MBA Students vs. ChatGPT: Guess Who Wins?

Professors Christian Terwiesch and Karl Ulrich from the Wharton School of the University of Pennsylvania recently pitted human creativity against AI, and the results were astonishing (via The Wall Street Journal).

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Traditionally, AI has been viewed as lacking in generating new and innovative ideas, especially in unstructured tasks like brainstorming new business ventures or naming a company. \

However, recent advancements in AI, notably large language models like ChatGPT, are challenging this perception.

Terwiesch and Ulrich, seasoned educators in innovation, entrepreneurship, and product design, frequently task their students with generating multiple ideas for new products or services.

Over the years, they have collected thousands of venture ideas from undergraduate students, M.B.A. candidates, and experienced executives.

In an exciting showdown, they compared human-generated ideas to those produced by ChatGPT4. The challenge involved 200 ideas from students versus 400 ideas from ChatGPT4, with half coming from a standard prompt and half from a prompt with examples of successful ideas.

The result? ChatGPT4 impressively outperformed humans in quantity and quality. It generated 200 ideas in about an hour, a task that would take humans days.

Market testing revealed that ChatGPT4-produced ideas were not only more numerous but also had higher purchase probabilities. Yet, the most remarkable finding was in the realm of exceptional ideas. ChatGPT4, powered by AI, dominated by generating 35 of the top 40 exceptional ideas.

Wharton

This victory of machines in generating outstanding ideas raises significant implications for creativity and innovation.

Firstly, generative AI introduces a valuable source of ideas that innovators should embrace. Whether working on a local business plan or a groundbreaking medical discovery, integrating AI-generated ideas is crucial.

Secondly, the bottleneck in innovation now shifts from generating ideas to evaluating them. Models like ChatGPT can produce a plethora of ideas, necessitating efficient selection mechanisms.

Lastly, rather than a competition between humans and machines, a collaborative approach is advocated. AI should be used as a co-pilot, aiding humans in identifying problems, exploring solutions, and making informed decisions.

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