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The pitfalls of algorithm-based recruitment

Controversy over the use of algorithms in determining school examination results has included claims of unlawful discrimination, which makes their use highly relevant to employers, says James Davies, joint head of employment, reward and immigration department at employment and immigration law firm Lewis Silkin.

Recent years have seen rapid growth in the use of algorithms in employment, particularly in recruitment. Algorithms are now being used even for senior role recruitment – for example, to assess candidates on their facial and vocal expressions. Chatbots are replacing people as interviewers and textbots are communicating with candidates by text or email. Algorithms and AI are even used in HR decisions such as redundancies, performance dismissals, promotions and rewards. As their use becomes more commonplace, claims regarding algorithms and discrimination are also likely to become more common – something which UK employment law and enforcement mechanisms are ill-equipped to deal with.

Reducing or embedding bias?

Academics, especially in the United States, have extensively debated the pros and cons of algorithms and whether they increase or diminish bias and unlawful discrimination in employment decisions. The proponents point out that while some bias is inevitable, algorithms reduce the subjective and subconscious bias involved in decisions made by humans. However, there is also evidence that algorithms can teach themselves to be biased and thus discriminate, for example on gender grounds, even when gender is not known. Words such as ‘executed’ and ‘captured’ are apparently used by men more often than women, and this can be identified and used by the algorithm. 

How do algorithms work?

An algorithm is merely computer code used to navigate and, often, develop a complex decision tree quickly. Algorithms used in recruitment can be ‘off the shelf’, which are appropriate when recruiting for jobs where the characteristics of successful candidates will be clear and will not vary from employer to employer. Alternatively, a recruitment algorithm can be created specifically for a client based on a specific data set, and customised to take account of the client’s own experiences and priorities.

Bias and unlawful discrimination can occur within an algorithm by reason of:

  • the objectives set for the algorithm
  • the data inputted to create the algorithm
  • the causal links identified by the algorithm
  • the data used when running the algorithm.

The use of algorithms to make employment-related decisions also raises difficult data privacy issues. The Information Commissioner’s Office recently published fresh guidance on AI and data protection, highlighting the importance of processing personal data fairly, transparently and lawfully and, hence, in a non-discriminatory manner. The guidance illustrates how discrimination can occur if the data used to train a machine-learning algorithm is imbalanced or reflects past discrimination.

James Davies

Many suppliers of algorithms reassure clients that their codes have been stress tested to ensure that they do not discriminate. An employment tribunal is unlikely to accept a supplier’s word for this. This begs the question: Can the algorithm supplier be sued for causing or inducing a breach of equality laws or helping the employer to do so? The supplier will often be based in the United States, introducing practical and legal complications for UK businesses.

Like it or not, the use of AI and algorithms in employment will inevitably increase and the conflict with existing laws and enforcement mechanisms will only become more evident.

Further information: Information Commissioner’s Office Guidance on AI and data protection here.

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