One of the greatest challenges of crowdsourcing is the high risk of fraud. In crowdsourcing, many people are exposed to sensitive information and since not all of them are manageable, some engage in fraud. The fraudsters ask for personal information such as zip code and they use it to fraud or even scam the person online (Lease 44).
The other challenge with crowdsourcing as explained by Lease (51) is abstraction. The people in the crowdsourcing fail to provide specific information but rather engage in generalizations and giving of abstracts. This leaves behind a lot of unknown information and it violates the ethics as well.
Computers are built with very high speed for processing data which cannot be compared with that of human beings. However, when it comes to processing of some types of data, human beings are better off as they can be able to handle large amounts of complicated data (Lease and Alonso 312). Computers are machines and cannot understand emotions hence are unable to effectively handle situations involving emotions or even motivation. These are left for the humans to handle. The data output depends on the input and therefore it comes to verification of assurance of quality of any data, humans are in a better position to handle what the computer has produced (Lease and Alonso 310).
According to Lease (16), crowds tend to be very noisy which hinders the wisdom of the crowds to make decisions or perform very important tasks as well as handling of overly sensitive information. The other issue with humans is the distraction brought about by social interaction and social organizations they carry out online. These are distractions which only act to pale facilitation of technological output and application. The social interaction may also lead to more damage than good such as was the case with facilitation of the Arab Springs using social media sites (Lotan, et al 1377). If the work is fully handled by computers, then such occurrences would not be