Ask the Expert: The AI productivity boom

These tools learn patterns from existing materials and can then produce their own original, creative content in any format, such as text, images and music. This technology has the potential to change the way we work and live to a degree on par with inventions like the printing press and mobile phones.

There’s been a lot of speculation as to when and how AI will impact society. Some pundits forecast massive increases in productivity. Others warn of massive job losses and a rapidly approaching dystopia. In trying to predict how a new tool might be used, it is helpful to understand how it works. Generative AI works by using a special type of statistical algorithm called a neural network that is trained on a large dataset of existing examples.

As a simple illustration, if we want to create a generative AI that can create new pictures of dogs, we might show it thousands of pictures of dogs and let it learn the patterns and features of what makes a dog a dog. Once it has learned enough, it can start generating new pictures of dogs all on its own, without any human input. Much like how dog breeders have combined poodles and Labradors to make Labradoodles, generative AI works by combining what it has learned to create something entirely new.

This leads this technology to be well-suited for content creation and is already impacting creative industries. Already we have artists and musicians who are using generative AI to create unique works of art or music by inputting certain prompts or constraints. This can help them to explore new creative directions and push the boundaries of their craft. These AI generated songs have already had millions of listeners.

Another way generative AI is impacting creative industries is through automation of repetitive tasks. For example, instead of manually creating dozens of unique images for a website or marketing campaign, generative AI can quickly generate a variety of options based on specified requirements. This can save designers and marketing professionals hours of work, allowing them to focus on other important tasks that require more creativity and strategic thought.

We are also seeing generative AI be used to augment and enhance already existing content. Natural language processing models, which are a specific type of AI, can analyze speech and text and then generate summaries that capture the essence of the original content. This can be particularly useful for communication tasks like writing product descriptions, emails or creating social media posts, where the goal is to convey a lot of information in a concise and engaging manner.

Although it has been the bulk of demonstrations we have seen so far, generative AI is not only for creative endeavors. By training AI models on large datasets, businesses can use generative AI to generate insights and predictions that would be difficult or even impossible for humans to identify. For example, generative AI can be used to analyze customer behavior and predict which products or services are likely to be popular in the future, enabling businesses to make more informed decisions about marketing and product development.

While the benefits and applications are undeniable, an important consideration when using generative AI as a productivity tool is the quality of the output. While generative AI can save time and resources, it’s critical to ensure that the output is of a high enough quality and accurate to be useful. This requires careful selection of inputs and ongoing monitoring and adjustment of the model and ultimate selection of the results by humans to ensure that it’s producing a valuable output.

Overall, generative AI is proving to be a powerful productivity tool that can save time, enhance creativity, and provide valuable insights for businesses and individuals alike. While we still don’t know all the ways generative AI can be applied yet, we can be sure it has the potential to revolutionize the way humans work and live.