Kind of.
At this point, there’s not much more to say about ChatGPT and the recent explosion of natural language processing – there are many, many commentaries and opinions on whether this will be the downfall of civilization as we know it or the best thing that ever happened to humankind. But, there is a lot to say about the potential of artificial intelligence and human ingenuity partnered together.
Despite its rapid growth and increasing capabilities, AI still requires human intervention to reach its full potential. Technology alone doesn’t solve problems – but it can help get us closer, faster.
This is where the concept of “Human-in-the-loop” comes in.
We’re in the loop
Human-in-the-loop refers to the integration of human decision-making into the AI process. In this approach, AI systems are designed to assist humans in their tasks, rather than replace them. It is a combination of both human and machine intelligence, where the machine takes care of the tedious and repetitive tasks, and the human provides the necessary judgement and decision-making. For instance, we used ChatGPT to generate the text about human-in-the-loop in this article, but it was heavily edited for style, accuracy, and to avoid sounding like, well, a robot.
You’ve already been using AI to help you write through predictive text in Google Docs and Word and editors like Grammarly – a miniature version of human-in-the-loop every time you bypass the auto-correct option. We’re now seeing that play out across dozens of industries and subfields, so that where AI goes, the human intelligence piece is paving the way before, during, and after the process.
Human-in-the-loop, in the wild
Take for example the medical field. Human-in-the-loop enables AI systems to make more accurate and trustworthy decisions – ensuring that medical records are indexed correctly and with the highest degree of accuracy, or that a diagnosis provided by an AI system is reviewed by a medical doctor.
Another benefit of human-in-the-loop is that it ensures that AI systems are aligned with human values and ethics. AI systems can be programmed to carry out tasks objectively, but it is still necessary for humans to oversee the AI’s actions and ensure that it is not acting in an unethical or harmful manner. This can also help prevent bias in AI systems, as humans can detect and correct any biases that may have been introduced during the AI’s training process.
AI isn’t magic
With the rise of AI and new developments in Intelligent Document Processing, natural language processing, etc, it’s easy to look at AI as a magic solution to your business problems. It’s not. AI requires human oversight, which in turn requires careful consideration and planning. There must be clear guidelines and protocols for how human intervention is to be carried out in the AI process, and it is crucial that human teams are trained and equipped to understand and interpret the AI’s outputs.
This article was going to be primarily written by ChatGPT – but that’s not exactly how it panned out. Truthfully, I (a human) wrote most of this and ChatGPT helped with technical language, which is still pretty helpful at the end of the day.
Learn more about AI and how we use it in intelligent document processing, or reach out if you’d like to speak with a human.