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Robust AI needs powerful, diverse, and expert human data. Prolific matches you with the perfect expertise, no matter how specialized.
Match the specific knowledge, skill, or linguistic ability you need
We have over 300 filtering options, so you can mix-and-match the criteria you need.
Fluent in English
Nurse
Lawyer
Javascript
Python
Product Designer
Atheist
Fluent in English
Nurse
Lawyer
Javascript
Python
Product Designer
Atheist
Fluent in English
Nurse
Lawyer
Javascript
Python
Product Designer
Atheist
Fluent in English
Nurse
Lawyer
Javascript
Python
Product Designer
Atheist
Fluent in English
Nurse
Lawyer
Javascript
Python
Product Designer
Atheist
Soldier
Republican
Democrat
Mental health
Parent
Student
Chess
Soldier
Republican
Democrat
Mental health
Parent
Student
Chess
Soldier
Republican
Democrat
Mental health
Parent
Student
Chess
Soldier
Republican
Democrat
Mental health
Parent
Student
Chess
Soldier
Republican
Democrat
Mental health
Parent
Student
Chess
Brazilian
Experienced annotator
Used chatbot
Maths
35-44
Brazilian
Experienced annotator
Used chatbot
Maths
35-44
Brazilian
Experienced annotator
Used chatbot
Maths
35-44
Brazilian
Experienced annotator
Used chatbot
Maths
35-44
Brazilian
Experienced annotator
Used chatbot
Maths
35-44
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Researcher, Google
Prolific’s demographic and distribution filters help us meet our participant diversity goals. Prolific makes it cost-effective to find and vet appropriate study participants.
Researcher, Modality AI
Prolific greatly facilitated the recruitment of high-quality research participants, including participants from more unique and difficult-to-recruit populations. The efficiency with which we were to screen and recruit participants greatly reduced recruitment time and allowed us to substantially increase our sample size.
Matthew Tull, Professor, University of Toledo
AI research is typically data hungry, and our development of robust models has relied in part on the large data samples we have been able to collect for our tests. With the ability to pre-screen participants based on demographic characteristics, we have also been able to collect data from population segments that are often underrepresented, and ensure that our technology is developed in an equitable manner.
Novoic
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Janet Pauketat, Research Fellow, Sentience Institute
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