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Hyper Automation, Multi Experience, And Securing AI (Or Baby Yoda)

Hyper Automation, Multi Experience, And Securing AI (Or Baby Yoda)
Are these Gartner identified trends unique to 2020?

If you google “technology trends,” one of the companies that will appear in the top 10 hits will be Gartner. The research and advisory firm not only analyzes numerous markets in terms of technical innovations but also covers business aspects of technology for C-suite professionals.

For 2020, Gartner has produced a number of predictive reports, including those covering digital and strategic technologies. From those lists, I’ve selected three trends that appear vaguely familiar from the recent past, albeit with new names. Do you agree? Don’t hesitate to ping me with your take on these trends at: [email protected]

Trend: Hyper Automation

Gartner: “Automation uses technology to automate tasks that once required humans. Hyper automation deals with the application of advanced technologies, including artificial intelligence (AI) and machine learning (ML), to increasingly automate processes and augment humans. Hyper automation often results in the creation of a digital twin of the organization. As no single tool can replace humans, hyper automation today involves a combination of tools, including robotic process automation (RPA), intelligent business management software (iBPMS) and AI, with a goal of increasingly AI-driven decision making. 

My Take: Do we really need yet another word or phrase to represent the ongoing digitization process that will eventually enable a complete digital twin? One might just as well say that the creation of a digital twin – from improved modeling, simulations, sensors, etc. – has accelerated the pace of automation thus creating a new hypeautomoation or superautomation reality.

It’s really a chicken and egg perspective. Which came first – the creation of hyper automation systems that eventually results in a digital twin? Or did the creation of a digital twin from a sensor-rich ecosystem lead to improved automation of tasks previously performed by humans?

Regardless of the answer, there seems to be little doubt about the movement toward a more complete digital twin within the next decade. Mordor Intelligence predicts that the digital twin market is anticipated to witness a CAGR of 35.0% over the forecast period 2019 - 2024. Growth in IoT and cloud-based platforms, the surge in adoption of 3D printing technology in the manufacturing industry, and the objective to reduce project cost are some of the major factors, driving the growth for the digital twin market. Mordor notes that IoT sensors have created a potential space for engineers to test and communicate with sensors integrated with the operating products, hence delivering real-time prescriptive of system functioning and timely maintenance.

Which came first: Hyper automation or the digital twin? It’s your call.

Image source: Photo by Daniele Levis Pelusi on Unsplash

Trend: Multi Experience

Gartner: “Multi experience replaces technology-literate people with people-literate technology. In this trend, the traditional idea of a computer evolves from a single point of interaction to include multi sensory and multi touchpoint interfaces like wearables and advanced computer sensors.

“For example, Domino’s Pizza created an experience beyond app-based ordering that includes autonomous vehicles, a pizza tracker and smart speaker communications.”

“In the future, this trend will become what’s called an ambient experience, but currently multi experience focuses on immersive experiences that use augmented reality (AR), virtual (VR), mixed reality, multichannel human-machine interfaces and sensing technologies. The combination of these technologies can be used for a simple AR overlay or a fully immersive VR experience.”

My take: Will multi experiences really replace technology-literate people with people-literate technology? This seems like a roundabout way of explaining what Dassault Systemes has been saying for a long time, namely, that we are in the age of experiences, not products. Think of it this way: The Internet has commoditized goods, i.e., price comparisons are easy. Now, services are being commoditized in the same way. What is the next stage beyond services? Experiences.

B. Joseph Pine II, a motivational speaker and book author, uses the gumball machine as an illustrative example of how an experience may supersede, and even supplant, the actual product. When using today’s gumball machines, kids enjoy watching the purchased product roll down a spiral column to reach the delivery shoot. Pine suggests that the adult version of this is the Autostadt’s car vending machine.

Another perspective for this idea of multi experiences comes from the high-tech world of chip hardware and software. Arm’s CEO Simon Segars once shared this quote from “Hitchhiker’s Guide to the Universe”:

“We are stuck with technology when what we really want is just stuff that works.

How do you recognize something that is still technology?

A good clue is if it comes with a manual.”

― Douglas Adams, The Salmon of Doubt

Designers of future high-tech products will need to develop their systems to provide experience that are truly intuitive and manual-free to be easily adopted by the consumers.

To achieve this end, Intel’s former CTO Justin Rattner (now retired Intel Senior Fellow), once noted that future chip designs and innovations should be focused in the area of enhancing user experience. This approach has sometimes been called experience driven design.

“User experience design makes engineers nervous, since it relies on one’s perspective for what makes for a good experience. But this is now becoming a formal, qualitative experience,” explained Rattner.

This approach involves more than just getting the user interface correct. It requires a great deal of user input and feedback throughout the product development process. One might be tempted to call this a multiexperience development process. Regardless of the name, this process has already been evolving for a number of years.

Image Source: Landmann, Lars

Trend: AI Security Or How To Teach Baby Yoda

Gartner: “Evolving technologies such as hyper automation and autonomous things offer transformational opportunities in the business world. However, they also create security vulnerabilities in new potential points of attack. Security teams must address these challenges and be aware of how AI will impact the security space. AI security has three key perspectives:

  1. Protecting AI-powered systems: Securing AI training data, training pipelines and ML models. 
  2. Leveraging AI to enhance security defense: Using ML to understand patterns, uncover attacks and automate parts of the cybersecurity processes. 
  3. Anticipating nefarious use of AI by attackers: Identifying attacks and defending against them.”

My take: Each of these AI security perspectives can be dramatized as the struggles faced by the Mandalorian in protecting, teaching and raising Baby Yoda. In the new Disney Plus TV series, the Mandalorian is a warrior that decides to save a small infant that resembles Yoda for George Lucas’s original Star Wars movie trilogy. Once saved, the Mandalorian is tasked with protecting and raising the infant. But how do you teach the impressionable yet force-powerful Baby Yoda right from wrong, especially when you are a once honorable warrior who must get by as a bounty hunter in a world where right and wrong are not always clear?

Returning to the real world, the same scenario and questions could be asked of nascent AI systems. How can human flaws and bais be kept out of the learning experience for AI products?

The challenge of AI machine-biasing came clearly into focus in 2019. Similar to human-bias, machine-bias occurs when the learning process for a Silicon-based machine makes erroneous assumptions due to the limitations of a data set and pre-programming criteria. One example of machine-bias was recently revealed in Apple’s new credit card, which contained an algorithm to decide how much trustworthy (or risky) a user might be. This evaluation used to be done by trained humans but now is often performed by AI-based algorithms.

Apple’s credit card was shown to have a gender bias. Males were more likely to get a higher credit line than females. This bias was highlighted when a male entrepreneur was assigned a spending limit 10 times higher than that of his wife, even though they have a common account.

Just like Baby Yoda, AI is an infant who has access to powerful (computing) forces. And like the Mandalorian, the humans setting up the AI and it’s learning dataset are flawed with bias and personal prejudices. May the force (of sound logic and reasoning) be with us all.

Image source: Lucasfilm/Walt Disney Pictures via Disney+

John Blyler is a Design News senior editor, covering the electronics and advanced manufacturing spaces. With a BS in Engineering Physics and an MS in Electrical Engineering, he has years of hardware-software-network systems experience as an editor and engineer within the advanced manufacturing, IoT and semiconductor industries. John has co-authored books related to system engineering and electronics for IEEE, Wiley, and Elsevier.

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