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Machine Learning and Neural diverse candidates

One way that machine learning could potentially be used to recruit neural diverse candidates using personality assessments is by analysing the results of personality assessments and identifying patterns or correlations between certain personality traits and the ability to think and solve problems in diverse and innovative ways.

For example, an organisation could train a machine learning model to identify candidates who score highly on personality traits such as openness to experience or intellectual curiosity, as these traits may be associated with a willingness to consider a range of perspectives and approaches to problem-solving.

It’s important to note that using machine learning in this way is still a relatively experimental approach, and it is likely to be more effective when used in combination with other methods, such as human judgment and observation. It’s also important for organisations to be aware of the potential for bias in machine learning models and to take steps to mitigate it.