Godswill O.

Key Skills

Software

Other

Top Subject Matter

AI-generated text detection (authorship identification) and text evaluation for AI training

AI output evaluation and structured feedback for training pipelines (preference/RLHF-adjacent)

Top Data Types

Text

Top Task Types

Computer Programming/Coding

Transcription

Evaluation/Rating

Data Collection

Prompt + Response Writing (SFT)

Text Summarization

Freelancer Overview

AI Training Contributor — Text Evaluation (Human vs AI detection). Brings 3+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Outlier Platform and Other. Education includes Certificate in Full Stack Web Development, Bafuto Institute of Management and Technology. AI-training focus includes data types such as Text and labeling workflows including Evaluation and Rating.

Labeling Experience

AI & Web3 Platform Tester (AI output review and feedback)

OtherTextPrompt + Response Writing (SFT)

Reviewed AI-generated outputs for accuracy, coherence, tone, and instruction-following to support model evaluation and preference-style data needs. Submitted structured written feedback reports documenting model behavior across AI-facing workflows and onboarding flows. Participated in beta programs to understand task guidelines and quality rubrics used for training-related evaluation work.• Evaluated AI outputs for correctness, coherence, tone, and instruction adherence.• Provided structured feedback reports on model behavior and quality.• Followed rubric-based guidelines during AI tool beta participation.• Supported training pipeline data quality through consistent output review.

2025 - Present

AI Training Contributor — Text Evaluation (Human vs AI detection)

AudioQuestion Answering

Conducted human vs AI text detection by reading and analyzing text samples to identify authorship signals, inconsistencies, and linguistic patterns. Applied detailed evaluation rubrics consistently across large text volumes while staying within platform quality thresholds. Produced reliable ratings to support AI training data quality and evaluation pipeline standards.• Completed human vs AI authorship detection on Outlier tasks.• Used evaluation rubrics to score and assess text quality signals.• Monitored accuracy and reliability across high-volume annotation sessions.• Practiced on subtle style cues (sentence structure, naturalness, and writing patterns).

2025 - Present

Education

Work History