Tag Archives: Algorithms

Microwork platforms: a challenge for artificial intelligence, a challenge for employment?

With our sponsors France Stratégie and MSH Paris-Saclay, we convene an international conference on micro-work in Paris on June 13, 2019, followed by the first INDL (International Network on Digital Labor) workshop on June 14. The event will include a “meet the microworkers” panel on June 13, where workers, platform owners and client companies will take the stage. There will also be presentations of the results of national and international surveys (notably ours, DiPLab) on these emerging forms of work, and discussions with French and international academic and institutional experts.

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After Uber, Deliveroo and other on-demand services, micro-work is a new form of labor mediated by digital platforms. Internet and mobile services recruit crowds to perform small, standardized and repetitive tasks on behalf of corporate clients, in return for fees ranging from few cents to few euros. These tasks generally require low skills: taking a picture in a store, recognizing and classifying images, transcribing bits of text, formatting an electronic file… Despite their apparent simplicity, these micro-tasks performed by millions of people around the world, are crucial to create the databases needed to calibrate and “train” artificial intelligence algorithms.

Internationally, Amazon Mechanical Turk is the most widely known micro-work platform. In France and in French-speaking Africa, other platforms are attracting a growing number of workers to supplement or even substitute for their primary income. How widespread is the phenomenon? How to recognize, organize and regulate this new form of work? How, finally, does it relate to traditional forms of employment?

Presentations and discussions are held in French and English, with simultaneous translation.

The programme is available here.

The data of my friend are my data

The rise of digital data, particularly data from the internet, is to be understood in social relational perspective. Online interactions – from email exchanges to use of VOIP services and participation in social media such as Facebook, Twitter and LinkedIn – make people’s social connections explicit and visible. The “social network”, once a metaphor used only in a small sub-field within sociology, is now familiar to everybody as the archetype of computer-mediated social interaction. Digital devices systematically record network structures, so that social ties become an essential part of every individual profile, and users are more and more aware of them.

One consequence of this is the booming popularity of network analysis concepts, which support the algorithms that handle digital data: for example, centrality measures are at the heart of search engine functionalities, and transitivity measures found “friend-of-a-friend” algorithms in social media. In passing, social network analysis itself which had been originally developed for small-sized, non-digital datasets (like surveys about friendship in schools) has undergone a major upgrade to account for social data from the web.

FOAFMore importantly, the relational nature of digital data and the underlying possibilities to use social network analysis, open up new avenues for data collection. If user B publishes a post on, say, their Facebook wall, comments and “likes” received from their friends A, D and E will be connected to the profile of B, accessible and visible from it; in other words, it is possible to retrieve information on A, D or E through the profile of just B. In general social networks, a friend of my friend is my friend; in digital networks, the data of my friends are my data.

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