Due to advances in computing power, the availability of big data and improvements in machine learning algorithms, artificial intelligence (AI) has made tremendous progress and is changing the world as we know it. While there are many image databases, a significant problem today is the lack of image databases for more specific classes that can be used to solve societal problems. Obtaining these datasets is a cumbersome process. While there are platforms that hire remotely located ‘crowdworkers’ to perform tasks such as image classification, these services have many disadvantages, e.g. the process of setting up such a data collection campaign is not streamlined in a standardized, user-friendly way, the crowdworkers are often being exploited and paid very little, far below minimum wage, and the results are kept private, making it impossible for others to use the data collected using the platform.
For those reasons the Picture Pile Platform (PPP) has been developed. Its aim is to become a commercially self-sustaining platform that uses the crowdsourcing game Picture Pile , which is a cross-platform app for the iPhone , Android and web browsers for efficiently and intuitively classifying images for machine learning. One of the key features of the platform is that it allows to create free and open labelled data which can be used by anybody for AI/ML based image classification thus having a positive socioeconomic impact. Picture Pile was developed within the ERC Consolidator Grant, ‘CrowdLand: Harnessing the power of crowdsourcing to improve land cover and land-use information’. A prototype of the app is available under
http://pppui.cloud.geo-wiki.org(opens in new window)
