New research from Sapia.ai has slated chat-based interviews as one of the fairest means of evaluating candidates with a disability.
The study canvassed global responses from 595 self-reporting a disability, 595 randomly selected from those not reporting a disability, controlling for similar gender, race, and answer length distributions.
The study — which was previously presented at the Society for Industrial and Organisational Psychology conference in the United States — canvassed global responses from 595 self-reporting a disability, 595 randomly selected from those not reporting a disability, controlling for similar gender, race, and answer length distributions.
It revealed a minute difference in the candidate passing rate for those reporting a disability against those without one, recording data for those declaring dyslexia, autism or a stutter.
The grid below indicates the percentage of candidates who passed the initial screen using the Sapia.ai platform. It also measured the level of effect their declared disability had in relation to their ability to proceed. Under 0.2 is considered a small impact and below 0.5 is considered a medium impact.
The grid below indicates the percentage of candidates who passed the initial screen using the Sapia.ai platform. The study also measured the practical impact of the results across groups shown as the effect size. Under 0.2 is considered a very small effect, likely to be of no practical significance and below 0.3 is considered a potentially noticeable but not substantial impact.
| Total count | Percent suggested to proceed to 2nd round | Effect Size | |
| Identifying without a disability | 595 | 35.63% | |
| Identifying with a disability | 595 | 30.86% | 0.25 |
| Autism spectrum disorder | 72 | 31.94% | 0.14 |
| Dyslexia | 324 | 32.72% | 0.24 |
| Stutter | 104 | 32.69% | 0.18 |
Sapia.ai’s technology asks candidates five questions via an AI powered chat platform. There is no time-limit for candidates to complete their responses, allowing for time to edit and think through their responses. Though, most candidates complete the chat within thirty minutes on average. Using these responses, Sapia.ai’s technology then provides the employer with an overall score and ranking of candidates, based on how their results line up with their required traits and skills for the role.
Barb Hyman, CEO and founder of Sapia.ai said: “Our latest research adds yet another argument for the use of chat-based tools in your recruitment process. Not only are they preferred by women candidates, but they level the playing field for those applying with a disability.”
“Candidates with a disability already fight against unconscious bias in the hiring process. Many of the tasks allocated to them during recruitment — such as video interviewing — discriminate against them. This data shows that a chat-based interviewing, as an initial means of screening, ensures your second-round candidate pool fairly represents all aspects of the community.”
A pioneer in ethical AI solutions and contributor to the scientific discussion on its use, global brands trust Sapia.ai to accelerate and enhance their recruitment and promotion processes. A conversational, Natural Language Processing (NLP) based chat AI interviews, assesses and screens for the best talent at scale via an easy-to-use platform, generating insights for both candidates and hiring teams.
A pioneer in ethical AI solutions and contributor to the scientific discussion on its use, global brands trust Sapia.ai to accelerate and enhance their recruitment and promotion processes. A conversational, Natural Language Processing (NLP) based chat interview, assesses and screens for the best talent at scale via an easy-to-use platform, generating insights for both candidates and hiring teams.
Its platform is available for use in over 10 languages, aiming to put all talent — even those who do not speak English as a first language — at ease during the hiring process. This process also aims to improve diversity outcomes by helping eliminate unconscious bias in candidate screening.
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