Language is how we communicate, a truly human skill that defines who we are. People express through text every single day – it’s familiar and comfortable.
All candidates are interviewed by a chat experience that is easy, fun and engaging. Every word, phrase, syntax, tone, definition and context is added to our machine.
This is important because these words and this language is the basis of our science – PredictiveHire’s Ai (Phai).more info
Words are data. Patterns are derived from the free-text answers that candidates give in response to 5~7 questions. They tell their own story in their own words.
More than than just simple keyword matching this frontier technology reads, deciphers, understands and makes sense of answers.
Through the advances in Natural Language Processing (NLP) and Machine Learning (ML) multi-dimensional features emerge with oodles of insights. These include the HEXACO personality assessment profile, role-based attributes, behavioural traits, communication skills and more.Want to chat?
PredictiveHire’s Ai uses a unique blend of Machine Learning, Natural Language Processing and Personality Theory to assess and rank candidates based on the text answers they give to a set of open-ended questions.
Chat experience is the method by which word data are collected for analysis. Chat experiences take the form of a standard text message conversation via a mobile device. PredictiveHire’s FirstInterview uses this experience to interview candidates at volume.
All interviews are standardised, with each job role having 5~7 interview questions. The language used is approachable and relatable ensuring candidates feel at their most comfortable for the interview. These chat experiences are then processed through machine learning technology to predict the candidates of best fit.
Language is predictive of personality. This is a fact proven by numerous studies including the origins of the popular five and six-factor models of personality. These widely adopted personality models are grounded on the “Lexical Hypothesis” that claims personality characteristics are encoded in language. PredictiveHire has built a personality classifier based on free-text responses to interview questions from over 46,000 candidates and their self reported personality profile based on the HEXACO (6-factor) model. A candidate’s personality can accurately be inferred using answers to interview questions with a minimum of 150 words long.
Machine Learning (ML) is a branch of Artificial Intelligence. Recommendation engines use ML to predict how a person rates on a specific range of items.
PredictiveHire machine-learning models are trained to predict the likelihood of a new applicant to be hired using predictive patterns found in thousands of candidates hired in the past into similar roles. These patterns are derived from the free text answers given by an applicant to the online interview questions.
Natural language processing (NLP) is a sub-field of Artificial Intelligence that is focused on enabling computers to understand and process human languages to get computers closer to a human-level understanding of language.
The ultimate objective of NLP is to read, decipher, understand, and make sense of the human languages in a manner that is valuable.
PredictiveHire uses NLP on candidate responses to interview questions that enable the identification of job-fit related themes.
Language is a mirror for communication skills. English fluency and English Proficiency are both discoverable via a candidate assessment that uses free-text answers to open-ended interview questions around past-experience and situational judgement.
Candidates are benchmarked on both fluency and proficiency across the candidate pool, and the wider role family pool.
Flight risk that comes from a candidate’s tendency to job hop (job-hopping motive) and this can be predicted via language.
PredictiveHire has proven this from analysing the answers to situational judgment and behavioural questions at the application stage of 45,000 new hires across multiple role families and their self-reported attitude towards job-hopping. By training a classifier with this data we job-hopping motive can be inferred from the candidate’s interview responses.
The machine has an inherent ability to learn. This makes it distinct from psychometric assessments.
Unlike traditional psychometric assessments which are based on a static success profile of norm data, machine learning is dynamic. This matters because people are complex and performance is not the same across all contexts. Some people may wane in one business culture yet thrive in others.
Phai continuously learns about YOUR organisation from the compounding results of candidate performance. This data shapes, evolves and refines your success profile against which your candidates are assessed.
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