Generative AI needs humans in the loop for widespread adoption

Work in progress

Generative AI by itself has many positives, but it is currently a work in progress and it will need to work with humans for it to transform the world - which it is almost certain to do.

This blending of man and machine is best described as “AI with humans in the loop” and it is already being widely adopted by businesses who want to cut operating costs and improve customer services, but also realise that humans will be crucial if these objectives are to be achieved.

One of the sectors embracing this new normal is in financial journalism. Reuters managing director Sue Brooks announced that AI will be used to cover news stories and will create a “golden age” of news.

Crucially, she also said it was vital there “was always a human in the loop to ensure total accuracy”.

Reuters content now has automated time-coded transcripts and translation of many languages into English, part of the Reuters Connect service. Brooks went on to say that this meld would “free up brain power to be creative and put all these tools in your toolbox to create magical experiences for readers”.

While this sounds a little utopian, it’s something that chimes with my company’s approach to AI and humans in the loop. EasyTranslate is a company that is pivoting from translation to content. AI is making that possible but we still need humans to ensure the best possible service for our customers.

When businesses expand into new markets and target audiences who speak different languages, the need for effective communication is paramount. Traditionally, translation has been the way to bridge linguistic gaps and to do it in the most localised way possible.

For instance, a Danish Christmas celebration may differ significantly from an American one and a direct translation may not adequately convey those differences. As a result, content may come across as inauthentic or culturally insensitive, potentially alienating customers and hindering market penetration.

At EasyTranslate, we have been talking about humans in the loop for a long time. We believe that it is the perfect combination for customers who want to utilise large language models (LLMs) to their optimal advantage.

By bringing in humans to finesse the early work of generative AI, there is likely to be a technological evolution towards proprietary small language models (SLMs), meaning that not only will translation will be perfect from language to language, it will also accurately convey the particular tone and language of each customer.

Heavy lifting

This approach saves clients money because AI, which is cheaper than human capital, does the heavy lifting with the bulk of copy and translations first, before a translator and/or copy editor is brought in for specific parts of the process to improve it. In this process, copy editors also assist to refine machine learning.

Aside from translation and journalism, many other industries are harnessing humans alongside generative AI, not least in healthcare where the collaboration will be of huge benefits to humans.

According to the World Health Organisation, 138 million lives a year are lost to human medical errors, be that diagnostic, surgical or even a confusing doctor’s prescription handwriting. In operational procedures, it is often AI in the loop as surgeons begin the operation and the AI finishes it.

There are many healthcare startups that are bringing human thinking into the development of methodologies through machine learning.

By combining the power of algorithms with human critical learning and knowledge, this collaboration improves AI models, irons out potential biases and creates models that can only improve over time.

Moreover, AI and humans working together are also making fast repairs to recently broken supply chains and using blockchain technology to do so.

Initially, the integration of blockchain and AI improves logistics operations by increased efficiency, transparency and decision-making. AI provides data-driven analysis, blockchain secures and tracks the data, ensuring its accuracy and integrity - and humans finesse this.

As Troy Norcross, blockchain enterprise architect at Serteam says: “Blockchain networks enable supply chain partners to share data securely and selectively while AI helps them adapt to disruptions. However, human input is still needed to verify and approve the best options for supply chain resilience, which are then executed by smart contracts or other automation.”

By leveraging AI, blockchain and humans, improved supply chain operations lead to increased customer satisfaction and business success.

Whether it’s Microsoft offering Co-Pilot AI in its operations, news organisations using AI for financial reports and stories, translation being augmented by AI or health, blockchain and supply chains being transformed, it will continue to be humans (in the loop) who will make the difference.

For a long time to come.

Frederik Pedersen is CEO of EasyTranslate.