Email Safety Net for Offensive Typos

Email Safety Net for Offensive Typos

Summary: Unintentional typos in email closings can lead to awkward or damaging communication. A proposed feature for Gmail would scan for common offensive typos in email signatures, helping users review before sending, thus enhancing professionalism and reducing errors.

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.

Source of Idea:
This idea was taken from https://www.ideasgrab.com/ideas-0-1000/ and further developed using an algorithm.
Skills Needed to Execute This Idea:
Software DevelopmentNatural Language ProcessingUser Experience DesignFeedback AnalysisMachine LearningEmail Client IntegrationPrivacy ManagementProduct ManagementQuality AssuranceData AnalysisAlgorithm DevelopmentUser TestingUI DesignTechnical WritingProject Management
Categories:Email CommunicationSoftware DevelopmentUser Experience DesignProductivity ToolsNatural Language ProcessingError Prevention Technology

Hours To Execute (basic)

40 hours to execute minimal version ()

Hours to Execute (full)

500 hours to execute full idea ()

Estd No of Collaborators

1-10 Collaborators ()

Financial Potential

$1M–10M Potential ()

Impact Breadth

Affects 100K-10M people ()

Impact Depth

Moderate Impact ()

Impact Positivity

Probably Helpful ()

Impact Duration

Impacts Lasts 1-3 Years ()

Uniqueness

Moderately Unique ()

Implementability

Moderately Difficult to Implement ()

Plausibility

Reasonably Sound ()

Replicability

Moderately Difficult to Replicate ()

Market Timing

Good Timing ()

Project Type

Digital Product

Project idea submitted by u/idea-curator-bot.
Submit feedback to the team