Due to technological innovations, the landscape of employment looks very different than it did even a decade ago. An interview might be scheduled—or an application rejected—before a human ever reads the candidate’s resume, and a computer may decide when an employee is due for a pay raise. Advances in technology are also creating new possibilities to boost accessibility and accommodation options at work for people with disabilities.
The future promises to continue expanding these exciting trends, but implementation requires deliberation. It’s essential that companies ensure the tools they use support their current goals to recruit and retain employees with disabilities—rather than unconsciously stepping back to outdated beliefs and practices.
This section of the Toolkit describes workplace applications for AI technologies, while the next section covers potential risks of AI in hiring tools.
AI for Talent Acquisition
Over 1/3 of respondents to LinkedIn’s 2018 Report on Global Recruiting Trends shared that AI was the top trend affecting how they hire. Generally, that’s to fulfill one or both of the following goals:
- Save time and money: Using AI can allow recruiters to rapidly sort and evaluate large numbers of applicants and track “passive candidates” not currently looking for jobs for outreach. It’s a quick, cheap process compared to traditional methods.
- Achieve consistent and high-quality results: Many vendors assert that AI systems can support them in achieving their augmented diversity goals by reducing human error, unconscious bias, and nepotism in the hiring process.
AI can support talent acquisition in many ways. AI assessment tools for talent acquisition attempt to match candidates to jobs, score employment tests, or recommend promotions based on past performance. Because they work by asking a computer to make judgments about people, these tools carry a heightened risk for discrimination and bias. They require significant consideration in both design and use to align with principles of responsibility and equity. Learn more about the risks of discrimination and bias in AI.
Here are examples of talent acquisition tasks that AI tools can help perform:
- Engaging job seekers through chatbots and automated emails and texts to support them in the application process.
- Reviewing background information on job seekers by scanning resumes and social media accounts.
- Analyzing interview performance through interpretation of facial movement and word choice during video interviews.
- Administering pre-employment tests to screen and assess candidate strengths and weaknesses, often through a series of virtual games.
- Scanning for discriminatory and bias language by automatically scanning recruiting boards and employee chat systems for discriminatory and non-inclusive messaging.
Learn more about how you can use AI-enabled hiring tools in inclusive ways by reading our Disability-Led Innovation Report.
AI to Support Workforce Management
Organizations are also adopting AI technology to support their existing employees and make improvements to general operations. As with talent acquisition, organizations must be especially cautious when using tools that make judgments about people, such as when someone is due for a promotion. Examples of AI in workforce management flows include:
- Performance management: Data-driven performance evaluations, based on data collected about employees, are replacing traditional performance reviews. These systems may also recommend raise structures and promotions. Some even predict when an employee is likely to be job seeking elsewhere due to an overdue promotion.
- Training and development: Advanced analytics make it possible to personalize each employee’s learning experience and recommend when employees need to reskill. Virtual trainings themselves, including Extended Reality (XR), also often rely on AI underpinnings.
- Collaboration and communication: Virtual collaboration and meeting tools increasingly use AI. AI may also be powering inclusion goals. For example, Slack administrators can set up custom automated responses or create a dedicated Slackbot to react immediately when discriminatory language is used in chat communications.
- Benefits management: Automated chatbots and virtual assistants connect employees to the basic information they need quickly and efficiently, with many questions answered without the need for human assistance. Of course, this goal requires that these systems are accessible.
AI for Accommodations
AI-enabled assistance tools can expand workplace inclusion by providing accommodation services for people with disabilities. Many workers with disabilities are already using AI tools to perform their jobs, including:
- Computer Vision provides facial, body, gesture, and image recognition services. This type of AI can aid in tasks such as wayfinding around an office or scanning a written document using Optical Character Recognition (OCR).
- Speech Systems convert text to speech and vice versa. This service can enable real-time captioning, automated speech recognition (ASR), and voice user interfaces like chatbots. For example, someone with limited use of their hands may work best using speech-to-text commands.
- Text Processing Systems analyze written text to summarize main points and enhance human understanding. These systems can translate a more complex document into simplified plain language.
- Chatbots and Conversational Agents can help people with disabilities find the information they are seeking, especially when designed for multimodal interaction. For example, chatbot prompts can help a person with a cognitive disability provide the information traditionally collected through resumes. This type of AI relies on speech systems and many components listed below to store and retrieve information.
