Newsletter September 2019
More and more companies are using crowdsourcing, particularly to perform the micro-tasks essential to the development of big data and artificial intelligence algorithms. How does it work? How can it be used in the most effective and optimized way? We tell you everything.
The term crowdsourcing was first coined in 2006 by Jeff Howe and Mark Robinson, editors of Wired magazine, in an article entitled:" The rise of Crowdsourcing ». The authors explained that technological leaps and the spread of cheap computer tools have greatly reduced the gap between professionals and amateurs, so companies can take advantage of the public's skills. This concept has been embodied in different ways. We think in particular:
More recently, the advent of big data and the rise of artificial intelligence have contributed to making this phenomenon essential to the development of algorithms and the proper use of data. For companies and organizations, this represents both an opportunity and a challenge. Focus on study published by Cloud Factory:" Scaling Quality training Data, Optimize your workforce and avoid the cost of the crowd. »
Talent, data and agility
Companies face two main problems in the processing and exploitation of their data:
Indeed, for the development of artificial intelligence, for the autonomous car for example, it is necessary to learn to "see" by machine, by annotating each image: this is a tree, a fire, a pedestrian... A tedious task, since it is estimated that it takes 800 hours of annotations for one hour of video. Crowdsourcing unlocks this barrier to innovation, while allowing the company's top talent to focus on higher value-added tasks.
3 hidden costs of the crowd
However, crowdsourcing is not a miracle solution in itself. If the concept is not properly applied, it can be costly for the company, in terms of both:
The right way to crowdsourcer
For Cloud Factory, it is essential to have a dedicated team (Managed cloud workers) that follows the companies' project over time and familiarizes itself with its specificities for a more accurate, agile and relevant work. It will also be necessary to design a clear data production line, from raw data to AI deployment, that distributes roles well between technology and people (see graph below) or choose a transparent provider on quality assessment.
Isahit: from crowdsourcing to impact sourcing
Isahit adapts to the needs of each client and the specificities of each project thanks to :
But isahit goes even further, by putting this crowdsourcing in the service of the socio-economic development of disadvantaged populationsand more particularly women from developing countries.
“L’économie de plateforme est le pilier d’une nouvelle révolution industrielle. Pour prospérer, elle s’appuie sur la foule (crowd) qui offre une plus grande flexibilité à des prix imbattables. Un business model qui pose parfois question, notamment au regard de la rémunération et du traitement de ses travailleurs. Chez isahit, nous y répondons par l’impact sourcing : ou comment mettre les atouts incontestables de cette révolution au service de chacun.” Isabelle Mashola, CEO et co-fondatrice d’isahit.
After a successful career as an information systems manager in large companies, Isabelle Mashola decided it was time to put her professional experience to responsible use.
Digital changes the deal in terms of outsourcing and asks many questions. While the criteria for choosing external partners are gaining to take into account CSR and commitment factors, some go further and propose to help businesses work with people from struggling populations.
Isahit has a wide range of solutions and tools that will help you train your algorithms. Click below to learn more!