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Political Science in the Age of Artificial Intelligence

Political science, probably like many other social sciences, seems stuck in an age that many of our students have never lived, and will never live. Our students live in an age of Artificial Intelligence (AI) and of problems that are far beyond local borders in a world dominated by thinking within borders.

In this age, it is time to work together on a global scale and to develop the Large Hadron Collider (LHC) for political science. This political science LHC would build on the recent developments in machine learning, deep learning, neural networks, and bring together thousands of political scientists and academics from other disciplines to start understanding political dynamics at a planetary scale.

I use the “LHC” as metaphor for an endeavour where large-scale collaboration of people of diverse backgrounds,  use of new technologies, and fast and open science come together with one purpose: to understand and provide ideas for a world that is evolving so fast that our local political systems and global institutions cannot follow suit unless political science evolves at the speed of society and technology.

Why do we need a political science LHC?

The World Wide Web is here because academics wanted to collaborate to build humanity’s largest machine – the LHC – to study the universe’s smallest particles. This machine is revolutionizing our understanding of physics, advancing engineering to levels unknown a few decades ago, and showing how seemingly outlandish theoretical physics can be tested when a large group of people collaborates to construct and run an outlandish machine while having another large group of people that can make sense of unprecedented amounts of data.

At the same time, as a ‘by-product’, the LHC led to the creation of the internet that we know today and that is changing societies beyond recognition. Technology-driven solutions are what is shaping today’s political and social reality.

In comparison to the 21st century science around the LHC, my discipline – political science or social science at large – feels stuck in the middle of the 20th century, with little glimpses to 21st century ideas because some of my colleagues have started to leave the borders of narrow ideological institutions, beyond the established working groups in professional associations of political science – national or international – and beyond the boundaries of faculties that still educate students like they used to do when Google, WeChat and the Ethiopian space program did not yet exist.

Faculty today does not mean, in many instance, collaboration at the scale of technological advancement. It mostly means turf war. The same seems true for professional associations.

The established political theorist does not trust the quantitative methods postdoc because she prefers numbers over meaning. The political systems PhD does not want to collaborate with the international relations professor because of some obscure epistemological difference in world view that has been breeding over the last 100 years. And the Canadian ethnographic researcher studying a local community and its politics in The Gambia never meets the IR ethnographer from Vietnam who walks through the halls of UNESCO to study the weird global culture of diplomatic politics.

At the same time, technology developed in California, in a political and social spirit of innovation, is copied and perfected in China because of a combination of national policy and local industry development. The radical political shift towards renewable energy paid by German tax payers is partly responsible for revolutionizing the global distribution of solar and wind power, allowing for new energy policies and much less costly political decisions in other countries around the world.

The historical evolution of nations and borders usually credited to the Peace of Westphalia is still the most powerful idea dominating most politics around the globe while AI-enabled automatic translation and cross-border migration are reframing how many people perceive, shape or resist a world in which cultural differences and the value of nation states are shape-shifting beyond comprehension. This is why the political system of ISIS is influencing security policy across Western political systems. This is why the ‘Panama Leaks‘ story could combine global financial flows, morally corrupt individuals from around the world, international journalistic cooperation and political reactions at national and international scale.

The LHC of political science takes all this together and combines it into a connected research programmes linking the smallest socio-political dynamics with politics on a global scale.

Knowing the complex and conflictuous political history of our planet; knowing the path dependency created by ideas, languages and institutions and the disruptive changes that still happen from time to time; knowing how human beings are both rational and irrational, biologically programmed and socially shaped; and observing the massive technological and related socio-economic changes of the past century, in particular the the advent of AI, one of the questions that we need to answer could be:

Is it possible to advance at the current speed of technological evolution without losing the ability to shape humanity’s destiny through collective human decision-making that we think of in terms of traditional politics?

You may ask: What does AI have to do with all of that?

My answer is simple: We are probably approaching a time when AIs know better about our individual, cultural and political preferences than politicians have ever known in the history of our political systems. Depending on the reach of AI(s), they will be able to analyse and deduct from individual interests and collective dynamics reaching from local, culturally close groups to the aggregated global system of humanity, beyond comparable abilities designed into traditional political institutions.

There are two options coming out of this advent of AI for future political systems:

There may be those political systems in which traditional politics makes use of this knowledge and policy recommendations generated by AI to shape our collective destiny (or destinies).

The other political systems might be the ones where the AI(s) take(s) over completely, maybe because we will collectively trust these all-encompassing new technologies more than the bounded rationality and limited knowledge of our human representatives, or because the AI simply takes over.

This raises further questions:Can we even shape where all this is going, for example by sending people’s ambassadors to global companies who design AIs like Denmark? Is a culturally divided but technologically interdependent humanity even able to organize meaningful collective action that is successful enough to influence how AIs shape the planet? Or is it even unnecessary to try this because AI-system as the new political systems will represent our collective will anyhow?

Will we give the nuclear launch codes to our AIs and let them decide to start global wars like we give AIs the power to decide on drone strikes? Will we, in the future, elect the best decision-making machine to lead our global institutions, simulating all possible decisions to agree on the best possible option for all humans, all cultures, all technologies?

To answer these questions, we need to build a new type of political/social science research organization, one like CERN for physics, but adapted to the knowledge and social realities of 2017 and the years to come.

We need to be fast and we need to work against the old social system of academic knowledge generation – build up reputation for 20 years, become a professor and then pass on your existing knowledge and decide over what get’s published and what doesn’t until you die.

Instead, we need people with various skills, from theory to practice, from big data to micro-ethnography, from introvert analysts to extrovert talkers, from those who are creative to generate knowledge to those who are creative to communicate it audio-visually, from the experienced researchers who know how to run effective research operations to new researcher who know how to run new technologies.

We need to include people of all cultures, genders and social background,  embedded both in local and in global society, because we need to be as good as the present and future AI(s) – or we need to be able to make intelligent use of AI in various cultural and political settings – if we want to be able to understand what’s going on in our societies and to help shape future technological advancement so that it reflects human and humanity’s interests.

To answer these questions, we need a collective exercise and theorise within and beyond existing schools of thought, do empirical research within and beyond existing borders, go for data analysis at the scale of AI far beyond human capabilities and at the scale of intersubjective human understanding.

And we need open science. Knowledge production may remain complex and long-term but the results have to circulate fast. Intermediate findings have to be immediately discussed and  knowledge about arcane developments at one end of the world are made accessible in fast and meaningful ways to researchers at the other end of the world. Only open social science will be able to keep up with the speed of technological evolution.

This all may sound a little over the top, but seeing how slow and how disconnected  from technological advancement most of the social sciences seem to work today, I’m convinced that our generation needs to change this. Either we start building the political science equivalent – or social science equivalent, if you want – to the LHC now, or we may miss to jump on a train that is accelerating fast.

This probably needs big money. We don’t need these large sums to pay exorbitant salaries to a few self-declared academic leaders but we will need it because we have to be many and we need to work together in new way. This probably means using both public and private funding, or combining resources from both worlds as borders between the two are anyway disappearing where global-scale corporations compete alongside global-scale public organizations.

We need those funds because we have to invest in technology adapted to the requirements of a social science that works on a global scale, that collaborates beyond disciplinary borders and that can stand up to the AI revolution that is on our doorsteps. This means communication   between well equipped research facilities around the world, combining languages, social science disciplines and local and global knowledge.

We need translation technology that works so that insights from minority languages can be injected into global research questions, and vice versa. We need data analysis facilities that can run calculations at the scale of planetary humanity while we need ethics ombudspersons around the world who can ensure that research respects cultural differences while new knowledge is generated.

We need to pay for new people to join the research endeavour regularly and to make everybody learn and adapt, simply because technology will be advancing faster than ever before.

And we need money to ensure that those working with us can still live social lives, take timeout to get children, to care for their parents and friends, to take creative timeouts, to return to their local communities or global societies not to lose touch while working on a big research endeavour, short: we need researchers to live humanity while going with the technological times.

Thus, it’s time to start constructing the social science CERN and build the political science LHC. It’s time to turn our current academic system upside down so that we social scientists turn towards those who are already shaping the future of our planet. If we want it or not, those working on technology beyond our imagination – in China, in the USA or wherever else – they are already rushing ahead. Only when social science travels at their speed, works with them or at least understands what is going on, can we design political systems that keep up with where technology will be in 5, 10, or 50 years.

This essay is a experimental, summarizing ideas that aren’t fully thought through but that have grown over my time inside and outside political science as a profession. Feel free to discuss and to contradict. And if you are already building the social science CERN: I’d be happy to know about it and eventually join.

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