Papers in Regional Science
Political Economy of Artificial Intelligence: Critical Reflections on Big Data Market,
Economic Development and Data Society, by Bhabani Shankar Nayak, Nigel Walton,
2024, 213 pp., US$ 117.32 (paperback) ISBN 978031623073; (eBook) ISBN
9783031623080
--Manuscript Draft-Manuscript Number:
Full Title:
Political Economy of Artificial Intelligence: Critical Reflections on Big Data Market,
Economic Development and Data Society, by Bhabani Shankar Nayak, Nigel Walton,
2024, 213 pp., US$ 117.32 (paperback) ISBN 978031623073; (eBook) ISBN
9783031623080
Article Type:
Book Review
Keywords:
Artificial Intelligence (AI); Platform Capitalism; Big Data; Political Economy; Data
Society
Corresponding Author:
DENI BAGAS PRADANA
Universitas Gadjah Mada
INDONESIA
Corresponding Author Secondary
Information:
Corresponding Author's Institution:
Universitas Gadjah Mada
Corresponding Author's Secondary
Institution:
First Author:
Muh Suardi Ihsan D
First Author Secondary Information:
Order of Authors:
Muh Suardi Ihsan D
Risti Selfia Oktavianti
DENI BAGAS PRADANA
Fajar Munichputranto
Order of Authors Secondary Information:
Abstract:
Political Economy of Artificial Intelligence by Bhabani Shankar Nayak and Nigel Walton
provides a comprehensive examination of how artificial intelligence (AI) and big data
are fundamentally altering the landscape of modern capitalist economies and societal
structures. The authors argue that AI is not merely a neutral technological tool but is
deeply embedded within and driven by capitalist frameworks, which it simultaneously
reinforces and transforms. By analyzing the historical evolution of AI, from its
theoretical foundations to its current applications in platform economies, the book
highlights how AI has become a central force in the creation of new forms of capital
accumulation and market dominance. This transformation is most evident in the rise of
"platform capitalism," where digital platforms like Google, Amazon, and Alibaba use
vast amounts of data to generate profit, maintain market control, and create
unprecedented economic power that challenges traditional businesses and labor
markets. The authors critically explore the implications of these developments for
Marxist economic theories, suggesting that the traditional concepts of value,
production, and class relations must be re-evaluated in the context of a data-driven
economy. Furthermore, the book addresses the socio-political consequences of AI,
particularly its impact on citizenship, democracy, and global geopolitics, emphasizing
the risks associated with state surveillance, the erosion of civil liberties, and the
increasing divide between digital superpowers. Nayak and Walton argue for the urgent
need to develop comprehensive policy frameworks that regulate AI and big data,
protect labor rights, and ensure social welfare, while also addressing the ethical and
privacy concerns that arise in this new digital landscape. Through its critical analysis
and forward-looking perspective, Political Economy of Artificial Intelligence offers
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valuable insights into the complex interplay between technology, economics, and
society, making it an essential read for scholars, policymakers, and anyone concerned
with the future of AI in a rapidly changing world.
Suggested Reviewers:
Andrea Caragliu
Polytechnic University of Milan
andrea.caragliu@polimi.it
Additional Information:
Question
Response
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Declaration of Interest Statement
Declaration of interests
☒The authors declare that they have no known competing financial interests or personal relationships
that could have appeared to influence the work reported in this paper.
☐The authors declare the following financial interests/personal relationships which may be considered
as potential competing interests:
Title Page (With Author Information)
BOOK REVIEW
Political Economy of Artificial Intelligence: Critical Reflections on Big Data Market,
Economic Development and Data Society, by Bhabani Shankar Nayak, Nigel Walton, 2024,
213 pp., US$ 117.32 (paperback) ISBN 978031623073; (eBook) ISBN 9783031623080
The Political Economy of Artificial Intelligence by Bhabani Shankar Nayak and Nigel Walton is a
thought-provoking analysis of the intersection between artificial intelligence (AI), big data, and economic
development. The book critically examines how AI, as a product of capitalist systems, transforms society into a
data-driven entity, affecting various aspects of democracy, labor, and economic structures. With its comprehensive
approach, this book serves as a significant contribution to understanding the socio-economic implications of AI
within the framework of contemporary political economy.
The first chapter sets the stage by providing a historical overview of the development of AI, tracing its
roots back to the mid-20th century. The authors begin by defining AI and discussing its foundational theories,
starting with the work of pioneers like Alan Turing and the pivotal Dartmouth Conference in 1956. This chapter
outlines the various stages of AI’s evolution, including the challenges it faced during its early development and
the technological breakthroughs that enabled its growth. The authors highlight how AI transitioned from a
theoretical concept to a practical technology, driven by advances in computing power, data storage, and machine
learning algorithms.
One of the key strengths of this chapter is its detailed explanation of how AI has evolved through different
generations of computing technology. The authors effectively demonstrate how technological innovations, such
as the development of transistors, microprocessors, and neural networks, have paved the way for modern AI
applications. This historical perspective is crucial for understanding the current state of AI and its potential future
trajectories. However, the chapter could have benefited from a deeper exploration of the ethical considerations
that accompanied these technological advancements, particularly in the context of their societal impacts. .
In the second chapter, Nayak and Walton shift their focus to the platform economy, exploring how digital
platforms have become central to economic and social life. The authors define platform companies and explain
the unique characteristics that distinguish them from traditional linear businesses. They argue that platforms, by
leveraging AI and big data, have created new forms of capital accumulation and market dominance, leading to the
emergence of "techno-feudalism," where a few tech giants control vast amounts of data and economic power.
This chapter provides a comprehensive analysis of how platforms like Google, Amazon, and Alibaba
have disrupted traditional industries and created new economic dynamics. The authors discuss the advantages of
platform business models, such as their ability to scale rapidly and generate value through network effects and
user-generated content. They also address the regulatory challenges posed by these platforms, particularly in terms
of anti-trust laws and market competition.
While the chapter offers a thorough examination of the platform economy, it could have delved deeper
into the implications for labor markets. The rise of gig economy platforms, for example, has significant
consequences for workers' rights and job security, which the authors only briefly touch upon. A more detailed
discussion of these issues would have strengthened the chapter’s analysis of the broader societal impacts of the
platform economy.
Chapter three delves into the relationship between AI, big data, and capitalist economic development.
The authors argue that AI and big data have fundamentally altered the landscape of capitalism, creating new
opportunities for capital accumulation and economic growth. They explore how data has become a critical
resource in the modern economy, replacing traditional factors of production such as land, labor, and capital.
The chapter discusses the implications of this shift for Marxist economic theory, suggesting that
traditional concepts of value and production need to be re-evaluated in the context of a data-driven economy. The
authors introduce the concept of the "neo-bourgeoisie" and the "neo-proletariat," where data owners and providers
represent new classes within the capitalist system. This theoretical framework is one of the chapter’s key
contributions, as it offers a fresh perspective on how AI and big data are reshaping class relations and economic
power dynamics.
However, while the chapter provides a strong theoretical analysis, it could benefit from more empirical
examples to illustrate these concepts. Case studies of specific industries or companies that have successfully
leveraged AI and big data for economic gain would have added depth to the discussion and made the theoretical
arguments more tangible.
In the fourth chapter, the authors continue their exploration of AI’s role in capitalist economies by
examining how platforms and big data are creating new forms of capital accumulation. They argue that the
traditional Marxist understanding of capital accumulation is insufficient to explain the dynamics of the modern
digital economy, where data and platforms play a central role.
The chapter introduces the concept of "platform capitalism," where digital platforms act as intermediaries
between producers and consumers, extracting value through data collection and algorithmic processing. The
authors discuss how platforms like Facebook, Google, and Amazon have created new markets and forms of value
extraction, often at the expense of traditional businesses and labor markets.
One of the strengths of this chapter is its detailed analysis of how platforms use data to generate profit
and maintain market dominance. The authors effectively demonstrate how platforms have become central players
in the global economy, with significant implications for competition, labor, and consumer rights. However, the
chapter could have explored more fully the potential long-term consequences of platform capitalism, particularly
in terms of economic inequality and the concentration of power..
Chapter five explores the emerging market for big data, discussing how data has become a valuable
commodity in the digital economy. The authors analyze the different types of data markets, including the role of
platform companies in aggregating, processing, and monetizing data. They argue that big data markets are
reshaping traditional economic structures, leading to the creation of new business models and market dynamics.
The chapter also discusses the potential future of big data markets, considering both the opportunities
and challenges they present. The authors highlight the importance of data governance and regulation, particularly
in terms of protecting privacy and ensuring fair competition. They also discuss the potential risks associated with
data monopolies and the need for policies that promote transparency and accountability in the big data market.
This chapter is particularly strong in its analysis of the economic implications of big data markets. The
authors provide a clear and concise explanation of how data is being commodified and the impact this has on
traditional market structures. However, the chapter could have included more discussion of the ethical
implications of big data markets, particularly in terms of surveillance, privacy, and the potential for data misuse..
The sixth chapter shifts focus to the social and political implications of AI, exploring how the rise of AI
and big data is affecting citizenship and democratic rights. The authors argue that AI-driven technologies, by
enabling mass surveillance and data collection, are undermining traditional notions of citizenship and democratic
participation. They discuss the concept of the "splinternet," where the global internet is fragmented into different
jurisdictions with varying levels of freedom and control.
The chapter also examines the geopolitical implications of AI, particularly the competition between
major powers like the United States and China for digital supremacy. The authors highlight the risks associated
with this competition, including the potential for increased state surveillance, censorship, and the erosion of civil
liberties.
One of the strengths of this chapter is its focus on the intersection of technology and politics. The authors
provide a compelling analysis of how AI is reshaping the relationship between citizens and the state, with
significant implications for democracy and human rights. However, the chapter could have explored more fully
the potential for resistance and alternative models of governance that protect citizens' rights in the digital age.
The final chapter of the book explores the "limits of data society," discussing the potential challenges
and risks associated with the widespread adoption of AI and big data. The authors argue that while data-driven
technologies offer significant benefits, they also pose serious risks to social cohesion, privacy, and individual
autonomy. They discuss the concept of "data society," where data becomes the primary currency for social and
economic transactions, and consider the potential consequences of this shift for individuals, families, and
communities.
The chapter also addresses the potential for digital divides and social inequalities to be exacerbated by
AI and big data. The authors argue that without proper regulation and governance, data society could lead to
increased economic inequality, social fragmentation, and the erosion of traditional social structures.
This chapter provides a sobering conclusion to the book, highlighting the potential dangers of unchecked
technological advancement. The authors effectively argue for the need for comprehensive policies that address
the risks of data society and promote a more equitable and sustainable digital future. However, the chapter could
have benefited from a more detailed discussion of potential solutions and strategies for mitigating these risks.
One of the strengths of this book is its ability to link theoretical concepts with practical implications. The
authors offer a critical reflection on the limitations of classical Marxist thought in the context of AI and big data,
advocating for a re-evaluation of these theories to better understand contemporary forms of capitalism. The book's
emphasis on the "data market" as a new and transformative institution is particularly insightful, as it sheds light
on the commodification of data and its role in shaping economic and social interactions.
The authors also make a compelling case for the need to develop policies that regulate AI and big data
to protect workers and promote sustainable development. This forward-looking approach is crucial, as it addresses
the potential risks associated with AI, such as labor precarity, environmental degradation, and the erosion of
democratic rights. The book's critical stance on the role of platform companies in driving AI development further
underscores the need for a balanced approach to technological innovation that considers its broader societal
impacts
While the book offers a comprehensive analysis of AI's political economy, there are some areas where it
could be further developed. For example, the discussion on the "limits of data society" could benefit from a more
in-depth exploration of alternative models that challenge the dominant capitalist framework. Additionally, while
the book touches on the global implications of AI, it would be beneficial to include more case studies from nonWestern contexts to provide a more nuanced understanding of AI's impact across different regions.
Another potential area for improvement is the book's engagement with the ethical implications of AI.
While the authors discuss the legal and human rights challenges posed by AI, a more detailed examination of
ethical considerations, such as privacy, surveillance, and algorithmic bias, would enhance the book's overall
contribution to the field
Political Economy of Artificial Intelligence is a significant and timely contribution to the literature on
AI and its socio-economic implications. The authors' critical approach provides valuable insights into the ways
AI is reshaping capitalist economies and social structures. Despite some areas for further development, the book
is an essential read for scholars and policymakers interested in understanding the complex dynamics of AI within
the broader context of political economy. It not only challenges existing theoretical frameworks but also offers
practical suggestions for mitigating the risks associated with AI and ensuring that its development benefits society
as a whole..
Acknowledgments
We express our deepest gratitude to the Indonesia Endowment Fund for Education (LPDP), Ministry of Finance
of the Republic of Indonesia, for funding our master’s studies.
Muh Suardi Ihsan D
Master of Science – Research for International Development, SOAS University of London, London
suardyihsan17@gmail.com https://orcid.org/ 0009-0002-8677-2599
Risti Selfia Oktavianti
Master of Business Administration, Universitas Gadjah Mada, Indonesia
ristiselfiaoktaviani@mail.ugm.ac.id https://orcid.org/0009-0007-8455-1430
Deni Bagas Pradana
Master of Business Administration, Universitas Gadjah Mada, Indonesia
denibagaspradana@mail.ugm.ac.id https://orcid.org/0009-0007-6439-6525
Fajar Munichputranto
Master of Business Administration, Universitas Gadjah Mada, Indonesia
fajarmunichputranto@mail.ugm.ac.id https://orcid.org/ 0000-0002-4576-6021
Manuscript (Without Author Information)
Click here to view linked References
BOOK REVIEW
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Political Economy of Artificial Intelligence: Critical Reflections on Big Data Market,
Economic Development and Data Society, by Bhabani Shankar Nayak, Nigel Walton, 2024,
213 pp., US$ 117.32 (paperback) ISBN 978031623073; (eBook) ISBN 9783031623080
The Political Economy of Artificial Intelligence by Bhabani Shankar Nayak and Nigel Walton is a
thought-provoking analysis of the intersection between artificial intelligence (AI), big data, and economic
development. The book critically examines how AI, as a product of capitalist systems, transforms society into a
data-driven entity, affecting various aspects of democracy, labor, and economic structures. With its comprehensive
approach, this book serves as a significant contribution to understanding the socio-economic implications of AI
within the framework of contemporary political economy.
The first chapter sets the stage by providing a historical overview of the development of AI, tracing its
roots back to the mid-20th century. The authors begin by defining AI and discussing its foundational theories,
starting with the work of pioneers like Alan Turing and the pivotal Dartmouth Conference in 1956. This chapter
outlines the various stages of AI’s evolution, including the challenges it faced during its early development and
the technological breakthroughs that enabled its growth. The authors highlight how AI transitioned from a
theoretical concept to a practical technology, driven by advances in computing power, data storage, and machine
learning algorithms.
One of the key strengths of this chapter is its detailed explanation of how AI has evolved through different
generations of computing technology. The authors effectively demonstrate how technological innovations, such
as the development of transistors, microprocessors, and neural networks, have paved the way for modern AI
applications. This historical perspective is crucial for understanding the current state of AI and its potential future
trajectories. However, the chapter could have benefited from a deeper exploration of the ethical considerations
that accompanied these technological advancements, particularly in the context of their societal impacts. .
In the second chapter, Nayak and Walton shift their focus to the platform economy, exploring how digital
platforms have become central to economic and social life. The authors define platform companies and explain
the unique characteristics that distinguish them from traditional linear businesses. They argue that platforms, by
leveraging AI and big data, have created new forms of capital accumulation and market dominance, leading to the
emergence of "techno-feudalism," where a few tech giants control vast amounts of data and economic power.
This chapter provides a comprehensive analysis of how platforms like Google, Amazon, and Alibaba
have disrupted traditional industries and created new economic dynamics. The authors discuss the advantages of
platform business models, such as their ability to scale rapidly and generate value through network effects and
user-generated content. They also address the regulatory challenges posed by these platforms, particularly in terms
of anti-trust laws and market competition.
While the chapter offers a thorough examination of the platform economy, it could have delved deeper
into the implications for labor markets. The rise of gig economy platforms, for example, has significant
consequences for workers' rights and job security, which the authors only briefly touch upon. A more detailed
discussion of these issues would have strengthened the chapter’s analysis of the broader societal impacts of the
platform economy.
Chapter three delves into the relationship between AI, big data, and capitalist economic development.
The authors argue that AI and big data have fundamentally altered the landscape of capitalism, creating new
opportunities for capital accumulation and economic growth. They explore how data has become a critical
resource in the modern economy, replacing traditional factors of production such as land, labor, and capital.
The chapter discusses the implications of this shift for Marxist economic theory, suggesting that
traditional concepts of value and production need to be re-evaluated in the context of a data-driven economy. The
authors introduce the concept of the "neo-bourgeoisie" and the "neo-proletariat," where data owners and providers
represent new classes within the capitalist system. This theoretical framework is one of the chapter’s key
contributions, as it offers a fresh perspective on how AI and big data are reshaping class relations and economic
power dynamics.
However, while the chapter provides a strong theoretical analysis, it could benefit from more empirical
examples to illustrate these concepts. Case studies of specific industries or companies that have successfully
leveraged AI and big data for economic gain would have added depth to the discussion and made the theoretical
arguments more tangible.
In the fourth chapter, the authors continue their exploration of AI’s role in capitalist economies by
examining how platforms and big data are creating new forms of capital accumulation. They argue that the
traditional Marxist understanding of capital accumulation is insufficient to explain the dynamics of the modern
digital economy, where data and platforms play a central role.
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The chapter introduces the concept of "platform capitalism," where digital platforms act as intermediaries
between producers and consumers, extracting value through data collection and algorithmic processing. The
authors discuss how platforms like Facebook, Google, and Amazon have created new markets and forms of value
extraction, often at the expense of traditional businesses and labor markets.
One of the strengths of this chapter is its detailed analysis of how platforms use data to generate profit
and maintain market dominance. The authors effectively demonstrate how platforms have become central players
in the global economy, with significant implications for competition, labor, and consumer rights. However, the
chapter could have explored more fully the potential long-term consequences of platform capitalism, particularly
in terms of economic inequality and the concentration of power..
Chapter five explores the emerging market for big data, discussing how data has become a valuable
commodity in the digital economy. The authors analyze the different types of data markets, including the role of
platform companies in aggregating, processing, and monetizing data. They argue that big data markets are
reshaping traditional economic structures, leading to the creation of new business models and market dynamics.
The chapter also discusses the potential future of big data markets, considering both the opportunities
and challenges they present. The authors highlight the importance of data governance and regulation, particularly
in terms of protecting privacy and ensuring fair competition. They also discuss the potential risks associated with
data monopolies and the need for policies that promote transparency and accountability in the big data market.
This chapter is particularly strong in its analysis of the economic implications of big data markets. The
authors provide a clear and concise explanation of how data is being commodified and the impact this has on
traditional market structures. However, the chapter could have included more discussion of the ethical
implications of big data markets, particularly in terms of surveillance, privacy, and the potential for data misuse..
The sixth chapter shifts focus to the social and political implications of AI, exploring how the rise of AI
and big data is affecting citizenship and democratic rights. The authors argue that AI-driven technologies, by
enabling mass surveillance and data collection, are undermining traditional notions of citizenship and democratic
participation. They discuss the concept of the "splinternet," where the global internet is fragmented into different
jurisdictions with varying levels of freedom and control.
The chapter also examines the geopolitical implications of AI, particularly the competition between
major powers like the United States and China for digital supremacy. The authors highlight the risks associated
with this competition, including the potential for increased state surveillance, censorship, and the erosion of civil
liberties.
One of the strengths of this chapter is its focus on the intersection of technology and politics. The authors
provide a compelling analysis of how AI is reshaping the relationship between citizens and the state, with
significant implications for democracy and human rights. However, the chapter could have explored more fully
the potential for resistance and alternative models of governance that protect citizens' rights in the digital age.
The final chapter of the book explores the "limits of data society," discussing the potential challenges
and risks associated with the widespread adoption of AI and big data. The authors argue that while data-driven
technologies offer significant benefits, they also pose serious risks to social cohesion, privacy, and individual
autonomy. They discuss the concept of "data society," where data becomes the primary currency for social and
economic transactions, and consider the potential consequences of this shift for individuals, families, and
communities.
The chapter also addresses the potential for digital divides and social inequalities to be exacerbated by
AI and big data. The authors argue that without proper regulation and governance, data society could lead to
increased economic inequality, social fragmentation, and the erosion of traditional social structures.
This chapter provides a sobering conclusion to the book, highlighting the potential dangers of unchecked
technological advancement. The authors effectively argue for the need for comprehensive policies that address
the risks of data society and promote a more equitable and sustainable digital future. However, the chapter could
have benefited from a more detailed discussion of potential solutions and strategies for mitigating these risks.
One of the strengths of this book is its ability to link theoretical concepts with practical implications. The
authors offer a critical reflection on the limitations of classical Marxist thought in the context of AI and big data,
advocating for a re-evaluation of these theories to better understand contemporary forms of capitalism. The book's
emphasis on the "data market" as a new and transformative institution is particularly insightful, as it sheds light
on the commodification of data and its role in shaping economic and social interactions.
The authors also make a compelling case for the need to develop policies that regulate AI and big data
to protect workers and promote sustainable development. This forward-looking approach is crucial, as it addresses
the potential risks associated with AI, such as labor precarity, environmental degradation, and the erosion of
democratic rights. The book's critical stance on the role of platform companies in driving AI development further
underscores the need for a balanced approach to technological innovation that considers its broader societal
impacts
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While the book offers a comprehensive analysis of AI's political economy, there are some areas where it
could be further developed. For example, the discussion on the "limits of data society" could benefit from a more
in-depth exploration of alternative models that challenge the dominant capitalist framework. Additionally, while
the book touches on the global implications of AI, it would be beneficial to include more case studies from nonWestern contexts to provide a more nuanced understanding of AI's impact across different regions.
Another potential area for improvement is the book's engagement with the ethical implications of AI.
While the authors discuss the legal and human rights challenges posed by AI, a more detailed examination of
ethical considerations, such as privacy, surveillance, and algorithmic bias, would enhance the book's overall
contribution to the field
Political Economy of Artificial Intelligence is a significant and timely contribution to the literature on
AI and its socio-economic implications. The authors' critical approach provides valuable insights into the ways
AI is reshaping capitalist economies and social structures. Despite some areas for further development, the book
is an essential read for scholars and policymakers interested in understanding the complex dynamics of AI within
the broader context of political economy. It not only challenges existing theoretical frameworks but also offers
practical suggestions for mitigating the risks associated with AI and ensuring that its development benefits society
as a whole..
Acknowledgments
We express our deepest gratitude to the Indonesia Endowment Fund for Education (LPDP), Ministry of Finance
of the Republic of Indonesia, for funding our master’s studies.