Empowering Image Accessibility with AI

Can AI help build a more inclusive digital world? (Part?4)

When I first got into accessibility, which wasn’t a long time ago, the first thing I learned about was alternative text. It’s also something many new developers encounter when they begin learning HTML since the image element has alt text by default.

Alt text is pretty straightforward to explain?—?it enables screen readers to read images. When there is no alt text, screen readers can only inform the user that there’s an image on the screen, but not what’s in it. Let’s face it: images and visual content, in general, are a massive part of the user experience across mobile applications.

The ability to perceive and understand visual content is an essential aspect of human interaction with digital platforms. However, for users with visual disabilities, the lack of descriptive information for images and graphics has often meant exclusion from the full digital experience.

Are Image Descriptions a Big?Deal?

In an increasingly visual digital landscape, where images dominate social media, websites, and apps, the importance of image descriptions cannot be overstated. For individuals with visual impairments or blindness, the ability to access and comprehend online content often hinges on the presence of accurate and informative image descriptions. This makes image descriptions a crucial element of web accessibility and a big deal for several reasons:

Legal Compliance:

Many countries, like the United States, have laws and regulations that require websites and digital content to be accessible to individuals with disabilities. The Web Content Accessibility Guidelines (WCAG), which serve as a global standard for web accessibility, emphasize the importance of providing text alternatives for non-text content, including images. Failure to provide image descriptions can result in legal liabilities for businesses and organizations.

In Israel, websites are mandated to adhere to Israeli Standard 5568, which specifies compliance with WCAG 2.0 guidelines. Similarly, in the United States, websites must meet ADA regulations and adhere to Section 508 standards to ensure that online experiences are accessible to all users, regardless of their abilities or disabilities.

Enhanced User Experience:

Image descriptions enhance the overall user experience for all website visitors. Sighted users may also benefit from image descriptions in various scenarios, such as when they have a slow internet connection, and images take longer to load, or when they want to understand the content of an image without viewing it directly.

SEO and Discoverability:

Image descriptions can improve the search engine optimization (SEO) of web content. Search engines rely on textual information to index and rank web pages. Appropriately crafted image descriptions not only help individuals with visual impairments but also contribute to the discoverability of content in search engine results pages.

Assistive Technology Compatibility:

Image descriptions are essential for compatibility with screen reader software and other assistive technologies. Screen readers read aloud the content of a web page to users with visual impairments, including image descriptions. Without these descriptions, users would miss crucial information conveyed through images.

Enriched Social Media Engagement

On social media platforms, images and visual content are prevalent. Providing image descriptions on platforms like Twitter, Facebook, and Instagram ensures that posts and shared images are accessible to all users, fostering a more inclusive social media environment.

Ethical Considerations

Beyond legal requirements, providing image descriptions aligns with ethical principles of inclusivity, diversity, and equity. It demonstrates a commitment to ensuring that all individuals, regardless of their abilities, can participate fully in the digital age.

AI-Powered Image Recognition

AI-driven image recognition technology has emerged as a game-changer for making visual content more accessible. By leveraging sophisticated algorithms and deep learning models, AI can “see” and interpret images, providing valuable context to users who cannot perceive the visuals themselves.

When users with visual impairments encounter an image on a website or within an application, AI algorithms can analyze the content and generate descriptive alternative text (alt-text). This alt-text is then read aloud by screen readers, allowing users to comprehend the visual context and meaning of the image.

Ways AI Can?Help

There are many ingenious ways we can use AI to make images, and as a result, the digital experience, more accessible.

1. Auto-Generated Alt Text: Social media platforms, such as LinkedIn, Facebook, and Instagram, can implement basic AI integration within their image upload features. When a user uploads an image to a post they want to share, AI can analyze the image and generate a description for the image. There can also be many fine-tuning settings, such as marking if the image needs a description or is just decorative, and even choosing between “rich” and “simple” descriptions, depending on the context.
2. When users ignore adding alternative text, AI can be used to generate alt-text for inaccessible images, replacing the ambiguous, uninformative “image” that screen readers often face.
3. Image Captioning: AI can recognize objects, people, and scenes in images and provide detailed captions, helping visually impaired users understand the content better. These captions can fundamentally change the user experience for people with visual impairments. Facial recognition technology has been shown to be accurate and very helpful. For example, photo-grouping by person in Google Photos, Apple Photos, and other photo library apps, can also be applied to social media images.
4. Color Contrast Enhancement: AI can analyze color combinations in images and suggest enhancements to improve readability for individuals with color blindness or low vision. I have encountered hundreds of low-contrast images that aren’t legible even by people with typical vision, often even published by big-name companies.
5. Multilingual Image Description: AI can automatically translate image descriptions into various languages, ensuring a global audience can access content. If I share a multilingual post, I often incorporate alt-text in both languages. In hindsight, this might be problematic for people who speak only one of the two languages. Separating alt-text for different languages can enhance the experience for people who do not speak English on the web.
6. Text-to-Image Generation: Let’s flip the equation. People with cognitive disabilities often find it hard to read walls of text. Imagine if AI was to create visual representations of text content, making it easier for individuals with cognitive disabilities to understand complex information. While this is nowhere near ideal, it still can be a viable option.

The Power of Descriptive Alt?Text

Descriptive alt text is a critical component of digital accessibility. As a product designer, I understand the importance of crafting meaningful alt text that accurately describes the content of the image without being overly verbose or ambiguous.

Incorporating descriptive alt text not only empowers users with visual impairments but also benefits all users. When images have well-crafted alt text, search engines can better index and understand the content, leading to improved search rankings and discoverability. It’s a win-win situation, where accessibility and SEO go hand in hand.

Tackling Challenges in Image Recognition

AI-driven image description technology has undoubtedly advanced significantly, yet it grapples with several critical challenges that require our immediate attention. These hurdles encompass not only the complexity of visual content but also extend to language barriers, OCR (Optical Character Recognition) limitations for images containing text, and inaccuracies plaguing current alt-text generators.

One pressing issue is the AI’s occasional struggle in accurately deciphering intricate or abstract visuals, which often results in less informative alt text. This limitation particularly surfaces when dealing with images containing text in languages like Arabic, where OCR capabilities may falter, hindering effective image descriptions.

Furthermore, even in cases without language barriers, OCR limitations can impede accurate alt-text generation, as AI may not fully recognize or interpret the text within images. This poses a considerable challenge, especially for images containing vital textual information.

In addition to these technological challenges, we must also address ethical considerations and prioritize user privacy when implementing AI-powered image recognition systems. As we harness AI algorithms to analyze and describe images, we bear the responsibility of being conscientious stewards of user data, especially when dealing with images.

Empowering User Contribution

One exciting aspect of AI in image recognition is the potential for user contributions to enhance accessibility. By enabling users to provide feedback on AI-generated alt text, we create a collaborative environment where users can help refine and improve the accessibility of visual content. This feedback loop strengthens the bond between designers, developers, and users, fostering a more inclusive and user-centric design process.

AI-powered image recognition and description represent a powerful tool for breaking down barriers and fostering a more inclusive online?world.

By leveraging AI to provide descriptive alt text for images and graphics, we create a more equitable digital experience for users with visual impairments. As AI technology continues to evolve, I’m excited about the possibilities it holds for further enhancing digital accessibility and making our products and services truly accessible to all.

But for now, use manual alt-text and share accessible images online?;)