It is nothing new. Alexandre Dumas crowd sourced the writing of his greatest work in the 1800s, The Count of Monte Cristo. It’s true! Some say that he had up to eighty ghost writers who worked on his novels. In fact there was a joke circulating at the time that went something along the lines of,
Alexandre Dumas says to his son, “Son, have you read my latest novel?” To which his son replies, “No dad, have you?”
They did not call it crowdsourcing at the time but it amounted to the same thing. The practice of hiring others to write has continued unabated since and probably for a significant time before then too. These stories are most often revealed when ghostwriters fess up in protest when a book they have written makes millions in sales and they do not enjoy any of the royalties. In fact, you may be surprised how much a little digging will show. There are many authors who continue to write long after they are dead, V.C Andrews and Agatha Christie two cases in point. They have not come back from the grave although ghostwriters are the culprits. These are frequently employed by publishers who do not want to see their profits stop with the loss of an author.
Today crowd sourcing words occurs more broadly as technology eases the flow of communication and more opportunities for crowdsourcing arise. Transcription and other professional service jobs are increasingly provided through websites or work hubs that employ pools of people to complete tasks. Unlike the ghost-written books of the past, this is usually a win/win situation. The advantage is of course that the crowd sourced work force can be used on demand and scaled to the needs of the day. The transcribers, or other crowdsourced professional, in turn, enjoys the lifestyle of the freelancer working hours that suit and fit in well with other commitments.
The hybrid version of this, one which may have served Dumas better in his time had it been available, is human-based computation. This is a computer science technique in which a computational process performs its function by outsourcing certain steps to human beings, or the crowd. This approach uses differences in abilities and costs between humans and computers to realise cooperative results. The computer then collects and integrates solutions to achieve the best possible outcomes. This model is increasingly popular because it represents the best utilization of people skills and computer resources combined. This is certainly true in the field of transcription where crowdsourcing words using computers makes great sense.
This post was written by Helga Sonier.