AI and Early Careers - Should we embrace it?

In the words of Sam Altman, CEO of OpenAI, ChatGPT is a calculator for words. The speed at which conversational AI tools are being used in our daily lives is nothing short of extraordinary.

Cue the flood of training contract and apprentice applicants that are using the latest AI tools to support their application writing. And why shouldn’t they? Well, the Big 4 says they shouldn’t and have warned graduates not to use AI in any part of their recruitment process, with PwC threatening action against rule breakers. Whilst large City law firms, such as Shoosmiths, have gone the way other and are embracing it, by encouraging candidates to flag where they have used it in their applications.

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A recent Dandi poll on LinkedIn says that a third of candidates used an AI tool in their Early Careers application. We expect the true figure to be higher as it’s very likely that candidates are reluctant to disclose that they’ve used AI in a public domain.

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The battle between AI tools and AI detection

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How do we counter the over-use of AI in applications? BDO have AI detection tools that review applications and checks them against the standard responses you would expect from AI tools. It can even check repeated answers across the candidate pool that has applied to a specific role.

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Much depends on how and where candidates are using AI. In its simplest form, it can be a research tool, like Google’s search engine, but in its most complex form, AI can be used in psychometric testing and is particularly impressive for verbal reasoning tests, where ChatGPT scored 98.8% better than human candidates across 36,000 candidates, based on a study conducted by Artic Shores.

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The cat and mouse between constantly evolving AI tools backed by big tech, alongside AI detection tools, backed by smaller tech, is likely to go on for quite some time. For now, BDO may have some success in counteracting the use of AI tools that are still in their infancy, but AI tools are likely to outpace the development of AI detection. ChatGPT, even shut down their own AI detection software because of its poor accuracy. That’s where Shoosmiths’ idea of embracing it, rather than fighting it, may well be the direction that other firms begin to follow.

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Application volumes for in-house teams

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Modern tech has created a world of efficiency. Applying for a new role can happen in less than a few clicks on LinkedIn, whilst other job boards now have ‘One Click Apply’ buttons. Couple that speed with AI tools that can tailor your CV to a role and write a cover letter in seconds, it has created a much faster applications process for a candidate, allowing them to apply for a much higher volume of roles. Firms are seeing increases between 20-50% in the number of applicants they are receiving compared to last year’s training contract cycle and expect that number to grow significantly, year on year.

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That means far more applications for in-house legal recruitment teams to filter and an additional step for some firms wanting to screen as many applications for AI usage as possible. That’s a great deal of extra work in the early stages of recruitment that could disproportionately impact less privileged candidates. Recruitment teams will have less time to spend on each CV and there is a risk that important details relating to social mobility, such as understanding a candidate’s extenuating circumstances, could be overlooked during the shortlisting process. That’s where contextual data on candidates applying for all roles, rather than just Early Careers, could ensure that social mobility data on a candidate’s record is clearly visible and not missed by recruiting teams.

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Law firm: Case study

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In part 2, we run a case study on a law firm and examine the answers AI tools produce for their training contract application questions. We will look at 3 different AI tools; ChatGPT 3.5 (free), ChatGPT 4 (paid) and Google Gemini. We want to experiment using two different versions of the same chat bot (ChatGPT 3.5 and ChapGPT 4) to see the progression AI tools are making year on year.