Artificial intelligence – Data Big and Small

Artificial Intelligence and Globalization: Data Labor and Linguistic Specificities (AIGLe)

We organized the one-day conference AIGLe on 27 October 2022 to present the outcomes of interdisciplinary research conducted by our DiPLab teams in French-speaking African countries (ANR HuSh Project) and Spanish-speaking countries in Latin America (CNRS-MSH TrIA Project). Both initiatives study the human labor necessary to generate and annotate the data needed to produce artificial intelligence, to check outputs, and to intervene in real time when algorithms fail. Researchers from economics, sociology, computer science, and linguistics shared exciting new results and discussed them with the audience.

AIGLe is part of the project HUSh (The HUman Supply cHain behind smart technologies, 2020-2024), funded by ANR, and the research project TRIA (The Work of Artificial Intelligence, 2020-2022), co-financed by the CNRS and the MSH Paris Saclay. This event, under the aegis of the Institut Mines-Télécom, was organized by the DiPLab team with support of ANR, MSH Paris-Saclay and the Ministry of Economy and Finance.

PROGRAM
9:00 – 9:15 Welcome session

9:15 – 10:40 – Session 1 – Maxime Cornet & Clément Le Ludec (IP Paris, ANR HUSH Project): Unraveling the AI Production Process: How French Startups Externalise Data Work to Madagascar. Discussant: Mohammad Amir
Anwar (U. of Edinburgh)

10:45 – 11:00 Coffee Break

11:00 – 12:30 – Session 2 – Chiara Belletti and Ulrich Laitenberger (IP Paris, ANR HUSH Project): Worker Engagement and AI Work on Online Labor Markets. Discussant: Simone Vannuccini (U. of Sussex)

12:30 – 13:30 Lunch Break

13:30 – 15:00 Session 3 – Juana-Luisa Torre-Cierpe (IP Paris, TRIA Project) & Paola Tubaro (CNRS, TRIA Project): Uninvited Protagonists: Venezuelan Platform Workers in the Global Digital Economy. Discussant:
Maria de los Milagros Miceli (Weizenbaum Institut)

15:15 – 15:30 Coffee Break

15:30 – 17:00 Session 4 – Ioana Vasilescu (CNRS, LISN, TRIA Project), Yaru Wu (U. of Caen, TRIA Project) & Lori Lamel (LISN CNRS): Socioeconomic profiles embedded in speech : modeling linguistic variation in
micro-workers interviews. Discussant: Chloé Clavel (Télécom Paris, IP Paris)

Learners in the loop: hidden human skills in machine intelligence

I am glad to announce the publication of a new article in a special issue of the journal Sociologia del lavoro, dedicated to digital labour.

Today’s artificial intelligence, largely based on data-intensive machine learning algorithms, relies heavily on the digital labour of invisibilized and precarized humans-in-the-loop who perform multiple functions of data preparation, verification of results, and even impersonation when algorithms fail. This form of work contributes to the erosion of the salary institution in multiple ways. One is commodification of labour, with very little shielding from market fluctuations via regulative institutions, exclusion from organizational resources through outsourcing, and transfer of social reproduction costs to local communities to reduce work-related risks. Another is heteromation, the extraction of economic value from low-cost labour in computer-mediated networks, as a new logic of capital accumulation. Heteromation occurs as platforms’ technical infrastructures handle worker management problems as if they were computational problems, thereby concealing the employment nature of the relationship, and ultimately disguising human presence. My just-published paper highlights a third channel through which the salary institution is threatened, namely misrecognition of micro-workers’ skills, competencies and learning. Broadly speaking, salary can be seen as the framework within which the employment relationship is negotiated and resources are allocated, balancing the claims of workers and employers. In general, the most basic claims revolve around skill, and in today’s ‘society of performance’ where value is increasingly extracted from intangible resources and competencies, unskilled workers are substitutable and therefore highly vulnerable. In human-in-the-loop data annotation, tight breakdown of tasks, algorithmic control, and arm’s-length transactions obfuscate the competence of workers and discursively undermine their deservingness, shifting power away from them and voiding the equilibrating role of the salary institution.

Following Honneth, I define misrecognition as the attitudes and practices that result in people not receiving due acknowledgement for their value and contribution to society, in this case in terms of their education, skills, and skill development. Platform organization construes work as having little value, and creates disincentives for micro-workers to engage in more complex tasks, weakening their status and their capacity to be perceived as competent. Misrecognition is endemic in these settings and undermines workers’ potential for self-realization, negotiation and professional development.

My argument is based on original empirical data from a mixed-method survey of human-in-the-loop workers in two previously under-researched settings, namely Spain and Spanish-speaking Latin America.

An openly accessible version of the paper is available from the HAL repository.

Human listeners and virtual assistants: privacy and labor arbitrage in the production of smart technologies

I’m glad to announce the publication of new research, as a chapter in the fabulous Digital Work in the Planetary Market, a volume edited by Mark Graham and Fabian Ferrari and published in open access by MIT Press.

The chapter, co-authored with Antonio A. Casilli, starts by recalling how In spring 2019, public outcry followed media revelations that major producers of voice assistants recruit human operators to transcribe and label users’ conversations. These high-profile cases uncovered the paradoxically labor-intensive nature of automation, ultimate cause of the highly criticized privacy violations.

The development of smart solutions requires large amounts of human work. Sub-contracted on demand through digital platforms and usually paid by piecework, myriad online “micro-workers” annotate, tag, and sort the data used to prepare and calibrate algorithms. These humans are also needed to check outputs – such as automated transcriptions of users’ conversations with their virtual assistant – and to make corrections if needed, sometimes in real time. The data that they process include personal information, of which voice is an example.

We show that the platform system exposes both consumers and micro-workers to high risks. Because producers of smart devices conceal the role of humans behind automation, users underestimate the degree to which their privacy is challenged. As a result, they might unwittingly let their virtual assistant capture children’s voices, friends’ names and addresses, or details of their intimate life. Conversely, the micro-workers who hear or transcribe this information face the moral challenge of taking the role of intruders, and bear the burden of maintaining confidentiality. Through outsourcing, platforms often leave them without sufficient safeguards and guidelines, and may even shift onto them the responsibility to protect the personal data they happen to handle.

Besides, micro-workers themselves release their personal data to platforms. The tasks they do include, for example, recording utterances for the needs of virtual assistants that need large sets of, say, ways to ask about the weather to “learn” to recognize such requests. Workers’ voices, identities and profiles are personal data that clients and platforms collect, store and re-use. With many actors in the loop, privacy safeguards are looser and transparency is harder to ensure. Lack of visibility, not to mention of collective organization, prevents workers from taking action.

Note: Description of one labor-intensive data supply chain. A producer of smart speakers located in the US outsources AI verification to a Chinese platform (1) that relies on a Japanese online service (2) and a Spanish sub-contractor (3) to recruit workers in France (4). Workers are supervised by an Italian company (5), and sign up to a microtask platform managed by the lead firm in the US (6). Source: Authors’ elaboration.

These issues become more severe when micro-tasks are subcontracted to countries where labor costs are low. Globalization enables international platforms to allocate tasks for European and North American clients to workers in Southeast Asia, Africa, and Latin America. This global labor arbitrage goes hand in hand with a global privacy one, as data are channeled to countries where privacy and data protection laws provide uneven levels of protection. Thus, we conclude that any solution must be dual – protecting workers to protect users.

The chapter is available in open access here.

Hidden inequalities: the gendered labour of women on micro-tasking platforms

Around the world, myriad workers perform data tasks on online labour platforms to fuel the digital economy. Mostly short, repetitive and little paid, these so-called ‘micro-tasks’ include for example labelling objects in images, classifying tweets, recording utterances, and transcribing audio files – notably to satisfy the data appetite of today’s fast-growing artificial intelligence industry. While casualization of labour and low pay have attracted sharp criticisms against these platforms, they appear gender-blind and accessible even to people with basic skills. Women with care or household duties may particularly benefit from the time flexibility and the possibility to work from home that platforms offer. So, are these new labour arrangements gender equalizers after all?

In a new paper co-authored with Marion Coville, Clément Le Ludec and Antonio A. Casilli, we demonstrate that this new form of online labour fails to fill gender gaps, and may even exacerbate them. We proceed in three steps. First, we show that legacy inequalities in the professional and domestic spheres turn platform-mediated micro-tasking into a ‘third shift’ that adds to already heavy schedules. Both working fathers and working mothers experience it, but the structure of the other two shifts affects their experience. Looking at their time use, it turns out that men dedicate long and uninterrupted slots of time to each activity: their main job, their share of household duties, leisure and micro-work. They tend to do all micro-tasks in a row, usually at night after work or in the morning before starting. Instead, women have more fragmented schedules, and micro-work during short breaks, here and there, eating into their leisure time. This is one reason why they earn less on platforms: they have short slots of time available, so they cannot search for better-paid tasks, and just content themselves with whatever is available at that moment.

Time use of typical female (left) and male (right), micro-workers, both of whom have a main job in addition to platform micro-tasks, and dependent children.

Second, we submit that the human capital of male and female data workers differ, with women less likely to have received training in science and technology fields.

Highest educational qualification (left) and discipline of specialization (right) of men and women micro-workers. Data collected in France, 2018 (n = 908).

Third, their social capital differs: using a position generator instrument to capture workers’ access to the informational and support resources that may come from contacts with people in different occupations, we show that women have fewer ties to digital-related professionals who could provide them with knowledge and advice to successfully navigate the platform world.

Gender assortativity index for each occupation in the 48-item position generator that measures respondents’ social capital. Each panel represents respondents’ choices, ordered from lowest (negative) to highest (positive) degree of similarity. Top panel: female respondents, bottom panel: male respondents. The bars corresponding to digital and computing occupations are hatched.

Taken together, these factors leave women with fewer career prospects within a tech-driven workforce, and reproduce relegation of women to lower-level computing work as observed in the history of twentieth-century technology.

The full paper is available in open access here.

It is part of a full special issue of Internet Policy Review on ‘The gender of the platform economy‘, guest-edited by M. Fuster Morell, R. Espelt and D. Megias.

Internship offer (3 months, master’s level, spring 2021)

The research project TRIA (from its French title “Le TRavail de l’IA: éthique et gouvernance de l’automation”) is a study of the production systems of artificial intelligence. We investigate “micro-work” platforms, which allocate small standardized tasks to crowds of providers, and use the outputs of their work to prepare and annotate data for machine learning algorithms. We study the ramifications of this phenomenon in Spanish-speaking countries, which have remained under-researched so far despite their strong participation. With data from an empirical survey already started in 2020, and to be analyzed through mixed methods (including advanced NLP techniques), we will address important issues related to digital platform governance, online work ethics, and consequences (e.g. in terms of bias) of the use of these humans in the production of artificial intelligence.
Funded by the French National Center of Scientific Research (CNRS), the TRIA project resembles research teams in the Paris and Rennes regions in France, as well as partners in Spain (Barcelona and Valencia) and Canada (Toronto).

We are currently looking for a student intern to help us set up a survey targeting micro-workers in Spain and Spanish-speaking Latin American countries.
He/she will help us to :

update an inventory of micro-work platforms operating in Spanish-speaking countries, a first version of which was created in 2020;
launch a replication of the online questionnaire, already fielded on Microworkers.com, on another micro-work platform;
to liaise and ensure communication between the project teams.

The applicant should :

be enrolled in the first or second year of a master’s degree in social science (like sociology, political science, management or economics) ;
have skills in the design and/or execution of questionnaire surveys;
have some prior knowledge of, or at least interest in, the transformations of work and/or the societal effects of digital technology;
be able to work independently, with advanced relational skills;
have a fairly good command of French or English, and at least a basic knowledge of Spanish.

More information is available in the enclosed job description.

Offre_stage_TRIA_2021-1 Download

Unboxing AI conference

I’m excited to be part of the organizing team for an upcoming conference entitled “Unboxing AI” and aiming to open – at least to an extent – the black box. What are the material conditions of AI production? Who are the multitudes of precarious workers who contribute to it in the shadow, by generating data and checking algorithmic outputs? What are the geographical areas and the social scope of the work that produces today’s intelligent technologies? These are some of the questions we aim to explore.

The first two days of the conference (November 5 and 6, 3pm – 7pm CET) will bring together highly regarded international specialists from a wide variety of disciplines (sociology, law, economics, but also the arts and humanities…). On the third day (November 7, also 3 pm – 7 pm CET), there will be a doctoral colloquium with a selection of very promising work by young researchers.

The conference was initially planned to take place in Milan in March 2020, and had to be postponed due to the Covid-19 pandemic. As the health situation is still critical, we have opted for an online-only version. At least, this format is cheap – no need to travel to attend – and we can welcome a more geographically diverse range of participants. Indeed the afternoon-only schedule is meant to enable colleagues from North and South America to attend.

Participation is free of charge but prior registration is required. You will find the programme as well as registration forms here
(please note that there is a separate form for each of the three dates of the conference).

The conference is organized as part of the initiatives of our ‘International Network on Digital Labor‘ and is co-sponsored by ISRF (Independent Social Research Foundation), the Nexa Center for Internet and Society, and Fondazione Feltrinelli.

Covid-19 and transfer of risk on digital platform workers

At an internal meeting of the IDHES lab in Gif-sur-Yvette, and then at an event at the University of Bologna, I have had the pleasure of presenting recent research on how the current health crisis reveals a new dimension of digital platforms – their tendency, wherever possible, to shift risk from clients to workers, within its ecosystem. The paper, co-authored with Antonio A. Casilli, is now under submission for a journal.

Here is an abstract:

As the recessionary effects of the 2020 Covid-19 pandemic become
manifest, the paper discusses their effects on digital platforms and the
workers in their eco-systems. Against the possibility that platform
labor may be a buffer against crisis-induced layoffs, our analysis of
the risks associated to it suggests that it may eventually increase
precarity, without necessarily mitigating health risks for workers. Our
argument is based on a comparison of the three main categories of
platform labor – “on-demand labor” (gigs such as delivery and
transportation), “online labor” (tasks performed by freelancers and
micro-workers) and “social media labor” (like content generation
and moderation) – in terms of the health and economic risks involved in
coronavirus times. We show that platform managers have deployed varying
strategies to transfer risk from themselves and their clients onto
workers, exploiting and deepening the existing power imbalance between
them. Success in achieving this has enabled them to secure their bottom
line even at the expense of working conditions. The Covid-19 pandemic
has brought to light how digital platforms apply a management style that
revolves around transferring the burden of risk to their own workforce.

Crowdworking Symposium 2020

With Antonio A. Casilli, I will be presenting a paper tomorrow at the Crowdworking Symposium organized by the University of Paderborn, Germany. Unfortunately, we will participate only online because of the health situation.

Our mini-paper (3 pages), entitled ‘Portraits of micro-workers: The real people behind AI in France’, is available here.

The platform economy, labour and Covid-19

On 18 September 2020, I present my research on the platform economy and its impact on labour in Covid-19 times at Nantes Digital Week, as part of a special event organized by CGT, a Union.

The mobility restrictions that accompanied the pandemic encouraged use of digital tools to socialize, study and work, suggesting that automation is gaining ground and that technology enables contactless – hence safe – interactions in much of our social life. Yet behind apparent automation, precarious and unprotected human labour is hidden. Workers recruited through digital platforms to make these solutions work, are in fact disproportionately exposed to risks. I illustrate these ideas in three main cases: food delivery workers, that enabled the restaurant industry to stand the crisis even during lockdown; commercial content moderators that are to return to office sooner than others, to protect our safety online; and AI micro-workers who trained tools whose sales have gone up during stay-at-home rules, such as voice assistants, and helped the creation of datasets for much-needed health applications.

First seminar of the year!

Next Thursday, 17 September, I have been invited to give a talk as part of the cycle of seminars organized by the quantitative sociology research group at CREST-ENSAE, Palaiseau (Paris area). Although the health situation is still bleak, I am glad to return to almost-normal functioning by giving an in-person talk. Hopefully there won’t be any new lockdown before that.

I will present an in-progress paper provisionally entitled:

«Disembedded or deeply embedded? A multi-level network analysis of the online platform economy»

The two types of platform labour analyzed in the paper.

In this paper, I extend the economic-sociological concept of embeddedness to encompass not only social networks of, for example, friendship or kinship ties, but also economic networks of ownership and control relationships. Applying these ideas to the case of digital platform labour pinpoints two possible scenarios. When platforms take the role of market intermediaries, economic ties are thin and workers are left to their own devices, in a form of ‘disembeddedness’. When platforms partake in intricate inter-firm outsourcing structures, economic ties envelop workers in a ‘deep embeddedness’ which involves both stronger constraints and higher rewards. With this added dimension, the notion of embeddedness becomes a compelling tool to describe the social structures that frame economic action, including the power imbalances that characterize digital labour in the global economy.