AI in hiring: expressing cause and effect

90 min

Premium

Think about these questions before reading. Share your ideas with a partner.

To what extent do you believe the 'human element' is indispensable in the recruitment process, and what are the potential pitfalls of over-relying on technology to make hiring decisions?
Imagine you're applying for your dream job and discover the initial screening is conducted entirely by an AI. How would this knowledge affect your approach to the application and your perception of the company?
People often talk about 'inherent human bias' in hiring. In what ways could an AI system either eliminate or, paradoxically, amplify these biases when screening candidates?

AI in Hiring: A Double-Edged Sword

Listen to the dialogue. Notice how the vocabulary and grammar from the lesson are used.

Answer these questions in your own words. Support your answers with evidence from the article.

01According to the article, what potential challenges in using AI for recruitment are highlighted by the key vocabulary 'inherent biases' and 'human oversight'?

Sample answerThe article suggests that these terms point to major pitfalls. 'Inherent biases' implies that AI systems can perpetuate or even amplify existing prejudices in hiring, while 'human oversight' highlights the critical need for people to monitor, question, and override the AI's decisions to ensure fairness and prevent errors.

02In what ways does the article suggest a professional should approach a discussion about implementing a new technology like AI?

Sample answerIt implies a balanced and critical approach is necessary. A professional should be able to articulate support for the technology's potential benefits, but also clearly raise concerns about its drawbacks, and finally, propose specific conditions or safeguards for its implementation.

03Based on the ideas presented, why is the ability to express cause, effect, and concession particularly crucial for a nuanced discussion about AI in recruitment?

Sample answerIt's crucial because the topic is complex with no simple answers. You need to explain the cause of a problem, like biased data leading to discriminatory outcomes. You also need to discuss the effects, both positive and negative. Using concession allows you to acknowledge a valid point, like increased efficiency, while still maintaining a critical stance on a more important issue, like fairness.

04Considering the vocabulary mentioned, such as 'to alienate' an 'applicant pool', what does the article imply could be a significant negative human-centric consequence of poorly implemented recruitment AI?

Sample answerThe article implies that a major risk is damaging the company's relationship with potential employees. Using a term like 'to alienate' suggests that if the process is impersonal or perceived as unfair, it could push qualified candidates away, shrinking the 'applicant pool' and harming the company's reputation as an employer.

Vocabulary

These expressions will help you communicate more naturally about this topic.

Examples

A double-edged sword — something that has both positive and negative effects.

Usage note: This is a common idiom used to introduce a balanced perspective. For example: 'AI in recruitment is a double-edged sword; it increases efficiency but risks introducing new forms of bias.'

To vet candidates — to carefully check someone's background, skills, and qualifications to see if they are suitable for a job.

Usage note: This is a standard, semi-formal phrase in business and HR. You can talk about 'the vetting process' or 'vetting criteria'.

To fall through the cracks — to be overlooked or forgotten, often due to a flaw in a system.

Usage note: This idiom is perfect for describing the risk of a good candidate being missed by an automated system. For example: 'We need human oversight to ensure great applicants don't fall through the cracks.'

To streamline the process — to make a system or process simpler and more efficient.

Usage note: This is a common business collocation used to talk about improving workflows. It's often cited as a key benefit of automation.

Algorithmic transparency — the principle that the decisions made by an AI should be understandable and explainable to humans.

Usage note: This is a key term in discussions about AI ethics and accountability. A lack of algorithmic transparency is a major concern for critics.

Complete the sentences with words from the box. One word is extra.

Word bank

01Our main objective is to the initial stages of recruitment, reducing the time it takes to move from application to interview.

02The new AI system is designed to automatically candidates by cross-referencing their CVs with the job description's key requirements.

03Without a robust system, it's easy for highly qualified but unconventional applicants to and never be seen by a human recruiter.

04Using AI to analyze candidate personalities is a ; while it can offer insights, it also risks introducing new forms of bias.

05Critics are demanding greater algorithmic , arguing that companies must be able to explain why their AI rejected a particular candidate.

Grammar: using participle clauses to show reason and result

Grammar

Participle clauses allow us to express complex ideas more concisely, which is common in formal and written English. By using the -ing (present) or -ed (past) form of a verb, we can connect two ideas without needing conjunctions like 'because' or 'after', making our language more sophisticated when discussing topics like AI.

Examples

Recognising the potential for bias, the company installed an ethics committee to oversee the AI.

The present participle (-ing) shows the reason for the action in the main clause. It has an active meaning: 'Because the company recognised the potential for bias...'

Trained on incomplete data sets, the system failed to identify qualified candidates from non-traditional backgrounds.

The past participle (-ed) is used here with a passive meaning. It explains the cause of the system's failure: 'Because it had been trained on incomplete data...'

Having successfully filtered over 10,000 CVs, the AI presented a shortlist of the top 20 applicants.

The perfect participle (having + past participle) emphasises that one action was completed before the next one started, showing a clear sequence of cause and effect.

Key points

The subject of the participle clause must be the same as the subject of the main clause.
Use the present participle (-ing) for active meanings and the past participle (-ed) for passive meanings.
These clauses are more common in formal writing and speaking than in casual conversation.

Spot the mistake

Read the sentences below, which discuss AI in recruitment.

Each sentence contains one error. Find and correct it.

01A major ethical concern is the lack of algorithmic transparent in AI-driven hiring platforms.

Corrected version

A major ethical concern is the lack of algorithmic ~~transparent~~ transparency in AI-driven hiring platforms.

02Despite of its potential to reduce costs, the company is hesitant to fully automate its candidate vetting process.

Corrected version

Despite of its potential to reduce costs, the company is hesitant to fully automate its candidate vetting process.

03Without careful human oversight, it's inevitable that some excellent candidates will fall into the cracks.

Corrected version

Without careful human oversight, it's inevitable that some excellent candidates will fall ~~into~~ through the cracks.

04Been trained on historical data, the AI unfortunately replicated the inherent biases of previous hiring managers.

Corrected version

Having been trained on historical data, the AI unfortunately replicated the inherent biases of previous hiring managers.

05The sheer volume of applications, coupled with the pressure to hire quickly, mean that AI tools are becoming essential.

Corrected version

The sheer volume of applications, coupled with the pressure to hire quickly, ~~mean~~ means that AI tools are becoming essential.

06This technology is a double-edged sword; it streamlines the process, therefore creating a new risk of alienating candidates.

Corrected version

This technology is a double-edged sword; it streamlines the process, ~~therefore~~ thereby creating a new risk of alienating candidates.

Useful phrases: Discussing new technology at work

Vocabulary

When a new technology is proposed at work, it's important to contribute to the discussion constructively. These phrases will help you voice your opinion—both positive and negative—in a way that is collaborative and professional.

Examples

I can definitely see the potential here, particularly when it comes to... — use this to express support by highlighting a specific advantage.

Register: Neutral/Formal. This is a great opening phrase to show you are on board and have thought critically about the benefits, for example, '...particularly when it comes to reducing time-to-hire.'

My only reservation would be around... — use this to politely introduce a concern or potential problem.

Register: Neutral/Formal. 'Reservation' is a softer, more professional word than 'worry' or 'problem'. It allows you to raise a negative point without sounding confrontational.

One thing we need to be mindful of is... — use this to raise awareness of a potential risk or unintended consequence.

Register: Neutral/Formal. This phrase positions you as a thoughtful and strategic thinker who considers all angles, e.g., '...is the risk of alienating candidates who aren't tech-savvy.'

As long as we have a clear protocol for [X], I'm on board. — use this to state that your support is conditional on a specific safeguard.

Register: Neutral/Formal. This is a constructive way to agree while ensuring potential problems are addressed. For example, '...as long as we have a clear protocol for human oversight.'

To build on what [colleague's name] said, we should also consider... — use this to agree with a colleague and add your own related point.

Register: Neutral/Formal. This is a highly collaborative phrase that shows you are actively listening and helps to create a constructive discussion.

Could you walk us through how that would work in practice? — use this to ask for a practical, real-world explanation.

Register: Neutral/Formal. This is a polite way to request more detail and move the conversation from theoretical benefits to concrete implementation steps.

The complexities of AI in recruitment

Read the passage about the challenges and benefits of using artificial intelligence in the hiring process.

Fill in each blank with the correct word or phrase from the word bank.

Word bank

While AI can undoubtedly the hiring process, its implementation is often seen as a . On the one hand, algorithms can thousands of candidates with unprecedented speed. On the other hand, without sufficient human , there's a significant risk that deserving applicants will through the cracks. Consequently, many experts are calling for greater algorithmic to ensure fairness and prevent systemic discrimination.

The human cost of automated hiring

Read the passage below, then answer the comprehension questions.

The drive to streamline the process of hiring has led many firms to embrace AI-driven tools, hoping to efficiently vet candidates in unprecedented numbers. In theory, it's a perfect solution for overwhelmed HR departments. In practice, however, this technology is proving to be a double-edged sword. Having been screened out by an opaque system without any human interaction, countless qualified applicants are left wondering why they were rejected. This lack of algorithmic transparency not only damages a company's reputation but also poses significant legal risks. Talented individuals, whose unconventional career paths don't fit the prescribed model, frequently fall through the cracks, resulting in a less diverse and innovative workforce. Consequently, a growing movement is demanding greater human oversight and 'explainable AI', arguing that without it, the efficiency promised by these platforms comes at too high a cost, alienating the very people companies need to attract.

01According to the article, what is the primary motivation for companies to adopt AI in recruitment?

Sample answerTheir main motivation is to streamline the hiring process and efficiently handle large numbers of candidates.

02What does the author mean by describing AI recruitment technology as a 'double-edged sword'?

Sample answerIt means the technology has both significant benefits (efficiency) and serious drawbacks (damaging company reputation, legal risks, and alienating candidates).

03Which type of candidate is particularly at risk of being unfairly dismissed by AI systems?

Sample answerIndividuals with unconventional career paths whose experience might not fit the standard models the AI is trained on.

04The passage mentions that a lack of algorithmic transparency poses 'significant legal risks'. What might these risks be?

Sample answerThe risks could involve lawsuits related to discrimination. If an algorithm unfairly filters out candidates based on protected characteristics (like age, gender, or race), the company could be held legally responsible, and without transparency, they cannot prove their process was fair.

05What is the central argument of the 'growing movement' mentioned at the end of the text?

Sample answerThey argue that the benefits of AI's efficiency are outweighed by the negative consequences, and that there must be more human involvement and transparency in the process.

Discuss these questions with a partner. Try to use vocabulary from the lesson.

To what extent is the drive to streamline the recruitment process using AI a double-edged sword? Considering the demand for algorithmic transparency, could the potential efficiency gains ever truly outweigh the risks of qualified candidates falling through the cracks?
Reflecting on the professional culture in your country, how do you think the large-scale adoption of AI to vet candidates would be perceived? Would there be widespread acceptance, or significant pushback over concerns about fairness and the loss of human oversight?
If you were tasked with designing a policy for the ethical use of AI in your company's hiring, what would be your top three non-negotiable principles? How would you balance the goal of streamlining the process with the need to prevent inherent biases from being amplified?