Can artificial intelligence really support human creativity? A US study says so

In some areas, progress is slowing. For example, it takes 18 times more researchers to double microchip density today than it did in the early 1970s. In fact, a Stanford University study found that while research effort has increased by a factor of 23, research productivity has decreased by a factor of 41 over the same period.

The prevailing opinion is that AI cannot generate fundamentally new ideas on its own, but that it can assist humans in doing so by catalyzing human creativity. However, what is easily overlooked is that AI can also inhibit human creativity, because the smarter AI gets, the more helpful and distracting it becomes. Therefore, we should know how AI can support human creativity and where it does more harm than good. A current study by the Gottlieb Duttweiler Institute investigated these questions.

3 Ways AI Can Catalyze Human Creativity

1. Identify patterns

AI can spot patterns in large data sets and inspire people to come up with new hypotheses they may have missed. For example, researchers have used machine learning to predict which chemical combinations could help make car batteries, and they’ve found four promising options to test in a real-world environment.

It can also present more digestible content than simple dates and numbers. Self-learning algorithms can write complete texts, speak to us with computer-generated voices or even create emotional pieces of music.

2. Provide the big picture

AI can cut through and automatically analyze large amounts of information from different sources by filtering, grouping and prioritizing. It can also create knowledge graphs and help people see connections between seemingly unrelated data. These could be used in drug research to identify interactions between different substances, develop new therapies and mitigate side effects.

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In the future, ChatGPT and similar tools will explain complex relationships without us having to read numerous websites and articles.

3. Conduct experiments

AI can even guide experiments, predicting the results of experiments using existing data and eliminating those deemed unpromising. For example, Rolls-Royce used a neural network to develop a new superalloy with an optimal combination of cost, density, strength, oxidation resistance and fatigue life.

Generative AI – algorithms that create entirely new content – ​​has received a lot of attention from AI image or text generators like OpenAI’s DALL-E 2 and ChatGPT. Autodesk is now developing generative design tools that create design concepts of objects entirely on their own, such as an interplanetary lander that is lighter than its human-designed counterparts. Such tools have led to the prediction that “people will go from creators to curators”.

The limits of AI in supporting human creativity

AI cannot replicate such real-world experiences or face-to-face interactions. Exploration without a specific outcome in mind, adding new areas of knowledge along the way, and improvisation are also challenges for AI.

A tool that optimizes flight routes with regard to CO2 emissions, for example, would not simply suggest switching to rail transport or video conference meetings. Ultimately, the AI ​​does what it is told, bound by the data we feed it and the goals we define.

“Looking ahead, the most successful ideas will likely not only come from bright minds, but from those who are best at driving intelligent machines mindfully while staying firmly in the driver’s seat.

— Jan Bieser, Senior Researcher and Speaker, Gottlieb Duttweiler Institute

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How AI can hinder human creativity

Given these limitations, freeing up time is arguably one of AI’s greatest contributions to human creativity. In fact, AI is expected to take on mundane, repetitive tasks, allowing us to become more human and creative. For example, a UK study estimated that AI assistants will give UK workers back two weeks a year by 2030.

However, studies on AI and time use often only focus on their time-saving potential and neglect other factors. If we intend to use AI frequently, it will inevitably reduce the time we spend without using AI. This time is valuable for creativity, as AI cannot support all activities that lead to new ideas, such as B. interactively exchanging and discussing ideas with others or relaxing and reflecting.

We used to divide our time mainly between two activities: time with others and time for ourselves. Today we spend more time alone, and there is also a third condition: the time we spend with digital technology. It is likely that the share of this third country will increase due to AI.

With AI, more everyday activities can be supported by digital technologies – smart speakers can talk to us while we cook or drive. Intelligent algorithms will also get better and better at predicting behavior, communicating with us in natural language, and attracting attention.

AI is already being used to analyze eye-tracking data on websites to optimize user attention or tailor product or film recommendations to users’ personal interests. Unfortunately, the more AI successfully distracts us, the more it prevents us from more creative activities.

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Resist the distraction of the AI

The use of AI will undoubtedly help generate new ideas and organizations that neglect AI risk losing competitiveness in the long run. The goal should be to use AI where it can support human creativity and not where it does more harm than good.

Resisting the distraction of AI is equally important in our personal lives and at work—so parents can consider the impact it will have on their children’s on/off screen balance, and managers can see where to boost creativity and where to hire employees from distracts from more creative activities like switching off -screen reflection and brainstorming.

When we become complacent, decisions about how we spend our time are made for us. Looking ahead, the most successful ideas will likely not only come from bright minds, but from those who are best at driving intelligent machines mindfully while staying firmly in the driver’s seat.

Jan Bieser, Senior Researcher, Gottlieb Duttweiler Institute

This article was originally published in the World Economic Forum.

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