The Communications AI Atlas

A freely accessible report to reduce fear and increase efficiency in young communicators.

The Communications AI Atlas was born from the reflective process of researching what the industry can learn about the future and adaptation to emerging media from similar fields. I am a communications professional and scholar, but my academic background is in foreign languages and cultures, making me aware of the existence of established technology that is essential for every professional. I decided to study their survival and adaptation to predict what’s to come for the communications field in the near future.

A survey by CNBC and SurveyMonkey found that almost a quarter of workers fear losing their jobs to AI in the next few years, including 51% of workers in the communications industry. But for translators, this stopped being a theoretical question years ago. ChatGPT is based on a neural network architecture called the transformer that was first used by Google for machine translation in 2017, while the EU already started working with LLM in 2013. Competition from AI has been an everyday reality for human translators for decades. On a very essential level, a translator’s job is to use his/her expertise in language and a topic to communicate ideas accurately, not too far from what communicators try to do (translate ideas or actions into clear messaging). At the higher level, both thrive on similar human skills: cultural awareness, subject expertise, human touch, creativity, adaptability, context awareness, and ethical considerations. Skills that AI can’t really grasp yet.

The question of how one should translate is just as old as our civilization. Roman poet Cicero dictated that a translation ought to be “non verbum de verbo, sed sensum exprimere de sensu” — expressing not word for word, but sense for sense.

“We’ve been ‘in danger’ of being taken over by AI for 10 years now, and it still hasn’t happened,” Eybert-Guillon, translator. “We keep getting told the same thing nowadays”.

The fact is that some translators do work AI or technology can’t do — they not only need strong language knowledge, but they are also experts on a specific topic and a high degree of cultural awareness.

Translation at the European Union (24 official languages) changed dictionaries in 2013 to a new data-driven engine — only to be replaced four years later by an even better translation system that uses an artificial neural network to predict the sequence of words. They also work with sophisticated software to create translation memories and databases where some AI is involved, for decades. These tools are known as Machine Translation.

A bigger budget followed more efficiency but not by better wages or bigger teams to divide the workload.

“I think rates for translators have stayed largely the same for 10 or 12 years,” said Mark Hemming, a translator in the UK. “I think it is harder to get work now. I think it’s harder to get well-paid work as well.”

Many companies are turning to having translators edit automated translations because it is more efficient and quicker, although many claim that sometimes it can be so bad it takes less time to do a human translation from the beginning.

What does this mean?: “The bad news for some translators is that repeatable, easy work is being turned off. The good news is that what remains will be brain-challenging stuff for people who have a knowledge of a language and something else”. (Johnson, The Economist). However, even though automation is good for customers at lower-risk tasks, translators have seemed to keep proving that human expert validation is essential in the important ones.

My explorative observations not only led me to validate the similarities between fields or predict what will probably happen to our industry in the coming years but also to realize the attitude of the translation industry towards emerging media: they are early adopters who learn the tools with an open mind to welcome efficiency and productivity even if you are a student at university. There is a gap in AI knowledge inside upcoming professionals which made me understand that most of the fear young communicators have towards AI and emerging technology comes from the uncertainty of what these tools can or can’t do for their jobs. So the idea for creating the Communications AI Atlas is to provide an introductory report of the most used platforms that are incorporating artificial intelligence to increase efficiency. Until learning the gadgets becomes a learning outcome at university degrees, this content will help you get up to speed and potentially become a practitioner who takes more time for highly creative and important tasks by knowing how to be efficient with these tools — which can at best assist you. The bottom line is simple: AI will force a demand for better practitioners, and those who master AI to foster creativity will dominate the workforce.

What’s in the report?

The report contains:

• A page about the purpose, including the 3 skills that Martin Ford, BBC’s investigative journalist and author of Rule of The Robots, says are safe from AI’s takeover (for now).
• The results of a Prowly report on the state of technology in PR (2023), which contains the current industry’s positive and negative views toward AI
• The classification criteria I used to select the platforms
• Overview of all 21 selected platforms organized by category: Writing, Monitoring, Generative AI
• Potential challenges with AI’s development
• Recommendations for the industry and practitioners

You can download the report here.