Newton M.

Key Skills

Software

Other

Top Subject Matter

AI output quality review

Generative art for a coloring book

Environmental research (rainfall analysis)

Top Data Types

Text

Image

Document

Top Task Types

Text Generation

Question Answering

RLHF

Freelancer Overview

AI Output Quality Review & Prompt Evaluation (Independent Projects). Core strengths include ChatGPT, Gemini, and Perplexity. Education includes Bachelor of Science, Jomo Kenyatta University of Agriculture and Technology (2024) and Diploma, Kenya Water Institute. AI-training focus includes data types such as Text, Image, and Document and labeling workflows including Evaluation, Rating, and Text Generation.

Labeling Experience

Rainfall Data Analysis — Academic Research Project

TextQuestion Answering

Conducted a 30-year rainfall analysis by using AI tools to interpret data and generate technical report content. Cross-referenced environmental information and validated findings to reduce errors in AI-surfaced interpretations. The project applied evidence-based methods to identify inconsistencies and gaps in generated analysis. • Used Perplexity AI and ChatGPT to support data interpretation • Structured technical written outputs for the rainfall report • Validated information by cross-referencing environmental datasets • Flagged inconsistencies and reliability issues in AI outputs

2024 - Present

Broader AI Ecosystem Participation (Communities & Learning)

OtherDocumentRLHF

Participated in AI-related communities and activities focused on understanding annotation workflows and RLHF concepts. Used this engagement to strengthen familiarity with responsible AI practices that inform labeling and AI training quality. The involvement supported broader readiness for data-labeling-oriented tasks even when not tied to a formal labeled dataset production role. • Learned annotation workflow concepts through community participation • Gained familiarity with RLHF principles and responsible AI • Built understanding of model improvement via feedback concepts • Strengthened operational awareness for future labeling work

2023 - Present

AI-Assisted Coloring Book Creator (Ongoing)

ImageText Generation

Conceptualised and produced an original coloring book using generative AI by iterating prompts until outputs were consistent and usable. Evaluated generated results to refine wording and achieve visual/text alignment required for practical publication. The work emphasized prompt crafting, output verification, and repeated iteration typical of AI training/annotation support tasks. • Developed prompts using ChatGPT and image generation tools • Iteratively refined prompts to improve consistency • Verified that outputs were usable for the coloring book format • Applied feedback loops based on generated results

2023 - Present

AI Output Quality Review & Prompt Evaluation (Independent Projects)

Text

Reviewed AI-generated outputs for coherence, style consistency, and suitability to ensure quality before reuse, mirroring core annotation QA practices. Applied structured thinking to detect inaccuracies and guide improvements through prompt refinements. This process functioned as continuous quality evaluation for AI-produced text artifacts. • Assessed responses for clarity, consistency, and appropriateness • Identified inaccuracies and gaps needing correction • Iteratively refined prompts based on evaluation results • Built judgment criteria for reliable AI output

2023 - Present

Education

Work History