The power of the crowd lies in the fact that it is oftentimes so large and diverse. Lurk on crowdsourcing websites for long enough, and you’ll find tons of weird concepts and odd projects with outright questionable objectives. Especially on open platforms like Amazon Mechanical Turk, requesters can find workers to complete just about any task you can imagine.
No matter the source, the possibilities for crowdsourcing services are endless. Here are some of our favorite crowdsourcing requests taken from the Mechanical Turk worker dashboard and reddit’s Turkkit that just might provide inspiration for your next machine learning project.
Who’s a good boy?
If you could ask your pet one question, and get a reply you could understand, what would you ask? A requester on Mechanical Turk looking for content generation services surveyed workers to collect unique questions for their furry companions. The purpose of the task wasn’t specified, but we’re almost as interested in what they intend to do with the data as we are the answers to the questions…
Upload image of your foot
For what we presume is an image recognition engine, this requester used Mechanical Turk to collect photos of feet. But wait, the task wasn’t that simple. The HIT came with detailed instructions and a survey for all participants, as detailed below:
- Socks on or off
- Must be standing on FIRM ground (ex. hardwood, tile)
- Use only one piece of NEW 8.5×11 paper (even if your foot is longer than paper, use one piece then measure the length of your foot)
- Foot must be centered on piece of paper
- Measure your foot to the nearest tenth (ex. 21.0, 27.2, 29.5)
- All four corners of the paper MUST BE VISIBLE
Are these people the same?
Facial recognition software is another unique application for machine learning. Many companies are using MTurk and similar platforms to create useful training data for facial recognition algorithms. Here’s a prime example:
Some tasks require more effort than others, like this one u/fallingleaves805 recalls:
Had a survey once that asked me to record a video of myself pouring ketchup all over my body and laying down on my bathroom floor. Wish I could remember who the requester was.
Another popular project type on crowdsourcing platforms are image recognition tasks. In the following example, workers were asked to describe the article of clothing worn by the model.
At Lionbridge AI, we understand that human created data is essential for developing quality machine learning applications. This particular requester took quality assurance to the next level by asking workers to complete one final step to ensure authentic results:
We hope these crowdsourcing requests have inspired you to get creative with your machine learning projects. At Lionbridge AI, we’ve seen our fair share of interesting requests similar to Mechanical Turk, such as gathering multi-ethnic eye tracking data and creating Arabic sentiment analysis data to develop a machine capable of understanding political discourse. Interested in collecting your own strange data for machine learning? Contact our sales team to see how Lionbridge AI can work for you.