Correlations between facial features and profession

Correlations between facial features and profession

Summary: This project examines the correlation between facial features and professions using machine learning on a public database. The unique approach aims to predict job suitability based on facial analysis, potentially offering more reliable insights than random selection.

Essentially a Machine Learning project where you’d take data from a huge public database of people with faces and professions. Then study whether there’s any correlation between having certain facial features and the profession you’re in. Maybe use results to create a tool that predicts how good a fit a person will be for a particular profession, given just their face. Perhaps this tool would give better results than random.

Why might there be a correlation in the first place? Certain Facial structure may make you a better fit for one kind of job than another (if you have better-looking jaws you’re more likely to get customer service roles, if you wear glasses you’re more likely in a tech role etc). Also, your job may require certain kinds of reactions more often than others (for example, if you’re in customer service, you probably smile more often than frown which shapes your muscles accordingly). There’s more possible reasoning here: https://chat.openai.com/share/3013a6e3-096f-463f-9413-11ae53d07cdd

It could totally happen that there is no correlation, but this seems promising enough to be worth investigating.

Source of Idea:
Just noticed how sometimes you can make a good guess about what a person does (or is like) based on just their face.
Skills Needed to Execute This Idea:
Machine LearningData AnalysisFacial RecognitionStatistical ModelingData MiningAlgorithm DevelopmentPredictive AnalyticsFeature EngineeringProgrammingDatabase ManagementData VisualizationResearch MethodologyEthical ConsiderationsModel Evaluation
Categories:ResearchComputer VisionComputer ScienceMachine Learning

Hours To Execute (basic)

100 hours to execute minimal version ()

Hours to Execute (full)

500 hours to execute full idea ()

Estd No of Collaborators

1-10 Collaborators ()

Financial Potential

$10M–100M Potential ()

Impact Breadth

Affects 1K-100K people ()

Impact Depth

Minor Impact ()

Impact Positivity

()

Impact Duration

()

Uniqueness

Moderately Unique ()

Implementability

Very Difficult to Implement ()

Plausibility

()

Replicability

Moderately Difficult to Replicate ()

Market Timing

Suboptimal Timing ()

Project Type

Research

Project idea submitted by u/aclearbag.
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