How AI tools are improving human ideation

How AI tools are improving human ideation

By Justin Eames December 2022

Advances in AI have come thick and fast in recent years, but one of the most exciting developments for us at fish in a bottle is in the way it can enable and improve ideation.

To jump right on the obvious point – we’re still a very long way from being able to feed an AI a requirement like “Can you come up with some ideas to improve my website?”* and getting anything useful back.

Creativity is a huge hurdle for AI to overcome.

However, if your requirement of an AI is that it helps to improve the performance of human intelligence, then we’re definitely at that point now.

There’s no doubt that AI now has a role to play in the ideation process. It can provide inspiration through suggestions and examples that relate to the specific threads of an idea. It can also intelligently introduce random elements into the ideation process which can stimulate creativity and generate new and unexpected paths to follow.

Randomisation techniques can help to prevent groupthink, where team members tend to converge on a single idea without fully exploring other options. By introducing randomness into the ideation process we encourage a more diverse and creative approach to problem solving.

Another area where AI is impacting ideation is in processing data.

Data is hugely important in the ideation process and AI can be used to analyse large volumes of user behaviour data, to identify patterns and trends that can inform the development of new ideas.

Let’s step back for a moment and remind ourselves that ‘ideation’ is the process of coming up with ideas. For our teams at fish in a bottle that process involves collaborating with our clients and partners around digital products and services – websites, apps, platforms, games and interactives.

We don’t leave ideas generation to chance, we use a tried and tested methodology called the Ideation Framework that vastly increases our chances of hitting upon great ideas in an efficient way.

We’ve made the The Ideation Framework available to everyone and you can download our Ideation Playbook and implement it yourself.

If you do that you’ll see that we define roles within ideation sessions. One of those is the role of Researcher. A Researcher is responsible for finding information in real-time during ideation sessions. They usually do this by carrying out web searches on topics being discussed, or answer questions raised.

Researchers work under some time pressure, so the results can, on occasion, be prone to error and misinterpretation. Sometimes the authority of sources of information, found in a hurry, can be poor and that brings into doubt the accuracy of the information the Researcher is feeding to the ideation session.

Even using easily accessible virtual assistants such as Apple’s Siri, Amazon’s Alexa, and Google’s Assistant can help to improve this process.

Now with advances in Natural Language Processing (NLP) – which means the ability of an AI to understand what is being typed into it or spoken to it – tools like ChatGPT allows Researchers to quickly ask complex questions and get useful answers with an impressive level of accuracy and authority.

You can try ChatGPT yourself for free.

Another significant area of advancement in AI is in the field of sentiment analysis which can be used to pre-process complex or large data sets of user opinions prior to ideation sessions.

Sentiment analysis tools use natural language processing (NLP) algorithms to analyse written and spoken phrases and determine whether they have a positive, negative, or neutral sentiment. You’ll struggle to use them without development work, but services that lead this field at the application level include Google Cloud Natural Language, IBM Watson, and AWS Comprehend.

If you have user data available to you – either through analytics, user research or feedback – then the key here is to pre-process it and make it accessible through a searchable interface (which could be as simple as a spreadsheet). The ability to quickly process previously collected user feedback during ideation sessions means we can get some insight into how people feel about specific features or user journeys as they are being considered.

Similarly, opinion mining tools, which use machine learning algorithms to identify and extract opinion-related information from noisey data, moves towards user testing but still has use in ideation.

You can get an idea of how powerful sentiment AI is using the tools provided by SentiStrength and MonkeyLearn.

Overall, human creativity isn’t going to be replaced by AI any time soon, but AI tools can be valuable in enhancing the creativity and efficiency of the ideation process.

*I asked ChatGPT to help me “Come up with some ideas to improve my website” and this is what it said:

ChatGPT can’t help you improve your website yet, but it can be a great research assistant in ideation sessions

Justin Eames
Blog Author:
Justin Eames
Justin is fish in a bottle’s CEO and Head of Innovation. He demystifies digital product development and helps organisations design for success.

Why constraints are good for innovation