Attention computing is an emerging field within artificial intelligence (AI) that uses techniques such as deep learning and machine vision to provide machines with the ability to interpret humans and their environment so that they can respond and react accordingly. The technology allows systems to detect attention levels and distinguish between the things a person looks at or interacts with. It can recognize objects, faces, body language, gestures, and speech patterns.Generative AI solution
Imagine a world where machines understand what we mean by a nod, a wave, a look, or simply being present. Attention computing aims to make such a world possible. Its breadth and versatility make it hard to define, and not surprisingly, its definition will vary depending on who you ask. I posed the question to a generative AI solution, and this is what it came up with:
I find this interesting because it aligns with how we think of attention computing at Tobii — as a means to harmonize technology and humanity. But I think it needs to include what I call the secret power of attention computing, solving problems beyond interaction, using the data it provides for research and developing new products. In this post, I will talk about what we mean by attention computing, why we need it, the deep side of it, and what makes it an empowering technology as we shift into Industry 5.0. Enjoy!
The techy part
At the core, attention computing leverages sensors to enable machines (and things) to understand people. It uses machine learning and neural networking techniques to predict intent by analyzing how people behave and what they pay attention to. In addition to the traditional device-based methods of getting information across the human-machine divide (like mice, keyboards, and touchscreens), interaction becomes augmented with voice, gestures, facial expressions, and movement.
The human part
One of the aims of attention computing is to make device interaction intuitive and inclusive for all users. Speech recognition and natural language processing make communication more efficient than typing, for example. Eye tracking facilitates an intuitive browsing and selection experience for people especially useful if your hands are busy or for those unable to use an input device. Machines could even respond in real time to nodding or hand gestures by tracking movement. Attention computing brings all these elements together in context to allow people to interact with devices in much the same way as we do with each other.
Since people began using computers, engineers have been designing ways to ease communication. In the mid-eighties, for example, Apple introduced the mouse and added icon-based menus to their GUI, making it easier to do things like launch applications. The iPhone brought touch into the mix. And applications that leverage speech synthesis and NLP have proliferated, enabling people to tell devices what they want. And for those who cannot speak, Tobii led the way with eye tracking, allowing people to navigate devices and communicate with the world by simply looking at their screens.
The fourth industrial revolution, Industry 4.0, brought platforms like computers and mobile phones. It delivered networking and cloud, compute power for analysis and sharing, and applications that take care of monotonous or dangerous work.
The goal of Industry 5.0 is to create an efficient, versatile, and sustainable production system by combining the best of the digital and physical worlds with people at the center. By taking advantage of advances in sensor technology, machine learning, and data analytics, we can create an ecosystem of connected technologies and people. Ultimately, Industry 5.0 seeks to improve productivity and reduce waste while providing meaningful experiences and improving outcomes for everyone.
The report Enabling Technologies for Industry 5.0 outlines all the key enabling technologies and societal factors at play. One of these elements is individualized human-machine interaction, which attunes machines to human behavior — attention computing.
[Video] What is attention computing?
Attention computing makes our devices intelligent, intuitive, and efficient. But it also uncovers truths about human behavior. What could attention computing mean for you?
Attention computing aims to get the most out of technology by ensuring everyone can interact with it and enabling machines to interpret human behavior and predict what action to take.Generative AI solution
The secret power of attention computing
Beyond removing the barriers between people and machines, attention computing can deliver deep insights into human behavior that can help to create affordable solutions for essential services like healthcare, education, and training.
And not only can we do this, but because the form factor of sensor technologies tends to be small, it’s possible to put the technology in just about anything. Allowing us to create innovative tech that people can access anywhere, irrespective of ability level or how technically savvy they are.
The deep side of attention computing is a vast array of applications with people at the center. To limit the scope to something tangible, I would say attention computing applies to situations involving people where there is some value (other than pure interaction) in understanding the signals we generate. Owing to the tight coupling between behavioral signals and cognitive function, the initial applications of attention computing have focused on neurology and learning. The early detection of cognitive impairment, for example — helpful in the diagnosis of diseases like Parkinson’s or Alzheimer’s — is possible because attention computing can capture that manual observation cannot. Attention computing is also suitable for learning and skills assessment applications because it can visualize what’s happening inside someone’s mind, the kind of insights people take years to learn but are hard to articulate.
In this post seeing through the eyes of your child, Sara McCracken (CEO Angel Eyes) talks about her charity and how it provides guidance to the support networks (primarily parents) of children diagnosed with a sight impairment. She talks about the complexity of raising awareness and deepening understanding and how they have simulated different conditions using attention computing on VR. As she says, understanding things are easier to understand when you can experience it.
In closing the literacy gap, we discuss the lack of a systematic approach to reading development — which can’t be solved by throwing more resources into the mix but where digital transformation and attention computing are ideal.
Vision care for everyone tells the story of a pilot study carried out by the government of South Korea. They were looking to use technologies like attention computing to expand preventative care services to more people — especially low-income earners and the elderly who often remain outside the primary-care bubble.
And in cognitive performance through decades of life, we talk with one sports researcher using a VR platform to show how taking care of your brain is just as important as taking care of your body.
These are just a few examples where attention computing has been successfully applied in commercial or pre-commercial settings. And while there are more, the potential of attention computing to solve previously unsolvable problems and improve the lives of many is something I look forward to delivering.
Learn more about attention computing
Read our article to find out more about attention computing.
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What is attention computing?
Attention computing enables machines and devices to understand people. It is the next gen of HCI leveraging sounds, gestures, and movement.
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