There are a number of misconceptions about Generative AI tools that it is important to address before we start exploring how to use them.
A common misconception is that GenAI and Google work in the same way. Google generates responses by retrieving and collating information from its vast database of indexed web pages. When a query is entered, Google searches to find and present the most relevant information related to the query.
In contrast, Generative AI tools create responses by generating new content based on patterns learned from a large dataset of text. These tools use machine learning models, specifically trained to understand and generate human-like text, to produce original responses that can answer questions, mimic styles of writing, or even create new content.
GenAI tools are often perceived as having an understanding of their outputs. In reality, these tools operate by processing and mimicking patterns found in vast amounts of data, rather than possessing an actual understanding or awareness of the content. They generate responses based on statistical likelihoods, predicting the most probable next word or phrase in a sequence. This process, while sophisticated, is fundamentally different from human understanding. Whilst the output of Generative AI can be impressively coherent and contextually appropriate, it's important to remember that these tools do not 'understand' the text in the human sense.
The belief that AI-generated outputs can be reliably detected is false. While there are tools designed to identify AI-generated text, the evolving capabilities of AI make it increasingly challenging to distinguish its output from human-written content. As a result, the distinction between AI and human writing becomes blurred, especially when AI is used skillfully. Let's stop talking about detection and embrace the robot!