## Grouped Bar Charts: Debater Agent Success Rates ### Overview The image displays two side-by-side grouped bar charts comparing the performance of two AI models, GPT-3.5 and GPT-4, acting as "Debater Agents." The charts measure the "Persuader's success rate" against these agents under three different helper conditions over three repetitions. The left chart is titled "GPT-3.5 Debater Agent" and the right chart is titled "GPT-4 Debater Agent." ### Components/Axes * **Chart Titles:** "GPT-3.5 Debater Agent" (left), "GPT-4 Debater Agent" (right). * **Y-Axis (Both Charts):** Labeled "Occurrences." The scale runs from 0 to 200, with major tick marks at 0, 25, 50, 75, 100, 125, 150, 175, 200. Corresponding percentages are shown in parentheses: (0%), (12%), (25%), (38%), (50%), (62%), (75%), (88%), (100%). * **X-Axis (Both Charts):** Labeled "Persuader's success rate in each scenario over three repetitions against GPT-3.5 debate" (left) and "...against GPT-4 debate" (right). The categories are: * Zero Success * One Success * Two Success * Three Success * **Legend (Top-Right of each chart):** * **Green Bar:** "No Helper" * **Red Bar:** "Fallacious Helper" * **Blue Bar:** "Logical Helper" ### Detailed Analysis **GPT-3.5 Debater Agent (Left Chart):** * **Trend Verification:** The overall trend shows a decline in occurrences as the number of successes increases. The "No Helper" (green) and "Logical Helper" (blue) conditions show a steady downward slope. The "Fallacious Helper" (red) condition peaks at "Zero Success" and then declines, but remains the highest bar in the "Two Success" and "Three Success" categories. * **Data Points (Approximate Occurrences & Labeled Percentages):** * **Zero Success:** * No Helper (Green): ~95 occurrences (48%) * Fallacious Helper (Red): ~85 occurrences (42%) * Logical Helper (Blue): ~100 occurrences (50%) * **One Success:** * No Helper (Green): ~55 occurrences (28%) * Fallacious Helper (Red): ~45 occurrences (22%) * Logical Helper (Blue): ~48 occurrences (24%) * **Two Success:** * No Helper (Green): ~30 occurrences (15%) * Fallacious Helper (Red): ~38 occurrences (19%) * Logical Helper (Blue): ~30 occurrences (15%) * **Three Success:** * No Helper (Green): ~20 occurrences (10%) * Fallacious Helper (Red): ~34 occurrences (17%) * Logical Helper (Blue): ~24 occurrences (12%) **GPT-4 Debater Agent (Right Chart):** * **Trend Verification:** The trend is more complex. For "No Helper" and "Logical Helper," occurrences are highest at "Zero Success" and drop sharply. For the "Fallacious Helper," occurrences are lowest at "Zero Success" and rise dramatically to peak at "Three Success." * **Data Points (Approximate Occurrences & Labeled Percentages):** * **Zero Success:** * No Helper (Green): ~115 occurrences (58%) * Fallacious Helper (Red): ~45 occurrences (22%) * Logical Helper (Blue): ~110 occurrences (55%) * **One Success:** * No Helper (Green): ~10 occurrences (5%) * Fallacious Helper (Red): ~26 occurrences (13%) * Logical Helper (Blue): ~14 occurrences (7%) * **Two Success:** * No Helper (Green): ~8 occurrences (4%) * Fallacious Helper (Red): ~18 occurrences (9%) * Logical Helper (Blue): ~8 occurrences (4%) * **Three Success:** * No Helper (Green): ~66 occurrences (33%) * Fallacious Helper (Red): ~112 occurrences (56%) * Logical Helper (Blue): ~68 occurrences (34%) ### Key Observations 1. **Inverse Performance Pattern:** The two models exhibit nearly opposite patterns. GPT-3.5 is most frequently unsuccessful (Zero Success) with all helpers, while GPT-4 is most frequently unsuccessful only when it has No Helper or a Logical Helper. 2. **Fallacious Helper Impact:** The "Fallacious Helper" has a dramatically different effect on each model. For GPT-3.5, it slightly reduces Zero Success but leads to the highest rates of partial success (Two/Three Success). For GPT-4, it drastically reduces Zero Success and is the dominant condition for achieving Three Success (56%). 3. **Logical Helper Ineffectiveness:** The "Logical Helper" performs very similarly to the "No Helper" condition for both models, suggesting it provided little to no advantage in these debate scenarios. 4. **GPT-4's Polarized Results:** GPT-4's outcomes are more binary: it either fails completely (Zero Success) or succeeds completely (Three Success), especially with helpers. The middle outcomes (One/Two Success) are rare. ### Interpretation The data suggests a fundamental difference in how GPT-3.5 and GPT-4 process and are influenced by helper arguments during a debate task. * **GPT-3.5** appears to be a more consistent but less effective debater. Its performance degrades predictably with the persuader's success, and it shows only modest, incremental changes when provided with helpers. The fallacious helper may introduce noise that occasionally helps it, but not systematically. * **GPT-4** demonstrates higher potential but also higher volatility. Its strong baseline performance (high Zero Success with no helper) is completely disrupted by the introduction of a fallacious helper, which paradoxically leads to its highest success rates. This could indicate that GPT-4 is either more susceptible to being misled by fallacious arguments (leading to unpredictable outcomes) or that it can leverage the structure of any helper argument, even a flawed one, to improve its own reasoning in a way GPT-3.5 cannot. The lack of impact from the logical helper is surprising and may indicate the helper's logic was not aligned with the debate's persuasive requirements or that GPT-4's own logic was already sufficient. **In essence, the charts reveal that more advanced models (GPT-4) may interact with external information (helpers) in more complex and non-linear ways, leading to greater performance swings, while less advanced models (GPT-3.5) show more predictable, but lower-ceiling, behavior.** The "Fallacious Helper" acts as a disruptive catalyst for GPT-4, while being a minor perturbation for GPT-3.5.