Feature
The World Health Organization estimates that by 2050, more than 3.5 billion people will need one or more assistive products to live and work. In response, the global assistive technology market is forecast to be worth $31.22 billion by 2030, with artificial intelligence (AI) algorithms rapidly fueling assistive technologies for individuals with disabilities.
In the workplace, while concerns over AI-related challenges such as data bias and factual inaccuracies remain, AI holds the potential to open up access to a range of workplace technologies for workers who were previously shut out or limited in their use.
The World Economic Forum estimates the cost of excluding people with disabilities represents up to 7% of the gross domestic product in some countries. A disability-inclusive business strategy could lead to 28% higher revenue and 30% higher profit margins — a strong argument to leverage when building support for this kind of initiative.
The AI-Powered Digital Workplace
Digital workplace tools gave organizations an increasing ability to have employees work from home, which in turn opened up the workplace to a more diverse population.
Yet, even with today’s digital workplace tools, accessibility is often an afterthought, an overlay added on to a completed design. Advancements in artificial intelligence suggest there are some improvements taking place.
The most significant differentiator for AI is that, unlike plug-and-play digital tools, it is not a fit-and-forget solution. Unlike automation, AI is not an end in itself — it is a dynamic and ongoing solution that, in theory, keeps learning and improving with use.
The constant stream of usage data and user feedback generated when an AI-powered solution is used can help improve the workplace experience for people with disabilities, as well as make digital productivity tools more responsive to user needs, said Matthew Elefant, managing director at digital accessibility solutions provider Inclusive Web.
Harnessing the vast amounts of high-quality data to train and fine-tune AI models effectively is key to unlocking AI's true potential as a driver of accessibility and inclusivity.
For people with disabilities, this can be a game changer. Instead of using AI as a gap filler for poor product design — similar to accessibility overlays used in websites, said Elefant — it can be used to support and improve the capabilities of standard productivity tools.
For instance, by helping to refine ideas, creating context and enabling audio or visual input, AI creates not just better access but also smarter and better productivity outcomes for users with disabilities.
Related Article: Artificial Intelligence Is Evolving Like Us, Just Faster
AI Shown to Enhance Access in Several Use Cases
As with all new technologies, AI’s potential impact can be both positive and negative for employees with disabilities (and other historically marginalized communities), said Tom Connolly, chief people officer at global executive search firm Kingsley Gate and co-founder of Ignyte.ai.
But when it comes to seeing, hearing, speaking and mobility-related disabilities, AI can be harnessed to help workers with disabilities do more, better and faster.
For example, automatic speech recognition or ASR tools are already used to transform audio into text or generate video captions for people with hearing disabilities. Adding AI LLMs can help improve user productivity by extracting context and meaning from audio and video content sources.
AI-powered visibility tools can also aid visually impaired workers by scanning and reading digital, printed and even handwritten documents aloud.
For example, when workers enter meetings, tools like Seeing AI from Microsoft can help them have more productive conversations by identifying coworkers in the room, informing users about the facial expressions of various participants and helping set the context by describing non-verbal cues that workers without visual disabilities take for granted.
Audio description tools already help workers better access everything from training videos to all-hands meetings and town halls. Recently, physical aids and wearables such as TranscribeGlass and heARsight claim to provide real-time close captions and subtitles for any conversations, using more affordable physical headsets.
AI is helping these tools move beyond transcribing to also describe what is happening. The added past and present context and recommended next steps can further empower people with disabilities.
For example, ASR tools can go beyond transcribing a speaker's words (“Let’s send an email”) to describe the speaker’s actions, body language and physical setting. (He is shuffling his papers while clearing his throat. Classical music is playing in the background. He looks unsure and says, “Let’s send an email”) — similar to what one can experience when enabling audio descriptions or closed captioning when watching a movie.
When it comes to typing and text, generative AI tools like ChatGPT make it faster and easier for people with disabilities to do tasks that would otherwise cost them much more effort and time than non-disabled workers, added Elefant. They increase productivity by helping workers take their core ideas or concepts and expand them into more refined and well-articulated ideas.
For example, people with mobility and visual disabilities may take much longer to finish tasks such as writing emails or reports. As a result, they may feel compelled to write fewer words or less descriptive content than others, putting themselves at a potential disadvantage or coming off sounding “short.” AI lets them not only access the tools but also use them more productively.
Neurodiversity champion and author of the Dyslexic Business Thinking newsletter on LinkedIn, Iain K, shared how AI tools like Duet AI incorporated into mainstream workplace productivity tools like Google Workspace help neurodiverse workers — among the most marginalized groups in the corporate world — perform more optimally. AI, he wrote, offers the ability to create digital environments that not only accommodate the unique needs of neurodiverse individuals but also leverage their distinctive strengths.
Related Article: Digital Workplaces Still Have Work to Do With Accessibility
Boosting Productivity in Core HR Areas
AI has also been shown to provide substantial advantages to the HR function. Among those:
Hiring
In the recruiting space, Connolly said internal company research shows that algorithmic advertising increases candidate flow from these communities, and selection processes supported by robotic process automation lead to more diversity in hiring and advancement decisions. AI-driven “job fit” software enhances those outcomes by narrowing the focus in hiring decisions and moving toward “round peg/round hole” hiring and advancement decisions.
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At the applicant's end, access to job boards alone does not mean the application experience is as smooth or easy as it would be for a person without disabilities. Companies such as OurAbility are using ASR to help people fill out applications faster, run voice searches to identify job opportunities and type faster.
Employee Experience
Building more responsive employee experiences with AI is important for everyone, and particularly for staff with disabilities, said Connolly. But for the best impact, he added, the AI models have to be deeply integrated with existing HR systems.
For example, generative AI like ChatGPT can enhance HR self-serve tools not just by providing access to the information but also by picking out the most relevant bits, responding to queries in real-time, providing data-powered resolution and intelligent escalation.
Learning
AI not only saves time, it can also improve comprehension for learners with disabilities.
It does so by identifying and recommending courses and material most relevant to a specific learner’s needs, summarizing long documents down to pertinent facts or rephrasing complex or technical content into more accessible language — all of which helps users with cognitive disabilities perform better.
Related Article: The Future of Work Is an Opportunity to Do Better With DEI
Leveraging AI for Human-Centered Solution Design
At the core of the human-centered design framework is designing with the users, not for the users, said Christophe Drayton, lead UX professor at the City University of New York (CUNY).
UX research must be focused on users who are — or will be — impacted by the design solution, from gathering their experience via surveys and interviews in the initial research phase to inviting them to test our design to improve and tailor the solution to their needs, he said. In other words, more people with disabilities need to participate in the design process of digital tools and the AI learning models that power them.
Drayton also sees AI becoming a companion in forecasting accessibility use cases and flagging them before they even see the light of a user screen, assisting UX researchers and designers to make better decisions for true human-centered design.
To support that, HR needs to shift from “content interventions” such as workshops and training to “structural interventions,” Connolly said. Those structural changes — building accessibility and productivity for disabled workers into system design — need to be made carefully and intentionally, and will require HR to develop new skills and competencies, he said.
“AI will force us to dig deeper as it’s fundamental to the new, inclusive workplaces HR is trying to build."
