Rise of China complicates ‘authoritarian’ vs ‘democratic’ binary
There is growing unease in how we describe political systems today. Words that once seemed clear no longer illuminate as they should. “Free”, “democratic”, “liberal” and “authoritarian” are among the most commonly used terms in political discourse, yet their meanings have become increasingly blurred and contested.
This is not simply a matter of semantics. It reflects a deeper mismatch between the language we use and the realities we are trying to describe.
The problem is not new. In George Orwell’s Nineteen Eighty-Four, published in 1949, he warned of a world where political language is stripped of precision and repurposed to shape perception rather than convey truth. While today’s discourse is far more open, that concern is increasingly loud in the way political labels are deployed – less as analytical tools and more as signals of approval or disapproval.
For much of the post-Cold War period, the vocabulary of “liberal democracy” carried both descriptive and normative weight. It described a system of electoral competition, rule of law and individual freedoms, but also implied a direction of travel for the rest of the world.
Countries were often assessed on how closely they approximated this model, on the assumption liberal democracy not only conferred political legitimacy but also expedited economic development and enhanced social well-being by enabling individuals to feel free to pursue their aspirations and realise their potential.
Within that framework, “authoritarianism” became its opposite: a system assumed to be rigid, repressive and ultimately inefficient. A widely held belief was that such systems, by restricting information and suppressing dissent, would struggle to innovate and adapt in a fast-changing global economy.
The trajectory of China over the past two decades has complicated this assumption.
A recent Foreign Affairs article revisits this debate, introducing “smart authoritarianism” to explain how China has combined strong political control with remarkable technological and industrial progress, including in robotics, electric vehicles, batteries and artificial intelligence.
The term is revealing. It acknowledges that earlier assumptions of authoritarian systems being inherently incompatible with innovation no longer hold. At the same time, it preserves the original framework by modifying the label. When reality no longer fits the category, the category is stretched.
The debate has moved on. It is no longer only about whether China’s “authoritarian” system can succeed, but whether its success might encourage others to follow. The concern, increasingly expressed in Western commentary, is that effective alternatives to liberal democracy could reshape global norms and governance.
This points to a broader issue. Political systems are multidimensional arrangements. Yet, the labels we use to describe them tend to collapse that complexity into a single axis. A country is described as either democratic or authoritarian, free or not free, and at times “partially free”, as if these were comprehensive explanations rather than partial descriptors.
Convenient labels don’t tell us how power is organised and exercised, policies are formulated and implemented, markets and states interact, risks are managed and long-term objectives are pursued. Reducing these differences to a binary set of labels is analytically limiting. It obscures the mechanisms that drive outcomes.
This matters because the world is entering a period of structural change. The geopolitical landscape is shifting, supply chains are being reconfigured and technological competition is intensifying. Also, global challenges such as climate change demand coordinated, long-term responses that test the effectiveness of governance models.
In such an environment, understanding how systems work is more important than categorising them. Consider innovation. It is shaped not only by freedom of inquiry, but also by factors such as investment levels, industrial policy, talent development, infrastructure and the ability to scale up new technologies. Different systems may combine these elements in different ways, with varying trade-offs between flexibility and coordination.
Or consider the energy transition. Moving towards a low-carbon economy requires aligning policy signals, private investment, regulatory frameworks and technological deployment. Success depends less on whether a system is labelled “liberal” or “authoritarian” than on whether it can create the conditions for a sustained large-scale transformation.
This suggests a more useful approach is to move beyond labels and focus on governance capabilities. How effectively can a system set direction and maintain policy continuity? How well does it coordinate across sectors and stakeholders? Can it mobilise capital and manage risk? Does it generate trust and predictability for businesses and citizens? These are the questions that determine outcomes. Labels, by contrast, offer only a shorthand and an increasingly inadequate one.
This is not to argue that values do not matter. Concepts such as freedom, accountability and participation remain fundamental to how societies organise themselves and citizens experience governance. But as analytical tools, these concepts need to be applied with greater precision and nuance. Otherwise, language risks become a substitute for understanding.
When “authoritarian” is used to explain both weakness and strength, or when “democratic” is invoked without examining performance, the terms lose their explanatory power. We are caught between an old vocabulary and a new reality. The rise of China – and the evolving nature of global competition – has exposed the limitations of the categories we inherited from an earlier era.
Adapting to this new context requires more than updating terminology. It requires a shift in mindset from classification to analysis, from labels to mechanisms, from assumptions to evidence. Only then can we begin to describe the world as it is, instead of reinforcing the biases embedded in the language we have so readily used.
Contributed by Prof. Christine Loh. The article was published on SCMP: