Why crowdsourcing is the solution to data annotation
                     Why crowdsourcing is the solution to 
 data annotation
It is easy to get confused when there are so many different areas of AI, 
but simply  put, AI is the ability for a computer to do work normally done 
by humans by imitating  human intelligence.
Artificial intelligence
Artificial intelligence is a versatile technology that sees use in a diverse 
range of  industries. It would seem there’s nothing AI isn't capable of as 
we continue to push  the boundaries of automation. Many processes and 
jobs can now be completed with  much greater efficiency thanks to the 
aid of AI models. However, despite rapid  advancement in AI over the last 
few years, most Machine Learning models still rely  on education from 
humans in the form of data annotation.
The process of annotating data to prepare high-quality training data is a 
major hurdle  in any AI development project. For small teams of data 
scientists, having to manually  label enough data points to create good 
training data consumes a lot of valuable  time. This time is better used 
making insights and working on other areas of  development, so many 
companies choose to outsource their annotation work to  specialised data 
annotation companies.
What is crowdsourcing?
The act of crowdsourcing involves obtaining the help of a large and usually 
open  group of people to complete a certain task. In the scope of data 
annotation this can  be especially effective at getting large amounts of 
data labelled. To give an example,  for a data set containing 1,000 data 
points, a group of 200 people would only need to  label 5 points each 
compared to a team of 20 people labelling 50 points each.
Dividing this work among a larger group of people also means it is less 
taxing on
each individual, which increases the likelihood of consistently accurate 
labelling for  each data point. Crowdsourcing allows huge numbers of data 
points to be labelled in  a fraction of the time it would take a traditional 
annotation team.
How does Tictag use the power of crowdsourcing?
At Tictag we have taken a unique approach to tapping on the 
power of  crowdsourcing. One of the main goals we have is to 
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With this, the process of data annotation is transformed from a 
traditionally slow and  tiring process for a small group of people to 
something that can be done quickly and  easily by anyone with a 
smartphone. Being able to perform these tasks at any time  and place in 
the world is also a great advantage of being a mobile application.
Building a community of skilled and enthusiastic data labellers or 
“Taggers” is not an  easy pursuit. A large incentive for people to become a 
part of the Tagger community  is the coin-based rewards system we use. 
As Taggers complete different types of  annotation tasks they earn coins 
based on the accuracy and number of data points  they label. These coins 
are exchanged for a range of prizes like Grab/Amazon  vouchers, 
household appliances, electronics and more.
Additionally, special big ticket items also come and go as part of the 
selection of  redeemable rewards. Badges can also be earned by 
tagging frequently and  consistently to show a Tagger’s skill and 
dedication to tagging, and to reward and  recognise them for familiarity 
with a particular task. A large crowd also means that
you might find expertise in specific niche areas that might not otherwise 
be easy to  come by!
A main concern for crowdsourcing data annotation work is the accuracy of 
the labels.  Fortunately, our annotation platform comes in the form of an 
easy-to-use phone  based app with an intuitive UI which gives users a high 
level of control to tag  accurately. Tasks are broken up when distributed to 
the crowd, and are brought  together again to ensure the highest level of 
accuracy possible. Several quality  control measures are also integrated 
into our annotation process that ensures the  production of high-quality 
labelled data.
Sourced from : 
https://www.tictag.io/post/crowdsourcing-solution-data-annotation