Spin the Wheel

AI Beer Judging Controversy

The intersection of artificial intelligence and craft beer judging has sparked one of the most heated controversies in the brewing industry's recent history. In October 2025, the Canadian Brewing Awards, one of North America's most prestigious beer competitions, introduced an AI-powered judging system called "Best Beer" in the middle of an active competition, catching judges completely off guard and igniting a firestorm of criticism that exposed deep tensions between technological innovation and traditional craft expertise. The controversy began when competition organizers, without prior warning or consultation, instructed judges to use the new Best Beer AI system to record their tasting notes and evaluations. Judges, who had been meticulously documenting their assessments using traditional methods, suddenly found their expertise being channeled through an AI interface that would convert their notes into standardized beer descriptions. The abrupt shift from human-centered evaluation to AI-assisted judging created immediate friction, as many judges felt their nuanced, contextual knowledge was being reduced to algorithmic inputs. What made the situation particularly contentious was the revelation that the AI model had been trained using data from previous competitions without explicit consent from the judges whose evaluations had been used. This raised serious questions about data ownership, intellectual property, and the ethical use of human expertise to train systems that might eventually replace those same experts. Many judges felt that their years of training, experience, and professional judgment were being co-opted to create a system that could potentially devalue their contributions to the craft beer community. The brewing community's response was swift and passionate. One judge wrote an open letter criticizing the use of AI in beer tasting and judging, arguing that the subjective, contextual, and deeply human aspects of beer evaluation cannot be reduced to algorithmic processes. The letter highlighted how beer judging involves not just taste perception, but also understanding of brewing techniques, cultural context, style guidelines, and the ability to provide constructive feedback that helps brewers improve their craft. These elements, the judge argued, require human judgment that AI cannot replicate. Best Beer's response to the criticism only escalated the situation. According to multiple sources, the company threatened legal action against the judge who wrote the open letter, a move that many in the brewing community saw as an attempt to silence legitimate criticism. This heavy-handed approach further alienated the very experts whose cooperation would be essential for any successful AI integration in beer judging. The controversy also revealed practical concerns about the AI system's implementation. Brewers were required to submit additional beer samples to facilitate the AI's data collection, creating logistical challenges and increasing costs. The system's ability to accurately capture the nuanced language of beer evaluation was questioned, with many judges reporting that AI-generated descriptions failed to capture the subtleties and context of their original notes. This episode represents a microcosm of a much larger pattern playing out across creative and evaluative professions. Just as AI has disrupted illustration, voice acting, music production, and other fields, it is now making inroads into specialized domains like craft beer judging. The tension between efficiency and scalability on one hand, and human expertise and artistry on the other, is becoming increasingly apparent as AI tools become more sophisticated. The craft beer industry has long prided itself on its artisanal nature, its emphasis on human skill and creativity, and its resistance to mass-market homogenization. The introduction of AI into this space challenges these core values, raising fundamental questions about what makes craft beer "craft" and whether technological efficiency should take precedence over traditional methods of evaluation and appreciation. Proponents of AI in beer judging argue that it could democratize access to expert-level evaluation, help standardize judging criteria, and make competitions more accessible to smaller breweries. They suggest that AI could assist judges rather than replace them, providing tools for consistency and efficiency while preserving human judgment for the final decisions. However, critics counter that the very subjectivity and human perspective that make craft beer evaluation valuable would be lost in such a system. The Best Beer controversy also highlights broader questions about consent, transparency, and the relationship between technology companies and the communities they seek to serve. The lack of prior consultation, the use of data without explicit permission, and the threat of legal action against critics all point to a pattern of top-down technological imposition rather than collaborative innovation. As the craft beer industry grapples with this controversy, it faces a critical moment of decision. Will it embrace AI tools as enhancements to human expertise, or will it resist technological change in favor of preserving traditional methods? The answer will likely shape not just how beer competitions are conducted, but how the entire craft beer community defines itself in an increasingly automated world. The episode serves as a cautionary tale about the importance of clear communication, informed consent, and respect for expertise when introducing AI into specialized domains. It demonstrates that technological capability alone is insufficient—successful AI integration requires understanding the values, practices, and concerns of the communities being affected. For the craft beer industry, this means recognizing that beer judging is not just a technical process, but a cultural practice that involves human connection, shared knowledge, and the celebration of artisanal skill. Looking forward, the resolution of this controversy will likely influence how other specialized industries approach AI integration. The craft beer community's response—whether it leads to collaborative solutions, complete rejection, or some form of hybrid approach—will provide valuable lessons for other fields facing similar challenges. What is clear is that the relationship between AI and human expertise is far from settled, and the craft beer judging controversy is just one chapter in an ongoing story about technology's role in preserving or transforming traditional practices.