Email Safety Net for Offensive Typos
Email Safety Net for Offensive Typos
Unintentional typos in email closings—like "Best retards" instead of "Best regards"—can turn professional correspondence into awkward or offensive moments. These mistakes often stem from autocorrect errors or fast typing, but their impact can be significant, damaging relationships or credibility. Given email's role as a primary communication tool, even small errors matter.
The Idea: A Safety Net for Email Closings
One approach to this problem could involve integrating a lightweight feature into Gmail (and later, other clients) that scans closing lines for common offensive typos. For example, it might flag phrases like "Kind retards" or "Warm retards" and prompt users to review them before sending. The feature could work similarly to spell-check, appearing as a pop-up or inline suggestion. Over time, it might learn from user corrections to improve its detection of nuanced mistakes. Since this would target only the closing section—a small, predictable part of emails—it would minimize performance impact while catching high-risk errors.
Why Existing Tools Fall Short
Current solutions like Grammarly or Microsoft Editor focus on general grammar and spelling, not the specific problem of embarrassing closings. Meanwhile, Gmail’s Smart Compose speeds up writing but doesn’t prevent slips. A dedicated feature could fill this gap by combining precision (targeting known bad patterns) and integration (working natively in Gmail without requiring installations).
Execution: Start Small, Refine Fast
- MVP: Begin with exact matching for a short list of offensive closings ("Best retards," etc.).
- Feedback loop: Test with Google Workspace users to refine accuracy and user experience.
- Scaling: Expand to fuzzy matching and contextual checks if feedback supports it.
Privacy could be addressed by keeping scans client-side, and users might have options to disable the feature or whitelist phrases. Over time, the tool could evolve to catch other high-stakes typos, like miswritten names in greetings.
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Digital Product