The HUSH project investigates the human factors in the production of artificial intelligence (AI) solutions. We look at “micro-workers”—online platform workers who execute essential albeit marginalized data-related micro-tasks which require limited skills, attract low remunerations, and are often paid by piece-rate. These tasks consist, for example, in tagging objects on a photograph to train computer vision models for autonomous vehicles, or in checking the accuracy of transcriptions made by speech-to-text algorithms. Micro-workers are not formally employees but independent contractors or sometimes simple “participants” of the platforms, with varying levels of activity and engagement. While some micro-work is performed through well-known publicly accessible platforms like Amazon Mechanical Turk or Microworkers, tech giants have their own proprietary ones (like UHRS for Microsoft or RaterHub for Google). The factory of the future, construed as a virtual networked infrastructure, puts in place business and communication processes while moving away from the traditional location-based manufacturing paradigm and tipping over into a platform paradigm. As the barriers between outside and inside of the factory are replaced by technological ecosystems where workers are at the core, humans are not vacated from the productive organizations to come—yet their role is often rendered invisible.
This project aims to uncover the chains that through platforms, link workers to their clients, French and European companies who demand data-related and algorithmic services. Methodologically, we will leverage a range of economic and social science approaches. The initial phase relies on existing data we have collected: surveys of users of a prominent French platform, a large database of messages from a micro-worker online forum, transaction data from a major international platform, and 92 in-depth interviews. On top of this, a new data collection will be carried out during the project. We will survey 2 000 French SMEs about their usages of micro-work and AI, at three points in time. Furthermore, we intend to collect additional online data through web scraping, API access and extractions via agreements with platforms. Complementary to these quantitative analyses, we will conduct qualitative fieldwork, partly with company managers, union representatives and other local stakeholders (40-50 interviews) and partly with micro-workers, platform operators and business intermediaries in emerging and developing countries where data-related work is outsourced (40-50 interviews).
Our study has five main objectives:
1) Study the use of micro-work by firms as a means of outsourcing. Focus is on small and medium sized enterprises (SME) which use intermediaries (platforms) to recruit online labor rather than running their own service.
2) Explore the variety of business models, specializations, and modes of functioning of local and specialized micro-working platforms. We aim to understand their different strategies in terms of pricing, internal governance, and in their degree of transparency and openness to the public.
3) Map cross-country channels through which micro-tasks are outsourced abroad. This will complete and systematize our prior findings towards a robust knowledge base documenting international AI-related outsourcing networks and enabling comparison to spatial patterns previously observed in the English-speaking world.
4) Link business models to working conditions and practices.
5) Develop managerial and policy guidelines, assessing their potential effectiveness in terms of improving the working conditions of individuals active in the micro-tasking platform economy, while enriching reflection around fair and socially responsible AI.
Monsieur Antonio CASILLI (Institut Mines Télécom - Télécom ParisTech)
The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.
TPT Institut Mines Télécom - Télécom ParisTech
LRI Laboratoire de Recherche en Informatique
Help of the ANR 348,300 euros
Beginning and duration of the scientific project: December 2019 - 42 Months