(Written without AI by Frederik R. Pedersen, Founder and CEO, EasyTranslate

Human beings, not AI, love to put themselves on a pedestal, they believe that all sentient life devolves from them and they are, literally, the best things on the planet. Look at the furore surrounding generative AI and how humans have reacted to its evolution.

Time perhaps thinks otherwise. In the age of the Anthropocene, humanity now has become the problem and that pedestal has never been so weak. Those ‘machines of loving grace’ as espoused by the American poet Richard Brautigan have never seemed more attractive. We need to be saved from ourselves perhaps.

I’m the CEO and founder of a translation platform and recently spoke to TechCrunch about how EasyTranslate is augmenting Large Language Models (LLMs) with human expertise to gain an edge over pure AI translation services.

‘Human quality’ in translation was always high level, but not without mistakes. I believe that the standard for on-brand (strategy) translation will be a perfect meld of human and AI. Humans-in-the-loop and AI-in-the-loop.

But let’s look at the bigger picture away from my silo of translation and why such a relationship between AI and human works in every business and why the challenges, especially customer perception, need to be addressed all the way to sales teams. 

In the ever-changing world of ecommerce, the advent of generative AI has revolutionised the way businesses operate. From predictive analytics to personalised recommendations, AI is a game-changer in optimising processes and cutting costs.

However, despite its potential to bring prices down, convincing customers of its benefits remains a challenge. In recent years, AI has permeated various sectors from e-commerce giants to brick-and-mortar stores. 

Retailers are leveraging AI-driven solutions to streamline operations, enhance customer experiences, and ultimately, drive sales. 

So far, so predictable, but as is usually the case with new technologies, it takes time for everything to align and for the real implications to emerge. Those teams that drive sales have another challenge and that is to convince customers that AI-powered price deductions are a real thing and not a race to the bottom.

Take Amazon, for instance, a pioneer in AI-powered retail. The tech behemoth employs algorithms to analyse customer data and tailor product recommendations, leading to increased conversion rates and customer satisfaction.

Moreover, AI-driven pricing strategies enable dynamic pricing, allowing retailers to adjust prices in real-time based on demand and market conditions. Yet, despite the evident advantages of AI in reducing costs and improving efficiency, customers remain sceptical.

One reason for this scepticism is the perceived loss of human touch. Traditional shopping experiences, characterised by face-to-face interactions and personalised services, are increasingly being replaced by automated processes and algorithms.

As a result, some consumers feel alienated and disconnected from brands, preferring the familiarity of human interaction over AI-driven interactions.

Furthermore, concerns regarding data privacy and security pose additional hurdles in convincing customers of AI’s benefits. With AI systems relying heavily on vast amounts of data to make accurate predictions and recommendations, the issue of data misuse and breaches looms large.

As the founder of a translation company that has used generative AI to transform our business and previously stated, I have always been an adherent of humans-in-the-loop and believe the juxtaposition of humans and AI to be the perfect way to service our customers.

However, human translation has been put on a pedestal in spite of machine learning being part of the process for more than a decade. 

Our sales teams know that humans prevent AI error and AI prevents human error – it is the perfect blend. It is better than it has ever been for translation, but we still face challenges in our customers’ perception of AI.

Based on 250,000 translated words, humans only edit a minority of the content, but they are paid to look through everything. And human quality, how good is that actually? 

Our data shows that humans make one mistake per 200 words, based on 2.000 random QA covering more than a million words. Generative AI completely fixes that and it has completely revolutionised the cost of doing so.

This transformation in the translation process has also paved the way for a new role within our industry—Language Leads. As AI takes on more of the repetitive tasks in translation, the role of human translators has evolved from merely converting text to overseeing and guiding the entire translation workflow. 

Language Leads now play a strategic role, ensuring that the overall quality and efficiency of translations meet the highest standards. They work closely with AI systems, not just to correct errors but to refine and enhance the AI’s capabilities over time. 

This partnership between human expertise and AI is at the core of our HumanAI product, which ensures that translations are not only accurate but also culturally and contextually appropriate.

HumanAI, our cutting-edge product, seamlessly integrates human expertise with advanced AI algorithms to deliver unparalleled translation quality. By leveraging the strengths of both human translators and AI, HumanAI ensures that every translation is not only accurate but also culturally and contextually appropriate. 

The AI component handles the initial translation, utilising vast language models trained on diverse datasets. Human translators then meticulously review and refine the output, correcting any nuances that the AI might miss. This collaboration drastically reduces the time and effort required for translations, while maintaining the highest standards of quality.