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How can computer engineers design AI systems with accessibility in mind?

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Artificial intelligence (AI) systems are becoming more ubiquitous and influential in various domains, such as education, health, entertainment, and security. However, not everyone can benefit from these systems equally, as some people may face barriers or disadvantages due to their physical, cognitive, or social characteristics. Accessibility is the practice of designing and developing systems that are usable and enjoyable by people with diverse abilities and preferences. How can computer engineers design AI systems with accessibility in mind?

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Kathleen Dickerson

Learning and Development Professional with 15+ years of experience | Skilled in Instructional Design, Content Creation,…

1 Understand the user needs

The first step to design accessible AI systems is to understand the user needs and contexts. Computer engineers should conduct user research and testing with people who have different types of disabilities, such as visual, hearing, motor, or cognitive impairments. They should also consider the cultural, linguistic, and ethical aspects of the user groups. By doing so, computer engineers can identify the potential challenges and opportunities for improving the user experience and satisfaction.

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Involve diverse users: Conduct user research with individuals from various backgrounds and abilities early and throughout the design process. This helps identify potential accessibility barriers and ensures the system caters to a wider audience. Empathy and understanding: Use techniques like user shadowing and persona creation to understand the challenges faced by users with different disabilities. This fosters empathy and informs design decisions. Accessibility standards and guidelines: Adhere to established accessibility standards and guidelines like WCAG (Web Content Accessibility Guidelines) and W3C (World Wide Web Consortium) recommendations. These provide best practices for making digital content accessible.

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2 Apply universal design principles

The second step to design accessible AI systems is to apply universal design principles, which are guidelines for creating products and services that are accessible and usable by as many people as possible. Some of these principles are: simplicity, consistency, flexibility, feedback, tolerance, and equity. For example, computer engineers can design AI systems that are simple and intuitive to use, that provide consistent and clear feedback, that offer multiple options and modes of interaction, that prevent or recover from errors, and that respect the diversity and dignity of the users.

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Kathleen Dickerson

Learning and Development Professional with 15+ years of experience | Skilled in Instructional Design, Content Creation, Curriculum Development, and Facilitation
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Computer engineers can apply the Simple and Intuitive Use principle to make AI more accessible. For instance, the AI interface should use a straightforward layout and give directions in clear, simple language. The program should provide model prompts to guide users in formulating queries and provide clear and immediate and clear feedback on user inputs. For responses containing complex information or data, engineers should include visual elements, such as icons, charts, headings, or bullet points, to aid in understanding. Lastly, engineers should conduct usability testing with a diverse group of users to identify any pain points or areas of confusion and refine the AI tool based on user feedback.

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3 Use accessible technologies and tools

The third step to design accessible AI systems is to use accessible technologies and tools that support the user needs and preferences. Computer engineers should choose or develop technologies and tools that are compatible with assistive devices and software, such as screen readers, keyboards, speech recognition, or eye tracking. They should also follow the web content accessibility guidelines (WCAG) and the accessibility features of the platforms and frameworks they use. For example, computer engineers can use alt attributes for images, label elements for forms, and aria roles for dynamic content.

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4 Evaluate and improve the system performance

The fourth step to design accessible AI systems is to evaluate and improve the system performance and reliability. Computer engineers should measure and monitor the accuracy, efficiency, and robustness of the AI systems, especially in relation to the user needs and expectations. They should also test and refine the system functionality and usability with real users and scenarios. For example, computer engineers can use metrics such as precision, recall, response time, and satisfaction to assess the system performance, and use methods such as debugging, optimization, and feedback to improve the system quality.

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5 Consider the ethical and social implications

The fifth step to design accessible AI systems is to consider the ethical and social implications of the system design and deployment. Computer engineers should be aware of the potential risks and harms that the AI systems may cause or exacerbate for the users and the society, such as bias, discrimination, privacy invasion, or social exclusion. They should also adhere to the ethical principles and standards of the computer engineering profession, such as fairness, accountability, transparency, and responsibility. For example, computer engineers can use methods such as impact assessment, stakeholder consultation, and auditing to identify and mitigate the ethical and social issues of the AI systems.

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Kathleen Dickerson

Learning and Development Professional with 15+ years of experience | Skilled in Instructional Design, Content Creation, Curriculum Development, and Facilitation
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Computer engineers should prioritize ethical and social considerations surrounding language and dialects. Including various linguistic backgrounds and non-standard dialects in training data mitigates biases. Ongoing user feedback, especially from non-standard dialect users, refines system inclusivity. Engagement with non-standard dialect communities, collaboration with experts, and regular audits can address biases and improve inclusivity. By incorporating these considerations, computer engineers can contribute to the development of AI systems that are not only technically proficient but also ethically and socially responsible, especially in embracing linguistic diversity.

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6 Learn and collaborate with others

The sixth and final step to design accessible AI systems is to learn and collaborate with others who have different perspectives and expertise. Computer engineering is an interdisciplinary field that requires the integration of knowledge and skills from various domains, such as mathematics, computer science, psychology, and sociology. Computer engineers should also engage with other stakeholders, such as users, clients, regulators, and researchers, who have different interests and expectations. By doing so, computer engineers can broaden their horizons, enhance their creativity, and improve their communication and teamwork skills.

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7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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How can computer engineers design AI systems with accessibility in mind?

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1 Understand the user needs

2 Apply universal design principles

3 Use accessible technologies and tools

4 Evaluate and improve the system performance

5 Consider the ethical and social implications

6 Learn and collaborate with others

7 Here’s what else to consider

Computer Engineering

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How can computer engineers design AI systems with accessibility in mind?

1

2

3

4

5

6

7

1 Understand the user needs

2 Apply universal design principles

3 Use accessible technologies and tools

4 Evaluate and improve the system performance

5 Consider the ethical and social implications

6 Learn and collaborate with others

7 Here’s what else to consider

Computer Engineering

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