Coke vs. Pepsi: A Commentary of AI's Expanding Role in Subjective Decision Making
Introduction
In this article, I explore the potential of AI to process competing narratives, organize subjective information, and present balanced analyses of topics where no objectively "correct" answer exists. To do this, I utilized Deep Research by OpenAI to craft arguments for both sides of the classic cola debate: Why Coca-Cola is superior to Pepsi–and conversely–Why Pepsi is superior to Coca-Cola.
The resulting AI-generated reports—which are published separately as companion articles ("Why Coca-Cola Is Superior to Pepsi" and "Why Pepsi Is Superior to Coca-Cola")—demonstrate how advanced AI can now function as a sophisticated decision support tool across domains where human judgment and values remain central to the final determination.
AI as a Tool for Complex Decision Support
The Coke versus Pepsi debate serves as a whimsical, yet important case study to examine AI's expanding capabilities in helping humans navigate domains where subjective judgment, competing ideas, and values-based decisions dominate. While the cola rivalry itself is relatively low-stakes, it exemplifies a fundamental challenge that affects critical decisions across business, policy, healthcare, and beyond: how to systematically evaluate options when there is no objective "best" answer.
Comparison Table of Arguments
Key Capabilities Demonstrated
These tables exemplify several evolving AI capabilities that have transformative potential:
1. Multi-Perspective Information Processing
The ability to ingest lengthy, passionate advocacy documents from opposing viewpoints and distill them without imposing bias that accompanies human review represents a potent advancement. The tables above demonstrate how AI can process competing narratives about the same subject and present them fairly, maintaining the strongest points from each side without defaulting to false equivalence.
2. Systematic Organization of Subjective Information
Converting unstructured, rhetoric-heavy arguments into structured, comparable frameworks demonstrates AI's ability to bring order to chaos. The comparison tables transform competing claims into parallel structures that decision-makers can evaluate side-by-side, creating a "decision space" that humans can navigate more effectively, even when dealing with subjective preferences.
3. Evaluating Evidence Quality Within Domains of Subjectivity
Perhaps most interestingly, the tables show how AI can now distinguish between different types of evidence within subjective domains - differentiating between empirical claims (market share figures, chemical composition), sensory arguments (taste descriptions), psychological factors (brand perception), and cultural impact. This nuanced categorization of evidence types helps decision-makers apply appropriate weight to different factors.
4. Identifying Underlying Values in Competing Arguments
The analysis reveals how AI can now identify the implicit values behind different arguments (tradition vs. innovation, consistency vs. boldness, purity vs. adaptability). This ability to surface underlying values is crucial for decision-makers to align choices with their priorities or organizational values.
Implications for Decision Support Across Domains
These capabilities point toward significant expansions in how AI may be able to assist human decision-makers in important domains:
Business Strategy
Executives facing competing strategic proposals can use similar table-based frameworks to organize conflicting viewpoints about market direction, investment priorities, or organizational changes. Rather than simply averaging opinions or deferring to the most confident voice, this approach creates a structured evaluation framework that preserves nuance while enabling clear comparison.
Policy Development
Policymakers regularly confront passionate advocacy documents from different stakeholders with competing interests. AI that can fairly represent multiple perspectives in structured tables could transform how policies are developed, making the process more transparent and rigorous.
Healthcare Decisions
When treatment pathways have competing risks and benefits, or when quality of life considerations intersect with purely medical outcomes, tabular comparisons could help patients and providers structure these complex trade-offs in ways that respect individual values while ensuring all relevant factors are considered.
Product Development
Teams evaluating different product directions could use similar capabilities to organize competing visions, ensuring that both measurable metrics and more subjective factors like user experience or brand alignment are properly evaluated.
The Expanding Frontier: From Binary Choices to Value Alignment
This exercise also points to a critical frontier in AI development: moving beyond optimization for objective metrics toward alignment with human values and subjective preferences. The cola debate tables demonstrate how AI can now operate in domains where the "right" answer depends on which factors you prioritize.
Future developments might enable even more sophisticated support for value-aligned decision-making:
Dynamic weighting systems that adjust factor importance based on articulated values
Scenario modeling that shows how different decisions might play out given various priority frameworks
Value contradiction detection that identifies when stated preferences conflict with implied values in decisions
Conclusion: AI as a Mirror for Human Judgment
The most profound implication may be that AI is increasingly capable of serving not as a replacement for human judgment but as a mirror that reflects our judgment processes back to us in more structured, comprehensive ways. By organizing the messy, subjective dimensions of important choices into clear tabular formats, AI can help us see our own decision-making more clearly.
The Coke versus Pepsi debate—with its passionate advocates, competing evidence types, and ultimately subjective conclusion—perfectly illustrates how AI can help us navigate increasingly complex decision landscapes where values, preferences, and judgment remain essential. The technology doesn't eliminate the need for human values-based choices; it amplifies our capacity to make those choices with greater awareness and rigor.
This represents a profound shift in how we might use AI—not just to optimize for known objectives, but to help us clarify, structure, and navigate the subjective dimensions of our most important decisions.
