Going into this experiment with Littlefoot, an AI-powered local discovery chatbot, Natasha Bernal in London and Amanda Hoover in New York had high hopes of discovering hidden gems in their home cities. With $100 (£77) each at their disposal, they were eager to see what exciting experiences the AI would recommend.

Unfortunately, the results of the AI-generated itineraries were far from perfect. Littlefoot seemed to have no real grasp of time or space, leading to recommendations that ranged from highly niche suggestions to incredibly vague ones. Inconsistent suggestions such as climbing up a hill in South East London or simply visiting the London Zoo without further instruction left the participants feeling perplexed.

Moreover, the AI chatbot’s map function proved to be unreliable, with two out of four suggested destinations in London being entirely wrong. This revealed significant technical issues with the platform, undermining the credibility of its recommendations.

As Natasha and Amanda explored the itineraries proposed by Littlefoot, they encountered several limitations that dampened their overall experience. From unrealistic activities that were out of budget to restaurants with opening hours that didn’t align with lunchtime, the recommendations fell short of their expectations.

Promising Future

Despite the initial setbacks, the creators of Bigfoot, the startup behind Littlefoot, remain optimistic about the platform’s potential. CEO Alex Ward acknowledges the challenges faced by the company and emphasizes the ongoing efforts to refine the AI agents based on user feedback. With plans to expand resources and enhance the platform’s capabilities, Bigfoot aims to deliver more accurate and tailored itineraries in the future.

The development of Littlefoot has been guided by feedback from alpha users, with 70 to 80 individuals testing the platform’s features and providing valuable insights. This iterative process of refinement is crucial for improving the reliability and relevance of the AI-generated recommendations.

Personal Experience

In a personal account, Natasha describes her experience following an AI-generated itinerary that led her to unfamiliar locations and inaccurate information. Despite her initial excitement, the day filled with unexpected twists and turns left her feeling disillusioned with the AI planning process.

Overall, the experiment with Littlefoot highlighted the current limitations and challenges of using AI to plan the perfect day. While the technology shows promise for future refinement and improvement, there is still a long way to go in achieving truly seamless and personalized experiences through AI-powered recommendations.

AI

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