AI Alt-Text Cleanup for Journal Submissions

Problem Context

Academic editors and journal teams submit research papers with figures that require alt-text for accessibility. Many submission platforms now auto-generate alt-text using AI, but this violates strict editorial policies that ban AI-generated content. Editors must manually remove this text before submission, wasting hours per quarter and risking rejection.

Pain Points

The AI-generated alt-text appears without warning, forcing editors to spend 5-10 hours per submission cycle manually checking and deleting it. Failed workarounds include ignoring the issue (risking rejection) or asking authors to clean up (which often doesn’t happen). The 'T bubble' indicator is easily missed, making the problem harder to catch early.

Impact

Submissions get rejected for policy violations, delaying publication by weeks or months. Editors waste 20+ hours per quarter on manual cleanup, and journals risk reputational damage if AI-generated content slips through. The frustration leads to burnout, especially for editors with tight deadlines.

Urgency

This problem can’t be ignored because journal policies are non-negotiable. A single rejected submission due to AI alt-text can delay a researcher’s career milestones. Editors need a solution now to avoid repeated manual work and last-minute scrambles before deadlines.

Target Audience

Academic journal editors, research team leads, and corporate R&D teams that submit papers to peer-reviewed journals. Also affects graduate students and postdocs who handle submissions for their labs. Any organization that publishes research with figures is at risk.

Solution Approach

A lightweight browser extension that automatically detects and removes AI-generated alt-text from journal submission platforms. It scans figures for alt-text patterns matching known AI generators, flags them for review, and provides one-click cleanup. The tool integrates with common submission platforms (e.g., Elsevier, Springer, PLOS) and works without modifying the user’s workflow.

Key Features

1. One-Click Cleanup: Highlights problematic alt-text and removes it in bulk with a single action.
2. Compliance Reports: Generates audit logs proving all alt-text is human-written, ready for editorial review.
3. Platform Integration: Works seamlessly with major journal submission portals without requiring admin access.

User Experience

Editors install the extension in 60 seconds. When submitting a paper, they open the journal’s portal, and the tool scans all figures automatically. Suspicious alt-text is marked in red; editors review and clean it in seconds. The tool runs in the background for all future submissions, ensuring compliance without manual checks.

Differentiation

Unlike generic AI detectors, this tool is trained specifically on journal rejection patterns. It focuses on alt-text (not full documents) and integrates natively with submission platforms. Free tools don’t handle compliance reporting, and manual methods are error-prone. The extension requires no IT setup, unlike enterprise software.

Scalability

Starts with individual editors ($49/month) and scales to team plans ($99/month for 5+ seats). Adds support for more submission platforms and export formats (e.g., Word, LaTeX) as demand grows. Enterprise version includes API access for institutional use.

Expected Impact

Saves 10+ hours per quarter of manual cleanup, eliminates submission rejections, and reduces editor stress. Journals avoid policy violations and reputational risk. Teams can submit papers faster, accelerating research publication timelines.