AI-Assisted Collaborative Citation (AACC) System

AI-Assisted Collaborative Citation (AACC) system based on your provided documents :

Summary: AI-Assisted Collaborative Citation (AACC) System

Purpose

The AACC system provides a standardized and transparent method for acknowledging the role of AI models in content creation. It ensures that human authors retain authorship, while crediting AI contributions in areas like generation, validation, and enhancement of content.

Core Principles

1. Author Attribution: The human author is credited as the primary contributor.

2. AI Assistance Acknowledgment: The AI model (e.g., GPT-4) and its developer (e.g., OpenAI) are credited.

3. Transparency in Contribution: Clearly specifies the AIs role e.g., generated summary, validated citations.

4. Versioning & Timestamp: Includes the AI model version and date of interaction to contextualize the AIs knowledge at the time of contribution.

Citation Format

Author(s), Title of the Work, Assisted by AI Model (AI Developer, Model Version), Date of Interaction.

Available from [URL or Publisher].

Additional AI Contributions: [generation, validation, enhancement, etc.].

Example Citations

Academic Research:

Stone, Travis Raymond-Charlie, Recent Advancements in Mathematics,assisted by GPT-4 (OpenAI, Version 4.0), April 27, 2024.

AI Contribution: Enhanced literature review, validated citations. Available from OpenAI API.

Educational Content:

AI Contribution: Generated examples, validated terminology.

Implementation Guidelines

For Authors

Track AI contributions explicitly.

Include version and developer of the AI.

Mention AIs role in the methodology (especially in academic works).

For Publishers

Introduce metadata fields (e.g., AI model, role, version).

Create guidelines for standardizing AACC citations.

For Readers

Understand AACC as a transparency tool for computational support.

Evaluate AI-assisted work with clarity on how AI contributed.

Automation Tool

A sample Python script is included in the documentation to generate AACC citations programmatically. It captures author name, AI model details, date, and contribution type to return a properly formatted citation.

Conclusion

The AACC system reframes AI from a passive tool to an active collaborator, giving proper credit while maintaining academic and creative integrity. It’s a forward-thinking model to navigate the evolving relationship between humans and intelligent systems in authorship.

Program logic:

This code defines a Python class, `AACC_Citation`, designed to generate citations for research papers that utilize artificial intelligence (AI) models. The class takes in parameters such as author names, paper title, AI model details, and file paths, and produces a formatted citation string. The citation includes information about the AI model's contribution, version, and date of interaction. The class also provides methods to print the AI contribution description and upload files to a server or storage. The code includes a placeholder for actual file upload logic, allowing users to implement their own upload mechanism. The example usage demonstrates how to create an `AACC_Citation` object and generate a citation for an AI-assisted research paper.

Code for core logic:

 ```python import os class AACC_Citation: def __init__(self, authors, title, ai_model, ai_developer, ai_version, ai_date, ai_contribution, url, files=None): """ Initialize an AACC Citation object. Parameters: - authors (list): List of human author names. - title (str): Exact title of the work. - ai_model (str): Name of the AI model used. - ai_developer (str): Developer of the AI model. - ai_version (str): Version of the AI model used. - ai_date (str): Date of AI interaction. - ai_contribution (str): Brief description of the AI's role. - url (str): URL or publisher of the work. - files (list): List of file paths to upload (PDFs and images). """ self.authors = authors self.title = title self.ai_model = ai_model self.ai_developer = ai_developer self.ai_version = ai_version self.ai_date = ai_date self.ai_contribution = ai_contribution self.url = url self.files = files if files else [] def generate_citation(self): """ Generate the AACC citation string. Returns: - str: The formatted AACC citation. """ authors_str = ', '.join(self.authors) ai_info = f"Assisted by {self.ai_model} ({self.ai_developer}, {self.ai_version}), {self.ai_date}" file_references = self._generate_file_references() return f"{authors_str}, \"{self.title},\" {ai_info}. {file_references} Available from [{self.url}]" def _generate_file_references(self): """ Generate references to the uploaded files. Returns: - str: A string containing references to the uploaded files. """ file_references = [] for file in self.files: filename = os.path.basename(file) file_references.append(f"See {filename} for additional information") return ", ".join(file_references) def print_ai_contribution(self): """ Print the AI contribution description. """ print(f"AI Contribution: {self.ai_contribution}") def upload_files(self): """ Upload the files to a server or storage. Note: This method is a placeholder and should be replaced with your actual file upload logic. """ for file in self.files: # Upload file logic goes here print(f"Uploading {file}...") # Example usage if __name__ == "__main__": files_to_upload = ["path/to/image1.jpg", "path/to/paper.pdf", "path/to/image2.png"] citation = AACC_Citation( authors=["John Doe", "Jane Smith"], title="AI-Assisted Research Paper", ai_model="GPT-4", ai_developer="OpenAI", ai_version="v1.0", ai_date="2023-01-01", ai_contribution="Data analysis and writing assistance", url="https://example.com/paper", files=files_to_upload ) print(citation.generate_citation()) citation.print_ai_contribution() citation.upload_files() ```