goal17 Podcast

TL;DR - The compounding consequences and constitutional violations by DOGE should be a call to action for practitioners of multi-stakeholder work, which needs to prove it can move quickly and decisively in complex environments in order to avoid future chainsaw approaches to government reform.

We seem to be in a moment where you have to work especially hard to find some cause for optimism, but in that spirit, today I want to look at the US Department of Government Efficiency, or DOGE, for a bit of a silver lining. While the whole thing might look like a train wreck, what I want to know is: can we learn anything from it?

Many Canadians like myself are watching in dismay as the administrative state of our neighbour to the South is being hacked to pieces, with the many checks and balances that have held them together for centuries are dismantled at a record pace.

While Elon Musk’s slash and burn tactics at Twitter caused some disappointment in the loss of what was - for some - a beloved platform, they were also a source of schadenfreude as the scattershot cuts destabilized the site, alienated users, repelled advertisers and violated a host of legal obligations. It was easy to sneer as Musk’s ham-handed tactics failed to account for the social, technical and legal complexities of running a modern social media platform.

But government is another animal entirely.

A few years ago I read Michael Lewis’s book The Fifth Risk, which stemmed from a column he had been writing about the various functions of US Government Agencies. Lewis began writing the column because he realized that at this stage, many Americans had no idea what agencies like the US Department of Agriculture or the Department of Energy actually did. His research happened to be ongoing when the first Trump transition took place, so he saw first hand as critical fumbles took place with the machinery of government took place, such as an employee finally going home with the nuclear codes when no one relieved him of duty.

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While in many Western countries there has been a narrative for years that government should be run more like a business, the fact is that no businesses exist that have both the obligation to service and the level of complexity that governments have. While business may have some practices and principles to be applied to elements of government, the idea of simply “running it like a business” is like saying you should run a railway like a bicycle - sure, they both have wheels and move things, but they exist for very different reasons.

At the same time, I think that it is important to recognize that political moments don’t just appear out of nowhere. The narrative of porting business into government, I think, comes in part from the view that businesses face a kind of Darwinian pressure to deliver that governments don’t, meaning that organizations that fail to deliver simply cease to exist. While this is debatable, I think it reflects a growing sentiment in Western democracies that governments are increasingly expensive, inept and incapable of change.

Enter Elon Musk

With his very subtle chainsaw metaphor, Musk has, in very short order, made more changes to the US government than, I think, anyone would have thought possible. Entire agencies shuttered, whole functions erased, and tens of thousands of employees sent packing. Clearly the business principle he is bringing in is “Move Fast and Break Things” - the early motto in Facebook used to experiment, iterate quickly and adapt based on results. In this case, cut everything, and if any of that causes a problem, switch it up and keep moving. Instead of debating what might happen, make the change and find out, then make more changes based on what you find out.

But as we’ve seen, the stakes are somewhat higher with the US Government than with, say, a micro-blogging platform. We’ve already seen programs to prevent ebola get briefly cancelled, workers who maintain nuclear weapons get furloughed and those responsible for fighting forest fires get sent home.

“Breaking things” on Twitter might cause some slow load times or a glitchy livestream. With the government, breaking things might mean nuclear disaster or a global pandemic.

Silver Lining

So, you may be asking; where is that silver lining I was talking about? What Musk has demonstrated is that, well, it turns out rapid change is possible in government. It also demonstrates one possible method for doing it, and a host of lessons that we are likely only just beginning to be able to learn from.

I’ll say up front that taking a chainsaw to a set of functions you don’t understand that affect the lives and wellbeing of millions of people is a terrible idea. It is almost inevitable that something very bad will happen.

I do think, however, that it is worth being specific about why it’s a bad idea, and also, if there’s anything that we can learn from it.

Why Chainsaws are Bad for Surgery

The four main issues with Musk’s approach are around risk, complexity, authority and purpose.

First, with risk, there does not seem to be any weighting to account for how much caution should be taken relative to the risk of the functions they are playing with, whether immediate - in the case of nuclear weapons - or long term, as in the case of kneecapping research. Generally, one would assume that the greater the risks involved with an effort, the more effort should be put into mitigating those risks. While juggling rubber balls and juggling chainsaws are both juggling, most would approach the latter with a bit more caution than they might the former.

Second, making changes becomes more fraught in complex environments where second and third order effects might not be immediately obvious. Governments in general, and the US Government in particular, are highly complex, navigating a wide array of responsibilities, legal requirements, security considerations as well as constitutional and treaty obligations. Given the status of the United States as the world’s pre-eminent superpower, there are also a web of geopolitical implications that extend far beyond the nation’s borders. Governments span a dizzying array of functions, with responsibility sometimes spanning across agencies, and systems of varying vintages supporting all kinds of mission-critical processes which are, in many cases, poorly documented, if at all.

Third, as is becoming increasingly clear, Musk’s group appears to lack the necessary authority to carry out their efforts. As he moves from agency to agency, cancelling contracts, seizing data and laying off staff, the justice system has been following, identifying a litany of legal, employment and constitutional violations.

Finally, one of the factors that is animating opposition the most with DOGE is the lack of any clearly defined purpose in their actions. While “efficiency” is often touted as an end in itself, it is actually simply a measure of the resources required to achieve a specific goal within a set of constraints. What is happening with DOGE, however, is the wholesale dissolution of functions because the goal is deemed unimportant, rather than finding the approach inefficient. Further, having a private citizen who is a recipient of significant government funding and whose activities are regulated by agencies he is now influencing creates - I’ll be generous - a lack of clarity on what the objectives, decision criteria and guiding principles of DOGE’s activities might be.

Speedrunning Complexity

When I first started in consulting at Capgemini Ernst & Young, I was in a group called the Accelerated Solutions Environment, which was based on the MGTaylor method, which I still use to this day. Most of the major consultancies still have some variation of this method somewhere in their mix of offerings - with notable investments by PwC, KPMG and Oliver Wyman building out their capabilities and Capgemini continuing with its own.

The conceit of the method, as we practiced it then, was to compress decision making in complex, high risk situations by gathering all the “right” people (decision makers, influencers and implementers) in a room, giving them access to all the information they would need, and running them through an intensive, three day, highly iterative process that would end in a decision and a plan to move forward.

There was obviously a lot of marketing jargon we built around the offering - “months or years of work in three days!” - but there was actually something to it. If you add up all the meetings, emails, working groups and conference calls, making a major policy or strategy change can take AGES. Not to mention that over time, groups tend to lose the plot and settle on the easiest answer. So, compressing that process, and making sure that everyone who either had knowledge or influence was in the room and fully dedicated to generating an outcome actually can allow for a significant amount of acceleration.

The challenge was that getting leadership teams to fully sign on to an intensive process where stakeholders of varying levels would roll up their sleeves side-by-side was always a tough sell. And in many multi-organizational processes, stakeholders would rather send subordinates to consult than to send decision-makers to commit.

What we’re seeing with DOGE, however, are the consequences of not being able to make meaningful change in complex environments on a meaningful timescale. What DOGE has succeeded in doing is making significant change non-negotiable and unavoidable, which is, actually, rather significant.

Due Process

This, to me, is where the idea of “due process” in decision-making is so important. The justice system accepts that in order to render judgement in a criminal proceeding, there are certain considerations that should be made, certain rules and procedures that should be followed, and certain types of evidence that should - or shouldn’t - be brought in to the decision making process if it is to be considered fair.

There is also the imperative built into the justice system that, however exhaustive the process might be, the end result will be a decision.

For anyone that has been involved in a “public consultation” or a “strategic review” in government, however, or even a multi-stakeholder process, there is not necessarily the same imperative. A lengthy process might end in a series of recommendations. Inter-agency talks might end up deadlocked. Inexpedient evidence might be ignored, and turf battles might undermine processes completely.

So, to learn from the DOGE example, and imagine how we might do things better to make change across our public services, the question becomes, how do we address the complexity of public services while at the same time running a decisive process that produces provably better results for citizens?

I fundamentally believe that a multi-stakeholder approach is the best way we know to address all of the interdependencies in a modern government. It’s not really rocket science to suggest that if you are going to make major changes to something like, say, forestry services, you should involve those responsible for leading them, but also those familiar with actually delivering those services, those who understand how they intersect with urban environments, how climate change might affect the future and so on. If a service is meant to solve a problem, it doesn’t seem crazy to consider all aspects of that problem to make a decision about how to address it. But complexity shouldn’t be a license to “agree to disagree.” At some point, a decision needs to be made, and that decision, ideally, should reflect the very best of our knowledge of the issue.

Those in my industry know that a well designed process with the right people in the room focusing on a problem uninterrupted, with the right information at hand and working through tight, iterative cycles can solve enormously complex problems in a matter of days, if properly supported. Which is to say, from a process perspective, it is absolutely possible to make good decisions very quickly about highly complex, interconnected issues, if certain conditions are met.

The complexity and risk elements that DOGE gets wrong are mitigated simply by ensuring that the right stakeholders, with direct knowledge, influence and decision-power over the issue are involved in the process.

Having a well defined purpose for the change is absolutely fundamental to the success of the effort, and is not only a major driver of what DOGE is getting wrong, but is also why so many change initiatives go off the rails. Clarity on the purpose, in this case, comes both from a definition of why the change is being made, but also rooted in why the function being changed exists in the first place. A lack of coherence in either of these areas is almost a guarantee of a poor decision. Why does NOAA exist? Why does the Department of Education exist? What outcomes are they designed to create? If we don’t know what, specifically, they are meant to do, it is very difficult to meaningfully change them, or even to make them more efficient. If cutting back on researchers doing weather modelling saves millions, but exposes us to billions more in damage from weather events, is that more efficient? Because there is a dissonance there, it also means everyone in the process becomes naturally suspicious of the purpose of the change effort itself - are we really working towards efficiency (achieving the same outcomes with fewer resources), or are we just not interested in those outcomes any more? Have we just decided that we’re better off when hurricanes and tornadoes are a surprise?

I cannot stress enough how important that clarity of purpose is - it is foundational to any kind of intentional change.

What DOGE almost gets right, and where a lot of multi-stakeholder processes fall apart or end up stuck is on the authority front. I say DOGE gets this almost right because, by simply pretending that they have the authority, DOGE has, indeed, been able to make changes at a scale and pace that were, to me, previously unimaginable. I also say almost, because it seems that they don’t actually have that authority, and are, more or less, violating the constitution.

But as a thought exercise, an interagency body tasked with change that has the authority to make final decisions is a powerful tool, if it were to exercise that power according to an acceptable set of processes. Similarly, having the necessary stakeholders in the process include decision makers that are obligated to make a decision - like a collaborative form of binding arbitration - could still preserve autonomy in such a process.

This, to me, is what caught my attention as Elon waded into the government with his chainsaw, and it is also what is so tragic about how the opportunity is being squandered by his haphazard approach. Whether it is in Crown-Indigenous negotiations, the creation of Digital Services in government or even changing policy on waste disposal, the proximity of authority in stakeholder processes prevents them from being decisive, and the removal of decision-pressure allows procedural drift and a lowering of expectations that becomes corrosive over time. If you know a process is just for show, or has no stakes, you know you don’t have to take it seriously.

Move Fast and Fix Things

The optimist in me hopes that we can use the shock of the current moment to put energy into really fixing things. The Trump administration only became possible in a timeline where frustration, stagnation and a lack of confidence in our collective ability to make things better have all been festering under the surface. Throughout Western democracies, our perceived inability to make change is giving space for leaders who gain power with little more than a promise to burn it all down.

We already have the tools and methods to move quickly; we just need to use them with courage, proving to ourselves that we can be decisive without being destructive.

I have spent the better part of my career working with individuals, organizations and groups to make better decisions. There are, of course, so many ways to make a decision, and there is also a lot of lore around decision making and, by extension, leadership.

As a consultant, I found over the years that a large part of the value I could bring as an outsider was in helping a group to test and challenge assumptions that they may have become blind to. It happens to all of us. But because of the nature of consulting, and the fact that people rarely hire a consultant when everything is going great, I found that actually the ability of a group to discern the facts in front of them and to make decisions accordingly became a pretty key indicator of whether they would succeed or not - especially when they were faced with changing or challenging circumstances.

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The difficulty, in many cases, is that there is rarely an immediate and linear relationship between a decision and the result. I’ve always loved John Sterman’s paper, Nobody Ever Gets Credit for Fixing Problems that Never Happened, for its explanation of why managers that spend their time putting out fires get more credit that those that prevent them, especially because of the role that delays play in that dynamic.

We are hardwired to discern cause-and-effect relationships; it is how, from infancy, we learn to navigate the world. Where we struggle is when the effects are complex, or, when they are delayed. The results of the decisions we make might not become apparent for some time, and when they do emerge, we might even attribute them to some other cause, or write them off as “unintended consequences”. This reminds me of another classic John Sterman line: “There are no side effects—only effects.”

In very large organizations, in protected industries and in governments, there might be enough of a buffer between us and the consequences of our decisions that we might spend an entire career working on faulty assumptions and still enjoy personal success. I have worked with many organizations that managed to do well enough with the status quo, and with individuals who just hoped to retire before the bill came due.

After many years of working with startups, I found a very interesting counterpoint to that dynamic. Because many startup companies are extremely resource-constrained, the inability to test your assumptions is generally seen as an existential threat, to the point where I would often consider it a negative for a young company to have too much funding; it would keep them from having to validate their assumptions for too long, and they would have more difficulty finding traction. Many startups now use variations on rapid hypothesis-testing frameworks to formalize their ground-truthing process, as the longer they spend tuning their approach, the more likely they are to go bankrupt.

Finding Truth

Now, there are two things happening in these cases that reflect two kinds of truth. First, in the case of startups, in the initial years as they try to build teams and woo investors, they are trying to create a shared narrative, or shared truth. Shared truth is an essential element of collective action - coordination and collaboration is almost impossible without some kind of consensus reality.

There is also the interaction with objective truth, or objective reality itself. History is littered with states, companies and cults that had done a great job of convincing themselves of a truth that, in the end, did not serve them well in navigating the real world.

As far as decision making is concerned, shared truths are what bind groups together in choosing certain actions, and the delays in feedback between those shared truths and objective truths are what allow them to persist over time when there is a misalignment.

I bring this up now because I believe that we are, as a species, in an existential crisis of mounting consequences, and in Western societies, at an inflection point in whether we are able to navigate the future successfully.

Fragmented Futures

Last year, I wrapped up a project with the United Nations Environment Programme (UNEP) to explore possible futures through a foresight process. As a science-based agency, UNEP typically pursues its planning through evidence-based forecasting, essentially, by taking objective measures of the current state of the environment, making projections into the future, and planning action accordingly. They decided to undertake a foresight process because of an acute awareness that there were a host of non-scientific factors that might influence whether or not we would take appropriate action to protect our biosphere from destruction. I say that with tongue in cheek as a massive understatement.

Scientists spend their lives in pursuit of objective truth, but decisions tend to dwell in the domain of shared truths.

The exercise we undertook was to explore four possible future scenarios and to flesh them out in detail in order to evaluate the probabilities involved, the desirability of each and the actions that might be required to prevent some of the worst from happening.

The scenario I focused on was “Post-Truth Division”, which we detailed with a somewhat harrowing dissolution of democracy and collapse of Western democracies. You can find the report here if you’re interested.

As my group detailed the all-too-plausible-and-already-underway collapse in social cohesion, we came, again and again, to a single root cause: the loss of shared truth.

Democracy works when enough people agree on a version of reality and a sense of shared truth. Polarization becomes problematic because what we are seeing is not a simple disagreement on policy, but a disagreement on reality, in which various factions hold their own truths that are not compatible with others.

While my work with social media companies had already made me suspect we had a problem, playing out this scenario made me very concerned about where this path would lead us, and that concern was solidified in my work with military and intelligence services.

Because democracy requires a shared truth, our sense of shared truth has become an attack vector for adversaries of democratic societies, as I outlined last year in a post about Open Source Intelligence (OSINT) and adversarial information environments.

It also helps to explain the approaches of many nascent political movements, which specifically attack traditional sources of knowledge, expertise and authority. Donald Trump’s MAGA movement has been tremendously successful because it has created a compelling and strong sense of shared reality among its adherents that has allowed them to achieve power through concerted, coordinated action across a very motivated base of supporters. It is no mistake that his own social media platform is called Truth Social.

Design, Neutrality and The Future We Want

I obviously hold my own, rather strong views on the direction that politics are going. But the designer and facilitator in me is more interested in building the tools we need to shape our decision-making and democracy to be fit for purpose in navigating current and future challenges. And because of my background in strategy, I have a bias towards frameworks that translate explicit intention into desired outcomes.

I believe that sustainable action comes from a group that is both bound together by a set of shared truths that are reliably connected to objective truths.

I am aware that as a species we can go along to construct our own reality, which, in very tangible ways can become “real". Yuval Noah Harari makes a compelling case around the role of imagined realities as a way of coordinating human action. Without going into a semantic rabbit hole, I would say these imagined realities largely fall within the “shared truth” category, but I recognize that things can get fuzzy in the political application of these concepts, as what is “true” in a certain case - like “tariffs won’t cause inflation” - exists within layers of our own creation. The distinction that matters for me here, then, is between the things that we say and believe to be true, and the actual tangible, verifiable outcomes and context for those beliefs.

With social policy and economics, even though our choices play out in a system that is also of our creation, there are, at some point, very real consequences. People have food or they don’t, have housing or they don’t. So while we are playing with abstractions within abstractions, eventually there is likely a real result.

With environmental and health policy, for example, we might be bumping up against reality in a more direct way; maybe your shared truth is that vaccines don’t work or that climate change isn’t real, but there are still actual viruses and your crops might fail.

So, if I were to withhold my personal opinion of something like MAGA and evaluate it from the place of professional neutrality, my questions would focus on how well the stated aims of the movement direct the actions of the Trump administration, how well the actions of the administration translate into outcomes that match the stated aims, and how well those outcomes serve the long-term interests of all parties involved.

Democracies are messy and imperfect, and it is always possible that they produce results that we don’t like. But the way that we are practicing democracy now seems like a kind of procedural malpractice.

Rebuilding the practice of collective decision making requires us to bolster, build and protect a few key functions.

Getting from Here to There

Making collective decisions about where we want to go requires us to achieve a few basic things:

* Agree on the current conditions we are in

* Agree on some general goals for how we would like things to be

* Understand how things could be given our constraints

* Agree on principles that should guide our choices

* Initiate actions that will get us from where we are to where we want to be

* Repeat in a cycle to evaluate that our actions change our conditions as expected

If this sounds overly basic, that’s because it is. But we are somehow in a place where we have general dysfunction in all of these areas. Our current political discourse:

* Chooses conflicting or false measures of our present conditions

* Obfuscates or generalizes goals to conceal priorities

* Avoids specifics on limiting factors

* Does not connect principles to actions

* Initiates action without context

* Undertakes evaluation primarily as an opposition exercise

While this is a simplification, my point is that where the above dysfunctions happen, there is no longer any sense of shock at the lack of coherence.

In a very basic model of getting from “here” to “there”, I think we need some first principles thinking applied to rebuilding function across a few areas. To know where we stand in the present, we should have a coherent approach to making observations, applying existing knowledge, designing experimental actions and interpreting results.

To define where we want to go, we should be defining probabilities of how current conditions might extend into the future, define possibilities that could be created through concerted action, and defining clear principles for what our expectations are of the outcomes of our actions.

I feel almost awkward writing this, as it seems terribly simplistic given the scope of the challenges that we’re facing. But if we accept that these are the basic building blocks of establishing shared truths in pursuit of collective progress, you can see how attacking the norms as well as formal and informal information infrastructure we have around these things puts us in an untenable position.

Attacks on basic science, defunding statistics, undermining academia, attacking media all work to erode the basis for any trust around the elements of knowledge required for complex decision making.

But just as we have established due process around judicial proceedings, I think we need to do the same for collective decision making and political process. A court case that involves false or inadmissible evidence or violates due process is declared a mistrial. What expectations should we have for truth and process in our politics?

As an exercise in design, then, that means building coherent process and infrastructure around each of these areas in ways that respect democratic principles. At a startup scale, a successful founder wouldn’t dream of ignoring these kinds of signals; bankruptcy would come quickly. But at the scale and complexity of governments and countries, the feedback loops and delays become so weak and long that only deliberate, multi-disciplinary, multi-stakeholder efforts can plot a way forward.

As a last thought, this brought to mind a conversation I had with Jimmy Wales, the founder of Wikipedia, many years ago as part of a project. I was creating a series of visual models that would express the essence of how various leaders were approaching change. I was intrigued by what Wales had defined as the core of his efforts; Wikipedia was intended as a trusted, shared source of truth meant to allow reasoned, informed debate in society.

I think that’s a start.

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While it often seems that people are just speaking for the sake of it, I want to talk a bit about conversations that are directed towards a specific purpose, and how we can adjust our listening to support a group to come to an outcome through conversation. When we speak with others, we are (ideally) trying to create a kind of shared understanding and meaning between us, but because we are all approaching the conversation from our own perspectives, worldviews and biases, we can get lost long before anything coherent emerges.

Having a few mental models that can help orient you in these situations can help to shape a conversation in a way where real progress can emerge, with the obvious caveat that trying to force-fit a conversation into the wrong frame can be as unproductive as using no model at all. A little nuance goes a long way with this.

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Here we address dialogue with the purpose of understanding a problem, or imagining a solution. As a listener, I have often heard groups talk past each other as they try to work through a problem, and the issue is often not just the way in which they were listening, but what they were listening for.

I offer two models here from MGTaylor, which are often used to design conversations. I won’t go into great detail on the models themselves, but will instead focus on how they inform the structure of conversation, and how they can help us make sense of what we are hearing. I first came across the use of one of these models as a listening lens from Dan Newman, who used the Vantage Points model to identify when participants were talking about different “layers” of the same system, and from Kelvy Bird, who would use the Creating the Problem model to create a visual structure as she recorded aspirational conversations.

In all of these cases, you can use these models to guide your listening in a few different ways, depending on your role in the conversation. As a listener or participant in the conversation, they can help orient you to where the other participants in the conversation are coming from, and how you might come to alignment. As a facilitator, you can use these models to discern where a group might be sliding into dysfunction, or how you might need to shift the conversation to come to resolution. As a graphic recorder, you can use these models as a way of reflecting the deeper structures of the conversation in order to reveal to a group the gaps in their thinking.

Vantage Points - Listening for Coherence

The first of these models is the Vantage Points model, which is meant to express the connections between the purpose of an organization, the things that it ends up doing, and everything in between. In professional settings, so many of our conversations focus on how we should work and what we should be working on, and sometimes, why we’re working on what we’re working on (a simplification, sure). The answer may lie at one of those levels, or at all of them, but be different depending on what vantage point we’re using to frame the issue. So we can listen, we can focus on the person, we can make connections…but can we solve the problem? Are we actually talking about the same thing?

Applied to these kinds of conversations, the Vantage Points model suggests that work unfolds across a number of layers…that there is a logical structure to what we do if all our decisions are in harmony and work as a system. An organization exists for a reason, organizes itself to do that work, sets rules to keep itself on track, charts a path for how it will achieve its goals, sets steps to achieve those goals, marshals its resources to take those steps and undertakes the day-to-day work to get it done. Each of the parts in that “stack” need to make sense for the whole thing to work (and if you missed it, they map to the layers in the model at the top of the post), and if the decisions and work at each level align with all the others, everything goes smoothly.

Based on time, personality, complexity, size, and our own particular role, we might focus on one part of that structure, and lose sight of the others. Likewise, when the world changes and we need to adapt, small changes at one level might have implications at others.

I might be focused on building a website for my company, and trying to make a simple decision on where to host my content. This is a tactical decision, it will affect the simple tasks I end up doing in the future (how easy will it be to post things?) but might undermine my strategic intentions (does it connect with the audience that matters most to me if I build it one place, or another?) or may conflict with the very purpose of my company (am I in the business of making content? Is that what we set out to do in the first place?).

A simple conversation with colleagues about a website, then, might involve thinking about our shared enterprise at multiple levels at once. I want to talk about how hard it is to upload new content, but IT is thinking about the infrastructure, while marketing is worried about our brand standards and strategy is starting to wonder why we’re doing this at all, when we’re actually in the business of selling staplers. But the conversation is just about “website”.

As a listener, try to tune in to see if individuals in problem solving discussions are actually all having the same conversation. The meeting might be about “Deciding where to host our content”, but one person might be talking about time management, another about user experience, another about customer acquisition and the fourth wondering about why we produce content at all. They all think they are having the same conversation, but because they are each speaking from a different vantage point, the conversation just seems to go in circles.

This same dysfunction can happen within an individual. I might seek advice of my peers on which accounting software I should be using for my company. This could be a lively debate about which ones manage exchange rates and expenses effectively. Ok, not that lively. But I appear to my peers quite fixated on this problem.

As they coach me through this choice, one might wonder, am I fixated on tasks and details I can control in accounting because I’m afraid to focus and spend my time on the harder question of how to bring revenue into my company?

Through attuned listening, we can pick up clues as to where disconnects lie.

Using the Vantage Points model as we listen can help us discern which level our conversation should be on. If we have collective clarity on one level, we can use that to tackle the next, but if I am talking about what while you are talking about why, we will both walk away frustrated.

Defining the Problem

Even when a group is engaging at the same level, a common struggle is to accurately define the problem that they are trying to solve. A typical back and forth might be between statements about how they wish things could be, and complaints about how things are now. These conversations can quickly begin to feel circular, as many of the points will often feel disconnected from one another.

But just because someone starts a sentence with “Well, the problem is…”, doesn’t mean that what they say next is the problem. The model we can use to tune our listening in these situations is the “Defining the Problem” model, from MGTaylor.

This is not only a useful lens to use during a problem-solving conversation, but also when you’re scoping a project or trying to hone in on a set of objectives.

The conceit of this model is that when we identify undesirable aspects of our reality, those elements we identify aren’t necessarily problems; they are conditions. They might not be conditions we are pleased with, but they are not necessarily the problem to be solved. That “problem” emerges when we define what we would like the conditions to be, that is, when we define a vision for that particular element of our reality. The problem, then, is whatever stands in the way of the conditions changing to meet our vision.

When we tune our ear using this model, we can begin to sort what we’re hearing between the conditions that people are upset about, and the aspirations they have for how things might be.

I’ve always felt that you can save a lot of energy by avoiding the trap of solving the wrong problem really well. Often, when someone in a group becomes fixated on a particular condition being “the problem”, it is because they have an unstated or undeclared idea in their head of what an ideal state for the issue might be. Someone else might find that condition to be equally problematic, but for entirely different reasons.

When participating in a conversation that is meant to define the problem, it is worth splitting out - either in your head, or explicitly with the group - which conditions, in particular, people think are problematic, but also what the elements of a desirable end state might look like. Breaking the conversation up in this way can allow you to find where the actual problems lie - between the conditions we agree we are unhappy about, and the vision we share for the future.

I have previously mentioned the importance of shared intent in group process, and I view the ability to effectively discern “the problem” as very central to finding that intent. A bug to you might be a feature to me. Being able to structure our listening around this type of model can help us navigate to some intent, and also keep us from getting hijacked by control statements like “…well the real problem is…” where participants try to capture the narrative.

Treat each “condition” as a point of inquiry, not a definitive answer. Listen if there is agreement on the conditions. Ask about what “good” might look like, and if there is agreement there, but keep in mind that if either side of that equation is unclear or not shared, then you probably haven’t found “the problem.”

And so…

As you might have guessed, you might be using both of these models at the same time, and possibly others. There is a third model I will explore separately that can help navigate the question of intent, but two models, for now, should be plenty.

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Building on “Why We Should Listen”, this is the first tool for tuning your listening in an intentional way, by clearing your head of mental models that can cloud your attention.

When I was studying zen meditation at Kouun-ji Temple (the “ji” actually means temple, so this is like saying “Fedex Express”, but it sounds weird without it) my teacher, Yoshitomi-san, would tell me stories about the visiting classes of kindergarteners that would come to visit on field trip. I loved that in Japan, kindergartens would visit a temple and learn about zen, instead of the standard maple syrup field trips we would do in Canada. Though I do love maple syrup.

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When explaining meditation to the little kids, he would talk about thoughts creeping in to your head, like an itch, or like a fly landing on your face. Suddenly all you can think about is the itch. You want to scratch it so badly, that it pulls you away from what you were doing, that it takes your whole attention.

I think trying to listen can be like that.

I know I asked you about what you’re doing, but now that you’re telling me, I realized I’m not sure what I’m making for the kids for dinner tonight. And I forgot to send that email. And I actually only wanted to talk to you because I’m hoping you could introduce me to that friend of yours who works at Apple. And I can’t believe how bad I look today. Didn’t I just get a haircut? How is my hair already sticking out again?

There are a lot of things that get in the way of connecting with another human through conversation, and quite a lot of them play out in our own heads. Being conscious of those things can help us to “show up” in an intentional way.

What gets in the way

I’ve simplified this down to “what gets in the way.” Jeff Hawkins, in his 2004 book On Intelligence, wrote a lot about how our brains are actually outputting a huge amount of information as we try to perceive the world around us. We are constantly comparing, remembering and projecting as we look and listen, and sometimes more than we are directly perceiving.

In this (super scientific) diagram, notice that while we’re speaking, there is the direct exchange of information in terms of what I’m saying, what I hear, and what I see, but there is a heap of possibly unrelated and possibly counterproductive activity happening in my head at the same time.

My mind is more pre-occupied with who I think you are, who I think you think I am, the impression I want to make, what I imagine you’re going to say and what I’m pretty sure you don’t want to hear than it is with what you’re actually saying, and why.

Nervousness, self-consciousness, social position, bias, prejudice, assumptions all play into this model, especially in settings where playing a certain role, achieving a certain outcome or making a certain impression are seen as important.

Cultivating a listening practice means reflecting on how you show up in a conversation, and identifying the barriers and baggage you carry into each interaction.

Do you want to be sure you’re seen in a particular way? Are you conscious of assumptions that others may hold about you? Do you have an expectation of how an interaction is going to go before it even begins? Is it based on what the other person is doing, what you think they might do, or what “others like them” have done in the past?

Our brains are pattern-recognition machines. We can’t help but build models of the world to make it easier to navigate in the future. But when we’re speaking more to our mental models than we are to other people, we become incapable of connecting and learning.

Whether you are part of a group, in front of a group, one-on-one, or trying to capture a conversation in notes, becoming aware of your mental “outputs” can help you tune in to start focusing on the “inputs”

As a listener, then, I want to peel away is the following:

* Who am I listening to, and what are my assumptions about that person, and what they would say?

* What are they talking about, and what do I think I know about that topic?

* How do I think others see my contribution to this topic or conversation?

* What do I think is “supposed to happen” in this conversation?

You can add many more questions to this list, but, in essence, what you want to surface in your awareness are your own expectations and projections of an interaction, so you can let go of them in order to dedicate more cognitive energy to what is actually being said.

If you are facilitating a group, you might be worried that what is being said will mess with your plan, or that the group might turn on you at any moment. If you are in conversation with a colleague, you might be waiting to hear if they finally “get” what you’ve been trying to tell them. If you are a graphic recorder, you might be worried if you’re doing a good job of capturing or if people will judge you.

In your next interaction, try to be conscious of the mental models you bring in, and try to consciously let them go. While you are listening, if something doesn’t completely make sense to you, resist the urge to fill in the blanks with what you guess they mean, and ask. Try to fully explore what you’re hearing, with no expectation.

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This material is the result of a line of inquiry that started with me trying to learn the craft of graphic recording. Graphic recording involves listening to group conversations, then using visuals to model the content and connections as they emerge.

Spending an inordinate amount of time in the workplace listening as a professional activity - and, in many cases, feeling as though I was the only person in the room that was actually listening - I found myself starting to wonder why some conversations were so easy and enjoyable to model, and why some were so frustrating and painful. As I tried to represent not just the content of the conversations, but also the meaning, I started to wonder about the structure of meaning, and how it gets created between people.

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Some conversations seemed so productive, with new and exciting ideas coming out of the back-and-forth, while others went in circles. I couldn’t help but wonder: why? What was the difference? As my practice shifted more towards facilitation, I found that the muscles I had trained in listening became one of the most valuable parts of my practice.

A few years ago, I wrote a small guide on how to begin training yourself to be a better listener. It was too short to be a book, but it is too long to be a post, and has, instead, just languished in the deep recesses of my hard drive. I’ve chosen to post it all here as a short series, as I have never felt so acutely that we all might benefit from taking a moment to really listen to one another. Hearing each other is not good enough. We need to really listen.

Why Listen

Ever since the Cognitive Revolution, Sapiens has thus been living in a dual reality. On the one hand, the objective reality of rivers, trees and lions; and on the other hand, the imagined reality of gods, nations and corporations.

Since large-scale human cooperation is based on myths, the way people cooperate can be altered by changing the myths - by telling different stories.

Sapiens, Yuval Noah Harari

Our success as a species has been built on our ability to create a shared understanding of reality - to craft a sense of meaning that exists only in our minds, and not in the world around us. Our capacity to communicate our thoughts and ideas with each other allows us, as individuals, to expand beyond what it is possible to experience in a single lifetime.

Through listening we can assimilate the wisdom of others. We can absorb entire lifetimes of experience. We can experience parallel experiences, infinite “what-ifs” and variations on our own chosen path.

Or not.

We are taught to lead, to inspire, to tell compelling narratives, to “fake-it-till-we-make-it”, to add value, to engage, find our voice, win people over and take space. But what happens if we all do that?

A group of people on broadcast-mode is trapped in a kind of social-dysfunction that undermines the very power that has gotten our species to where it is today. Listening enables us to extend beyond ourselves and tap into a collective conscience that is available to all of us, but accessible only to those who consciously choose to do so.

Whether you believe neuroscientists, Daniel Kahneman or Gautama Buddha, we are locked in our own heads interacting with faded and faulty representations of the world around us, and only rarely the world itself. We live in our own mental models.

Daniel Kahneman’s important work on mental function showed that our early life is spent building a set of representations of the world around us - mental models - that allows us to navigate the world in a very low-energy-consuming way of being that very much resembles auto-pilot. He calls this System 1 thinking. We spend most of our time in System 1 thinking, following our mental models’ idea of what the world is, rather than responding to the world itself.

We only access System 2 thinking when we encounter dissonance with our expected results, at which point our full mental faculties are “switched on” to figure out what is happening.

When we spend all our time talking, we generally stay locked within our own representations of the world. Reflexive listening is what we most often do - waiting for an auditory stimulus that triggers us to make a culturally, contextually and situationally appropriate response. “How are you today?”, “How will you be paying?”, “What are you up to this weekend?”, “So what do you do?” all trigger near-automatic responses. Try answering randomly - in many cases, people will often ask you to repeat yourself, as though they hadn’t actually even heard the response, or will become flustered, confused, or annoyed. This is what finding the edges of a mental model looks like.

We live our lives in layer after layer of mental models, some conscious, many unconscious, from how we walk down stairs, to how we structure our tasks to who we believe ourselves to be.

So why listen?

Deeply listening to others can allow us to challenge the limits of our own assumptions, biases and mental models to learn from the experiences of others and become more than only ourselves.

Deeply listening can also be a profound act of service to others, unlocking their own constraints and boundaries by creating a space between you that is more than either of you.

Ways of Listening

When we interact with others, we are aware that there is probably more to that person than just the interaction we are having. Sometimes we interact with just the representation people put out. Sometimes we interact more with the context we are in than the person - the roles we play, whether it is a server in a restaurant, or a colleague at work. The iceberg metaphor comes up so often because we know that beneath the surface, there is more than just the context, and more than just the representation or projection of a person in front of us.

Let’s be honest; we use roles and mental models because accessing our full faculties all the time is exhausting. Part of the path of Buddhism is to free yourself of all the models - assumptions, beliefs, ideas of other and self - that shroud the the world around us from our view.

But that’s kinda hard.

One simple “hack” to start on the path of deeper listening is to substitute an explicit model for how to approach the conversation for all the implicit ones rattling around in our heads that we might not be aware of.

Over the next few posts I will share some models that you can use as a way of thinking about why you are listening, as a way of tuning your ear, and directing your inquiry.

It’s easy to get lost in the details of a conversation, or be in a rush, or be thinking of everything you have to do, and forget about what the purpose of the conversation is. And, when I say purpose of the conversation, I’m trying to set a higher bar. I’m advocating for a purpose that is beyond simply being transactional, and that is part of the assumptions built into the models I’ll be sharing.

In a series of posts, which I will add links to here as they go live, we will explore the use of listening to transform a network, to build community, to shift a system, to build a relationship, to reframe a problem, or to create something new. Each has a different model you can use as a listening lens.

Listening Model #1: Listening With Your Whole Self

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I’ve had a few requests on where to get started to develop a practice in graphic facilitation, so I thought I would write my response here instead of firing off a few links.

I still remember walking into my first MGTaylor environment and seeing a krew member scribing on the whiteboards. The first thing I noticed was that she was writing in a font. She was capturing what a group was saying, as they were saying it. When I asked her afterwards if she knew what they were going to be saying beforehand, she just shrugged, and said she just listens and lets it flow. I was awestruck, and knew that if we got to choose which role we would do, I wanted to do that.

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A lot of people seem to have the same reaction when they see graphic facilitation for the first time, but as I’ve seen the practice become more common, I’ve also seen a lot of drift, and a much wider range of practice into some that is more utility-focused, and some that seems mostly aesthetic.

If you'd like some more context and background on what graphic facilitation is and where it comes from, I suggest you read this great post by Christopher Fuller. I'm grateful that he wrote it, so I can avoid writing that context and get down to answering the question of how to get started.

This post is for anyone hoping to take visual notes either for themselves, or in a group setting. While I use these techniques in workshops all the time now, as a side note, this is a skill I wish I had when I was in college. Oh, the notes I would have had!

The most useful distinction I found early on in trying to learn scribing was made by Tony Buzan in "The Mind Map Book" in which he differentiates between note taking and note making. Note taking is capturing information uncritically, usually as it comes at you in time. It tends to be linear, and reflect the order in which information is presented. Note making, by contrast, requires the listener to reflect on the meaning, structure and connectivity of information before recording it in order to capture it in a way that reflects the information at a conceptual level, as opposed to a strictly sequential level.

Whatever style you end up choosing for how you represent information, if you pay attention to this difference, you'll immediately get a few benefits:

* Improved Memory: by taking the extra step of considering how pieces of information connect with one another, we switch our brains from passive consumption to active processing, which aids in our ability to recall that information later.

* Pattern Recognition: Actively listening and recording connections over time allows you to spot patterns and structure in the information, which can give you a second order of understanding in the content.

* Surfacing Meaning: Information on its own isn't necessarily useful, but as patterns emerge we can start to find new meaning in the flow. Depending on the amount of information and the length of time in which it is presented, that can easily outstrip our working memory - by visually structuring information as it comes, we can go beyond our cognitive "buffer" and find meaning in larger pools of information.

* Useful Reference: By creating a distinct visual structure that we associate with a time, place or conversation, we create a handy reference that we can use for later recall. Well structured visual notes can allow you to replay a conversation months and years later, creating a strong association with the moment they were captured.

These benefits apply both to when you use these techniques in your own notebook, but also when you use them to capture notes for a group on a whiteboard in a meeting. It is also worth noting that in a group setting, having a shared experience of those benefits can create a very positive dynamic on a collective conversation.

I would also say that each of those benefits should be applied as a kind of design principle for whatever style you choose to develop in your scribing. As graphic facilitation has become more popular as a profession, there has been a swing towards more form over function, where scribes create beautiful murals with little informational density or usefulness. Always ask yourself what the purpose is for the record that you are making, and be sure that the way that you are making that record will serve that purpose. I have actually found that my style has become more austere over time, as I focus on adding just enough beauty to trigger interest, but with an emphasis on the ideas that emerge and creating a record that will live beyond the moment in its usefulness.

So, on to where to get started. Accept that this is a journey, and that mastery will come slowly, but utility can come relatively quickly. There are a few dimensions you will need to consider as you develop, and I'll give some guiding questions for each in the interests of keeping this from getting too long. You'll need to work on technique, practice and structure.

Technique

There are some basic techniques involved in scribing, and these are what give learners the greatest amount of anxiety coming in. "But I can't draw!" is the usual refrain. While artistic talent never hurts, focusing on the basics will get you 80% of the benefit.

First, you need good lettering. There are lots of resources out there, but I'm biased towards lettering from architectural drafting. I learned old-school drafting in high school, and the discipline of that style has informed my lettering ever since. I found a great video here, which you can use as a starting point, but developing a legible, consistent style is an important baseline.

Along with great lettering, you’ll need some basic shapes, connectors and basic iconography. Graphic Facilitators Guillaume Lagane and Nicolas Gros did a great job of laying out hundreds of common objects in three levels of visual fidelity in this book, but you can find plenty of inspiration in comics and across the internet. If you’re in the “but I can’t draw!” camp, get some inspiration from books like Stickman Odyssey (the entire story of Homer’s Odyssey, illustrated with stickmen) or classics like Ed Eberly’s “Drawing Book of Animals” (did anyone else grow up with this?).

When in Doubt, Copy

There are so many talented graphic facilitators out there, it can help when you’re starting out to find someone with a style that you like and start out by trying to emulate their style. Some are illustration-heavy, some very text-based. Some use colour in novel ways and others are monochrome. Structure, hierarchy, layout all manifest differently in different styles, so it helps to look at what is out there and see what speaks to you. Some examples of practitioners that I admire (in no particular order, and also just based on who has some of their stuff online: Alicia Bramlett, Kelvy Bird, Guillaume Lagane, Alfredo Carlo & Housatonic, and Liisa Sorsa. There are so many others, but I’ve realized to my dismay that many of us don’t have much out there online - I’d be grateful if anyone sends me links to more that I can include here.

Practice

A common misperception is that good graphic recording is all about drawing. What many of us have found as we’ve tried to structure trainings around graphic recording, however, is that it is much more about listening and structuring information. I found a very old piece I wrote on the topic (2009!!) when I was working in parallel rooms with Sita Magnuson and Kelvy Bird. Between sessions, I took a peek at their work and realized that we were all representing what we heard in fundamentally different ways. It got me thinking about how we were engaging with what we heard, and how we structured that on the boards.

I have a lot of other materials that I’ll be formatting on to this Substack soon on developing a listening practice. Kelvy Bird has also published a great book on her approach called “Generative Scribing” that is worth a read.

Other Stuff

A few other resources that are out and about:

* Christopher Fuller’s take on how to get started in graphic facilitation

* Lots of examples from Peter Durand at Alphachimp

* Dave Gray’s Marks and Meaning

* Graphic Facilitation Group on Facebook (I know, Facebook…remember that?)

I am aware that I am leaving so much out of this - this post has been a classic case of having so much that I want to include in it, that I get overwhelmed and put it off until I have more time to get it all in. Which never happens.

So, this is the starter pack. I welcome any other links or resources people want to send my way, and for my part, there are more detailed parts of this I’ll dive into at a later date, but here’s to a first draft seeing the light of day.

Note: I started writing this before Trump and Melania launched their own memecoins, which really raised the stakes for everything I was trying to lay out - it validates for me how important it is for people to understand what is involved, and what is at stake, in the crypto space.

Policy moves slowly, tech moves quickly and finance moves in the shadows. I am always fascinated by the intersections of these worlds, and by the difficulty in making good decisions in the places where they overlap. Having policy keep up even with something as straightforward as ridesharing is a challenge, and it took years for the world to understand what was happening under the surface on Wall Street with CDOs.

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So crypto, which involves both a deep, obscure tech ecosystem wrapped in jargon and hype, and an intersection with financial services is ripe for policy chaos and poor decision making.

I believe that having the right questions sits at the heart of good decision making, and that, as it stands, we are so conditioned to ask the wrong questions about crypto that we are sleepwalking into a crisis.

The Problem with Crypto

I’ve been meaning to write this for some time, and the push that has finally made me do it was this article by Paul Krugman - the public economist and (formerly) NYTimes columnist - called “Crypto is for Criming”. It is infuriatingly elitist and dismissive, with a mocking image of Doctor Evil at the top driving home the point that this is a topic barely worthy of debate in polite society; it is, instead, the domain of “crypto bros” and criminals, rather than serious economists and investors.

So, then, one wonders, why would a Nobel Laureate feel the need to comment on it at all?

For context, I went “down the rabbit hole” on crypto and blockchain a few years ago when a colleague at a major tech company reached out because they were trying to evaluate whether blockchain technology would be a good choice for a particular challenge they were working on. She found that the answers she got from her peers were either cultishly supportive of blockchain, or vehemently dismissive, with little clear justification either way. I was intrigued, because there didn’t seem to be a clear way to evaluate the suitability of the technology for her particular use case, and the level of passion in the responses didn’t seem to correlate with any rational criteria.

And you see this pattern reproduced in media and society more broadly - either people are fanatically supportive of “crypto”, or adamantly opposed to the “Ponzi scheme” that is only fit for money-launderers, drug dealers and gamblers.

I believe that ignoring what’s happening in this space is increasingly dangerous, not least because backers of the technology are now taking over its regulation in the US, and we’ve spent the last 5-10 years deliberately avoiding the real issues surrounding it.

Question #1: Who Wouldn’t Want to Use Crypto?

In Krugman’s article, he can only think of three possible explanations for the rise of crypto:

* Maybe it’s a digital asset, like virtual gold, so it’s uselessness is okay? (but he clearly doesn’t think so)

* Maybe it’s “all speculation or gambling…largely driven by testosterone”

* Maybe it’s just for “tax evasion…blackmail [and] money laundering?”

Krugman, like many others, are limited in their thinking from their starting premise that this is all rather ridiculous. The persistence of crypto is so insane, that the only possible explanation for its continued existence is that it enables shadowy crime syndicates and knuckle-dragging, UFC-obsessed, Trump-supporting gambling bros.

So, what is the original proposition of a cryptocurrency that is so insane? The original problem it was meant to solve?

“How do I quickly, securely and efficiently send money or to someone I don’t trust, without a middle-man?”

Have you ever tried to send money to someone? How was the experience? Was it quick? Was it cheap? Are you a criminal, or were you just trying to split a dinner bill?

Have you ever tried to send money between countries? How did you like the fees? Why did it take days to clear?

If I reframed cryptocurrency as “competition on financial infrastructure to allow open systems of peer-to-peer exchange”, then one thing becomes VERY clear; the people who wouldn’t want to use cryptocurrency would be those with a vested interest in the current financial infrastructure.

John Cassidy, with The New Yorker, wrote a fabulous article years ago just after the 2008 financial crisis, titled “What Good is Wall Street?” that is very instructive here. Going back to base-principles, he explores just what the role of financial services is supposed to be.

When the banking system behaves the way it is supposed to…it is akin to a power utility, distributing money (power) to where it is needed and keeping an account of how it is used. Just like power utilities, the big banks have a commanding position in the market, which they can use for the benefit of their customers and the economy at large.

Part of the thrust of the article explores how the financial services industry has gone from a public utility to a rent-seeker on the entire economy. If up to 25% of GDP is devoted just to a set of functions that could be automated…might there be some resistance?

Question #2: What Does Crypto’s Persistence Really Mean?

Suffice it to say, the regulatory environment for crypto has not been very easy. Bitcoin was routinely criticized by the Biden administration for its voracious appetite for energy, with threats to clamp down to protect the environment. When the #2 cryptocurrency changed protocols to make it more energy efficient (to the tune of 99% more energy efficient), the administration turned around and threatened its users because now it had become a security (it’s a long story). The Securities and Exchange Commission has routinely refused to provide any regulatory frameworks for crypto, but has instead approached the industry only through enforcement, that is, they would never say what was allowed, but would prosecute based on shifting versions of what wasn’t allowed. High profile disasters like the collapse of FTX were the predictable result of setting no regulations around an industry with billions of dollars flowing through it.

Which is all to say, there has not really been any strictly legal ways to experiment with cryptocurrencies. I’m struggling to think of any example of an industry with no rules or regulations that has grown to the size of the crypto space, which is, by today’s count, standing at 3.64 Trillion US dollars. That’s right. Trillion.

So what’s going on? What does that mean? If Krugman is right, are we really looking at $3.6T worth of testosterone and drug deals? Isn’t this all just a scam, and a Ponzi scheme?

I think that the single biggest risk that policy makers miss when looking at young crypto investors is not that stupid young men have been tricked into a Ponzi scheme, it’s this:

Most crypto investors don’t think that crypto markets are fair, just like the stock market; they believe it’s fixed, just like the stock market. The only difference is that everyone in crypto admits it’s fixed.

What this represents is a colossal, generational, and entirely rational, loss of faith in the traditional financial system. Young people feel shut out of the stock market, knowing that a very small group is capable of manipulating markets in ways that work to their benefit at the expense of “the rest”.

A lack of regulation, in that case, becomes a feature, not a bug, as regulators are seen only as protecting the interests and privileged access of the elite.

This couples with a second risk to create a systemically volatile combination:

Stagnant wages, high living costs and a bleak sense of the future means many young people don’t believe it is possible to enjoy the quality of life their parents had without some kind of game-changing windfall.

The social contract between generations and classes is breaking down, and the “rules of the game” seem more geared towards protecting the old and the rich than they are to keeping free and fair markets. Elite economists and commentators will mock a young generation focused on get-rich-quick schemes, while missing the fact that many don’t see how they could ever afford a house or a family without some kind of breakout. An investment that gets a steady return of 5% over decades won’t pay back student loans, medical bills and next month’s rent, but a sudden 1000x return on investment for some imaginary coin named after a dog or a cartoon frog might just pull them back from the brink. Why else would someone invest their child’s college fund in a coin named after an oral sex sound effect?

Just as many in the establishment were blindsided by Trump’s election victory because they missed out on how alienated and disenfranchised many in the country felt, they are once again going to miss the same dynamic playing out in financial markets.

Ironically, crypto markets as speculative investments seem to have emerged largely because a lack of regulation has prevented cryptocurrencies from fulfilling their original use case: paying for stuff. In fact, wildly fluctuating, volatile markets make cryptocurrencies largely unsuitable as a medium of exchange. Instead of a relatively stable “coin” spreading through its use in new and interesting applications, the technology is spreading through proliferation into new speculative assets (as of today, there are more than 2.4 million cryptocurrencies being actively traded).

Question #3: Does Crypto Signal Parts of a Future We Want?

A big part of the reason the crypto world lined up behind Trump was a total frustration with the SEC under Gary Gensler and the Biden Administration, which seemed hell bent on the destruction of the industry. You can charitably say that the hostility towards crypto came from a genuine concern for investor rights and the integrity of the financial system. You could also, less charitably, argue that the Biden administration was acting primarily in the interests of the financial services industry, which is facing its Napster Moment.

With the Trump administration coming in on promises of setting the crypto industry free of its shackles, it’s worth asking what the actual potential risks and benefits are, and what design challenges new regulations would have to solve for.

What amazes me is that as we collectively mock cryptocurrency and ask “what is it good for?”, we don’t question why the financial sector soaks up a quarter of global GDP for what is, essentially, plumbing. If that was our entry point, you might start the inquiry with questions like “what would a financial system look like if it was designed for a globalized, digital age?” From that frame, and realizing that this January, we are going to start seeing some very rapid movements in this space, here is what I think we should be paying attention to:

First, let’s accept that exchanges have all the dumb risks we’ve already solved over the last 250 years with banks and stock markets

Let’s get the stupid questions out of the way first. It’s frustrating to watch the same risks play out that we’ve already sweat blood over. People wanted to buy and sell crypto easily, but it’s distributed. So some people made a centralized place - an exchange - to trade them. But there were no rules. Would you let the NYSE trade against the market, giving themselves an edge? Would you let a bank say it has your money, but actually spend it all? Would you let the bank bet all your money on something for itself? No. We’ve already been through all this, but we thought that somehow, with billions at stake, that “trust me, bro” would work just fine. This is almost a copy/paste on regulations. It is also no small irony that so much of the risks in crypto emanate from centralization in exchanges, when the technology itself is based on decentralization.

Because the regulators have just been captured, we need to be clear on the stakes of the game…and what game we’re playing

The debate so far has been successfully contained to “what would you even use the internet for?” Advocates of cryptocurrency have been so insufferable that everyone’s eyes glaze over when it comes up, but we are in a situation where Biden decided that the entire future of money and global financial flows was not worth talking about, so now all of those rules will be set by Trump. There are three possible, not-mutually exclusive futures with their own implications.

The Bitcoin Future - Virtual Gold Standard & Digital Scarcity

In this future we decide that cryptocurrency is best seen as an asset, or commodity to be traded and held as a store of value. Many in the crypto industry have been fighting for the classification of cryptocurrencies as a commodity, because the bar for regulation is much lower, and the requirements for disclosure and reporting are much less stringent. In this case, a digital asset is bought and sold with no implied contracts or obligations.

Like gold, the asset is valuable because it is scarce and there are people who will pay for it. Scarcity, in this case, is created by the rules that are encoded in Bitcoin’s blockchain itself and the algorithmic limitations on how quickly new coins are added to the available supply.

In its own way, the idea that a Bitcoin has value is no less ridiculous than saying a small piece of paper has value; it does because we agree it does. What we should be asking is, what does this allow that other methods of exchange do not? If we treat it as a prototype for a new system, we can evaluate its features, rather than just dismiss it completely for ideological reasons.

Pros: It is digital, moveable, universal, decentralized (i.e. not controllable by any particular entity), scarce (value responds to demand), immutable (creates a permanent record), open.

Cons: It is volatile (thus making it inefficient for exchange), inherently energy inefficient (scarcity created by increasing energy consumption), immutable (you can’t change it, even if you want to), open (as criminals have found out, all transactions are public).

As you can see, some of the things that are features, can also be bugs. But they are all elements to be considered in the future we want.

The MemeCoin Future - Snake Oil and Swampland in Florida

The generous reading of the SEC’s enforcement posture to date is that they were trying to avoid this future (the less generous reading is that they have been in the pocket of the financial services industry, preventing open financial infrastructure from emerging). This is the version of crypto that everyone tends to think of - it’s a Ponzi scheme, a scam.

Securities regulations have emerged over time as a way of protecting against scammers. While small, private companies can represent themselves as they please (up to a point - fraud is still fraud), once they attract a certain number of investors, there is a level of disclosure that we require of them to ensure that their claims are largely verifiable, so that the broader investing public can make informed decisions about where they put their money. At least, that’s the idea.

As crypto projects began to emerge, it became clear that instead of offering shares on a public exchange, groups could offer tokens on crypto exchanges to raise funds, with none of the rigour or disclosure required by the stock markets. While there were many serious projects that did this to fund real efforts in creating new use cases, it also sparked a gold rush of memecoins that would hype a release then sell quickly to make a quick exit. In the stock world this was known as a pump-and-dump, and in crypto is referred to as a “rug pull”. There is a very classic shape to these graphs:

The far left of the graph is the pump, and immediately after is the dump, where the project originators liquidate their holdings, take profit, and use retail investors as their exit liquidity. It means that the sellers make a fortune, and anyone who joins in even moments too late loses everything. The above graph, by the way, is $TRUMP coin.

This is what the SEC has been trying to prevent. When I first started researching crypto, the Reddit forums for TerraLuna - which had just imploded in spectacular fashion - had suicide hotlines pinned as the top post. It was that bad.

For the serious members of the crypto community, these are the embarrassing projects that tarnish the industry - hucksters and scammers hustling useless but catchy coins to the desperate, who are hoping to change their lives by catching the next big thing. At this stage, these “projects” make no claim to any kind of utility, but are acting as a kind of digital Beanie Baby. Melania Trump’s coin offers the following in its Terms and Conditions:

THE MELANIA MEMES ARE DIGITAL COLLECTIBLES INTENDED TO FUNCTION AS AN EXPRESSION OF SUPPORT FOR, AND ENGAGEMENT WITH, THE IDEALS AND BELIEFS EMBODIED BY THE SYMBOL “MELANIA” AND THE ASSOCIATED ARTWORK (THE “ARTWORK”) AND ARE NOT INTENDED TO BE, OR TO BE THE SUBJECT OF, AN INVESTMENT OPPORTUNITY, INVESTMENT CONTRACT, OR SECURITY OF ANY TYPE.

This version of the future is one where anyone can make any claim they like, and the onus is entirely on the buyer to ascertain whether a given project has any inherent value or not. The explicit classification here of digital coins as collectibles says it all, but also does nothing but reinforce scepticism about digital currencies.

The Ethereum Future - The World Computer

Ethereum represents an extension of the original logic that Bitcoin brought to life; if value could be stored and transmitted through a distributed, digital platform, then bringing that together with the many ways in which we exchange value in the digital world could allow us to collaborate and exchange in new ways.

Put another way, the first wave of the internet was all about the decentralized sharing of knowledge, but nobody really knew how to share any way other than free. The next wave of the internet was all about extracting value, as advertising and surveillance incentivized centralization and control. This is also the wave that has brought endless subscriptions and user-lock-in as the model for rewarding work. Ethereum, as a distributed computing platform, brings in the possibility of incentive design - the ability to create and share value between people and groups in a peer-to-peer fashion without the intermediaries and tech giants that have crushed the open internet today. Web browsers that share the reward for viewing ads, or micro-tip the authors of content you read. Content networks that distribute benefit to creators. Business cooperatives that are governed by stake, and distribute benefit based on contribution. Music that auto-distributes to creators based on baked-in rights contracts.

The vision is quite radical, and potentially quite disruptive to the many industries that are controlled by highly centralized organizations, like financial services, music, film, gaming, media, publishing and software.

And so…

It’s quite easy to see why there might be a considerable amount of resistance to blockchain and cryptocurrencies, given all that they potentially threaten in incumbent powers. Just in Canada, for music rights distributions, SOCAN collects $523 million (CAD) in royalties, and even after years of improvements, still only distributes $442 million…either by direct deposit, or by sending a cheque; a literal piece of paper in the mail. In 2025. Music rights on the blockchain could always and forever disburse automatically and instantly to all rights holders. The SWIFT network, Visa and other financial intermediaries would be potentially obviated as payments would settle themselves in real time.

Which is all to say that the reason to pay attention to how all of this unfolds is not because, as Krugman says, crypto is only good “for criming”, but because crypto is good for everything that involves an exchange of value. So here are a few policy areas we should all be paying attention to:

* Monetary policy: at scale, something like Bitcoin as a reserve currency affects a key monetary policy lever, as it involves a store of value that can’t be easily manipulated to address issues like inflation in a given economy.

* Privacy: part of the reason crypto currency was appealing to criminals originally was the perception of anonymity. What they have since realized is that the blockchain is a permanent, public record of all transactions, which means future crypto currencies would need to balance the needs for privacy for individuals and the ability to mitigate illicit flows like money laundering and terror financing.

* Securities: there has been no clarity on when crypto is a security and when it is a commodity. Initial coin offerings and similar efforts, to my mind, were clearly securities, but with Ethereum, a given contract on the network might be a security while the token is a commodity. There needs to be good faith, modern design applied to these rules to create regulations fit for a digital economy, not simply using old analogues for new paradigms.

* Transparency: blockchains and cryptocurrencies should be uniquely good at creating transparency because they are public; failures of centralized entities like FTX are inexcusably stupid, because creating transparent proofs should be easy, and financial disclosure for things like ICOs can and should be hard-coded into the blockchain. Good regulation would set standards for these things that could be instantly verified.

* Global Reserve Currencies: Again, at scale, this could represent a major rebalancing of how international finance works, and this comes at a time when global powers want to challenge the supremacy of the US dollar as a global reserve currency. Sanctions work, in part, because of that system, and the shift away from the US dollar to a universal digital currency would have a lasting impact on trade and geopolitics.

* Security: there have been a number of high-profile cases where coding errors and various exploits have been able to siphon money out of various crypto networks. The more value that is stored in these networks, the more attractive they will be as a target (not to mention the threat of Quantum computing to cryptographic systems). If, for example, the US were to create a National Bitcoin Reserve, it would be nice to know that a 12 year old in Latvia couldn’t just walk away with it.

So, while the previous US administration decided to just ignore this whole space and hope it would go away, we are now looking at the Trump administration setting the rules for, potentially, how all future trade and transactions will take place.

I happen to think that’s worth paying attention to, and I’d love it if people like Krugman - a Nobel Prize-winning economist - would take it seriously enough to weigh in on the future.

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During a recent training I delivered for a group focused on supporting multi-stakeholder processes, I realized that there were a few missing steps needed to get them in the right headspace to explore some of the concepts we would be going through. Everything we were going to explore would be largely useless if they didn't first accept that a lot of the decisions they would have to make were part of a domain of design, and if they accepted that, that they needed some clarity on just what type of design we were talking about.

I think it's easy to accept that we can design a better car, a better app, or a better running shoe. When we can hold, touch and use something, we can imagine there was some care, some method to how someone designed all the elements that constitute the use and construction of that artifact.

But when it comes to the intangible, I have found that there is a leap of logic required for people to accept that there is the possibility of applying method to the design of an idea, an agreement, or a decision.

So, of late, I've found myself starting out any training by first making the case for design for those who find themselves in a situation where they work with other humans. The frame that I have found unleashes the most curious practitioners who follow down the most interesting paths of inquiry are those who imagine that their domain is not "design thinking," it is "designing thinking".

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In making the case for design, there is a kind of red pill/blue pill choice to be made for the practitioner. What it boils down to is this: given what we know about how humans behave, and what we have learned from psychology, economics, biology, sociology, history, anthropology and all of their many sub-domains and combinations, are there any factors that make outcomes in groups more or less likely, more often than not? Are there any patterns that can be identified among variables that might be isolated? Does one environment vs. another create a different outcome? One thought pattern vs. another? Could these patterns be abstracted, or modelled?

If you answered no to all of these things, and you believe that email is as conducive to deep dialogue as a mountain retreat, then you can take the blue pill.

If you believe that, in fact, different conditions can produce different outcomes within individuals and groups, then you take the red pill, and this starts quite an interesting journey in exploring just which conditions might facilitate which outcomes.

This inquiry might be guided purely by intuition. Indeed, I have met many who believe that while differences matter, method isn't possible - this is purely a matter of personal instinct and intuition.

I happen to believe that method is possible; that our decisions about time, place, sequence and focus can, more often than not, create conditions in which certain types of human experience are more likely to emerge.

In short, I believe that decisions, ideas, thoughts, communities, innovations can all be designed...but not directly. More specifically, I believe that the conditions for human outcomes can be designed, even if we do not know specifically what those outcomes will be.

To design this way, we need to think about design a little differently based on a few variables related to design: the object of design, influence on the end product, and agency in the process.

I'll illustrate the difference with three very crude examples, which I think are useful, because I've seen so many cases where they are used almost interchangeably.

Classic Design: in our classic conception of design, the designer perceives a need in the world, and uses their knowledge, experience, skill and intuition to devise something to meet that need. The object of that design process is the artifact itself. The designer, as the visionary and expert, has absolute influence over its creation, and all agency in this process lies with the designer - the end users, in fact, might not even appear in the process at all.

Human-Centred Design: Human-centred design disrupted this model by asking a radical question that now seems pretty basic: "before we make a thing for people, what if we, like, talked to them first?" In this model, the designers engage with the end users to understand their context and needs before they create the artifact. The object of the design process is still the artifact itself, and while users in this model now have some influence - largely as input, final influence still lies with the expert designers. A limited form of user agency enters this model, but only insofar as they are asked.

Increasingly, you see situations where the products we are talking about might be something less tangible. As design filters into the sphere of collaboration or human interaction, the artifacts we start designing for tend to be more conceptual than strictly functional; creativity, new ideas, innovations, partnerships, learning, agreements and strategies. You can't sit on or drive the products of these kinds of design processes, but the outputs are, nonetheless, very much something that groups or organizations want and need. Which brings us to...

Emergent Design: Emergent design focuses on methods to create novel outputs that are not present from any of the individual inputs in a group process; to create conditions in which the desired outcome can't, itself, be directly designed. Learning, innovation, creativity, decisions, agreement, alignment, excitement, understanding are all highly desirable outcomes, but can't be directly manipulated; they are emergent outcomes based on a series of inputs and conditions which either make their emergence more likely or less likely. The object of design, then, is focused on the conditions, as opposed to the outcomes or outputs themselves. The degree to which the outcomes represent the potential of the group depends on the level of influence the "users" have over their creation. The durability of the outcomes depends on how much agency the "users" have before, during and after the process.

This is not intended as a good, better, best model of design, but rather a lens for deciding what approach to design one should use. If you are in the business of producing software, and it is ultimately you who must code, test and ship your product, emergent design is probably not the approach for you.

In any of these situations, if the beliefs and behaviours of participants in a process as individuals or as a collective (or both) is instrumental to the success of the outcomes, that is a good sign you need an emergent design process. If their input is required, but not their actions, then a human-centered design processes might be a good fit. If neither their input, nor their actions are required...you can head to your basement and get to work. This is where agency comes in.

Considering agency can help expose where you are, in fact, designing for emergence. Many of our failed processes result from a focus on centralized agency in situations where the coordinated action of a great number of individuals is required, or where the one holding the pen is not the one responsible for delivering the outcomes. Education often focuses on how to teach, rather than the conditions in which learning occurs. A strategy might focus on an objective opportunity, rather than the appetite of those required to achieve it. We focus on what makes a great leader, and less on how groups work with shared intent.

Many of the groups I have been brought in to help over the years wrestle with very basic questions that, nonetheless, remain very difficult to answer, especially as organizations get larger and the context gets more complex. "Where do we go next as an organization?" "How can all of us work to solve this shared problem?" "How do we adapt our organization to changing circumstances?" "How do we have better ideas?"

This brings me back to my recent training. Nowhere is this more true that in "multi-stakeholder" groups, where individuals from various organizations, all with their own pressures and motives, need to coordinate around a collective issue. Success, at an aggregate level, comes from each individual reaching a personal decision point an impetus to act that matches with enough of the other individuals in the partnership to create a change that all of them contribute to, but none of them control. Emergent Design is the set of principles, models, practices and tools that creates the conditions for that to happen.

When I first started doing facilitation and design work, it was almost always in the context of a single company or organization. They needed a collaborative process because they were generally large organizations, and the only way to make sure their strategy took into consideration all the necessary complexity they were facing was to bring in all the people with direct knowledge from the far-flung parts of the company. Not only did it make for more nuanced strategies, it also got a jump-start on rolling out the plan afterwards, as so many of the key people had a hand in building the strategy and were thus much more likely to be bought into it.

And that was the key challenge in those processes; finding a strategy or idea that was sufficiently compelling to enough people that they would actually want to do it. We always talked about how important it was to find that shared intent.

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What I didn't know then was how much easier it was to find shared intent in a process where most people were told they had to be there. Don't get me wrong; having your boss order you to be in a room doesn't automatically guarantee your buy in for whatever happens in that room. The reason so many large projects fail is that we consistently under-represent the impact of misalignment, misunderstandings, passive resistance and apathy. But as a starting point, having people who feel they at least need to show up, and feel they have at least something at stake in the outcomes is a decent place to start.

It wasn't until I started doing multi-stakeholder work that I realized just how important intent was. For those who are unfamiliar, multi-stakeholder work revolves around the many areas where people or organizations who don't necessarily have any responsibility or accountability to one another find themselves exploring an area in which they all have a stake or an interest. That might sound like a vague problem space, but it's actually where many of the biggest challenges facing civilization lie right now; the growing spaces and cracks in our systems that no individual actor has the knowledge, influence, resources, ability or mandate to tackle on their own.

Back in the easy days of working on smaller problems, bad faith actors in a collaborative process could face consequences from their boss. In a multi-stakeholder process, if a crucial stakeholder becomes bored and decides to drop out, there's no boss to compel them. They have to want to be there, or feel they need to be there.

We used to say that a group needed a "burning platform" in order to really move to action, but more and more, I don't see that as being anywhere near sufficient. In fact, I think that when it feels like the whole world is on fire, a burning platform doesn't seem as urgent as it used to. Just looking at issues like climate change, we are still not compelled to decisive action despite having a very real, and not-so-metaphorical burning platform.

That's why, these days, I've come to think that intent is everything.

There is a magical moment when people move from a thought or a conversation of some possibility into a visceral desire to act, to bring that possible future into reality. You can feel it in yourself, when you move from indecision into action. You can feel it, as well, when the intent you hold connects with others.

There are so many things in life, whether in our personal lives or our working lives that we do out of routine, obligation or inertia. We go along to get along, we don't rock the boat, we do things the way they've always been done, we do things because we have to, because we're supposed to. Sometimes we change because we're forced to, because our conditions change. Change is happening, but not by design.

Making deliberate change requires intent, and while we may experience intent as spontaneous, as something that "is there or it isn't", I believe there is a process to it. Intent is always individual, even when it's collective. It springs up in the place between a problem and a possibility, when the problem can be seen clearly enough and the possibility is desirable enough to motivate action.

Groups of individuals need to go through the same process to build intent that individuals do, with the added challenge of, well, being a group. For shared intent to emerge, that group needs to come to a collective understanding and definition of the problem they are solving, and a collective vision for how to solve it. Everyone comes to intent on their own, but individual intent that is reached as part of an emerging group intent is incredibly powerful. So, the design challenge is to create a container where a group can arrive at that place together.

A few tips for finding group intent:

* Remember that organizations aren't people: just because an organization has been involved, doesn't mean that the person representing an organization has any context. Focus on people.

* Every new person resets the clock: every time people come and go in the process, you have to assume a reset. If they haven't been on the journey, you need to think how to take them through that journey...but the journey might change with each new person and perspective you add.

* Take time to build language: we all see the world a little differently, and while sharing diverse perspectives can be powerful, moving forward on the assumption that we already share the same perspectives is a recipe for misunderstandings. Diverse viewpoints tend to only be valuable when participants make the differences explicit, and build a new synthesis together.

* Go slow to go fast: taking the time to build shared understanding slowly. Sometimes a first attempt at coming up with a solution will change your definition of the problem; allow these iterations, as it is part of the process of a group making sense together. Solving the wrong problem really well doesn't help.

* Relationships matter: shared intent is not only about a shared understanding of what we want to do, but also a shared understanding of each other. Trusting that others want something as much as we do can help us take the leap into a new reality.

Remembering some of these tips allows you to move from a mechanical approach to movement building to a more organic approach. Scheduling a series of consultations and one-on-one meetings may fill a project plan and look like progress, but understanding that intent is a core design consideration means you need to design for emotion and experience.

If we want a future by design, and not default, we need to design for intent.

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