The Super Bowl has long been a showcase for innovative advertising, with companies vying to captivate audiences through memorable and impactful commercials. With GenAI at the core of product innovation for most organizations across all industries, consumers and analysts were expecting to see incredible achievements in ad effectiveness through GenAI. Instead, we recognized that even the largest enterprises are challenged in how to effectively use GenAI in a matter that supports the needs of their consumers.
Cheese Missteps and Poor Predictions
In its Super Bowl ad, Google showcased its Gemini AI by presenting a factoid that claimed Gouda cheese accounts for 50-60% of the world’s cheese consumption. This statistic was later quietly corrected, as it was inaccurate. The error not only undermined the credibility of Gemini but also highlighted a broader issue: the potential pitfalls of deploying AI without thorough validation. ChatGPT also incorrectly predicted the Chiefs as the winners, potentially resulting in many gambling losses for those who placed their bets on OpenSource AI.
These incidents serve as a reminder that while AI can generate content rapidly, it is imperative to ensure the accuracy and relevance of the information presented. This is why Reinforcement Learning from Human Feedback (RLHF) is so important. RLHF is particularly valuable for tasks where defining success is complex or subjective. For instance, concepts like humor or creativity are challenging to quantify mathematically, but through RLHF, AI models can learn to produce outputs that humans find more appropriate or engaging.
RLHF has been instrumental in advancing large language models (LLMs), enhancing their ability to generate text that is not only coherent but also aligned with human expectations. By incorporating human feedback, these models can better understand nuances and deliver responses that are more helpful and accurate.
Mountain Dew, Seal, and the Uncanny Valley
Mountain Dew’s commercial featured a digital rendition of singer Seal performing in a surreal, AI-generated landscape. The ad aimed to blend nostalgia with cutting-edge technology but was met with mixed reactions. Many viewers found the digital representation unsettling, venturing into the “uncanny valley” where human-like figures appear almost, but not quite, real, evoking discomfort. This response underscores the importance of understanding audience perceptions when leveraging GenAI in creative content. Just because one can create something doesn’t necessarily mean they should.
Lessons from Self-Made Billionaires: Empathy and Imagination
The missteps in these advertisements can be better understood through insights from “The Self-Made Billionaire Effect,” which emphasizes the dual power of empathetic insight and imagination. Self-made billionaires often succeed by deeply understanding consumer needs and creatively addressing them. They distinguish between what is possible and what is necessary, ensuring that innovations serve a clear purpose. As highlighted in the book, “good ideas are hard to find, and great ideas even harder. But they are conceivable by Producers who consciously and meticulously cultivate the skills of empathy and creativity in order to see potential where others don’t.”
Balancing Innovation with Consumer Needs
The key takeaway from these Super Bowl ads is the importance of aligning technological innovation with genuine consumer needs and preferences. It’s not enough to deploy GenAI capabilities simply because they are available; organizations must ensure that such technologies enhance the consumer experience rather than detract from it. This involves rigorous testing, audience feedback, and a commitment to authenticity.
This is precisely why TechCollect was created. Unlike the attempts we saw during the Super Bowl, where AI was deployed for spectacle rather than substance, TechCollect leverages GenAI to address a real, pressing issue: accounts receivable (AR) recovery for community association management.
Collections have traditionally been plagued by inefficiencies, excessive attorney involvement, and labor-intensive processes. TechCollect’s AI-driven platform was designed with a clear purpose: to streamline AR recovery, reduce legal costs, and improve financial outcomes for communities. This isn’t AI for AI’s sake; it’s AI solving a critical business problem.
The lesson from this year’s Super Bowl ads is clear: Generative AI should be deployed where it adds real value, not just where it looks impressive. TechCollect embodies this principle by using GenAI to improve efficiency, drive better financial health for HOAs, and reduce reliance on costly legal proceedings. Reach out to us for a free trial for your communities, and learn how to use GenAI for the real world.
