You can’t have missed it: Artificial Intelligence tools like ChatGPT are taking the world by storm. They are making waves in HR and recruitment media with suggestions on how they can streamline workflows. From generating content (such as job vacancies, interview questions, and marketing materials) to AI-aided candidate screening and communication, ideas are plentiful. While some of these will be more fruitful than others, it is certain that recruitment and HR are among the many industries that will be impacted, if not revolutionized, by this new generation of AI technology.
In this blog, we explain what this technology is about and how it relates to previous generations of AI. In subsequent blogs, we will delve deeper into the limitations you should be aware of and evaluate the pros and cons of applications in recruitment technology.
A brief history of AI disruptions
The adoption of AI algorithms in recruitment and HR processes has accelerated over the past few decades. Early rule-based AI systems of the 80s had limitations due to their error-prone and difficult-to-maintain nature, which affected their quality.
Machine learning
The introduction of statistical machine learning technology started to change this, as it could help automate language tasks with substantial accuracy (e.g. data entry from CVs). However, these systems were still limited in their ability to digest context and required more human engineering than desired.
Deep learning
These drawbacks were overcome by a special kind of machine learning technology called deep learning (see this blog and this one), which excels at learning complex patterns without the need to tell it what to learn. It turned out that these capacities could be further amplified by making deep learning models larger and feeding them with more data. Scaling the model and data size eventually gave rise to a family of deep learning models called Large Language Models (LLMs). These include OpenAI’s GPT-4 and its chat-oriented cousin ChatGPT, as well as Google’s LaMDA and other industry competitors.
*Want to know more about Textkernel’s journey through these different stages, and the impact each one of them had on recruitment technology? Come back to our website to see our upcoming blog.
LLMs
LLMs are among the most disruptive developments in language technology. LLMs are AI systems that simulate language and try to predict the most likely word to follow a sequence of previous words. By using increasingly larger neural networks and more language data, LLMs have started to exhibit abilities that surprised even their creators, such as generating high-quality text, summarizing text, and rewriting text in specific styles. The possibilities of LLMs are exciting, but with great power comes responsibility.
Not so fast?
Having pursued AI-driven innovation for over two decades, at Textkernel we are well aware that technological breakthroughs are not merely reasons for excitement. And we’re not the first to note that the use of technologies like ChatGPT come with limitations and risks. There are technical limitations concerning scalability and cost. But more importantly, valid concerns exist about data privacy, transparency and bias. These concerns should be taken very seriously, and upcoming AI legislation, such as the EU AI Act and the NY AEDT Law, will help ensure they are addressed.
Stay tuned for the next part of this blog series to hear more about how LLMs relate to AI legislation, how Textkernel envisions combining compliance with cutting-edge innovation and how we are already putting LLMs in practice in a responsible manner.
