Christopher Patnoe, Head of Accessibility and Inclusion for EMEA at Google, shares his perspectives on emerging issues in accessible technology. He delves into hot topics, including how to handle immersive captioning in virtual reality and the need to recognize that traditional accommodations may not be the optimum solution for hybrid workplaces. […]
October is National Disability Employment Awareness Month (NDEAM). If you are a worker with a disability or an employer of someone who has a disability, you likely already know the unique considerations and often under-recognized benefits that stem from employing people with disabilities. According to Accenture, companies who hire people with disabilities earn 28% higher revenue, two times the net income, and 30% higher economic profit margins than their peers. [...]
Susan Mazrui, Director of Global Policy for AT&T, discusses the importance of accessible workplace technologies and how a commitment to accessibility and inclusion can help employers navigate the implications of long COVID as we shift to an increasingly hybrid workplace. Original publication date: October 18, 2021 […]
This white paper gives an in-depth look at ways accessible extended reality (XR) technologies can enhance organizations and promote inclusion.
This brief overview is designed to help leadership understand the value of inclusive extended reality (XR) technologies in the workplace.
Staffing for Equitable AI: Roles & Responsibilities Start with a Model The Equitable AI Playbook encourages organizations to consider a hub-and-spoke model for their Equitable AI initiative. In a Hub-and-spoke model, a central group (“Hub”) is led by C-Level and establishes standards, processes, and policies. “Spokes” are business unit or function teams that oversee execution of the policies and processes by implementation teams. This type of model has typically [...]
John Robinson, President and CEO of Our Ability, discusses how harnessing the power of AI technology can improve employment opportunities for people with disabilities. […]
What if a construction company could use virtual reality to train employees on worksite hazards from the safety of a conference room? Or an expert wind turbine technician could use augmented reality to guide on-site technicians through repairs, despite being in a different country? […]
Ahva Sadeghi and Paula Mora, founders of Symba, discuss how companies can increase their access to a diverse talent pool through remote internship and apprenticeship programs. […]
This resource library will help guide you through specific aspects of implementing and incorporating AI-enabled tools within your workplace. Each section contains an overview of the challenge or activity as well as links to guidance, tips, and templates to assist you as you move forward with your equitable AI initiative.
Implementing AI-Enabled Assistant Tools to Make Workplaces More Inclusive AI-enabled technologies are adding new ways to make a workplace more directly accessible to people with disabilities. The following tools are increasingly available as organization-wide subscriptions. They offer a wonderful opportunity to reduce the need for individual accommodation by making the workplace more directly accessible. It’s a best practice to offer such features to all employees, who can turn the [...]
Interview Checklist for HR Professionals Using AI-enabled Tools HR professionals using AI-enabled tools must ensure their assessment methodologies are ethical and accurately measure potential in candidates. Even after a technology has been vetted and procured, the way it’s used can affect how inclusive it is in practice. To ensure a level playing field, everyone involved in the recruiting process should understand and follow these ongoing actions. [...]
The Challenge of Fairness Audits Many vendors provide “fairness audits” that claim to be able to measure when bias is taking place and recommend course corrections. In practice, many of these tools have only considered race and gender as dimensions of diversity. And if they are considering disability, the methodology behind it is likely flawed. The 80/20 rule In 1978, the federal government adopted the Uniform Guidelines for Employee [...]
Developing Staff Trainings for Equitable AI Staff training is an essential component of your Equitable AI professional development program. Like other elements of staff training on disability inclusion, putting these structures in place helps ensure all employees understand their organization’s vision, policies, initiative structure, and resources for implementing equitable AI. Developing a successful culture of inclusion requires that everyone an organization gain a basic understanding of these issues, and [...]
The Equitable AI Playbook is a blueprint that can help your organization foster inclusion as you procure, develop or implement artificial intelligence (AI) technologies in your workplace. Organizations are increasingly using AI to screen job candidates, streamline the application process, monitor employee actions, and provide employee training. However, AI technologies can often be unintentionally biased and produce unfair outcomes for different protected classes. This can increase the risk of bias and discrimination against job candidates and employees.
Examples of Equitable AI Below are examples of how AI tools can support job seekers and employees with disabilities, recruiters, and staff responsible for diversity, equity, and inclusion. Each example describes the value of applying Equitable AI Principles in the design and implementation of the AI Tool. Considerations that Apply to All Examples Before procuring and implementing AI tools, organizations should examine how they were designed, how they function, [...]
Adopting Equitable AI Principles can make your organization a better and more inclusive place to work. It’s a strategic opportunity for an employer to be seen as a leader and innovator in its field. We created the following guidelines to help organizations consider what can be included in your business case for Equitable AI. After reading these guidelines, refer to Play 1: Build an Equitable AI business case in our Equitable AI Playbook to learn valuable tips for building your own business case.
AI Hiring Tools and the Law The development of AI technologies is outpacing the evolution of regulations and standards that directly enforce the use of AI hiring tools. However, employers should proactively consider legal and equity concerns related to AI hiring tools before implementing these technologies in their organizations. Acting in accordance with existing guidance can put your organization on the right path as new standards unfold over time. [...]
Civil Rights Principles for Hiring Assessment Technologies In 2020, the Leadership Conference on Civil & Human Rights and other advocacy groups released Civil Rights Principles for Hiring Assessment Technologies. The Center for Democracy and Technology summarized these principles, with emphasis on the elevated risks based on disability, in the report Algorithm-driven Hiring Tools: Innovative Recruitment or Expedited Disability Discrimination? They recommend the following framework for employers to consider to [...]
The Problems with Personality Tests Many AI tools assessing “personality” and “cultural fit” make big claims that they provide accurate identification of personality traits such as openness, conscientiousness, extroversion, emotional stability, adaptability, assertiveness, responsiveness, intensity, optimism, sociability, and grit. However, these assessments aren’t actually based on scientific methods. It is often unclear what these tests assess—and there is significant evidence that they work particularly poorly for underrepresented groups like [...]
How Good Candidates Get Screened Out AI reflects the implicit biases of the people that design it. Models learning from biased training data may perpetuate historical bias against marginalized groups, such as people whose gender is non-binary, people of color, people with disabilities, or other minorities. Further, training data typically underrepresents marginalized groups. Because these groups include people with disabilities, mitigating bias against people with disabilities is a more [...]
Risks of Bias and Discrimination in AI Hiring Tools Disabilities are highly diverse and virtually impossible to analyze at scale Consider that half of disabilities are invisible, and only 39 percent of employees with disabilities disclose their disability to their managers, let alone an interviewer. Disabilities are also highly diverse, ranging from physical disabilities like mobility or blindness to cognitive and psychosocial disabilities. They are further diversified when considering [...]
As organizations increase their use of AI tools in the workplace, they can become vulnerable to new risks and modes of discrimination against people with disabilities and other protected classes. Like other innovative technologies, the speed of AI advancement has outpaced the community’s ability to put in place clear guidelines, standards, and regulatory structures on equitable technology design and implementations. Until recently, computer scientists have not been asked to consider the ethics of their research. Ethical consideration is crucial in many fields, including biology, psychology, and anthropology, where researchers are asked to follow many legal regulations and codes of conduct.
AI in the Workplace 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 [...]
AI Basics What is AI? AI refers to the use of computer systems to perform tasks that traditionally require human intelligence and senses. Instead of a programmer assigning AI a set of step-by-step instructions, AI “learns” by using statistical techniques that allow it to improve performance on a task. This process of machine learning equips AI to generate rules and predictions on its own by analyzing large quantities of [...]