BANI and the Participatory Panopticon

I’ve been a futurist for over 25 years, and I’ve learned that an important part of doing professional foresight work is the acceptance that much of what we imagine and speculate upon will be entirely wrong. This is fine; as I’ve said in a number of talks, part of the goal is to be “usefully wrong,” able to gather insights and make connections from otherwise off-target forecasts. That said, it’s nearly always pleasant to have a forecast map closely to real world developments (“nearly,” because some scenarios are very dire, and I desperately want to be wrong about them). 

Among the forecasts and scenarios I’ve created and made public over the years, the first one to draw real attention also turned out to be one of the most prescient: the “Participatory Panopticon.” And it turns out that the Participatory Panopticon is a valuable example of thinking through a BANI lens.

The core idea of the Participatory Panopticon is that portable technologies that combine always-on network connections, high-quality cameras, and large amounts of cheap data storage will radically change our behavior, our politics, and, in so many ways, our lives. We would be surrounded by constant observation and recording of our actions (the Panopticon part), but not just by authorities surveilling us, by our peers, both friends and strangers (the Participatory part). We’d be able to pull up archived recordings or put the video online live, and we all would be doing it.

This might sounds everyday in 2022, but I first started writing about the concept in 2003, and started speaking in public about it in 2005. Mobile phones with cameras (then referred to as “cameraphones”) had existed for a couple of years, but they were slow, very limited in what they could capture, and produced terrible pictures. At best they were on 2G “Edge” networks, so uploading even a low-resolution image could take minutes. None of what I talked about in the Participatory Panopticon would be an obvious implication of the technology of the day. There were hints, and broadly-connected examples, but nobody else had put the pieces together, at least for a public audience.

Let me be quick to note that much of what I wrote and thought about the Participatory Panopticon was off-target. I had an odd focus on always-on recording (underestimating how intrusive that would feel) and wearable tech (still a few years off, even now). But the core of the concept resonated for many: being able to document the world around us, in real-time, through a vast number of personal devices, has enormous consequences for human interaction and politics. I’ve been told that it influenced the strategic direction for human rights organizations, and helped to push the concept of “sousveillance” into more common (albeit still limited) usage.

I say all of this not as a flex, but as a way of underscoring that this is a topic I have been thinking about for a long time. Even though it’s a nearly 20-year-old idea, it still has salience. In my view, the Participatory Panopticon offers a useful illustration of what BANI can mean.

(As a refresher: BANI stands for Brittle, Anxious, Nonlinear, and Incomprehensible, and is a framework for discussing and understanding the present chaotic environment, just as VUCA — Volatile, Uncertain, Complex, and Ambiguous — was for understanding the nature of the post-Cold War/early Internet era.)

Credit: Tesfu Assefa


The “B” in BANI talks about changes that are sudden, surprising, and hard to ignore. Brittle systems seem strong but break — shatter, even — under a sufficient amount or sufficient kind of pressure. I would say that the way the Participatory Panopticon has engendered a brittle chaos is in its intersection with law enforcement. Pathological or harmful policing norms and habits that had persisted for decades remained hidden, allowing those behaviors to fester. We would have occasional stories or scandals, but it was easy for mainstream institutions to assume that these were outliers, since these episodes seemed so infrequent. 

However, the technologies of the Participatory Panopticon upended all of this, and delivered a massive blow to the ability of mainstream institutions to simply ignore the prevalence of police violence.

We’ve seen a variety of responses to the digital shredding of the cloak over law enforcement behavior. Although attempts to change laws around police accountability have been largely unsuccessful, cultural norms about the legitimate and ethical use of police power have evolved considerably. The biggest change has been the adoption of police body cameras. This was a direct counter to the proliferation of citizen cameras; that the body cameras would add to the Participatory Panopticon was likely unintentional. However, the ability of officers to shut off body cameras, the tendency for the cameras to “fail” just when needed most, and frequency with which the recoded content is held as “private” by many law enforcement agencies have only fed the growth of citizen documentation of police behavior.


The “A” in BANI points to changes that are often confusing, deceptive, and emotionally painful. Anxiety-inducing situations and conditions may result in dilemmas or problems without useful solutions, or with unavoidably bad outcomes. This is probably the most visible manifestation of BANI in the Participatory Panopticon world, as we’ve become hyper-conscious of the constant observation made possible by these tools. More importantly, many of us are relentlessly judged for our appearances and our behaviors, even if that behavior happened years in the past. 

This, in turn, has prompted problematic choices like “face tuning,” allowing for changes not just in facial structure and skin quality, but even things like ethnicity, body form, and apparent age. “Social network anxiety” is a frequent subject of mass-media attention, but in the vast majority of cases, the aspect of social media triggering anxiety is visual — photos and videos.

Arguably, many of the fears and complications around privacy can be connected here as well. The original 19th century Panopticon was a design for a prison where all prisoners could be under constant watch. That there’s now a participatory element doesn’t decrease the oppressive nature of being under permanent surveillance. Moreover, the nature of data collection in 2022 means that the surveillance can be through metadata, even through inferences known as “probabilistic identifiers,” the creation of targeted personal information using machine learning systems on “anonymized” data. In other words, the cameras that don’t see you can be just as informative as the cameras that do.


The “N” in BANI refers to changes that are disproportionate, surprising, and counter-intuitive. Input and output may not match in speed or scale. For the most part, the nonlinear elements of the Participatory Panopticon concern the exponential effects of network connections. Most of us are familiar with this; the utility of social media largely depends upon how many other people with whom we want to connect can be found on a given platform. The size and spread of a network greatly impacts one’s ability to spread a video or image around.

For many of us, this may not seem terribly chaotic in its day-to-day existence, as it’s a familiar phenomenon. The disruption (and ultimately the chaos) comes from the ability of networks like these to enable a swarm of attacks (abuse, doxing, threats, SWATting, etc.) on a particular target. 

Seemingly out of nowhere, tens or hundreds of thousands of people attack a person they’ve been told has done something wrong. In reality, this person may not even be connected to the “actual” intended target. Although such mis-targeting can arise due to error (such as being confused for someone with the same name), in too many cases the driver is malice (such as being made a scapegoat for a particular, tangentially-related, event). Even if the attacks go after the “right” target, the impact of social swarm abuse on the psyche of an individual can be devastating.


The “I” in BANI looks at the changes that might be senseless, ridiculous, or unthinkable. Changes where much of the process is opaque, rendering it nearly-impossible to truly understand why an outcome has transpired. The incomprehensible aspects of the Participatory Panopticon are non-obvious, however. The technological aspects of the phenomenon are well-understood, and the social motivation — “why is this happening?” — can often be quite blatant: aggrandizement, narcissism, politics, and so forth. What’s incomprehensible about the Participatory Panopticon is, in my view, just what can be done to limit or control its effects.

One of the cornerstone arguments I made in the original public presentation of the Participatory Panopticon idea was that this situation is the emergent result of myriad completely reasonable and desirable options. I still believe that this is the case; each of the separate elements of a Participatory Panopticon (such as the ability to stream video or instantly map locations) have enormous utility. Moreover, the social (and political) value of a mass capacity to keep an eye on those with institutional, economic, or social power has become critical. This compounds the inability to take useful steps to mitigate or eliminate its harm.

Admittedly, this last element of BANI in the Participatory Panopticon isn’t as direct or clear as the others. We could instead simply argue that specific drivers of a chaotic world need not check each of the four BANI boxes; just being a catalyst for increased brittleness in social systems or anxiety among citizens may be enough.

The Participatory Panopticon has been a concept woven into my thinking for nearly two decades, and to me represents one of the clearest examples of the way in which technological developments can have enormous unintended (and unexpected) impacts on our societies and cultures — which then, in turn, shape the directions taken by developers of new technologies. 

BANI, then, serves as a lens through with to examine these impacts, letting us tease out the different ways in which a radical shift in technology and society can lead to a chaotic global paradigm. We can then look at ways in which responses to one arena of BANI chaos — other forms of brittleness, for example — may help us respond to the chaos engendered by the Participatory Panopticon.

Giving a name to a phenomenon, whether the Participatory Panopticon or BANI itself, is a way of giving structure to our understanding of the changes in our world. As I said above, it’s a lens; it’s a tool to focus and clarify our view of particular aspects of the changes swirling around us. It’s not the only tool we have, by any means. But if giving names and structure to the increasing maelstrom of chaos we face helps us see a path through, the value of that tool should not be underestimated.

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A Taxonomy of Chaos

Being a futurist is quite a bit like being a historian. History isn’t just a listing of events, it’s a discipline that seeks to figure out why this or that happened, what led that direction, and what choices we had along the way. The same thing can be said for foresight work — the goal isn’t to list future events, it’s to get a better understanding of why we’re getting various outcomes, and how our choices can lead us in very different directions. I think of futurism as Anticipatory History.

The success of this process depends upon our ability to spot patterns; as Theodor Reik said, “It has been said that history repeats itself. This is perhaps not quite correct; it merely rhymes.” But what happens when the rhyme scheme breaks? That is, what happens when our expectations about patterns start to fail?

I’ve been working as a futurist for over 25 years, so I’ve spent quite a bit of time observing (and learning from) global patterns. About five years ago, I started to get a sense that patterns weren’t repeating (or rhyming) as readily, that big global systems that had once been fairly consistent had become far less so. Looking back, I suspect that the primary catalyst was the accelerating impact of global climate disruption.

Big economic, political, environmental, technological, even sociocultural systems seemed like they were starting to fail, or at least become much less reliable. I wasn’t alone in these observations.

In 2018, I started working on a framework for understanding the scale of what we’re facing as once seemingly-reliable global systems started to break down. So many of the people I spoke with over the past half-decade had started to express great surprise and confusion about what was going on around the world; it quickly became apparent that this wasn’t just the standard “the future is an unknown” that we all live with, it was an increasingly desperate sense that things we thought we understood were spinning wildly out of control. We couldn’t as reliably make reasonable judgments about what was to come in the weeks and months ahead. Systems that appeared strong were suddenly on the verge of collapse; processes that were becoming increasingly critical to our daily lives were becoming less and less understandable.

Creating a framework like this wasn’t just a random idea; I was trying to bring a conceptual tool already in the foresight analyst’s kit into the 21st century. The world of strategic consulting had long relied on a basic framework to offer language and structure to a changing world. It was the “VUCA” model, which was  invented in the late 1980s at the US Army War College and spreading quickly throughout the world of consulting. VUCA is an acronym comprising four descriptive terms: Volatile; Uncertain; Complex; and Ambiguous. For a world moving out of the Cold War era and into the Internet era, these terms felt right. They perfectly captured the kinds of disruptions that were starting to happen more often, especially as the global war on terror fired up.

But the world has rocketed past merely being “uncertain” or “volatile.” At this point, VUCA no longer captures disruptions to the norm, it is the norm. But if a VUCA world is all around us all the time, the term has lost its utility as a way of labeling discontinuities in how our world functions. Something new was needed.

In late 2018, I presented the “BANI” framework for the first time. BANI parallels VUCA, in that it’s a basic acronym for a set of descriptive terms. In this case, however, the terms are as subtle as a brick. BANI comes from: Brittle; Anxious; Nonlinear; and Incomprehensible. These four concepts let us articulate the ways in which the world seems to be falling apart. It’s a taxonomy of chaos.

Credit: Tesfu Assefa

The quick summary:

B in BANI is for Brittle. Systems that are brittle can appear strong, even work well, until they hit a stress level that causes collapse. Brittle does not bend, it breaks. Very often the breaking point isn’t visible to most people in advance, and comes as a surprise. Sometimes this is because the weaknesses are hidden or camouflaged; sometimes this is because the stress that causes the break is external and unexpected. The example I like to use is guano, fecal matter from birds and bats. In the 19th century, its use as a fertilizer gave the world its first taste of an agricultural revolution. It was so important that countries fought wars over ownership of guano-covered islands. And in a few short years late in the century, that all disappeared after the development of the Haber-Bosch process for making artificial fertilizer. Something that was absolutely critical became worthless seemingly overnight.

Brittle chaos is sudden, surprising, and hard to ignore.

A is for Anxious (or Anxiety-inducing). Systems that trigger anxiety are those that pose dilemmas or problems without useful solutions, or include irreversible choices that have unexpectedly bad outcomes. Anxious systems make trust difficult, even impossible. Things that had been well-understood suddenly seem alien or false. My usual example of an anxiety-inducing system is malinformation, the term that encompasses intentional misinformation, errors, insufficient information, and confusion. Noise in the signal. The last half-decade has been full of this, and we’ve seen some especially powerful uses in recent months and years. Malinformation often relies on technological tools, but the importance doesn’t come from the technology, it comes from the human response. In many, if not most, cases, malinformation isn’t used to make a target believe something that is false, it’s to make a target doubt the validity of something that is true.

Anxious chaos is confusing, deceptive, and emotionally painful.

N is for Nonlinear. Nonlinear systems are those where, most simply, input and output are disproportionate. Cause and effect don’t match in scale or speed. Audio feedback is a familiar example of a nonlinear phenomenon; the spread of pandemic disease is another. Nonlinear in the BANI usage refers to systems that see changes that don’t match expectations built on familiar reality. They’re common in nature, although often met by countervailing forces that keep the nonlinear aspects in check. The biggest (and most important) example of a nonlinear phenomenon is climate disruption, more precisely the hysteretic aspect of climate change. Hysteretic means a long lag between cause and effect, enough so that the connections are often functionally invisible. The connection between atmospheric greenhouse inputs and temperature/heat-related results is slow — potentially on the order of 20-30 years, although some more recent evidence suggests that it might be close to 10 years. Either way, the seeming disconnect between cause and effect means that (a) what we’re seeing now is the result of carbon emissions from one or two decades ago, and (b) whatever changes we make to cut carbon emissions won’t have any visible benefits for decades.

Nonlinear chaos is disproportionate, surprising, and counter-intuitive.

Finally, the I is for Incomprehensible. I got the most pushback on this one — can we really say that something is truly incomprehensible? But what I mean here is that, with an incomprehensible phenomenon, the process leading up to the outcome is thoroughly opaque, with difficult or incomplete explanations. The decision-making of machine learning systems gives us a current example. Increasingly, it’s difficult at best to explain how a deep learning system reaches its conclusions. The consequence can often be that sophisticated systems can make strange or inexplicable errors (such as a self-driving vehicle repeatedly mistaking the moon for a traffic signal). Incomprehensible can also mean behavior outside the realm of rational understanding.

Incomprehensible chaos is ridiculous, senseless, even unthinkable.

Credit: Tesfu Assefa

When I created BANI, I did so largely as a way for me to visualize the diverse ways in which global systems were failing. But it turns out that there’s hunger around the world for just this kind of framework. Over the past year, I’ve given a dozen or more talks and presentations on BANI for audiences everywhere from Amazonia to Zürich (people in Brazil seem especially interested); in the coming months, I’ll be speaking about BANI for audiences in places like Sri Lanka.

But it’s important not to overpromise what the BANI framework can do. Thinking in BANI terms won’t give you a new leadership strategy or business model. It won’t tell you how to better make profit amidst chaos. When I talk about what can be done to withstand the chaos of a BANI world, I go to human elements and behaviors like improvisation, intuition, and empathy. The chaos of BANI doesn’t come from changes in a geophysical system or some such, it comes from a human inability to fully understand what to do when pattern-seeking and familiar explanations no longer work.

Even if BANI is only descriptive, not prescriptive, we’ve long known that giving a name to something helps to reify it. People had been groping for a way to articulate their sense of chaos, and BANI provides a common, understandable language for doing so. BANI helps to give structure to our experience of the chaos swirling around us, and in doing so, helps us to consider more fully what to do next.

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