T4-09: The global discourse on digital work

Rossana Merola, International Labour Organization (ILO)

The current wave of technological change based on advancements in artificial intelligence (AI) has created the sentiment of vastly accelerating technological change that is feared to disrupt labour markets in yet unforeseen magnitude. Many analysts are warning that advances in both robotics and AI over the next few decades could lead to significant job losses or job polarization and hence widen income and wealth disparities (Korinek and Stiglitz, 2017).

Three main factors are deemed to have triggered the rapid increase in AI patent applications across the world. First, the drop in computing costs has led to an explosion in installed computing power and storage capacity. Second, the development and wide-spread adoption of the internet and other forms of digital communication has led to a significant increase in the supply and storage of digital information. Finally, the drop in capital costs for digital technologies has significantly lowered barriers of entry for start-ups.

This paper aims at addressing this knowledge gap to gain a better understanding of the economic and social implications of AI. In order to do so, it suggests to start from a granular analysis of how previous waves of automation have changed occupations and employment opportunities in the past. Specifically, we look at experiences of advanced and emerging economies with the automation of physical tasks through the rise in robotization. This approach can shed some light on the likely impact that the development and wide-spread diffusion of AI might have on employment, incomes and inequality through the automation of mental tasks. We also look at offshoring as much as it affects the role that AI can play in the structural transformation in developing countries. The questions this paper then tries to answer are twofold: First, to what extent is the current digital transformation through the rise in AI labour-augmenting rather than labour-saving? Moreover, what will be the implications for productivity and inequality given the specific, digital nature of AI applications? In particular, can we expect an acceleration in productivity and earnings growth thanks to wide-spread diffusion of AI in areas that so far have not yet been subject to large-scale automation? Or, on the contrary, should we be afraid of technological rents arising from AI to be appropriated by the lucky few?

The answer that this paper gives to these questions is moderately optimistic. New, AI-based digital technologies will allow larger segments of the labour market to improve their productivity, to access better paying occupations and, thereby, will help promote (inclusive) growth. This requires, however, the adoption of a certain number of policies aiming to support the necessary shift in occupational demand, maintain a strong competitive environment and keep up aggregate demand to support structural transformation. At the same time, AI applications rise the potential for productivity growth for interpersonal, less technical occupations and tasks, leading to higher demand for such work, which is likely to dampen inequality trends observed over recent decades. A particular challenge arises for developing countries when they are part of a value chain that forces them to adopt capital-intensive technologies despite an abundance of underutilised labour. Here, AI-driven automation might further drive up informality unless governments ensure a wide-spread adoption and diffusion of digital technological change beyond the value chain sectors. In other words, the productivity enhancing potential of AI is real, but the specific characteristics of this new technology require policy responses that differ from those given during previous waves of technological change in order to generate shared benefits for the world of work.

To develop our argument, this paper in Section 2 will start by looking at the historical perspective of automation. It will argue that the rise in educational attainment has led to an increasing skill-biased nature of technological change, bringing fewer benefits for productivity but increasing inequality; it is against this background that the introduction of AI needs to be assessed. Section 3 will shift the focus on tasks and away from jobs to help understand the implications this had for employment and the organisation of production. Section 4 discusses the particular experience that advanced and emerging economies have made during the recent wave of robotization. In section 5, our focus will then turn towards AI and the various aspects that this new technology brings for job growth, earnings dynamics and firm productivity. In section 6, we will develop possible policy answers that can help address the issues that AI brings in order to allow for a proper sharing of technological rents both within countries but also between advanced and less developed economies. A final section concludes.

A comparative perspective

Samuel Mbah, University of Lagos

Introduction

This paper adopts a qualitative approach to investigate effects of online outsourcing on marginalised groups in developing countries. The study utilised secondary data because of the novelty of online outsourcing. The purpose is to compare different models of online outsourcing initiatives with a focus on Nigeria, Malaysia, and Philippines. Online outsourcing is a “digital labour” in a “gig economy” which involves exchange of goods and services from clients to workers for money via digital platforms such as Freelancer, Upwork, Fiverr, etc (Wood et al., 2016). These platforms represent digital labour markets where outsourcing of tasks takes place under competitive and flexible arrangements (Beerepoot & Lambregts, 2015). The online outsourcing provides employment opportunities for vulnerable groups like the unemployed men and women to gain permanent employment or low income earners to earn extra money. In contrast, this digital process is fraught with social policy challenges and challenges arising from the need for partnership among social actors such as the employers, government, World Bank and NGOs. Apparently, little is yet known about online outsourcing and very little evidence of comparative studies exist in developing countries. It is the need to fill this knowledge gap and add to literature that prompted this research.

The aim of this paper therefore, is to undertake a critical comparative analysis of “Models of Online Outsourcing Initiatives (MOOI)”and relative implications for marginalised groups in Nigeria, Malaysia and Philippines. This aim raises some basic research questions on:

RQ1: Why the comparison i.e., reasons for comparison?
RQ2: What are bases of comparison i.e., variables or indexes for comparison?
RQ3: How is the comparison undertaken i.e., approaches or methods of comparison?
RQ4: To what extent does social actors’ contributions impact vulnerable groups and maintain stable employment relationship?
RQ5: What are possible implications for theory and practice?

In order to gain as much insight as possible, we generate more specific objectives of the study to:

a. Find out if there are significant differences and similarities among the different Models of Online Outsourcing Initiatives namely “NaijaCloud”, “eREZEKI” and Infographic “Digtal Market” respectively;
b. evaluate content and structure of models in comparative perspective;
c. examine different forms of work processes and practices relating to each Model and compare their impacts;
d. compare level of speed/widespread of initiatives or density of vulnerable groups affected by using descriptive statistics i.e., Tables;
e. assess impacts of contributions made by social actors and development agencies on vulnerable groups and labour relations and
f. explain implications for theory and practice in comparative research.

Theoretical framework and concepts

The theoretical framework of this research is predicated on the strategy of “Constant Comparative Method” of analysis drawn from the “Grounded Theory Method,” originated by Glaser and Strauss (1967). The choice of this theory is premised on Morse’s (2009) view that grounded theory is not something that is ‘performed’ in exactly the same way, every researcher factors the approach or generates their own version of the theory to suit particular research purpose. It is based on this inductive reasoning that the choice of “Constant Comparative Method” is made to analyse and compare concepts and incidences of online outsourcing initiatives embedded in the three different models and apply inductive method to provide answers to the research questions.

Conceptual framework

Duncombe (2006) came up with earliest livelihoods framework of analysis that focuses on Information Centered Technology (ICT) and its application to poverty reduction in Botswana. Malik, Nicholson and Heeks’ (2018) livelihoods conceptual framework in online outsourcing via digital labour platforms in Pakistan was a modification or adaptation of Duncombe’s (2006) livelihoods Approach,

In the same way, we adapt Heeks et al.’s (2018) conceptual approach in the context and come up with a modified version that we refer to as a “welfare Framework”, derived via qualitative inductive approach (Morse, 2009).

Methods

The study is qualitative research that utilised secondary sources of data. The secondary sources of data utilised in this study include Journal articles, textbooks, records and reports of the World Bank, excerpts from Government reports, Central Bank of Nigeria (CBN) Bulletins, empirical studies, dissertations and internet source. The adopted methods of data analyses include descriptive, narrative, comparative and inductive methods of analyses.

Key findings / Research in progress

• The study found that each of the country has a unique label that reflects unique aim and objectives of online outsourcing initiatives such as “NaijaCloud” in Nigeria, “eREZEKI” in Malaysia and “Infographic Ditital Market” in Philippines and so forth.

Implications for theory and practice / research in progress

• The new form of “Constant Comparative Method” perspective of the grounded theory derived via qualitative and inductive approach as well as the adapted model can be of immense benefits to researchers in comparative studies.
• In practice, is relevant to policy making, digital labour relations and socio-economic development and so forth.

Contributions to knowledge

• The study established new perspective of “Constant comparative Method” derived from “Grounded theory” as organisational lens devise useful in online comparative research. Thus, fills the knowledge gap and adds to literature.

References

• Beerepoot, N., & Lambregts, B. (2015}. Competition in online job marketplaces: Towards a global labour market for outsourcing services. Global Network, 15(2), 236-255.
• Duncombe, R. (2006). Using the livelihoods framework to analyse ICT applications for poverty reduction through microenterprise. Information Technologies and International Development, 3(3), 81-100.
• Glaser, B. &. Strauss, A. (1967). The discovery of grounded theory strategies for qualitative research. Chicago: Aldine Publishing Company.
• Heeks, R., Malik, F, & Nicholson, B. (2018). Understanding the development implications of online outsourcing: A study of digital labour platforms in Pakistan. UK: Centre for Development Informatics Global Development Institute, SEED.
• Lacity, M.C., Yan, A., Solomon, S., & Willcocks, L. (2011). Business process outsourcing studies: A critical review and research directions. Journal of Information Technology 26(4), 221-258.
• Morse, J.M., & Niehaus, L. (2009). Mixed method design principles and procedures. Venut Creek: C A Lest Coast Press.

Nothing new under the sun!

Calogero Massimo Cammalleri, University of Palermo

The paper jointly studies the impact of work through digital platforms and of the vast AI robotics implementation on issues of employment law and social security. The point of view and the remedy that is suggested are both quite unorthodox. The point of view is one of law and literature; the remedy is taken from law and economics. Even if the essay agrees that the proposal of introducing both a social contribution on robots and a new regulation via apps poses the right question, it holds that such solutions are not necessarily the right way. In fact, since these would ‘anthropomorphise’ robots and algorithms, it would inevitably be useless, similar to an increase in social contributions. Conversely, the article proposes a radical change in perspective, deeming that social protection in the digital era requires new relationships between ‘every’ market and ‘the’ social justice. For the latter purpose, the article proposes to break the two alternative dichotomies of Bismarckian/Beveridgean systems of social provisions and that of employee/independent-contractor (at the level of regulation through the law). In this regard, such change is reached without extending the regulation of employees. Consequently, the essay suggests introducing a new ‘uniform’ and indirect financial system for protections for those who are not in a Standard Employment Relationship. Such a ‘uniform’ financing device for social contributions is based on the ‘added value’ of work rather than (the opposite of how it actually is) based either on the wage of an employee or on the earnings of the self-employed. This way, the shifting boundaries of contracts between companies or firms and employees or workers, or even the self-employed and so on, can be overcome because no particular contract is needed for protection. The same applies to the use of robots.