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Digital accessibility: the data says I don't exist

Kevin Mar-Molinero
Two people stood in front of a whiteboard ideating about product experience design

Kevin Mar-Molinero at Axe-Con

Data can provide us with the answers to many challenges but it can also be a source of inequality and fail those with disabilities. Our Director of Experience Technologies, Kevin Mar-Molinero, recently spoke about this issue at Axe-Con, a major digital accessibility conference. 

"Based on data", or "data driven solution" are often seen as silver bullets to meet any challenge, championed by everyone from finance to design. Data is used to justify decisions and validate our choices. But data can also be the problem rather than the answer. It can exclude people, hide its innate bias and motivate us to make the wrong decisions.

Watch the talk on YouTube

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Self-perpetuating bias

One of the reasons for a healthy scepticism towards data is that it only looks at what has come before. Data, and data collection relies on the past to predict the future, and if that past has bias - intentional or accidental - built into it, then the future it creates will only enshrine the bias even deeper.

Imagine a shopkeeper with a store at the top of a flight of stairs. When asked whether they need a ramp for access, they might say “no, I don’t have any customers that use a wheelchair”.  Their data might be correct but it neither indicates there’s a problem or motivates a solution. It's this kind of thinking that creates issues for those with disabilities who want to access a digital experience. 

The tools you use

In the same way, incomplete data can result from your current analytics tools. They ignore the access needs of some users. They cannot tell you if a user employs an assistive technology, much less if they have a disability or impairment.

Reliance on these tools can lead to a significant bias problem, As analytics only captures those who currently use your system, it will always say those currently excluded don’t use it.

A practical issue

There are means to capture data on assistive tech usage but moral and practical reasons make it a  problem. The practical issues are based on the core principles of API architecture set out by W3C which sets the standards for a web for all. They say:
"Make sure that your API doesn’t provide a way for authors to detect that a user is using assistive technology without the user’s consent.”

If a site can detect that a user is using an assistive technology, then that site can deny or restrict the user’s access to the services it provides. But how will you know if people have access problems if you can’t detect them in the first place?

The ethics of data collection

Ethically speaking, you need to ask what you are using your data for. Is it to help people with disabilities or to silo them further? Always remember that there’s a human being behind the number.  If you’re only collecting data to send them somewhere other than your main digital experience then you’re using data unethically. Also, make sure you’re tracking a wide range of disabilities, not just groups such as the partially sighted or deaf. And remember that some disabilities cannot be tracked by even the most advanced technology.

The data sceptic

In conclusion, it’s important to understand the data you have but not rely on it completely. Exclusion will be inevitable sometimes but you can predict it and plan for a solution. User testing is an important part of developing your digital experience but it needs to be extensive enough so that it's not just the opinion of a small group. Finally, data is an option while ethics should be compulsory. Question whether you even need certain data that can contribute to exclusion. 

The answer is to assume those with disabilities will be trying to access your web platform and build that into your design. Co-create alongside those with issues of accessibility and make your digital experiences accessible to people with disabilities from the start. Build with not for them and remember the maxim that ‘it’s nothing about us without us’.  

Do this and they will feel like they exist, whatever your data says.

See the talk in full on YouTube

Watch now

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