconductors, One Tech, Renesas Electronics and STMicroelectronics. Also new to the Hype Cycle for the first time this year, Generative AI is the most used technology for creating “deep fake” videos and digital content. Generative AI is a variety of ML methods that learn a representation of artifacts from the data and use it to generate brand new, completely original, realistic artifacts that retain a similarity to the training data but do not replicate it. Generative AI can produce original content (images, video, music, speech, text – even in combination), improve or modify existing content, and create new data elements. Generative AI are the technologies used for creating “deeply fake” digital content by bad actors seeking to cause dangerous disruption of regional and political stability. The Partnership on AI and DARPA aims to detect “deep fakes” to counter fraud, disinformation, incitement of social unrest. Responsible AI is another new category on the Hype Cycle this year and is defined as a range of technologies whose aim is to help businesses make more ethical, balanced business decisions by trying to reduce bias. The purpose of Responsible AI is to streamline how organizations put responsible practices in place to ensure positive AI development and use. One of the most pressing use cases of Response AI is identifying and stopping “deep counterfeit” production worldwide. Gartner defines the category with use cases that involve improving business and societal value, reducing risk, increasing trust and transparency, and reducing bias mitigation with AI. Of the new AI-based additions to the Hype Cycle this year, this is one that leads all others in its potential to use AI for good. Gartner believes that responsible AI should also increase the explainability, accountability, security, privacy and regulatory compliance of organizations. AI-augmented development is on the Hype cycle for the first time this year and its goal is to improve the cycle times of application and DevOps teams to create high-quality software faster and more consistently. Gartner defines AI-augmented development (AIAD) as the use of AI technologies such as machine learning (ML), natural language processing (NLP) and similar technologies to accelerate application and DevOps cycles. Early leaders in this space include Codota, Deep Code, Google, Kite, Mendix, Microsoft, OutSystems and Parasoft. Self-supervised learning is new to the Hype Cycle this year, positioned as an enabling technology to help organizations adopt machine learning supervised techniques. While initial R&D at Craftworks, Facebook, Google, and Microsoft, self-supervised learning is an emerging technology that seeks to overcome one of the major drawbacks of supervised learning, which is the need to access typically large amounts of tagged data. Gartner predicts the potential impact and benefits of self-supervised learning are very large, as it will expand the applicability of machine learning to organizations that lack the availability of large data sets. Twenty-two technologies have been removed or reassigned from this year’s Hype Cycle for Emerging Technologies compared to 2019. The 22 technologies no longer on the Hype Cycle for Emerging Technologies include: 3D surveillance cameras, 5G , AI Cloud Services, AR Cloud, Augmented Intelligence, Autonomous Driving Level 4, Autonomous Driving Level 5, Biochips, Decentralized Web, DigitalOps, Edge AI, Edge Analytics, Emotion AI, Flying Autonomous Vehicles, Graph Analytics, Immersive Workspaces, Knowledge Graphs, Lights cargo delivery drones Earth Orbiting Satellite Systems, Personification, Synthetic Data and Transfer Learning.

Sources:

5 Trends Driving the Gartner Hype Cycle for Emerging Technologies, 2020 by Kasey Panetta. Published on August 18, 2020.

Gartner identifies five emerging trends that will drive technology innovation for the next decade Aug 18, 2020.

Hype Cycle for Emerging Technologies, 2020 by Brian Burke, Marty Resnick and Arnold Gao. Published July 24, 2020 (client access requested).