Introduction: Why Innovation Needs Methodology, Not Just Intelligence

Researchers across disciplines are closely watching the rapid evolution of AI for Science (AI4S) and asking a fundamental question:

What kind of impact can AI realistically have on scientific innovation?

AI systems today can act as tools, assistants, or advisors. They can summarize papers, generate hypotheses, and even propose experimental ideas. However, most AI-driven research tools focus on information processing rather than innovation itself.

Innovation, especially breakthrough innovation, is not primarily an information problem. It is a methodological problem.

Without a guiding methodology, exploration becomes incremental, fragmented, and biased by existing paradigms. Even powerful AI models, when used without structure, tend to reproduce known patterns rather than generate fundamentally new ones.

This is where Question Innovation (QI) positions itself differently.

---

What Is Question Innovation (QI)?

Question Innovation (QI) is an AI-powered innovation system grounded in TRIZ, the Theory of Inventive Problem Solving.

Unlike tools that search for answers within a semantic space, QI operates at the methodological level. Its goal is not to propose solutions directly, but to systematically explore innovation directions based on structured reasoning principles.

QI is designed to:

• Abstract problems beyond domain-specific terminology
• Identify underlying contradictions or functional tensions
• Apply proven innovation principles in a disciplined way
• Return structured, interpretable innovation paths

Because it works at the level of methods rather than content, QI demonstrates a degree of cross-domain universality. The same reasoning framework can be applied to biology, materials science, engineering systems, computational methods, and beyond.

---

Why TRIZ Matters for Scientific Innovation

TRIZ was developed through large-scale analysis of patents and technological evolution. One of its central insights is that most meaningful innovations arise from resolving contradictions, not from incremental optimization.

TRIZ classifies innovation into five levels:

• Level 1: Minor improvements within existing systems
• Level 2–3: Resolution of technical or physical contradictions
• Level 4–5: Radical system-level transformation

Most academic and industrial innovation remains at Level 1/2. QI is designed to help researchers move toward Level 2/3 and above by explicitly working with contradictions and system dynamics.

When a problem lacks an obvious contradiction, QI switches to "realizing functions" and employs alternative TRIZ tools, including:

• Functional analysis
• Scientific effects
• Substance–field (Su-Field) modeling
• Ideality and evolution trends

This ensures that QI remains applicable even when classical contradiction framing is not immediately available.

---

What QI Produces

QI does not output a single “best idea.”

Instead, it generates a structured innovation exploration report, consisting of:

• Multiple solution paths derived from different methodological lenses
• Explicit reasoning traces linking principles to ideas
• Comparative scoring across novelty, impact, feasibility, and risk
• Tiered prioritization to guide further investigation

These outputs are starting points, not conclusions. Their purpose is to accelerate exploration while preserving intellectual rigor.

---

STEP 1: Provide High-Quality Input

QI requires a specific, actionable problem. The clarity of the input directly affects the usefulness of the output.

You can provide:

1. QM Outputs (Recommended)

Paste a structured research question generated by Question Miner (QM). This is the most reliable input because the problem is already framed with scope, limitation, and opportunity context.

2. Paper Abstracts

You may copy all or part of a paper abstract. Be aware that some abstracts emphasize results rather than problems, which can limit downstream innovation quality.

3. Your Current Research or Engineering Bottleneck

Describe the obstacle concisely. QI will abstract the problem, identify contradictions, and generate innovation paths.

Recommended input length: ~1,000 characters QI encourages concise, well-considered input. Longer text is supported but not required.

---

STEP 2: How QI Performs the Analysis

Once input is submitted, QI runs an asynchronous, multi-stage reasoning pipeline.

A typical run takes approximately 5 minutes or so, depending on complexity.

Each run produces a structured report containing:

• Contradiction or functional analysis (up to two core frames)
• Multi-angle solution generation (≈10 solution paths)
• Opportunity ranking by novelty and impact
• Methodologically grounded reasoning suitable for research planning

The internal reasoning process is engineered for stability and reproducibility, even though intermediate steps are not exposed in real time.

---

STEP 3: Reviewing the Output

The number of solutions may vary depending on the nature of the problem and the applicable TRIZ tools. This variability is expected and scientifically reasonable.

When results are ready, you can:

• Read directly on the results page
• Export via browser “Print to PDF”
• Reopen reports from your History section
• Download the full report in Markdown format (including structured metadata)

If an error occurs (e.g., unclear input or network issues), QI will provide explicit feedback and suggested next steps.

---

STEP 4: Understanding the Innovation Report

Consider the following example input (A complete structured question copied from QM):

How can we optimize PRKD1 inhibitors to enhance nuclear–cytoplasmic transport in KIRC? In KIRC specifically, our co-expression and enrichment analyses suggest that reduced PRKD1 activity may coincide with dysregulation of nuclear–cytoplasmic transport.

Structured Question Create systems that achieve both reduced PRKD1 activity and improved nuclear–cytoplasmic transport without compromising either.

Opportunity Level Medium

Innovation Scope Cross-Subfield

Cross-boundary Example Integrating PRKD1 modulation strategies with transport mechanism analysis across different cancer types.

QI generates a report structured as follows:

1. Problem Context

• Domain background
• Precise problem restatement
• Contradiction or functional analysis

This section establishes a shared understanding of the problem before proposing solutions.

2. Tiered Innovation Solutions

Solutions are grouped into Tier 1, Tier 2, and Tier 3, based on a composite scoring model:

Composite Score = 0.4 × Novelty + 0.4 × Impact + 0.2 × Feasibility

Tier 1 solutions are selected not only by score but also by methodological diversity. Tier 2 and Tier 3 solutions are ranked purely by score.

Each solution includes:

• Core inventive principle
• Rationale
• Design heuristic
• Implementation approach

Scores are calibrated to simulate peer-review–like evaluation, but should be treated as guidance rather than judgment.

3. Fusion Innovation Highlights

This section emphasizes combinatorial innovation, helping users understand how different principles interact.

4. Appendix: Full Solution Metadata

A compact overview for rapid scanning and comparison.

---

STEP 5: How to Use QI Outputs in Practice

Each QI report represents a systematic exploration of innovation space for a given problem.

Recommended usage strategies:

• Prioritize Tier 1 solutions for immediate deep investigation
• Rapidly screen Tier 2 and Tier 3 for elimination or inspiration
• Use solutions as starting points for proposal writing, experimental design, or interdisciplinary discussion

Typical Use Cases

• PhD topic exploration
• Early-stage project ideation
• Grant proposal preparation
• R&D bottleneck resolution
• Cross-domain innovation scouting

---

Conclusion

QI is not designed to replace human creativity. It is designed to discipline and amplify it.

By embedding proven innovation methodologies into an AI-driven system, QI helps researchers move beyond trial-and-error and toward systematic, reproducible innovation exploration.

---