Gary Zhexi Zhang


Interview by Sunshine Wong

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Published in June 2021

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Artist Gary Zhexi Zhang has been working on his project fud, a co-commission between Arts Catalyst and Bloc Projects comprising three distinct episodes. Episode one is The First 10,000 Years, a digital simulation narrative that is at once a hurricane observatory, financial exchange and chatroom. Zhang has just completed fud’s second episode Cycle 25, an exhibition focusing on the occult foundations of legal and financial systems.

Cycle 25 is at Bloc Projects from 4 June to 3 July 2021. In a correspondence with Curator Sunshine Wong, he plots out some of the key ideas that inform fud.

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Image courtesy of Gary Zhexi Zhang


Hi Gary! Thank you for carving out the time to hash out some of the main ideas in fud. Maybe a good question to start is: what is fud? Does it stand for something?

Hi Sunshine! fud stands for Fear, Uncertainty and Doubt. It’s generally a term used in markets to describe a pessimistic or anxious mood amongst traders. Sometimes, in hype-driven markets like crypto-currency, devotees accuse the non-believers of “introducing fud” – that is, bringing the reputation and price of the currency down with the insufficient faith. In this project I’ve been interested in belief-based structures as well as uncertainty; the way it pervades everything these days. I also like the anticlimactic way it sounds, the *fud* of speculative worlds falling over like a sack of flour.


I’m really intrigued by what it means to “predict” in your project fud, as it appears through calculation: of hurricane seeding, catastrophe bonds, and the movement of celestial bodies in relation to finance or natural events. Can you talk a bit more about what “prediction” is doing in your project?

It’s true, prediction was where the project originally started. I was interested in how history of computation and information have been bound up with a desire to know and control the future. The formal understanding of information that underlies modern computation is about quantifying the value of uncertainty and calculating things in time, whether it’s coin flips or cloud movements. Around the same time this was emerging in the 1940s/50s, you also had techno-scientific movements like cybernetics and systems dynamics which were looking to model complex systems, from human bodies to industrial economies, in terms of interactive feedback loops. These technological lineages that have been much explored in recent years, by artists like James Bridle, or scholars like N. Katherine Hayles and Paul N. Edwards, in part, I think, to understand a world system that grows ever more unpredictable. I’ve been interested in this history for some time now, because it speaks to how we enframe, calculate and operate within an uncertain world.

The historian of science Lorraine Daston comments in her book about the history of probability that, whatever we think modernity is, it probably has something to do with people feeling like they had some control over the future. I’m interested in this idea, and what comes after it, since life does not feel like that, intuitively at least, today. The only thing that seems certain is that the stock markets continue to rise, despite everything. Meanwhile we’re surrounded by predictive technologies, like most AI applications, which focus on chewing up vast quantities of data in order to influence attention behaviour or worse, impose normative social control based on all kinds of discriminatory norms. So predictions are not only anticipatory, they can also be prescriptive, as in self-fulfilling prophecies. When you act on a prediction you also intervene in the system. So the interesting thing here is, what happens when you can’t use the past to predict the future? And how do we come to terms with this uncertainty?


What you’ve described really complicates the role of prediction, so that it is no longer just forward-thinking -- or “anticipatory”, as you say -- but something we do with a material, concrete impact on the present. Can you give us an example of what these predictions are actually doing “right now”, what they look like?

I was introduced to someone who worked in risk management, specifically as a catastrophe modeling engineer at a big modeling firm in the insurance sector. They described to me how the industry uses things like “10,000 year models” to run large-scale statistical simulations of the next year’s hurricane conditions, or agricultural drought risk. The simulated versions of the near-future are used to create a value, which insurers use to price their premiums, which in turn affects property prices, especially in places which are already impacted by the climate crisis, like Miami. In a sense it’s a fairly rigorous kind of science fiction, where meteorologists and engineers make an educated guess at the probability of future catastrophes and the financial sector hedge their bets accordingly. Meanwhile, someone living in Florida who may not even believe in climate change is experiencing it through their mortgage payments. And then there’s this whole wider financial market for catastrophe bonds (or CAT bonds) and other insurance-linked securities, which see climate risk as a lucrative source of income because it’s largely ambivalent about the stock market. For them, climate change is just another source of volatility, in which they can extract rent from the ecological crisis.


The “rigorous form of science fiction” really gets to nightmarish thinking of profit-making unto death! How will these different, complex strands meet in your project?

So the project fud is an attempt to think about this “risk universe” historically and in the present crises, where prediction is “an engine, not a camera” (to borrow Donald MacKenzie’s great phrase), and  where risk is a kind of resource that is extracted from a portfolio of planetary futures. It feels like a post-enlightenment story, where, against the “modern” narrative of a rational and calculable universe, you have fragmented worlds of belief, splintered timelines, radical uncertainty, and the re-emergence of mysticism and magical thinking, not least in the form of finance itself. And of course, it’s about a deeply stratified spatial and temporal politics. Who makes these predictions and whose futures (livelihoods) are collateral? How did we get to this moment of privatised gains and socialised risk?

The project explores practices of prediction and the conceptual stakes of this universe in a few different ways. On the practical side, The First 10,000 Years, made with Agnes Cameron, is a “performative” year-long online work which plays out a hurricane simulation interface, using the same techniques as the insurance industry, as well as a simulation of a financial market that track the monetary value of each hurricane as it develops. It’s all calculated live, so the work itself is inherently unpredictable, a simulation of a simulation if you like. Meanwhile I’ve also been working with a couple of financial astrologers (they’ve both had long careers in the business, though a new breed of gen-z financial astrologer has cropped up!), learning about how they use planetary motions to predict stock market movements.

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If you like this why not read our interview with Alia Hamaoui.

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