SAN FRANCISCO – In an unusual twist reflecting the unpredictable influence of artificial intelligence on product development, a music-teaching application has been prompted to build a new feature based directly on a persistent, inaccurate claim generated by OpenAI’s ChatGPT.
Adrian Holovaty, the founder of the acclaimed music-learning platform Soundslice, observed a peculiar pattern among his users: a notable number were attempting to upload screenshots of conversations with ChatGPT. These interactions invariably included what is known as ASCII tablature, a text-based method for notating musical instrument fingering, particularly common for guitar. The reason for this user behavior stemmed from a false assertion by ChatGPT: the AI model incorrectly informed users that Soundslice possessed the capability to convert and play this ASCII text notation.
The AI’s Unexpected Influence
Soundslice has built its reputation on innovative tools for musicians, most notably its signature feature that synchronizes video lessons or performances with interactive sheet music. The platform also incorporates an AI-powered scanner designed to digitize traditional sheet music into interactive formats. However, despite these technological capabilities, support for ASCII tablature was not a part of Soundslice’s existing feature set. [18]
The influx of users arriving at Soundslice with ASCII tabs generated by ChatGPT, expecting the platform to handle them, presented a unique challenge. Users were following the AI’s instructions, only to encounter an error or the absence of the promised functionality on Soundslice. This scenario, driven by ChatGPT’s confident but erroneous output, highlighted a potential problem for Soundslice: the risk of reputational damage. Users, having been told by a widely used AI that a feature exists, might perceive Soundslice as deficient or misleading when the feature is not found.
Confronting the “Hallucination”
The phenomenon of AI models like ChatGPT generating false information, often referred to as “hallucinations,” is a known challenge in the field of artificial intelligence. In this instance, the hallucination was particularly problematic because it directly and persistently misinformed users about the capabilities of a specific third-party product. The repetition of this false claim by ChatGPT across numerous user interactions effectively created a phantom feature in the minds of potential Soundslice users.
Adrian Holovaty was faced with a decision: ignore the issue, attempt to contact OpenAI to correct the AI’s behavior (a often difficult and slow process), or adapt. Recognizing the volume of users arriving with this specific, AI-induced expectation and the potential negative impact on user experience and Soundslice’s reputation, Holovaty chose a pragmatic and, perhaps, unprecedented path. He decided to make the AI’s false claim a reality.
Turning Error into Innovation
Rather than allowing ChatGPT’s persistent hallucination to damage Soundslice’s standing or confuse its user base, Holovaty elected to develop the capability to process and render ASCII tablature directly within the Soundslice application. This strategic decision effectively transforms an AI’s error into a new, tangible feature for the music platform.
The development effort required engineering resources to build the necessary parsing and rendering engines for the text-based notation. While Soundslice already had sophisticated systems for handling complex musical notation and synchronizing it with media, integrating support for the distinct structure and conventions of ASCII tabs was a new undertaking, directly motivated by the external pressure from ChatGPT’s output.
This case illustrates a fascinating dynamic in the age of powerful generative AI: third-party developers may find their product roadmaps unexpectedly influenced, or even dictated, by the confident but sometimes inaccurate assertions of large language models. It raises questions about the responsibility of AI developers for the downstream effects of their models’ outputs and the proactive measures companies might need to take to counteract AI-generated misinformation about their services.
Broader Implications
The incident with Soundslice and ChatGPT is more than just an anecdote; it serves as a compelling example of how AI “hallucinations” can ripple out from the digital realm into real-world user interactions and business decisions. It underscores the fact that as AI becomes more integrated into daily life and becomes a primary source of information for users, the accuracy of its claims, particularly about specific products and services, becomes critically important.
For companies operating in markets where AI models might discuss or describe their offerings, this case highlights the potential necessity of monitoring AI outputs and being prepared to respond – whether by seeking corrections from AI providers, clarifying capabilities to users, or, as Soundslice did, incorporating features that align with AI-generated expectations, even if they were initially based on misinformation.
In effect, ChatGPT’s persistent fabrication acted as an unintentional, albeit flawed, form of market research, revealing an unexpected user need or perceived capability. Soundslice’s response transforms a potential liability into an asset, adding a feature that a segment of users, guided by AI, were actively seeking. [18] This development not only resolves the conflict created by the AI’s error but also broadens Soundslice’s functionality, potentially attracting the very users who were initially misdirected by ChatGPT.
