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Authorship and originality in AI-Assisted Creative Work.

Hosted by Silali Banerjee

Sat, Jul 18, 2026

12:00 AM UTC (30 minutes)

Virtual (Zoom)

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User's framework for minimizing drift and genericity in open-ended AI response.
Silali Banerjee
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What you'll learn

Preserve your originality in your work

Use the AIgogy Framework™ to teach the AI to preserve your originality in your work, not just your tone and voice.

Use the AI power wisely

Use AIgogy Framework™ to leverage the AI power and speed with the right combination of prompt and context.

Get the best combination of AI power and human originality.

Beyond teaching the model your tone and let it create. Leverage AI power to increase productivity in original work.

Why this topic matters

AI work overall is moving toward human-AI collaboration, not full automation. For creative work specifically, letting a model generate freely from your tone doesn't produce original work at scale; it produces averaged approximations. Effective collaboration preserves originality while cutting the permission-seeking and editing fatigue that slow creators down, still using AI speed.

You'll learn from

Silali Banerjee

Creator of the Aigogy Framework™ for Effective Human AI Communication

I work in an often-overlooked area of human–AI communication. With experience in both teaching and software engineering, I approach AI interaction as a teaching problem rather than a technical one.

I created the AIgogy Framework™ to replace random prompts with a structured approach for getting reliable results from AI tools. Work is based on ongoing research(https://dx.doi.org/10.2139/ssrn.6502620). I currently serve as an advisor to the Executive Education Program at Rockford University. I teach AI and software engineering courses. As an ex-software engineer and avid content creator, I participate in data labeling for software engineering, human-ai communication and image-generation projects.

Advisor| Creator of AIgogy Framework

Rockford University
Leland
Per Scholas
Handshake
CodePath
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