What’s New In Gartner’s Hype Cycle For Emerging Technologies, 2020

Louis Columbus

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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 enter the Hype Cycle for the first time at the top of the Peak of Inflated Expectations due to the extraordinary amount of media coverage and client 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 are 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 of a technology’s lifecycle and is explained here.

Of the many Hype Cycles Gartner produces every year, this one is noteworthy as its methodology evaluated more than 1,700 emerging technologies into a concise set of the 30 most transformational 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:

HTTPS://WWW.GARTNER.COM/SMARTERWITHGARTNER/5-TRENDS-DRIVE-THE-GARTNER-HYPE-CYCLE-FOR-EMERGING-TECHNOLOGIES-2020/

AI-Specific Details Of What’s New In Gartner’s Hype Cycle for Emerging Technologies, 2020

Health passports are mobile apps that indicate the relative level of infection risk a person is and whether they can gain access to buildings, supermarkets, restaurants, public spaces and transportation. Early adopters in China and India are proving the combination of health passports and screening methodologies that are effective in stopping the spread of Covid-19 while also giving people the freedom to use public spaces and transportation. China’s Health Code is widely used as a screening tool to minimize the risk of Covid-19 transmission. It provides the user with a color QR code based on their designated health status: Red is confirmed infected with Covid-19; Yellow should be in quarantine 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 uses cases of formative AI would be providing UI/UX designers with real-time interactive feedback to improve the usability of software and intelligent products. Gartner also predicts formative AI will be used to streamline how mathematical and machine learning models are created and fine-tuned over time. Key technologies that comprise formative AI in the Hype Cycle include the following: AI-augmented design, AI-augmented development, ontologies and graphs, small data, composite AI, adaptive machine learning (ML), self-supervised 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, produced and sold. Gartner defines AI-augmented design as the use of artificial intelligence (AI), machine learning and natural language processing technologies to generate automatically 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 builder platforms, including those from B12 who have added AI to assemble content and best practices for your business type in under 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.

Composite AI is new to the Hype Cycle this year and refers to the aggregating or combining of different AI techniques to improve learning accuracy and efficiency. Gartner believes that Composite AI will be an enabling technology for organizations that don’t have access to large historical data sets or have AI expertise in-house to complete complex analyses. Second, Gartner believes that Composite AI will help expand the scope and quality of AI applications. Early leaders in this area 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 gained could transform sensor-based intelligence and the data being captured using IoT and smart sensors. From consumer electronics products to production machinery and long-life assets, embedded AI could provide insights needed to improve customer experiences, increase production efficiency and know more about the Maintenance, Repair and Overhaul (MRO) cycles. Early leaders in this area include Arm, Cartesiam, NXP Semiconductors, One Tech, Renesas Electronics and STMicroelectronics.

Generative AI is also new on the Hype Cycle for the first time this year and is the technology most often used for creating “deep fakes” 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 preserve a likeness to the training data, but do not repeat it. Generative AI can produce original content (images, video, music, speech, text — even in combination), improve or alter existing content and create new data elements. Generative AI is the technologies used for creating “deep fakes” digital content by bad actors attempting to cause dangerous disruption to regional and political stability. The Partnership on AI and DARPA is pursuing the detection of “deep fakes” to counteract fraud, disinformation, instigation of social unrest.

Responsible AI is another new category on the Hype Cycle this year and is defined as a series of technologies whose purpose is to assist businesses in making more ethical, balanced business decisions by attempting to reduce bias. The goal of Responsible AI is to streamline how organizations put responsible practices in place to ensure positive AI development and use. One of the most urgent use cases of Response AI is identifying and stopping “deep fakes” production globally. 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 on its potential to use AI for good. Gartner believes responsible AI also needs to increase the explainability, accountability, safety, privacy and regulatory compliance of organizations as well.

AI-augmented development is on the Hype Cycle for the first time this year and its purpose is to improve the cycle times of application and DevOps teams in creating high-quality software faster and more consistently. Gartner defines AI-augmented development (AIAD) is the use of AI technologies such as machine learning (ML), natural language processing (NLP) and similar technologies to accelerate app and DevOps cycles. Early leaders in this area 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 supervised machine learning techniques. While in initial R&D at Craftworks, Facebook, Google and Microsoft, self-supervised learning is a nascent technology that seeks to overcome one of the biggest drawbacks of supervised learning, which is the need to have access to typically large amounts of labeled data. Gartner predicts the potential impact and benefits of self-supervised learning are very large, as it will extend the applicability of machine learning to organizations that do not have the availability of large datasets.

Twenty-two technologies were removed or reassigned from this years’ Hype Cycle for Emerging Technologies compared to 2019. The 22 technologies that are no longer on the Hype Cycle for Emerging Technologies include the following: 3D sensing 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, Light cargo delivery drones, Low Earth orbit satellite systems, Personification, Synthetic data and Transfer learning.