US Culture-Savvy, English-Speaking Music Lovers for AI Chat & Feedback Project

About OpenTrain

OpenTrain is a central place to discover data-labeling and AI-training work. We aggregate projects from many AI companies and labeling platforms so job seekers can find music-, language-, and audio-focused gigs in one place.

Creating an OpenTrain account is free and applying takes just a few minutes. This listing is for a short research project hosted through the OpenTrain network.

About AI Training Work

AI training (also called data labeling or human feedback work) is the human side of building smarter, safer models. People contribute by talking with systems, rating responses, and giving feedback that helps models learn how to understand and recommend music.

Many projects are remote, flexible, and accessible to people without specialized degrees — your experience as a music fan and ability to communicate clearly are what matter here.

The Role

We’re looking for English-fluent music lovers who are familiar with U.S. music culture to participate in a short AI research study. You will join three AI-driven conversations about your music preferences and then provide feedback on the experience.

This is an entry-level contractor position, part-time and remote, with a total time commitment of approximately 60–90 minutes (three conversations, each 20–30 minutes).

• Payment: $6.65 USD per hour (PAY_PER_HOUR).
• Work type: Contractor, Part-time.
• Availability: Less than 20 hours/week; this task requires about 60–90 minutes total.
• Open to applicants worldwide; conversations conducted in English.

What You’ll Do

Participate in three conversational sessions with an AI interviewer about your music tastes and experiences, then provide feedback about the interaction. Sessions should feel natural and engaging — like a chat between music fans.

• Join three audio conversations (each ~20–30 minutes) about favorite artists, genres, albums, songs, concerts, and music discovery habits.
• Discuss your perspective on U.S. music culture, influential artists/genres, and comparisons between musical eras.
• Share personal music memories and storytelling to illustrate your points.
• Provide feedback on the AI conversation experience afterward, including what felt natural or awkward.

Tone & Interview Flow

The interview style is friendly, engaging, and conversational. There are no right or wrong answers — we want honest, thoughtful responses that show how you communicate about music.

You’ll be encouraged to speak in complete sentences, tell stories, and explain your opinions clearly so the project can assess language fluency and cultural knowledge.

• Warm introduction and brief explanation of the casual, research-focused interview.
• Questions about music preferences, recent listening, discovery methods, and live music experiences.
• Discussion prompts about U.S. music trends, iconic artists, and era comparisons.
• A short feedback segment asking how the conversation felt and any improvement suggestions.

Requirements

Please meet all listed requirements. We cannot consider applicants who do not meet these essentials.

• Fluent English speakers with clear verbal communication.
• Familiarity with U.S. music culture and contemporary or historical American artists/genres.
• Enthusiastic about music and comfortable discussing tastes, memories, and opinions for up to 90 minutes total.
• Entry-level: no formal education or prior labeling experience required.
• You will interact via audio; ability to record or join audio conversations is required.

Assessment Criteria

Your responses will be evaluated on communication, cultural knowledge, and engagement. This helps researchers improve AI music-discovery and conversational systems.

• English proficiency: clear, natural responses with coherent sentence structure.
• Knowledge & passion for music: genuine enthusiasm and understanding of music culture.
• Conversational engagement: ability to hold a flowing, story-driven discussion.
• Constructive feedback: clear suggestions about the AI interaction experience.

How It Works & Next Steps

If selected, you’ll schedule three short audio sessions and receive instructions for joining. After each session you’ll provide brief feedback. The project uses audio data and includes evaluation and text-generation style tasks.

This posting is categorized as audio work for evaluation and text-generation labeling; the labeling software used will be marked as 'OTHER.'

• Data type: AUDIO. Label types: EVALUATION_RATING and TEXT_GENERATION.
• Labeling software: OTHER.
• Employment: CONTRACTOR, PART_TIME.
• Apply through your OpenTrain account — the application process takes just a few minutes.