With the advent of AI (Artificial Intelligence), countless people have doubts about the relevance of humans in language-based exams such as IELTS—which is still the human-orientated exam and is considered the king for several reasons.
Students think they now have a personal teacher and can save money.
This is a MYTH.
Now, many would mock me or hate me for saying AI is bad, and I, being an IELTS teacher, am being partial. I AM NOT!!!
Although highly advanced, AI can never replace human thoughts and language understanding. Humans have developed language over the years and keep working on its efficiency, such as adding new words to dictionaries to increase the vocabulary as we advance in sciences.
REMEMBER….
AI fails terribly when working on a language. Yes, to some extent, it can do wonders, helping a novice write a professional email or helping students write their theses or do their assignments, but…
Designing an IELTS exam is a league apart, and deploying AI to check the IELTS writing and speaking tests will never happen.
Humans write subjectively, and AI are trained LLM (Large Language Models) models that fail to counter the subjective thoughts altogether.
In the future, the University of Cambridge, which owns the IELTS Exam with its co-partners, the British Council and IDP, can use AI in some ways to lessen its work, but it is the king of language-based English exams because they are human-based exams.
Possibly, that’s why when you take the IELTS exam, you not only become qualified for all the top-ranked universities around the globe but also improve your English language skills, which is unlikely to do with other language-based exams due to their AI-based approach.
You must be an expert to find an AI’s mistakes in any given task. Students who depend on AI for their IELTS practice make this mistake. They are unaware of the mistakes they accept as truth and repeat them in exams, only to be disappointed.
For example, asking AI to write a certain code will do it quickly if you are not an expert coder. However, you will not know its mistakes, which can harm your website. The same is true with the IELTS exam.
Below are some reasons why AI-based exams don’t do justice and will remain under scrutiny for their errors.
Click here to read how much time and effort are required to design a full-length IELTS exam, which is impossible to solely do with the AI.
1. Human Insight into the Nuances of Language
Humans have a nuance to languages that AI can never replace and replicate. Though AI is smart enough to do massive calculations or many other things, it still fails massively on many things, especially when it comes to working on a language.
- Example: A phrase like “break a leg” means “good luck” in English, but an AI might interpret it literally or fail to recognise the idiomatic usage. This could lead to inappropriate question creation or evaluation.
- Relevant Example: During an IELTS Speaking test, a candidate might say, “I was on cloud nine when I got my dream job.” A human examiner might understand this as an idiom expressing extreme happiness, but an AI might misinterpret it as irrelevant or redundant.
- Relatable Scenario: A student writes, “She took the bull by the horns when dealing with a difficult manager.” A linguist recognises it as a strong expression of courage, while an AI might misjudge the phrasing.
- Data: A 2022 study by Stanford University found that AI misinterprets idiomatic expressions 18% of the time, compared to 4% by human evaluators.
2. Creativity in Test Design
- Example: Linguists design tasks like describing a futuristic invention or debating climate change’s impact. These tasks aim to stimulate the critical thinking and creativity of test-takers. AI might only generate predictable or formulaic topics.
- Relevant Example: A human linguist might create a task such as “Imagine you are an astronaut sent to live on Mars for a year. Write a diary entry about your first day.” AI might default to generic topics like “Benefits of Exercise,” which are less engaging.
- Relatable Scenario: For listening, a linguist could craft a dialogue about visiting a historical site with local cultural anecdotes. AI might create a repetitive shopping or train station scenario.
- Data: According to a 2020 British Council report, studies show that human-crafted tests score 20% higher in candidate engagement than those generated by algorithms.
3. Ethical Considerations
- Example: AI might disproportionately penalise accents or dialectal variations. For example, South Asian speakers might pronounce “v” as “w” (e.g., “wisit” instead of “visit”). A human examiner accounts for such regional influences, while AI might flag it as incorrect.
- Relevant Example: In IELTS Speaking, a West African speaker might use phrases like “I am coming now” to mean “I will be there soon,” which is acceptable in their cultural context but may confuse AI.
- Relatable Scenario: A linguist may understand that a candidate’s use of “She doesn’t know” reflects exposure to vernacular English rather than a lack of proficiency. AI, however, might penalise it severely.
- Data: An MIT study found that AI grading systems were 60% more likely to penalise non-native speech patterns than human evaluators.
If you are wondering how much time one needs to prepare for the IELTS exam, click here. This will give you an idea about it completely.
4. Critical Judgment in Scoring
- Example: For an essay on climate change, a candidate writes: “Deforestation is harming biodiversity.” A human examiner recognises this as a valid point, even without elaboration. AI might grade it poorly for insufficient complexity.
- Relevant Example: A candidate says, “In the present era, technology is taking over every aspect of our lives.” Despite the statement’s lack of detail, a human examiner recognises its relevance and coherence. AI might penalise it for a lack of specific examples.
- Relatable Scenario: A candidate answering an IELTS Speaking question about travel may say, “I think travelling helps people grow personally and professionally.” Humans can assess the depth of the idea even if the grammar isn’t perfect, while AI might overlook the nuanced thought process.
- Data: According to an ETS report, AI-based systems like e-rater failed to distinguish between off-topic but grammatically correct and high-quality essays 15% of the time.
5. Evolving Nature of Language
- Example: The word “yeet,” popularised on social media, might be misunderstood by AI as a typographical error or irrelevant term. Human linguists recognise such trends and decide whether they belong in formal language contexts.
- Relevant Example: A linguist might include a task where candidates discuss the impact of memes on communication, while AI might fail to generate such contemporary topics.
- Relatable Scenario: Imagine an IELTS listening passage about sustainable technology referencing a “circular economy.” Linguists understand this is an emerging term, while AI might exclude it due to limited training data.
- Data: A survey by Cambridge English showed that 40% of candidates relate better to exams incorporating modern, evolving language contexts, underscoring the importance of staying current.
6. Holistic Understanding
- Example: In IELTS Writing Task 2, a question like “Do you agree or disagree with banning plastic bags?” requires integrating vocabulary, grammar, coherence, and ideas. AI might assess these in isolation without appreciating how they contribute to overall effectiveness.
- Relevant Example: A candidate writes, “Banning plastic bags is important, but alternative solutions should be affordable and accessible for everyone.” A human examiner recognises this as a well-balanced argument. AI might penalise it for lacking advanced vocabulary.
- Relatable Scenario: In a speaking test, a candidate says, “I travelled to Paris last year. It was amazing; the Eiffel Tower looked stunning at night.” Humans evaluate the emotional connection and descriptive detail, while AI might score it based only on grammar and sentence length.
- Data: A 2019 Pearson study showed that human examiners excel in evaluating responses that combine multiple skills, with a 94% accuracy rate compared to AI’s 81%.
Role of AI as a Tool
- Example: AI could automate initial scoring for grammar and spelling, freeing linguists to focus on creative and subjective aspects.
- Relevant Example: AI could flag common errors like “She go to market” (verb agreement), but humans decide if it’s a systematic error or a one-time oversight due to nervousness.
- Relatable Scenario: AI could generate practice questions, such as filling in blanks with prepositions or correcting verb forms. Human linguists would review these questions and ensure they align with the test’s objectives.
- Data: According to a 2021 Duolingo English Test report, hybrid systems (AI + human) reduce scoring time by 30% while maintaining high accuracy.
Conclusion
AI complements linguists by assisting in repetitive tasks and large-scale analysis. However, linguists ensure creativity, cultural relevance, and fairness, which remain essential for global exams like IELTS.
Remember, AI can be a very powerful tool but has limitations.
Note: To test the waters, we asked AI with relevant prompts to generate the content for this post. It did a fantastic job, but it took us a lot of time to edit the content so that no jargon and confusion would remain in the readers’ minds.
We are telling it because we wanted to test it live, and we are rest assured that IELTS will remain the king in the foreseeable future, and AI exams may have to up their game by bringing the human involvement for the fair scores and marking.
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HOWEVER …
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