Why Human Transcription Still Matters: AI Backlash in Market Research & Recruitment

AI transcription tools have become increasingly popular thanks to their speed and low cost, such as ChatGPT, Microsoft Copilot etc… but faster doesn’t always mean better. As businesses put these tools to the test in real-world settings, many are finding the trade-offs aren’t worth it.

From growing concerns about accuracy and data security to contractual clauses that ban the use of AI altogether, it’s clear that many businesses are beginning to push back on AI use. In doing so, they’re reinforcing the value of human transcription, where quality, context, and confidentiality remain front and centre.

We’ve already written about the pros and cons of AI transcriptions, looking at where automated tools can be helpful and where they might fall short. In this article, we’re exploring the backlash that AI transcription has gained, particularly in market research and recruitment.

The rise of AI in transcription

In recent years, artificial intelligence has made significant strides in various industries, and transcription is no exception. AI transcription software can process vast amounts of data in a fraction of the time it takes human transcribers, which has made it an appealing option for businesses looking to save time and reduce costs.

However, while AI transcription is still far from perfect, as the technology evolves, more industries are realising that while AI has its place, there are still critical gaps in accuracy and nuance that only human transcribers can fill. This has sparked a growing conversation, particularly in fields like market research and recruitment, where precision and understanding are paramount, areas also explored in Copilot training courses london.

The growing distrust of AI in the market research sector

As AI technology has gained traction in the market research sector, it has been met with increasing skepticism. Market researchers rely on accurate, nuanced data for meaningful insights, and many believe that AI-driven transcription systems fall short when it comes to capturing the full context of conversations. Whilst AI tools can transcribe spoken words quickly, they often struggle with identifying subtleties such as tone, emotion, and intent, which are all vital components for interpreting qualitative data.

In addition, the accuracy of AI transcriptions can vary, especially when dealing with diverse accents, dialects, or technical jargon. In a field where the smallest misinterpretation can lead to skewed results, market researchers are concerned that relying on AI could undermine the quality of their data, which, in turn, can lead to flawed conclusions.

Finally, there is growing concern around data privacy and security. Market research often involves sensitive information, and AI systems often do not have the same level of confidentiality and control as established human transcription services. For many in the sector, the risk of sensitive data being exposed or mismanaged outweighs the benefits of using AI.

Why AI doesn’t always meet the mark in recruitment

AI has become an attractive option for many recruitment processes, providing a quicker way to sort through large volumes of applications, conduct initial screenings, and even handle preliminary interviews. However, when it comes to transcription, particularly in the context of candidate interviews, AI falls short in a few important areas.

One main issue is that AI isn’t able to accurately capture the subtleties of human communication. In recruitment, how something is said is often as important as what is said. Non-verbal cues such as tone, pauses, and emotional undercurrents play a crucial role in understanding a candidate’s true intentions, level of confidence, or potential fit for a role. AI, however, can only transcribe the words and often misses these essential human elements, which can lead to less insightful records.

In addition, AI can struggle with accents, regional dialects, and varied speech patterns, which are particularly problematic in a multicultural and multilingual recruitment landscape. The nuanced way people speak in different regions or even within different professional fields can confuse AI transcription systems, which can result in errors that negatively impact the candidate assessment process.

AI-driven transcription can also lead to biases, as algorithms often reflect the biases of the data they’ve been trained on. In recruitment, this could manifest in ways that unintentionally favour certain candidates over others based on factors such as accent, tone of voice, or even speaking speed. In an environment where diversity and inclusion are a priority, relying solely on AI could unintentionally perpetuate these biases.

When contracts say no to AI

For these reasons and more, many organisations are becoming increasingly cautious about the use of AI, so much so that some now include explicit clauses in their contracts stating that AI cannot be used in the transcription process.

This isn’t just about preference. For sectors that deal with sensitive, confidential, or proprietary information, the potential risks associated with AI tools, such as data being processed through third-party servers or stored in the cloud, are simply too big. In environments governed by strict compliance standards, from legal and healthcare settings to high-level corporate research, these risks can breach contractual obligations or regulatory frameworks.

There’s also the question of accountability – AI tools don’t offer transparency around how decisions are made or how errors occur. When a transcript must be verifiable and traceable, businesses need the assurance that comes from a fully human process. In contrast, human transcribers provide a clear, auditable chain and are able to explain and amend any issues, something AI systems, by their nature, can’t do.

Why industries still need human transcribers

So, whilst AI transcription sometimes offers speed and convenience, it’s not always compatible with the legal and ethical standards some businesses must uphold. In these cases, human transcription isn’t just safer – it’s a contractual necessity.

There are also inherent qualities of human transcribers that machines simply cannot replicate, which makes them indispensable in many professional environments. These include:

Human judgment and decision-making

One of the key strengths of human transcribers is the ability to make judgment calls during the transcription process. In complex or ambiguous situations, such as when speakers are talking over each other, using slang, or referencing context-specific terms, a human transcriber can determine the best course of action, applying logic and knowledge that an AI system can’t mimic.

Flexibility and adaptability

Human transcribers have the flexibility to adapt to varying requirements. Whether it’s adjusting the formatting to meet specific client needs, recognising regional variations in speech, or tailoring the transcription style to match the tone of the original conversation, human transcribers can personalise their work in a way AI can’t.

Contextual understanding and cultural sensitivity

Human transcribers bring a level of cultural sensitivity and contextual awareness that AI systems can’t replicate. Transcriptions often require an understanding of cultural references, idiomatic expressions, or situational context. For example, understanding the local dialects or recognising industry-specific jargon within a conversation can significantly influence the transcription’s accuracy. A human transcriber, with their understanding of the cultural and contextual background, can ensure these subtleties are preserved and correctly conveyed in the transcript.

Quality control and consistency

Even the best AI transcription tools still require human oversight. While AI may offer a first draft, human transcribers provide an essential layer of quality control, ensuring that the final transcript is not only accurate but also consistently aligned with the original audio. A human can assess the overall flow, coherence, and clarity, and make adjustments where necessary. This level of editorial oversight is crucial when dealing with high-level transcriptions, such as legal proceedings or business meetings, where even minor errors can have serious consequences.

You can read our case study evaluating AI-generated transcripts vs human transcription to see more data about the differences in accuracy and efficiency in real-world interview scenarios.

Personalised service and client relationships

Human transcribers also offer a more personalised service than AI can. Transcribers can build relationships with clients, so they can better understand their needs, preferences, and expectations. Human transcribers often work directly with clients to refine processes, offering tailored solutions, and ensuring that the end result meets their exact requirements. This level of personal engagement enhances the overall experience and helps create trust, something that AI systems struggle to establish.

Emotional intelligence and empathy

In certain sensitive environments, such as interviews, therapy sessions, or focus groups, the emotional tone of the conversation can be just as important as the content. Human transcribers possess the emotional intelligence needed to recognise and appropriately handle sensitive content. From specific language used in difficult conversations to understanding the subtle implications of what is being said, human transcribers can make decisions regarding how to record and present these exchanges, which AI systems typically can’t address with the same care.

Need a human touch for your transcriptions? We’re here to help

If accuracy, confidentiality, or compliance are non-negotiable for your transcriptions, relying on AI just isn’t worth the risk. At McGowan Transcriptions, we’ve been delivering trusted, human-only transcription services for over 30 years, with no shortcuts, no subcontracting, and absolutely no AI.

Contact our team today to find out how we can help with your next project.