Generative AI + User Experience

Generative AI has come a long way since its inception. The field has experienced tremendous growth and advancements in the past few years, leading to a greatly improved user experience. From the quality of output to the ease of use, here’s a look at how the user experience of generative AI has changed in recent times.

Advancements in Deep Learning Techniques

One of the biggest drivers of improvement in the user experience of generative AI has been the advancements in deep learning techniques. Deep learning algorithms have enabled the creation of models that can produce high-quality output that is almost indistinguishable from human-generated content. This has greatly improved the user experience, as the output is now more coherent, natural, and human-like.

So what? As the quality of Generative AI continues to improve, trust in content will continue to erode. In a study I did with the Alexa team, people often used visual signals to evaluate whether a website was trustworthy based on the interface, content quality and professionalism. As the barriers to those signals decrease, people will have fewer signals to understand whether a source is factual. As a result, the user experience will need to change to help users understand whether content is trustworthy or not.

Increased Computing Power

Another factor that has contributed to the improvement in user experience is the increased computing power available today. This has allowed for the development of larger and more complex models, which can generate more diverse and sophisticated output. With the continued advancement of computing power, we can expect even more improvements in the user experience of generative AI in the future.

So What? As a technology industry, we've seen major changes based on computing power changes moving from hardware servers to cloud, parallel processing, etc. We have seen a similar technological change in AI with memory and the ability of these programs to take in and contextualize human requests based on lengthy conversations rather than just the immediate request. The completely changes the way humans phrase their queries and

Wider Range of Tasks and Industries

Generative AI has also been developed for a wider range of tasks and industries. From creative arts to finance, there are now models that can generate content for a variety of fields. This has increased the accessibility of generative AI, making it more relevant to a wider audience and improving the overall user experience.

So What? Everyone needs to be thinking about how Generative AI will be used in their field, in their products, and in their roles. Play around with some of the Generative AI tools available right now and think about how you would like to apply this to your job or field.

User-Friendly Tools and Interfaces

The creation of user-friendly tools and interfaces has also made a significant impact on the user experience of generative AI. These tools make it easier for non-experts to use and benefit from generative AI, without having to have a deep understanding of the underlying algorithms and techniques. This has opened up the field to a wider audience and improved the overall user experience.

So What? For those of us that can't (or don't want to) code, the ways we interact with generative AI has a profound effect on who can use it and in what capacity. By allowing text and voice as an input to generate content, it should really speed up our ability to let anyone and everyone create. Instead, our focus will be on developing the best prompts, diversifying inputs we can use to generate AI, and editing the output to polish, focus, and strategically use the outputs.

The user experience of generative AI has greatly improved in recent years, due to advancements in deep learning techniques, increased computing power, wider range of tasks and industries, and user-friendly tools and interfaces. As the field continues to evolve, we can expect even more improvements in the user experience in the future and need to align our personal and professional development to how work will change over the next decade.