Journal of Evolutionary Economics - Call for Papers: Special Issue on "Artificial Intelligence, Varieties of Next Capitalism and Beyond"

Guest Editors

Luca Grilli (Politecnico di Milano)
Sergio Mariotti (Politecnico di Milano)
Riccardo Marzano (Sapienza University of Rome)

Overview

The term “artificial intelligence” (AI) is associated with a mixture of multiple research fields, each with its own goals, methods, and applications, all called “AI” mainly for historical, rather than theoretical, reasons (Wang, 2019). However, convergence is unanimous on the idea that our future is a society in which AI applications will play a key role as a complement and/or substitute for human intelligence by relying on its enormous capability of collecting, elaborating and coordinating information, robotics and automation, and machine learning algorithms (Dwivedi et al., 2021; Makridakis, 2017).

Looking at the furthest-reaching implications of the AI cluster, scholars have proposed different, sometimes opposite, views of the transformation of capitalism (or its overcoming), grounding on the increasing evidence on the pervasiveness of AI applications and platforms (Gawer, 2021; Kenney et al., 2021; Peneder, 2021). On the one hand, some have underlined the authoritarian potential of AI, coining various terms that emphasize the dangers to the freedom of individuals due to the concentration of data and knowledge in the hands of a few economic organizations and/or institutions: platform capitalism (Srnicek, 2017), surveillance capitalism (Zuboff, 2019), neuro capitalism (Helbing and Hausladen, 2022), inhuman capitalism (Dyer-Witheford et al., 2019). On the other hand, some scholars propose that AI paves the way for a society of abundance, free goods and almost zero marginal costs of reproduction, in many respect beyond capitalism: post-capitalism (Mason, 2015), digital socialism (Morozov, 2019), fully automated luxury communism (Bastani, 2019), are evocative terms used to represent this (r)evolution.

Futurism nourished by the (very controversial) idea that “machines think”, up to the final outcome of AI that transcends human capabilities and control, can lead to a sort of “digital animism”, displaying accordance with the human inherent tendency to anthropomorphize the unknown and to attribute autonomous minds to non-human entities, today represented by the abstract abyss of computation, data centers and machine learning (Pasquinelli, 2016). Indeed, futurism can be a fruitless effort or can fall into determinism, proclaiming the arrival of a technological singularity (self-conscious computing machines), if it does not take into account that the future reality can take a multitude of paths, depending on the past, but open to the human action. As it is well-understood since Dosi (1982), from the same (new) technological paradigm may stem many possible different technological trajectories, the emergence of which is strongly shaped by social, economic, industrial, and institutional factors.

Being doomed by reality to living with uncertainty, it is imperative for scholars to try to link technological forecasting to social and economic change, as transformative applications and social impacts of AI are expected in the near and intermediate future, long before any final scenario. This requires studies that integrate both the technical characteristics of AI systems, and the social, economic, industrial and institutional context in which they are deployed.

Aim

The special issue aims to enhance our understanding of how the present forms of capitalism (will) coevolve with the AI ​​innovations, giving rise to desirable or undesirable outcomes for humanity.

Our starting point is what history has taught us. According to the comparative capitalism literature, economies and societies are variously coordinated in different countries, giving rise to varieties of capitalism (Hall and Soskice, 2001; Hancké et al., 2007). Country-specific institutions as resources for coordination have emerged in fundamental spheres in which firms operate, such as industrial relations, vocational training and education, corporate governance and interfirm-relations (Hall and Soskice, 2001). Differences between typology, quality and coherence between institutions have given rise to a spectrum of institutional forms, from liberal market economies to coordinated market economies, passing through intermediate configurations oscillating between laissez faire and state dirigisme. Furthermore, in recent decades, we have witnessed the emergence and success of new authoritarian forms of state capitalism, where central planning and decentralized autonomy of economic agents co-exist to some extent (Musacchio, et al., 2015). Varieties in capitalism favor varieties in the economic and social outcome, not least in the environment where firms develop capabilities to innovate (radical versus incremental innovation), and where markets are variously conducive to innovation (generation versus diffusion).

In this light, the aim of the special issue can be expressed by the following three broad questions: i) how do varieties of capitalism select between different AI technological trajectories? ii) how does AI influence the evolution of varieties of capitalism in the light of the latter's path dependence? iii) what are the relative performance of different possible arrangements arising from the co-(r)evolution of AI applications and varieties of capitalism in terms of static and dynamic efficiency? 

Both theoretical and empirical contributions are encouraged, where methods and methodologies can be chosen in the whole available spectrum of scientific perspectives, approaches and techniques. Studies may also embrace different levels of analysis, such as individuals, firms,  markets, industries and socio-economic systems.

Topics

Exemplary research questions within the intended scope of the special issue include, but are not limited to, the following themes:

• What are the main institutional transformations that AI requires so as to maximize gains from exploration and exploitation of technological opportunities? According to the ongoing debate, which varieties of capitalism and/or which reforms of them are best suited to promote radical AI-based innovations, thus allowing the deployment of AI applications (e.g., Akkermans et al., 2009; Soskice 2020; 2021; Witt and Jackson, 2016)? Which institutional contexts can best accommodate AI, ensuring positive externalities to firms in terms of efficient labor markets, training, education and skill upgrading, flexible industrial relations, so as to reach higher levels of employment in the long term and limit unemployment in the short one (e.g. Herrmann and Peine, 2011; Tschang and Almirall, 2020)?
• How AI may impact the evolution of specific sectors, the way firms are created, survive and grow, the way individuals interact each other and relate themselves with machines? How all these dynamics are affected by a specific institutional matrix, i.e. the interdependent web of formal and informal norms (North, 1990), characterizing a particular setting? To what extent institutional complementarities (Hall and Soskice, 2001) are likely to characterize the evolution of AI technologies and, in turn, influence the whole actors in the economic system? 
• Can AI trigger a virtuous circle between mass production and mass consumption of new products and services similar to that promoted by Fordism in the 20th century, allowing for sustained and sustainable growth in output, productivity, and income (Agrawal et al., 2019)? How the institutions can favor the activation of this circle, simultaneously guaranteeing the freedom and equality of people, the right to privacy, and the preservation of ethical values (Floridi, 2021)? What history on other general-purpose technologies can teach us about the evolutionary dynamics of AI in diverse forms of capitalism?
• Might advances in AI render an economic order based on central planning practically feasible and more efficient than a market economy, by resolving the conflict between opposing conclusory assertions — Hayek’s (1945) assertion of impossibility versus Lange’s (1967) assertion on the possibility of planners to replicate markets’ socially optimal allocation — in favor of the latter? Could this only apply to part of the existing market structures? Or is Hayek still relevant in the age of AI, and is the market superior to the state both in protecting individual freedom and privacy, and in contextually giving economic agents greater incentives to exploit the AI potential? 
• Should the type of economic planning promoted by AI be conducted by the State or by a single central entity taking all the decisions, according to a mission-oriented policy? Or, will the power of command, coordination and control reside in networks of private organizations and public institutions, the latter mainly devoted to diffusion-oriented policy? So far the centralization and control of big data has favored the formation of markets dominated by digital giants. Will AI determine a progressive process of ownership concentration in all industries, with the emergence of privately-owned or state-owned large enterprises? Could coordinated market economies foster ownership alternatives, such as public sector platforms, digital municipalism, open source institutions, platform cooperatives and inclusive ownership (Dyer-Witheford, 2020)?
• How the spectrum of varieties of capitalism will be modified by the co-evolution of AI and institutional forms? Will we have a reduction in the varieties of capitalism? Or will the proliferation of divergent selection processes produce a greater variety and enrichment of forms of capitalism? Will the different varieties find an equilibrium between them, or will disequilibria emerge that will trigger a "battle of systems"?
• Looking at economic development and innovation, will AI foster a capitalist world in which dynamic entrepreneurs and a liberal market system incentivize the creation and distribution of innovations (Schumpeter (1912) Mark I, or Entrepreneurial Capitalism)? Or will the economic concentration pushed by AI leave only to large hierarchically organized companies the task of enhancing the innovation process, while entrepreneurs, deprived of their animal spirit (creativity and risk seeking), will leave economic and social power to the State (Schumpeter (1942) Mark II, or State Capitalism)? 
• Will human-machine interaction foster creativity and innovation, or will the increasing delegation to learning machines and robotics drain some of the sources from which the innovative idea draws inspiration (Balasubramanian, et al., 2020)? How organization routines are going to be modified by the diffusion of AI, whether AI is destined to replace or, instead, complement humans in their creative functions? And, in both cases, what are the implications for exploration and exploitation of technological opportunities and their deployment in economic systems? 
• Recent literature has illustrated the potential of AI in helping firms escape or circumvent market regulation and in encouraging market manipulation through personalized dynamic pricing, price discrimination, algorithmic collusion, and so on (Calvano et al., 2020; Mariotti, 2021; Rab, 2019; Van de Rest, et al., 2020). Could these attacks on economic welfare be countered by an AI conceived as a comprehensive regulator (rather than a market-like coordinating mechanism), i.e. a complementary actor to the state in regulating the market externalities and failures? Is the current set of antitrust norms, rules and laws capable of preventing large AI-based firms from extracting value and wealth, while instead contributing to societal goals (Kenney et al., 2021)? Can self-regulation be helpful (e.g. Cusumano et al., 2021)? Or do we need new regulatory actions? 
• Last, but surely not least, are there specific AI innovation clusters whose evolutionary dynamics are particularly relevant per se or as trend signals in a future perspective? How does the AI sector itself look now and how will it evolve in the next future across different institutional contexts? How will AI change the locus of economic activities? Both sectorial focuses and specific case studies are very welcome for all these different areas of investigation.

Deadline, submission and review process

The deadline for submitting papers is November 30^th 2022.

Submissions to the special issue should be sent electronically through the Journal web platform.

Submissions should be prepared in accordance with the guidelines provided by the Journal of Evolutionary Economics (JEEC). All manuscripts must be original, unpublished works that are not concurrently under review for publication elsewhere. All papers will be subjected to the standard JEEC review process. Enquiries about this call for papers can be directly posted to the guest editors, i.e., Luca Grilli (luca.grilli@polimi.it (this opens in a new tab)), Sergio Mariotti (sergio.mariotti@polimi.it (this opens in a new tab)) or Riccardo Marzano (riccardo.marzano@uniroma1.it (this opens in a new tab)).

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