Adobe, Google and UCF Join Forces to Launch the Readability Consortium
Artificial intelligence can help readers with better readability and comprehension. Global technology leaders Adobe and Google have joined hands to launch The Readability Consortium at the University of Central Florida (UCF). The Readability Consortium will explore ways to enable the world to read better by tailoring text to the individual. As part of the collaboration to personalize the digital reading experience, UCF, Adobe, Readability Matters and Google will focus on improving people’s digital reading proficiency and comprehension in the new era of remote learning and training environment.
Reading Habits Influence Education: AI to the Rescue
A digital reading experience can accelerate adults’ reading, according to research. Adobe and UCF had partnered during the peak of the COVID-19 pandemic in 2020 to identify potential applications of AI, digital software solutions, and graphical expertise to boost reading habits among adults.
According to The U.S. Department of Education, a majority of US-based adults perform at the lower levels of literacy. Students barely make any improvement in their reading proficiency despite having access to best resources and tutoring, which affect the overall literacy levels among US adults. Due to the pandemic, the educational gains, particularly in vocational reading and comprehension, have further deteriorated, which could impact millions of school-going children, with possible negative performances in 2022.
The COVID-induced changes have influenced reading habits among people of all age groups. The limited access to quality resources for improvements in reading habits has further challenged the current paradigm. Truly, there is a huge scope in the technology-driven world to improve reading experiences, and AI Machine learning is creating realistic opportunities for everyone. Leading from the front, Adobe, Google and Readability Matters have come together with their visionary capabilities and features powered by AI, machine learning, and deep learning techniques.
According to research, digital reading habits differ from person to person, and this largely depends on the type of content and devices used to access various forms of content, such as text, audio, video, and emails. It is clear that to deliver personalization at its highest level, researchers recommend use of technology that enable readers to see the written text properly even if the formatting changes. UCF’s effort with Adobe, Readability Matters and Google will boost reader’s proficiency and comprehension at school and work.
Role of AI, Machine Learning and Psychology in Delivering Personalized Reading Experience to Readers
The Readability Consortium will leverage the Artificial Intelligence (AI), and Deep Learning (DL) expertise of its participating collaborators- Adobe and Google. AI, machine learning and psychology would amalgamate as a visionary technology to develop individual reading “prescriptions” for people, which would be contained in profiles that can be distributed across any and all digital reading surfaces. The Readability Consortium is planning to link these digital reading surfaces as a global digital token that would allow readers to access and comprehend any text content in a format that suits their taste and reading habits.
Readability Consortium Director Dr. Ben D. Sawyer ’14MS ’15PhD said, “We can build you a format to boost your speed and understanding while reading. We want to link it to your digital reading surfaces as a digital token,” he says. “It’s like digital eyeglasses for your information, letting you ‘see’ better because the information is tailored to you.”
Dr. Ben D. Sawyer ’14MS ’15PhD is currently an assistant professor in UCF’s Department of Industrial Engineering and Management Systems.
How AI adjusts Text with Your Reading Pattern?
The Readability Consortium is developing an AI-based machine learning algorithm that ideally matches with a reader’s reading habits and adjusts the text in real-time to facilitate better experience powered by software developed by Adobe. For example, Adobe Acrobat Reader mobile app through its AI-driven Liquid Mode will put the control of the reading format in the readers’ hands. This would further allow the readers to adjust aspects like font size and character spacing using AI-based font adjustment tools.
Researchers are using Virtual Readability Lab, an online reading test. The idea is to assimilate the Machine Learning algorithms to detect automatic reading habits using eye-tracking technology and artificial intelligence for creating a better experience.
In addition to developing AI solutions for a better reading experience, Readability Consortium would also develop and market new research techniques in data science and deep learning for the creation of new controls for digital reading.
Zoya Bylinskii, a research scientist at Adobe Research and the driving force behind Adobe’s readability research, says the effort is about designing diverse reading experiences.
“What better way to do it than to bring a diverse set of experts to the table?” she says.
Itai Vonshak, head of Google Design Platform, says he is proud that Google is a member of The Readability Consortium because of the urgent need to make reading easier, more accessible and personalized.
“Millions of adults and young people lack basic literacy skills,” Vonshak says.
Vonshak added, “And this is personal for me as I experience a form of dyslexia and my first language is not based on the Latin alphabet. The Readability Consortium is championing new approaches to research and bringing the ‘reading science’ community together in understanding how to increase reading proficiency and digital inclusion around the world.”
Improved Reading Experiences: What the Readability Matters Foresees for the Future
The impetus for the project came from consortium member, Readability Matters, a nonprofit formed to promote the use of technology to change reading formats and improve reading outcomes.
“We’ve been involved with this work since the early 2000s,” says Readability Matters co-founder Kathy Crowley. “After hearing struggling children read with greater fluency and expressiveness using small changes to text format, I realized that this could be a game-changer for education. It turns out that personalized reading formats can improve reading effectiveness for both children and adults. Technology can really make a big difference in implementation.”
Application of Digital Reading Tokens
The Readability Consortium is developing a wide variety of AI-driven solutions to promote education and to improve the scholastic abilities among school-going children.
Itai Vonshak, head of Google Design Platform, says he is proud that Google is a member of The Readability Consortium because of the urgent need to make reading easier, more accessible and personalized.
“Millions of adults and young people lack basic literacy skills,” Vonshak says. “And this is personal for me as I experience a form of dyslexia and my first language is not based on the Latin alphabet. The Readability Consortium is championing new approaches to research and bringing the ‘reading science’ community together in understanding how to increase reading proficiency and digital inclusion around the world.”
The Readability Consortium would expand on its technology innovation to:
- to improve reading proficiency in school children
- to help physicians improve their reading under time pressure
- to improve reading in extreme environments, such as Antarctica and space, and much more.
Elizabeth Klonoff, vice president for the Office of Research at UCF, explains the role of their academic expertise in developing new capabilities to solve reading challenges.
Elizabeth said, “At UCF, we look for innovative ways to solve problems and improve lives. We have the potential to make a big impact on reading comprehension, which is the vehicle for knowledge acquisition. I can’t wait to see what the collective effort will deliver.”
[To share your insights with us, please write to sghosh@martechseries.com]
Comments are closed.