Do not edit this directly
Name: nalinc, Type: individual
One of the most challenging problem in today's crowdsourcing marketplace is to let workers reach the right requesters and vice versa. However the prime motive should be not just to connect the right worker-requester pair, but also to enable workers access right set of tasks that fit their skills or domain of expertise. The premise behind this statement is: Sometimes workers want to work on tasks they are good at and not just earn money doing something they dont find interesting
Critical problems in the area
Workers demand the option to choose tasks based on their preferences. As an example, a worker from literature background, would like to work on audio/video transcription or maybe tasks that demand summarizing a material(paper/video) whereas someone with an inclination towards creativity would find 'image-tagging' pretty interesting. A single themed task-feed is pretty dull and less motivating. An ideal crowdsourcing platform tends to address different concerns of workers(make money, minimize rejection, maximize hourly wage, or just to have fun), and a monotonous task-feed is insufficient to cover all such edge-cases. Moreover, workers periodically change their priorities to choose HITs. There are times when they would prefer choosing high paying tasks(or tasks that maximize their hourly wage), but there are times when they prefer choosing tasks that don't need serious attentiveness. Some example of tasks that do/don't require intense focus are as follows:
- audio/video transcription, where one need to listen/watch the whole N minutes(sometimes hours) audio/video.
- Summarizing a video or research paper or article ?
- Tasks that require one to open a link(of-course in a new browser tab), do 'X' task and verify if 'Y' works properly or not.
not-so time-intensive tasks
- Image tagging*
- Sentiment analysis*
- Classification tasks to choose the odd one out, or identify 'X'*
(provided it doesn't require additional work and text is provided inline)
Author: Nalin Chhibber @nalinc