Welcome to ‘AI for thought’, a series where we explore the intersection of artificial intelligence, technology, and the translation industry in a simple and digestible way.

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Introduction

The ascent of artificial intelligence has sparked both excitement and apprehension en masse: AI-skeptics to AI-fanatics, you name it. The uncertainty that AI advancement brings, just like politics, is creating an increasingly polarising environment and beliefs.  

Amongst them, one emerges as a fundamental, and almost philosophical question: will AI regulations ever catch up with their advancement?   

From history, we can derive that innovation consistently outpaces legislative frameworks – vaccines are invented after the explosion of certain diseases; the draft of aviation safety protocols in the United States came after brutal incidents in the 1950s; environmental protection laws are a result of climate changes becoming visible.  

This presents us with a unique set of challenges and responsibilities. Who, then, is accountable for guiding the responsible deployment of AI, and where does the ultimate responsibility lie? 

The pacing problem: why regulation lags

The inherent nature of technological innovation dictates that development often precedes formal governance.  

AI models, particularly those leveraging deep learning and vast datasets, are iterating at an unprecedented rate. New capabilities emerge, get deployed, and thus begin to reshape industries and societies long before policymakers can fully comprehend their implications, let alone draft effective legislation. This “pacing problem” means that regulations are often reactive, attempting to address issues that have already manifested, rather than proactively shaping the technology’s trajectory.  

This raises critical questions about accountability: if a novel AI system causes unforeseen harm, who bears the burden of responsibility when no clear regulatory framework exists? 

The counterargument: Is the lag acceptable?

Some argue that this lag is not only inevitable but, in some contexts, even beneficial. Historically, technological breakthroughs – from the advent of the internet to the rapid evolution of biotechnology and robotics – have often developed in relatively unregulated spaces, allowing for rapid experimentation and innovation.  

For instance, the National Health Service (NHS) and regulatory bodies like the MHRA often adopt new technologies through a process of trial and error, adapting guidelines as real-world data emerges. This “learn-by-doing” approach, proponents suggest, is crucial for scientific progress. 

Professor Anu Bradford, a leading AI legal scholar at Columbia Law School, argues that the gap between the US and Europe’s AI advancement is not only a result of a lack of regulations in the States, but rather we see a highly punitive nature of European investment policies, which can often act as a barrier to investment and innovation. 

However, even if the ‘lag’ in regulations is beneficial to development, the stakes with AI (and healthcare, to a large extent) are arguably higher. What if the consequences of unchecked AI are irreversible? Consider the potential for pervasive algorithmic bias, the widespread dissemination of deepfake misinformation, or autonomous systems operating without sufficient human oversight.  

In such scenarios, the trial-and-error of scientific process could lead to societal costs that are too high to bear, raising urgent questions about who is held accountable for systemic failures. 

The fear of falling behind

There is a growing, albeit fragmented, global awareness of the need for AI governance. International organisations and major corporations are increasingly engaging in discussions and developing ethical guidelines. Initiatives from bodies like the IEEE (Institute of Electrical and Electronics Engineers) aim to establish standards for ethical AI, and historical precedents like the Montreal Protocol demonstrate that global consensus on complex technological issues is achievable, even if difficult. 

Yet, these efforts are often countered by a pervasive fear of falling behind in the global AI race. Nations, especially those with economic powerhouses, are wary of implementing stringent regulations that could stifle domestic innovation.  

For example, President Trump’s recent executive order has explicitly aimed to “remove barriers to American leadership in artificial intelligence,” signaling a prioritisation of AI development over restrictive oversight.  

Similarly, the UK’s approach has largely involved applying existing statutory frameworks to AI, a reactive rather than proactive stance, driven by a desire to remain competitive in the tech landscape. All signs point to a geopolitical reluctance to impose controls that could cede a perceived advantage. 

A humanist take: responsibility and protection

Just like the course of historical events, the ongoing cycle of AI advancement outpacing regulation nonetheless tells us a fundamental truth: the impact of technology is ultimately shaped by human intent and oversight.  

While the ebb-and-flow of technological progress may be an inherent part of human development, there is always a cost. The challenge lies in recognising that as humans, we bear a profound social and corporate responsibility. 

This responsibility extends beyond compliance and thus demands proactive education and robust protection for those who are most vulnerable to the unintended consequences of technological hierarchies. It means prioritising data privacy, ensuring confidentiality, and embedding human-first principles into the very core of AI development and deployment. 

Good governance, good delivery

The central question of our century is not if AI will transform our world, but how we ensure “good governance” and “good delivery” of its growing power. This necessitates a commitment from organisations to build AI with a conscience.  

At GAI Translate, we built our platform on a humanist value system. We prioritise data privacy and confidentiality, ensuring that our AI is a tool that empowers, rather than exploits. Our human-first approach to AI translation means that while our technology delivers the speed and efficiency you need, but it is always complemented by the irreplaceable nuance and ethical judgment of human linguists. 

We believe that the future of AI is not about machines replacing humans, but about intelligent systems elevating human potential, guided by principles of responsibility and equity. 

Contact us for a demo today to learn how human-first AI translation can transform your global communication.