Explaining Auto Remediations
How AudioEye uses code-based solutions to correct website accessibility errors across the web.
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The internet is vast. As of March 31, 2021, it was estimated to comprise more than 5.27 billion indexed web pages filled with every conceivable tool, diversion, entertainment, asset and resource. It is at once a library that catalogs most every idea and emotion ever expressed by humankind and a workshop or laboratory capable of generating innovation and advancing the human condition.
The internet, which did not exist 40 years ago, is a place created by human beings for human beings. It is a singularly human enterprise, and yet not everyone can use it. Among those billions of web pages are trillions of errors — man-made mistakes — that make the internet’s myriad benefits and possibilities inaccessible to billions of its intended users worldwide. Fortunately, 100% of those errors can be fixed.
Every website accessibility problem has a solution. Some fixes are easy and others quite difficult, but there are no website accessibility knots that cannot be untied. The biggest challenge in accessibility is not figuring out how to repair all the problems. It’s about acquiring the resources to get the work done. Although there’s just too much for human beings to fix right away, people need to navigate the internet right now. They don’t have the luxury of waiting.
One of the tools we have to help speed up this process is automated remediations. In the following pages, we’ll explain everything there is to know about them. In addition to walking you through their capabilities and limitations, we’ll show how we use the technology at AudioEye now and how we hope to see it used in the future.
What Is Auto Remediation?
Before we explain auto remediation, we should talk about what it means. "Remediation" is the term website accessibility experts use to describe the system of removing the barriers to accessibility in a website's code. In other words, remediation is the process of making websites accessible to every user.
When remediation is done by a human being, it's called manual remediation. When it's done by a machine (or, more accurately, a line of code), it's called automated remediation, or just auto remediation.
“The amount of manual work that's required to detect all of a site's accessibility problems and to make everything on it completely accessible is tremendously high. It's just a massive, unattainable mountain of manual labor. If we are ever to have a hope of trying to make the entire web accessible, we have to leverage the power of automation.”
Director of Data Science and Engineering at AudioEye
The In-Between Remediation
AudioEye uses three main types of remediation. In addition to auto remediations, which are purely code, and manual remediations, which are conducted by human beings, there’s a hybrid guided-remediation type that requires human input but does not require that person to be an expert in coding or website accessibility.
Completely automatic code-based tools capable of repairing website accessibility problems in a fraction of a second.
They combine the speed of code with the power of human judgment. Especially useful because they do not require an expert’s skill set.
Human interventions remain the gold standard for remediation, but they are not as fast or cost-effective as automated solutions.
You may be surprised to learn that auto remediation of websites isn’t new. In fact, auto remediation technology has been around for about as long as there have been websites. The first version of HTML was published in June 1993, and the first HTML validator followed just a few weeks later.
Since that time, developers and web accessibility specialists have used automated tools in different forms to fix all kinds of website accessibility issues. Some of those problems have always been able to be corrected by automated means, while others have become fixable as the technology has progressed. Unfortunately, despite numerous advances, it's not possible to rectify everything with automated remediations.
How Does Auto Remediation Work?
If you're not a technical person, it might help to think of auto remediation as a sort of accessibility "spell checker" for the code running behind the scenes of a website. Like spell-check, auto remediation is a helpful and reliable tool that's capable of catching lots of mistakes. Of course, like a spell checker, auto remediation has its limitations. It can't catch everything, and there are some nuances it's simply unable to detect (at least for now).
All the fixes made by the auto remediation process are completely invisible to users who do not require the use of assistive technology to access your site. That's because auto remediations do not adjust a site's source code. Rather, they step between the code and the visitor's browser.
If you want to share an idea with your end user and your site's source code has an error, the auto remediation will provide a fix so the browser can deliver that information to them.
Where auto remediation excels is where there are identifiable patterns. A good example of a pattern would be HTML header tags that are not in the correct order. The proper pattern should start at header 1 and proceed in order. When the auto remediation code detects an out-of-order tag, it can make the fix automatically. Other common patterns would include factors like fields having labels or hotlinks having descriptions of their destinations.
At the most basic level, these auto remediations work on an "if X, then Y” basis. If the code detects a header 2 tag before a header 1 tag, then it puts the tags in order. The code becomes more advanced in cases where the “then Y” component requires more information. For example, “if a form field is missing a label, then figure out what the label should be.” That “figure out” component requires artificial intelligence (AI) capable of making assumptions. For instance, if the words “first name” are nearby, an AI can determine that “first name” is the probable missing label.
The time that it takes for the average blink of a human eye.
The time required for AudioEye auto remediations to fix millions of errors.
Two Auto Remediation Code Types
AudioEye uses two code types to make its auto remediations. Right now, there are more than 70 thoroughly tested auto remediations available.
This category of code provides rules-based instructions to auto remediations, which can then fix every broken “rule” it finds.
This code category is more sophisticated and nuanced instruction based on modeling and predictive capabilities.
Where auto remediation technology falls short is where context is required. Like a spell checker that can’t tell whether you meant to write “his” or “hers” in a particular sentence, auto remediation is unable to tell details about what might be featured in an image or how a tab sequence is supposed to work.
Auto Remediation at AudioEye
AudioEye embraces a hybrid approach to website accessibility that takes advantage of both automated and manual remediation techniques. We want our auto remediation tools to fix as much as possible, however, because automated fixes are faster and more affordable than manual options, and that allows every website owner to make their site accessible regardless of their resources or skill.
Did You Know?
Although we understand that auto remediations can't solve every website accessibility problem, we are devoted to improving our capabilities. And the reason for that is simple: Every time we're able to solve an issue reasonably well with automation on one website, we become capable of fixing hundreds of thousands of problems across the internet.
Who Creates AudioEye Auto Remediations?
AudioEye believes in the power of auto remediations and continues to invest resources toward the development of new solutions. Among the contributors to the innovations dreamt up by the auto remediation workshop are highly skilled experts, including:
AudioEye accessibility experts may be certified in the use of screen readers, alternative input devices and other assistive technologies, and they may even hold a professional credential from independent professional organizations like the International Association of Accessibility Professionals (IAAP) or the Rehabilitation Engineering and Assistive Technology Society of North America (RENA). Accessibility experts are in charge of using screen readers and other assistive devices to QA-test the auto remediations coded by the front-end developers.
Data engineers are close colleagues of data scientists. They specialize in building pipelines that transform huge quantities of information into formats data scientists can use. Such engineers build and maintain database systems and data warehousing solutions, and frequently apply their skills with programming and machine learning to solve problems. Because their data scientist colleagues require access to so much information, data engineers work to develop ways to organize data sets so they can be optimally delivered and optimally stored.
Data scientists use computer science, programming, modeling, mathematics and statistics to drive insight and innovation regarding some of website accessibility’s most vexing problems. They apply their considerable skill to find answers from data sources no matter how vast or minute. During the process of building new auto remediations, data scientists look at monitoring data to identify the type of problems we should try to solve next.
What We Track
To focus our efforts, we rely on mountains of anonymous data (AudioEye does not require or track individual user information for this work). We constantly collect and monitor data that helps us identify the most prominent problems and most urgent needs. Once we zero in on a challenge, we can apply our know-how and resources toward finding a solution.
Again, our goal is to improve our capabilities. We want to reduce the need for manual attention in testing, monitoring, and fixing. And when a manual fix cannot be avoided? We want to provide no-code solutions like guided remediations so people can make the fix easily and without having to understand the technical details of the issue. Of course, when a problem is just too complex for automated remediations, we know we can apply our skill to repair it manually. AudioEye seeks to maximize usability — for everyone. As the standards evolve, we want to continue leading that charge and doing more with automation than any other company.
“At AudioEye, our long-standing mission is to eradicate every barrier to digital access for individuals with disabilities. We are pushing the envelope when it comes to the reaches of AI to identify and fix issues of accessibility.”
Co-founder and senior vice president of customer advocacy at AudioEye
Automation That Works
AudioEye’s robust suite of automated tools can improve the accessibility of your website in seconds so you can serve more people — starting now.
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