I want to compare ChatGPT Deep Research mode with its default answers. To do this, I will ask ChatGPT two questions. The question must be complex enough that the Deep Research mode is forced to use its analytical andsource-checking capabilities, while the Default mode is likely to give a good, but less structured, overview.. For this comparison, a question that requires deep analysis, synthesis of information from multiple fields, and forecasting is ideal.
Stick around, because in the end, I’ll show you the pros and cons of each and help you decide which one is right for your next big question.
Default Answer vs Deep Research
1. Interdisciplinary Impact and Forecasting (Tech & Law)
The first question I ask ChatGPT: How will the increasing adoption of AI in creative domains (such as music and art) impact global intellectual property laws by 2030?
Why this question works: High Complexity: The answer requires synthesizing information from technology, international law, the creative economy, and future trend forecasting.
The Default Answer: The Executive Brief
The default answer is exceptionally well-written, structured like a high-level industry briefing.
- Structure: It immediately provides a “Short Answer (big picture)” and follows up with sections that are excellent for forecasting and strategy, such as “Three plausible scenarios” and “Practical implications & actions.” This structure is designed for a user who needs a quick summary of the likely future and what stakeholders should do about it.
- Content Focus: The focus is on macro trends and general market forces (“Mass litigation,” “Tighter controls,” “Mandatory transparency”). It tells you what the legal changes will be (e.g., clearer authorship rules) and why (courts are forcing change).
- Specificity Gap: It remains less granular. While it references administrative and regulatory actions, it avoids naming the specific legal instruments that are driving the change. It provides context but stops short of providing the specific legal data points needed for an authoritative, detailed argument.
The Deep Research Answer: The Academic Report
This answer is structured as a comprehensive academic research paper, built directly around the specialized, multi-faceted clarification we requested. This structure is fundamentally superior for a complex, interdisciplinary topic.
- Structure: The answer is meticulously organized by the analytical dimensions (Copyright Ownership, Regional Variations, Economic perspective, Ethical considerations). This bespoke structure forces a deeper dive into each facet of the problem.
- Specificity Power: This is the defining difference. The answer is dense with verifiable, specific legal mechanisms that the Default mode missed:
- It names specific court cases (e.g., Thaler v. Perlmutter and Li Yunkai v. Liu Yuanchun).
- It cites specific legislation and policy documents with their implementation dates (e.g., the EU AI Act and the UK December 2024 White Paper).
- Synthesis and Breadth: It demonstrates superior interdisciplinary synthesis by dedicating separate, detailed sections to the Economic and Ethical dimensions of the IP debate. It uses specific data (e.g., private funding figures, projected market value losses for creators) to back up its arguments, which goes far beyond the Default mode’s general claims.
Comparison of the answers to the first question
The core difference is that the Default Answer is a master of synthesis and strategic foresight (telling you what will happen and what to do), while the Deep Research Answer is a master of granularity and evidence (telling you what will happen, why, and naming the exact legal documents and cases that prove it).
For an article aiming for academic credibility, the ChatGPT deep research mode is essential because its structure is designed not just to simplify the information, but to support a complex argument with specific, concrete legal and economic data.
2. Deep Analytical and Economic Comparison (Economics & Policy)
The second question I ask ChatGPT: Analyze the primary reasons for the global rise of inflation post-2020, and structurally compare the monetary policy differences between the US Federal Reserve and the European Central Bank.
Why this question works: Need for Data and Citation: Answering this requires analyzing real economic data, synthesizing various causes (supply chain, demand, conflict), and comparing two complex entities (The Fed and the ECB).
The Default Answer: The Executive Summary
The Default answer excels at clarity, ranking, and macro-synthesis for a broad, informed audience.
- Structure and Readability: The answer is structured like a top-tier executive briefing. It begins with a “Short answer (quick summary)” and then uses numbered, ranked headings (“1) Primary reasons…”) for effortless reading. The comparison table is clean, concise, and easy to grasp immediately.
- Content Focus: It accurately identifies the multi-causal nature of inflation and effectively introduces all the major policy concepts: FAIT (Flexible Average Inflation Targeting), TLTROs (Targeted Longer-Term Refinancing Operations), and the Dual Mandate vs. Single Mandate.
- Thematic Strength: Its strong point is its Synthesis (Section 1, “Synthesis”) and its clear explanation of the implications of the structural differences (e.g., “The Fed has an explicit trade-off to consider between jobs and inflation; the ECB’s decision calculus is legally anchored to price stability”).
The Deep Research Answer: The Economic Report
The ChatGPT deep research answer operates at a higher level of technical density and analytical rigor, transforming the answer into a professional-grade economic report.
- Structure and Rigor: The structure is formally academic, built around distinct analytical sections: “Global Inflation Surge (2020–2023): Causes,” “Central Bank Mandates and Targets,” and “Monetary Policy Instruments.” This organization adheres strictly to the request for a structured report. The resulting comparative table is much denser and more detailed than the one provided by the default mode.
- Content Detail and Specificity: This is where the Deep Research mode is clearly superior. It embeds specific data and findings directly into the narrative to build its case:
- It mentions that a Fed study found that supply-chain pressure “contributed about 60% of the rise in U.S. inflation.”
- It cites specific numerical policy rates (Fed’s 5.25–5.50% range; ECB’s deposit rate at 4.00%).
- It includes highly specialized policy tools often omitted in summaries, such as the ECB’s Transmission Protection Instrument (TPI) and the exact timing of the ECB ending its negative rate experiment (July 2022).
- Conceptual Integration: The answer seamlessly integrates complex economic concepts and policies into its comparison, transforming the analysis from a list of differences into an explanation of how different statutory mandates shape practical policy implementation.
Comparison of the answers to the second question
The Default Answer is an exceptional teacher and communicator. it structures complex economic theory into a digestible, easy-to-understand briefing. It is ideal for a general business audience.
The Deep Research Answer is an analyst and verifier. it uses specific data points, policy mechanisms, and formal structure to create an authoritative, rigorous, and specialized report. It is essential for an academic, a market analyst, or any author seeking the deepest possible evidence to back up their claims. The choice between the two is not about quality, but about the required level of factual specificity.
