Tag Archives: change leadership

Top 10 Human-Centered Change & Innovation Articles of May 2026

Leave a reply

Top 10 Human-Centered Change & Innovation Articles of May 2026Drum roll please…

At the beginning of each month, we will profile the ten articles from the previous month that generated the most traffic to Human-Centered Change & Innovation. Did your favorite make the cut?

But enough delay, here are May’s ten most popular innovation posts:

  1. Making Change Stick — by David Burkus
  2. Why You Need to Leverage Shared Values in Change Leadership — by Greg Satell
  3. Why Zero UI Will Redefine Experience Design — by Art Inteligencia
  4. Winning with Artificial Intelligence in 90 Days — Exclusive Interview with Charlene Li
  5. The Micro-Enterprise Explosion — by Braden Kelley
  6. Direction of Fit — by Geoffrey A. Moore
  7. The End of AI Data Centers — by Braden Kelley
  8. Cognitive Enhancement and the Augmented Worker — by Braden Kelley
  9. Leveraging Multi-Agent Orchestration Frameworks for Innovation — by Art Inteligencia
  10. We Must Think Less Like Engineers and More Like Gardeners — by Greg Satell

BONUS – Here are five more strong articles published in April that continue to resonate with people:

If you’re not familiar with Human-Centered Change & Innovation, we publish 4-7 new articles every week built around innovation and transformation insights from our roster of contributing authors and ad hoc submissions from community members. Get the articles right in your Facebook, Twitter or Linkedin feeds too!

Build a Common Language of Innovation on your team

Have something to contribute?

Human-Centered Change & Innovation is open to contributions from any and all innovation and transformation professionals out there (practitioners, professors, researchers, consultants, authors, etc.) who have valuable human-centered change and innovation insights to share with everyone for the greater good. If you’d like to contribute, please contact me.

P.S. Here are our Top 40 Innovation Bloggers lists from the last five years:

Subscribe to Human-Centered Change & Innovation WeeklySign up here to get Human-Centered Change & Innovation Weekly delivered to your inbox every week.

Thin Lizzy – An Innovation Miracle from a Monster

Leave a reply

Gila monster in the Southwest desert - a source of bio-inspired innovation and GLP-1 medical breakthroughs

GUEST POST from Pete Foley

The pejoratively named Gila monster is a protected and borderline endangered species that inhabits my adopted Southwest.  It is the only venomous lizard in the USA, but while its venom can be deadly, human deaths are extremely rare.  It’s generally a shy, slow moving creature that spends much of its time underground.  It presents little danger unless you try to handle it, and if you are lucky enough to see one, it’s pink and black colors make it quite stunning to look at.

Monsters and Weight Loss: But whether you perceive it as beauty or beast, it has recently played a surprisingly important and beneficial role in human health.  As many reading this will already know, it’s venom is the origin of GLP-1’s. These are the ‘miracle ingredient’ found in diabetes and weight loss drugs like Ozempic and Wegovy.  GLP-1’s were initially isolated from Gila Monster venom about 30 years ago. These ‘Thin Lizzy’ drugs are now manufactured synthetically, but it’s unlikely that we’d have discovered them without the help of this maligned ‘monster’

A Benevolent Monster. Type-II diabetes and obesity are deadly diseases, and GLP-1’s have helped many patients live longer, better quality lives. I sometimes worry about over and unsupervised use, and long term effects of such a widely used new drug.  But there is no question around the benefits it has brought to the human race.  Gila is a benevolent monster, and we owe it our thanks for saving countless lives.  

Bio-Inspired Innovation:  In a broad sense, this is a great example of biomimicry, or at least copying innovation from nature.  Nature is a huge untapped resource of largely pre-cooked innovations.  Pretty much any problem we face, somewhere nature has already solved. It’s not always easy to find or adapt those solutions, but sometimes when we do, we get miracles like GLP-1. We can find innovations anywhere in nature, but marginal environments often have disproportionately more. They force evolution, as nature has to solve more difficult problems.  Often we hear biodiversity expressed in terms of ‘number of species’. That is a valid claim. There is no question, for example, that the density of species and fierce competition in the Amazon make it a rich source of biodiversity, and hence bio-derived innovation. But the huge number and diversity of species there also adds to the ‘needle in a haystack’ challenge we find with seeking innovation in nature. But the extremely harsh, hot, dry, environment of Southwest Deserts can also drive unusual adaptations.  In the case of GLP-1’s, their metabolism and glucose management help the Gila monster navigate an environment where food and water is scarce, and feeding sporadic.   Perhaps more importantly, given the harshness of the environment here, it’s likely that GLP-1’s are the tip of the ice-berg, and that our desert contains a reservoir of many more useful secrets waiting to be unlocked, especially around metabolism and water management.

Destruction of Wilderness:  But marginal environments are often also where species are most fragile and under threat.  In the desert southwest, the Gila’s habitat (and that of other marginalized species like the desert tortoise) is being squeezed from all directions.  An historic drought has gripped much of the area for decades.  And we are now compounding that with massive housing developments, even bigger industrial scale solar farms, and the massive infrastructure needed to transmit the energy those farms create. Even more recently, we are further compounding that ’squeeze’ with data centers, increased mining for rare metals and more.  These ‘developments’ not only destroy massive swathes of wilderness, and put additional pressure on already endangered species, but also compound drought and climate change by piling rapidly accelerating heat island effects on top of a warming climate.

Don’t Shoot Yourself in the Foot. As an innovator I embrace change, and recognize that progress inevitably comes with trade-offs.  But change needs to be managed thoughtfully, especially the inevitable trade offs that change creates in a complex system. Speed is often important, but it needs to be weighed against the need to have some basic understanding of the broad impact we have beyond the narrow, core objective. To use a ‘western’ analogy, in a gunfight it’s important to fire first, but not so fast that you shoot yourself in the foot.

The Desert is an Ocean with its Life Underground: In my last article I talked about the need for more scientists in leadership positions. One of the reasons for this is that our leaders today often appear unable, or perhaps unwilling to look at the big, complex picture, but instead over-simplify issues.  Nowhere is this more evident than in the southwest United States, where in the rush for growth, ‘renewable’ energy, raw material independence and AI development is destroying huge swathes of wilderness. While well intentioned, this is often driven by leaders who are focused on narrow goals, and ignore collateral damage by simplistically regarding the Mojave and as ‘s ‘only a desert’. But that desert is really an extremely complex and fragile system. GLP-1’s are likely the tip of the iceberg. We don’t know what else lies below the surface, but we need to be careful that we don’t destroy it before we have a chance to find out

The Pros and Cons of Solar Energy in the Desert: Just taking mass solar as an example of well intentioned but overly simplistic thinking.  Our deserts are rapidly getting littered with massive industrial scale solar farms, together with the equally massive infrastructure needed to transport the electricity they create to population centers, and/or AI data centers.

At a basic level, the concept of solar is a good one; what’s not to love about pollution free energy independence?  But if we look at the bigger, far more complex picture, it’s nowhere near that simple.

Too Hot For Solar? For example, a hot sunny desert is a superficially obvious place to build solar infrastructure.  But that’s until we realize that surface temperatures are so hot cells operate far below optimum efficiency.  Meanwhile dust further reduces efficiency, and remote locations make building, maintaining and connecting these farms difficult, expensive and environmentally damaging.

Collateral Damage: Solar farms and their infrastructure do extensive damage to our desert wilderness. They remove habitat for endangered species, and block migration roots for others.  Their installation and maintenance uses scarce water, and creates significant CO2 emissions (the thing they were supposed to prevent).  Much of the technology is shipped from China, posing a question around true energy independence, and that shipping and manufacture also creates CO2.  Climate change is a global issue, and while shifting CO2 emission for solar manufacture from the US to China may look good on some spreadsheets, it does nothing to solve the actual problem. 

These solar farms also create enormous amounts of dust.  Installing them requires removing of both surface crust and vegetation whose slow growing root systems hold the desert surface together (and ironically store CO2 via a symbiotic relationship with a mycelium).  That dust not only reduces the efficiency of the solar panels themselves, but also presents a hazard to traffic, and can even be quite toxic.  Mojave desert dust contains both natural asbestos and potentially deadly valley fever.  Its why all construction has to be constantly sprayed with increasingly scarce water.

With industrial scale desert solar, the narrow view of ‘renewable and ‘clean’ solar energy’ is highly attractive.  The reality is more complex, and full of trade offs that pit a green core technology against the environmental cost of construction, maintenance, eventual decommissioning, destruction of habitat and unintended consequences such as toxic dust. This makes a superficially simple choice far more complex. Some trade offs are alignable. For example, we can probably calculate actual net CO2 savings over the lifetime of a solar farm after manufacture, shipping, installation and decommissioning are taken into account.  But I’m not even sure if we can truly compare some of the other trade offs.  How do we quantify the trade off between toxic dust and reduced CO2 emissions?  Or how do we quantify and compare the impact of water usage, or loss of habitat to endangered species? 

Simplistic Focus: The result is a very complex calculation. But what is clear is that our leaders today typically ignore this, and instead remain simplistically focused on the narrow view.  Maybe if we could get more scientists into leadership positions we might do a better job of understanding trade offs, and the cost benefit of new technologies.  Today politicians all too often line up in favor of, or in opposition to projects based on overly simplistic, partisan frames, when really we need to manage complex trade offs. 

Calculating the Cost of Change in Complex Systems: Now, although I believe we need to do much better at managing complex systems, that doesn’t mean the pendulum needs to swing to far in the other direction. Complexity and uncertainty should not become an excuse for procrastination, inaction, or what I like to call the tyranny of data. The later is when we get stuck generating data and reports in increasing detail that add so much complexity, we never make a decision. As an innovator I embrace change, and recognize that progress inevitably comes with trade-offs.  But it’s about balance, and its critical to understand those trade offs at a systems level before charging ahead with initiatives, but still be willing to move forward embracing some uncertainty. All innovation comes with some risk, but smart innovators minimize those risks and balance them against timely progress.  And scientists are trained to learn as they go. That’s a balance I’d argue our leaders are struggling with today, swinging between inaction, and massive investments based on limited knowledge.

Solar is one example. But there are many more. In my home city of Las Vegas we are already facing a severe water crisis and extreme heat island effects.  In light of that, the mass destruction of wilderness to build 250,000 new MacMansions in the desert seems to lack even minimal big picture thinking.  Data centers, the innovation de jour are a more complex challenge. There is certainly a demand for them, and there is  a powerful, albeit US centric argument for keeping the US at the head of the AI innovation curve.  That means we do need data centers, but the cost in water and energy, two resources that are in relatively short supply here, arguably makes the SouthWest a poor choice of location.  Although I’ll acknowledge that data centers are rapidly becoming a somewhat universal ‘good idea as long as it’s not here’ technology.

Embracing Complexity and Solving Trade Offs:  But embracing complexity and looking at these at a systems level does not mean stopping innovation or progress. Quite the opposite, it should ultimately help us to innovate more effectively, and maybe face-plant less often. Identifying and challenging trade offs had long been a source of innovation, and is at the core of many innovation processes.  For example, with AI, could the US stay ahead of the AI curve by focusing data centers on more useful tasks, while cutting out less useful and energy expensive ‘slop’ such as action figures and/or caricatures?  That is maybe where regulation comes in, but as I mentioned in my last article, regulation without understanding risks both being ineffective, or creating unintended collateral damage. So this all supports the need for more technical ‘savvy’ in leadership.  
 
We Don’t Know What We Don’t Know.  When we try to evaluate trade off’s associated with innovation, what we don’t know is always one of the biggest challenges.  Who would have guessed 30 years ago that the Gila monster would provide the cure for obesity, and significantly reduce Type -II diabetes.  As mentioned before, we can be fairly sure that our desert wilderness holds many more untapped innovations, but we just don’t know what they are.  That harsh environment drove the evolution of tools for metabolism and glucose management that today treat obesity and diabetes management.  Longer term, could they also be a source of chemistry with efficacy against cancers, where glucose restriction and differentiation between the kinetics of healthy and cancer cell replication are effects we have, and will likely continue to exploit?  That’s speculation, but it highlights that we often don’t know all of the trade offs, and so those complex models need to be monitored and updated.  Narrow focus on a simplistic model means we miss so many potential opportunities. We also risk destroying the sources of the innovations and breakthroughs we haven’t found yet

Image credits: Google Gemini

Subscribe to Human-Centered Change & Innovation WeeklySign up here to join 17,000+ leaders getting Human-Centered Change & Innovation Weekly delivered to their inbox every week.

The Anatomy of Agentic Trust

Leave a reply

A Mechanistic Interpretability Framework for Change Leaders

LAST UPDATED: June 5, 2026 at 3:13 PM

The Anatomy of Agentic Trust - A Mechanistic Interpretability Framework for Change Leaders

GUEST POST from Art Inteligencia

The Impasse of the Black Box: Why Agentic AI Demands a New Trust Paradigm

Digital transformation has reached an inflection point. Organizations are moving away from traditional, deterministic software and basic copilots toward Agentic AI—autonomous systems capable of executing complex, multi-step operational workflows with minimal human oversight. While this shift promises unprecedented efficiency, it introduces a severe psychological and operational barrier: The Wall of Trust.

The Shift to Autonomy

Unlike previous iterations of artificial intelligence that relied on simple pattern-matching or isolated text generation, agentic systems possess agency. They can formulate plans, interact with external software ecosystems, and make consequential business decisions independently. However, because these systems are built on top of massive deep learning architectures, their reasoning remains entirely opaque.

The Psychological Friction of Current AI Explanations

Traditional approaches to Explainable AI (XAI)—such as post-hoc approximations, saliency maps, or text-based self-justifications—are no longer sufficient for enterprise governance. These methods merely show what data correlated with an output; they do not reveal the actual underlying computational logic. When an autonomous agent makes a flawed decision, a post-hoc explanation acts as a guess rather than an audit trail. For a workforce tasked with collaborating alongside these machines, this lack of transparency breeds deep-seated skepticism.

The Change Management Mandate

Successful innovation and experience design depend entirely on psychological safety. Change leaders cannot integrate autonomous agents into hybrid human-machine teams if the machine’s logic remains inscrutable. To transition employees from defensive resistance to confident collaboration, organizations must establish absolute legibility. Mechanistic interpretability provides the exact verifiable transparency required to align AI agents with human ethics, compliance mandates, and organizational values.

Demystifying Mechanistic Interpretability: From “Black Box” to Open Circuit

To dismantle the black box, innovation and change leaders must embrace a paradigm shift in how we audit artificial intelligence. Mechanistic Interpretability (MI) moves away from treating neural networks as abstract, unknowable minds. Instead, it approaches them like complex, physical objects—akin to an intricate mechanical watch or an integrated circuit board—that can be systematically disassembled and reverse-engineered.

The “Neuro-Industrial” Approach

Rather than merely observing what goes into a model and what comes out, MI focuses on internal computational mechanics. By treating deep learning structures as physical systems waiting to be mapped, researchers and engineers can trace the exact pathway information takes as it moves through the network. This shifts the conversation from passive observation to rigorous, empirical auditing.

Deconstructing the Neural Architecture

Understanding this open-circuit paradigm requires looking at three core components of modern model architecture:

  • The Communication Channel (The Residual Stream): Think of the residual stream as the primary information highway of a Large Language Model. As data passes from layer to layer, each computational mechanism reads from and writes to this central highway, iteratively refining the concepts the model is processing.
  • The Challenge of Superposition: Deep learning models are incredibly efficient compactors. Through a phenomenon known as superposition, a network can compress thousands of overlapping concepts into a relatively small number of neurons. This results in “polysemanticity”—where a single neuron might fire for a medical diagnosis, an ancient historical event, and a specific lines of code, making raw network readouts look like total gibberish to humans.
  • The Solution (Sparse Autoencoders): To untangle this mess, researchers use an auxiliary tool called a Sparse Autoencoder (SAE). The SAE acts as an analytical lens, expanding the compressed neural activity back out into an uncompressed, highly specific map of distinct business concepts and features. Polysemantic neurons are separated into clean, human-readable concepts.

Mapping the Circuits

Once the concepts are isolated by Sparse Autoencoders, change and safety leaders can trace how individual components connect to form causal, end-to-end pathways—or circuits. These circuits execute specific pieces of logic, such as a circuit that detects tax compliance rules or a circuit that handles data privacy boundaries. Mapping these circuits turns an opaque mathematical matrix into a transparent, visual map of organizational logic.

The Commercial Frontier: Leading Organizations and Startups Shifting MI from Theory to Tooling

What began as an academic and safety-centric pursuit has quickly evolved into a critical layer of the enterprise AI value chain. As organizations demand verifiable trust before deploying agentic workflows, a robust commercial ecosystem has emerged. Today, the development of Mechanistic Interpretability tools is divided among frontier research labs, open-source consortia, and specialized AI safety startups.

Frontier Research Labs: Setting the Scale

The foundational model developers themselves are treating internal architectural translucency as both a primary safety barrier and a competitive advantage.

  • Anthropic: Widely recognized as a pioneer in dictionary learning, Anthropic demonstrated commercial-scale concept mapping by isolating millions of abstract, safety-critical, and real-world features inside its Claude models. Their pioneering work in circuit tracing maps not just which features are active, but how they causally influence each other in sequential processing chains.
  • OpenAI: Operating at massive computational scale, OpenAI has focused on automating the interpretability pipeline itself. By utilizing advanced Large Language Models as automated “feature explainers,” they systematically analyze, score, and catalog millions of dense neuron activations simultaneously across models like GPT-4, laying the groundwork for algorithmic “lie detectors” built directly into model internals.
  • Google DeepMind: DeepMind significantly accelerated industry-wide adoption with the release of Gemma Scope, a massive, comprehensive open-source interpretability toolkit mapping across the entirety of its Gemma model families. This initiative effectively democratizes MI, giving enterprise change and innovation leaders the open tools needed to audit fine-tuned models independently.

Open-Source Consortia

Bridging the gap between frontier research and accessible development is EleutherAI. Through specialized open-source libraries like sparsify, EleutherAI provides researchers and enterprise engineers with the standard blueprints required to train Sparse Autoencoders (SAEs) and transcoders directly on HuggingFace transformers, allowing organizations to extract custom, localized operational feature dictionaries without relying on proprietary third-party APIs.

The Emerging AI Governance & Steering Startup Ecosystem

As the market shifts from post-hoc model analysis to real-time behavioral intervention, a specialized group of AI safety, security, and compliance startups has emerged. These early-stage innovators are building platforms that operationalize MI principles for the enterprise:

  • Algorithmic Auditing & Protection Platforms: Emerging vendors—including teams like Protect AI, Turing, Holistic AI, and Enkrypt AI—are actively developing continuous monitoring guardrails, neural audit logs, and PII containment shields.
  • From Observation to Intervention: Rather than just notifying a business that an autonomous agent has hallucinated, the vanguard of this ecosystem is building enterprise toolsets focused on feature steering. By giving compliance officers and change managers the ability to programmatically clamp down or amplify specific feature vectors, these platforms provide an exact knob to safely steer agent behavior in production environments without requiring costly model retraining cycles.

The Collaborative Interface: Designing the Human-Machine Audit Trail

For change and innovation leaders, a technical map of a neural network is only useful if it can be translated into operational reality. To turn Mechanistic Interpretability from an engineering luxury into a practical governance mechanism, organizations must implement a standard action loop. This practical paradigm is defined by three continuous operational steps: Locate, Steer, and Improve.

1. Locate (The Diagnostic Phase)

When an autonomous AI agent produces an unexpected anomaly, drifts from compliance, or triggers a customer experience failure, traditional troubleshooting is useless. Under the MI framework, operations teams initiate the Locate phase. By utilizing Sparse Autoencoders, corporate compliance teams can systematically look under the hood to isolate the exact subgraphs and internal feature nodes that dictated the agent’s flawed decision path. Instead of guessing why an error occurred, leaders can pinpoint the specific computational circuit responsible for the behavior.

2. Steer (The Real-Time Intervention Phase)

Once a problematic circuit or feature node is located, the organization does not need to undergo a weeks-long, financially draining model-retraining process. Instead, leaders use feature steering to intervene directly. By programmatically adjusting, clamping, or dampening specific feature activations within the live system, operations teams can instantly align the agent’s behavior. For example, if an insurance agent begins using unapproved geographic criteria to assess risk, a compliance manager can safely dial down that specific feature vector without degrading the agent’s overall processing capabilities.

3. Improve (The Continuous Alignment Phase)

The final phase transitions the organization from reactive intervention to proactive refinement. Over time, data engineers, risk managers, and business unit leaders iteratively review the agent’s global modular vocabulary. By continuously updating and refining these feature dictionaries, the enterprise can permanently align autonomous workflows with changing regulatory landscapes, ethical guidelines, and internal corporate values. This creates a living, transparent human-machine audit trail that ensures autonomous systems remain accountable to human intent.

The Human-Centered Angle: Using Circuit Translucency to Drive Adoption

The ultimate success of any digital transformation initiative hinges on the psychology of the people expected to drive it. Technology alone does not yield ROI; adoption does. By turning the “black box” into a translucent, auditable map of circuits, Mechanistic Interpretability addresses the deepest root cause of workforce resistance: the fear of the invisible, unaccountable driver.

Abolishing the “Us vs. Them” Dynamic

When autonomous agents are introduced as inscrutable forces that magically output decisions, an adversarial dynamic inevitably forms between employees and technology. Teams view the AI as an opaque competitor designed to replace or undermine their judgment. Providing an interactive, auditable look “under the hood” radically reframes this relationship. When employees can visually trace the model’s logic pathways, the AI shifts from a mysterious threat to a legible, controllable tool. Demystification actively dissolves defensive skepticism and replaces it with shared ownership.

Designing the Experience of AI Auditing

Innovation and experience design leaders must proactively design the workflows that connect humans to these neural circuits. This requires upskilling traditional Subject Matter Experts (SMEs)—such as underwriters, clinicians, or compliance officers—from passive users into active “circuit overseers.” Instead of forcing SMEs to learn complex linear algebra, organizations must build intuitive, human-centered dashboard experiences. These interfaces translate complex Sparse Autoencoder feature dictionaries into plain language, empowering business leaders to confidently monitor, validate, and sign off on automated reasoning.

The Safety-Trust Horizon

Psychological safety cannot coexist with unpredictability. True confidence is built on empirical predictability—knowing exactly where the guardrails are and how to enforce them. By establishing a verifiable baseline for risk mitigation, circuit translucency gives operations teams the concrete evidence they need to trust autonomous systems. When a team knows they can structurally audit a workflow, catch compliance drift before it impacts a customer, and pinpoint exactly why an anomaly occurred, they can deploy agentic workforces at scale with absolute confidence.

Operationalizing the Framework: A Roadmap for Innovation Leaders

Transitioning an organization from opaque, unverified AI deployments to a translucent, mechanistically interpretable architecture requires an intentional, staged approach. Innovation and change leaders cannot implement this infrastructure overnight. Instead, they must systematically align technical capabilities with human experience design. This roadmap provides a practical three-phase deployment strategy to operationalize agentic trust across the enterprise.

Phase 1: Diagnostic Readiness and Risk Mapping

The first step is identifying high-stakes operational workflows where opaque agent logic presents an unacceptable risk to compliance, organizational stability, or brand trust. Leaders must audit their current AI roadmap and pinpoint “red zone” processes—such as autonomous financial underwriting, automated contract enforcement, or clinical triage routing. By scoring these workflows based on regulatory exposure and the psychological impact on the employees overseeing them, organizations can prioritize exactly where mechanistic transparency is required to maintain operational stability.

Phase 2: Architectural Translucency and Feature Extraction

Once high-risk workflows are mapped, innovation leaders must partner directly with AI engineering and data science teams to build out the technological transparency layer. This phase involves integrating open-source frameworks or commercial governance platforms directly into fine-tuned enterprise models. Engineers deploy Sparse Autoencoders (SAEs) and transcoders across the model’s layers to untangle polysemantic neurons, systematically extracting a structured, human-readable dictionary of the specific business concepts, compliance rules, and operational parameters the agent uses during execution.

Phase 3: Cultural Integration and Co-Creation Loops

The final phase embeds this structural transparency directly into the company’s operating model and culture. Change leaders must design and establish cross-functional governance loops where compliance officers, risk managers, change management practitioners, and front-line business leaders systematically review and steer agent behavior. By designing intuitive dashboards that translate extracted features into plain language, organizations empower non-technical personnel to participate in feature-steering exercises, transforming AI alignment from a back-office engineering chore into a collaborative corporate discipline.

Conclusion: The Future of Co-Elevation

As organizations stand on the precipice of widespread Agentic AI deployment, a critical truth becomes apparent: the ultimate bottleneck to scaling artificial intelligence is not computational power, data density, or algorithmic sophistication—it is human trust. Businesses cannot capture the exponential ROI of autonomous workflows if their own teams pull back in skepticism, or if compliance frameworks reject the inscrutable nature of the systems driving them.

The Core Philosophy

Mechanistic Interpretability represents far more than a technical patch for AI safety. It is a fundamental philosophical shift that treats neural networks with the same empirical rigor we apply to physical engineering. By transforming the “black box” into a legible blueprint of interconnected circuits, we strip away the unhelpful mystique surrounding deep learning. This structured transparency provides the absolute bedrock for psychological safety, transforming autonomous agents from opaque wildcards into predictable, reliable partners.

The Innovation Call to Action

Forward-thinking innovation and change leaders must stop viewing AI safety and interpretability as a narrow, back-office technical function left solely to data scientists. True, sustainable digital transformation requires a holistic approach. It is the responsibility of culture builders, experience designers, and corporate strategists to champion architectural translucency. By operationalizing Mechanistic Interpretability, enterprises can successfully bridge the cognitive divide, mitigate systemic operational risk, and unlock the true potential of a highly confident, collaborative, and co-elevated human-machine workforce.

Frequently Asked Questions

To help both your human teams and automated search crawlers understand the intersection of AI safety and organizational change, this section includes a standard human-readable FAQ alongside a structured JSON-LD Schema block optimized for modern answer engines.

1. How does Mechanistic Interpretability differ from standard Explainable AI (XAI)?

Traditional Explainable AI (XAI) usually generates post-hoc guesses or approximations—like text descriptions or heat maps—of why a model arrived at an output. It tells you what inputs correlated with the result, but not the actual path taken. Mechanistic Interpretability (MI) reverse-engineers the network itself, unpacking compressed neural activity to reveal the literal computational “circuits” and logical workflows inside the model. It moves from correlation to true mechanical causation.

2. Why is structural transparency critical for human-centered change management?

Successful digital transformation requires psychological safety. When organizations deploy fully autonomous “Agentic AI” workflows without visibility, employees experience defensive skepticism because they cannot audit, predict, or trust the system’s logic. By making the model’s internal reasoning translucent, change leaders can transition human teams from resistant onlookers to confident collaborators who can proactively steer and manage their AI partners.

3. What is “feature steering” and how does it protect an organization?

Feature steering is the ability to programmatically amplify, clamp, or dampen specific concept vectors isolated inside a model using Sparse Autoencoders (SAEs). Instead of undergoing a long, expensive retraining or fine-tuning process when an AI agent drifts out of compliance or experiences a workflow anomaly, compliance and innovation managers can adjust the model’s specific internal logic dials in real time to ensure safe, ethical execution.


Disclaimer: This article speculates on the potential future applications of cutting-edge scientific research. While based on current scientific understanding, the practical realization of these concepts may vary in timeline and feasibility and are subject to ongoing research and development.

Image credits: Gemini

Subscribe to Human-Centered Change & Innovation WeeklySign up here to get Human-Centered Change & Innovation Weekly delivered to your inbox every week.

We Need More Innovators and Scientists in Leadership Roles

2 Replies

We Need More Innovators and Scientists in Leadership Roles

GUEST POST from Pete Foley

Our world is changing at an unprecedented rate. We are in an innovation driven economy. AI, genetic manipulation, energy innovation, climate, and virtually anything driving change are all highly technical and complex. And all come with high stakes pros and cons.

Scientists and innovators navigating this requires strategic leadership that understands technical complexity, uncertainty and that collectively has some knowledge of basic science and engineering. 

Politics Lacks Scientists: Today, while more than half of US Senators have a law background, only one has a science PhD.  I believe this creates a serious gap in fundamental knowledge between our strategic leaders and the innovators that are driving change.

Experts or Oracles? Of course, our leaders have access to ‘experts’ to help them with complex topics.  But when the fundamental knowledge gap between leaders and experts becomes too big, experts become oracles. They pronounce rather than persuade. When this happens we risk the determining factor in strategy becoming superior communication skills, instead of knowledge or superior ideas.  The ideas (and regulations) that win are not the necessarily best ones, but the ones championed by good communicators, salesmen scientists or smooth talking lobbyists.  It’s dangerous to follow the science blindly, and even riskier to regulate what we don’t understand. That invites dangerous unintended consequences. But increasingly, that is the path we are on.
 

Why We Need More Innovators and Scientists in Leadership Roles

Of course, our leaders don’t need to all be 160 IQ polymaths with PhD’s in quantum mechanics. But to make good decisions they do need to at least be able to understand and apply critical thinking to the inevitably conflicting opinions of experts.

Communicating Science and Technology: Now of course, much of the onus for promoting understanding of complex technology lies with us in the broader innovation and science community.  If we cannot communicate knowledge to people who own resources and executive power, then we risk that knowledge becoming redundant.

But communication is always a two way street. Bridging between leaders and experts requires some common ground.  It’s really hard to have a useful discussion with someone who does even have a basic vocabulary for a topic. As technology and innovation become increasingly important, without more technically savvy leaders we risk a disconnect between strategy, regulation and knowledge. As our leaders get older, and more disconnected from the science driving change they rely less on quality of ideas, and more on appealing framing of ideas, or perhaps familiarity with equally disconnected experts. That is a dangerous path.

Non Scientific Mindsets Facing Technical Challenges. One key danger is the tendency to view choices as binary, another is sunk cost. Binary choices are superficially easy, but in the real world most innovation is not black and white, but instead involves some form of trade off.  Whether it is AI, energy strategy, pharmaceutical development or one of the other ever growing list of emerging technologies, there are benefits, but also costs.  With AI for example, the benefits of gaining and holding global leadership of the technology are likely as economically huge as the opportunity cost of not doing so.  But with big opportunity also comes big risks, including the environmental costs of data centers, risks to societal structure, and even existential risk to humanity itself.  The stakes don’t get much higher.

The Uncertainty Principle: And this is multiplied by the sunk cost fallacy. Over commitment to an incorrect binary choice can be really risky. While we know there are going to be pros and cons to any new technology, we rarely understand them very well in advance.  Innovation is by definition a dive into the unknown, and that makes accurately predicting both upsides and downsides really difficult.  This requires flexible, agile thinking, openness to new data, and a willingness to adjust mid-flight, skills inherent to science and technology . 

But as a society, if anything we seem to be moving away from flexible thinking, and towards more rigid viewpoints that are often heavily pre-primed by affiliations, preconceptions and bizarrely, politics.  People are often passionately for or against AI, but all too often without really knowing why. ‘Green’ energy is polarizing, climate change is divisive.  But while passion and ownership have their place, often the best answer is not cheerleading for a team. Instead it’s beneficial to find a flexible balance that acknowledges the pros and cons, and that ideally identifies non zero sum answers for those contradictions. But that again typically requires nuance, and some level of technical understanding. 

Finding Non Zero Sum Answers: The good news is that once we step away from polarized and binary thinking, non zero sum solutions are sometimes not as hard to find as we think.  Just as an example, with AI, there is potential to have our cake and eat it.   If we cut out digital slop, it’s conceivable that could we achieve and maintain technology leadership, but with much lower environmental cost.  For example, using AI to solve complex medical problems may be a net benefit that is worth some damage to our wilderness, or use of our scarce resources.  But action figures, generic illustrations, mediocre music and often pointless copies of master artists not so much!  I’m sure all of the latter help advance our knowledge to some degree, and help to justify AI investment, but by being more selective, could we achieve the same or similar ends with a superior benefit/cost ratio? 


The Human Advantage: But making smart trade-off decisions like this requires flexible and creative thinking.  Ironically that is one of the things humans still do better than AI.  We just need to embrace our human strengths, but also make sure our leaders also reflect those strengths.

Innovators in Leadership Roles: This means we need a more balanced and scientific approach to leadership if we are navigate the increasingly technology driven future.  Having lawyers making laws is not bad per se, but I passionately believe we need a more diverse set of skills at our upper leadership levels if we are to effectively navigate the coming years. That means the innovation and scientific community needs to step up.  We also need to get much better, and mea culpa, at communicating complex issues.  It’s critical to be clear and simple but not simplistic.

The Tyranny of Simplicity: Simplistic answers, memes, and binary choices have a great deal of superficial appeal.  And politicians and the media exploit this very effectively. In our information overloaded, time constrained world, everybody’s cognitive bandwidth is stretched.  We often seek answers rather than understanding because that’s all we have time for.  But from a leadership perspective, we need to understand that limited cognitive bandwidth is not the same as limited intelligence. People may grasp for simplistic answers, but because they have no commitment to them based on their own knowledge or critical thinking, that grasp is tenuous. This means that being simplistic can be self defeating in the long run.  For example, take the much quoted, ‘globally agreed’ climate target; to not exceed a 1.5 degrees Celsius increase since pre-industrial times. For sure, some people will accept this without question. But other enquiring minds will ask if 1.49C OK? Is this a tipping point? Do we fall of a cliff at 1.51C. Conversely, what happens if we exceed that limit and nothing dramatic happens?  Do we discard that boundary, or move it? Then there are obvious questions around how we address that boundary. What will it take to prevent crossing it?  What are the trade offs?  Who has the sphere of influence to actually make a difference?  It’s OK to have a simplistic position, but it needs to be supported by layered reasoning.


Cry Wolf: I’m not suggesting that climate scientists who promote 1.5C don’t grasp this complexity.  But somewhere in the path from science to politicians and media the real world complexity it often gets lost in translation.  And thats not trivial, as it creates the risk of ‘cry wolf’ effects, and of leaders being perceived as manipulative.   If we overstate the importance of 1.5 C, and it proves to be wrong, or at least a softer limit than previously advertised, we risk people perceiving that they have been mislead or manipulated.  That then feeds skepticism, and even gives support to some of the wilder ‘conspiracy theories’. Once a source has become discredited on one vector, it is typically discredited on everything. 

No easy answers to this.  But I believe innovators and scientists really need to take a bigger leadership role in a world where innovation is increasingly the driving force. Politicians generally don’t get elected because they deeply understand complex issues, but because they understand how to motivate, communicate, simplify and manipulate. They often rely on peoples limited cognitive bandwidth, as this helps them to craft simple slogans, concepts, and sometimes trigger fear and division. Remember that we dislike losing something about twice as much as we like gaining it, which makes fear a very powerful manipulative tool. That brings power, but not necessarily wisdom. But limited cognitive bandwidth is not the same as limited intelligence. And simplistic concepts are vulnerable to challenge, or evolving data.

Of course, we don’t want to make every issue a PhD thesis.  But we do need to acknowledge increasing complexity and uncertainty, and at the very least develop authentic, layered narratives that acknowledge complexity and the inevitable uncertainty of an innovation driven world.  Without that, our strategies become extremely fragile, and easily shattered the first time we are proved wrong. Even if we may start from a position of intense conviction, we must also change paths in the face of compelling evidence. Scientists and innovators tend to be good at this. It’s a skill that maybe needs to be used more broadly

Image credits: Google Gemini

Subscribe to Human-Centered Change & Innovation WeeklySign up here to join 17,000+ leaders getting Human-Centered Change & Innovation Weekly delivered to their inbox every week.

Why You Need to Leverage Shared Values in Change Leadership

Leave a reply

Why You Need to Leverage Shared Values in Change Efforts

GUEST POST from Greg Satell

When Lou Gerstner took over at IBM in 1993, the century-old tech giant was on its knees. Many thought it should be broken up into smaller, more focused companies. Others had different ideas. So at Gerster’s first press conference, people were curious about his strategy and disappointed when he failed to deliver one.

“The last thing IBM needs right now as a vision,” he said. What he meant was that IBM’s culture was broken. “Culture isn’t just one aspect of the game,” he would later write. “It is the game. What does the culture reward and punish – individual achievement or team play, risk taking or consensus building?”

What Gerstner saw was that IBM had lost sight of the values that had made it successful in the first place. He wasn’t “disrupting.” He was making IBM culture safe to innovate again and, by doing that, he achieved one of the most remarkable turnarounds in corporate history. If you want to achieve truly radical change, you need to start with shared values.

Making The Shift From Differentiating Values To Shared Values

IBM wasn’t Gerstner’s first stint leading a company. He’s been President at American Express and CEO at RJR Nabisco, both of which were very different from technological companies. Yet Gerstner didn’t focus on how his experiences were different, but on how they were the same—each of these businesses have to serve the customer.

“Lou refocused us all on customers and listening to what they wanted and he did it by example,” Irving Wladawsky-Berger, one of Gerstner’s chief lieutenants would later tell me. “We started listening to customers more because he listened to customers.” It was upon that simple principle that he changed the course of IBM’s future.

In a similar vein, when Nelson Mandela wanted to create a new future for South Africa, he organized a Congress of the People, a multi-racial gathering which produced a statement of shared values that came to be known as the Freedom Charter, which is still revered even today. He would later say it would have been very different if his organization, the ANC, had written it by themselves, but it wouldn’t have been nearly as powerful

When we’re passionate about an idea, we want to show how it’s different. We want to explain all its beautiful complexity and nuance, so that people can share our passion and fervor. That’s almost always a mistake. The first step to creating truly transformational change is to anchor it in what people already know and feel comfortable with.

Creating Safety Around The Change Conversation

When an enterprise is in crisis, one of the first things that often gets cut is investments in the future. So when Gerstner scheduled his first non-headquarters visit at IBM to the firm’s legendary research facility at Yorktown Heights, everybody there got nervous. Many expected there to be deep cuts and, possibly, that the entire facility would be shut down.

Actually, quite the opposite. “I saw the pain of IBM’s problems on their faces,” Gerstner remembered. “I talked about how proud I was to be at IBM. I underscored the importance of research to IBM’s future.” It was a wise move. Although few knew it at the time, scientists at IBM had just made a major breakthrough that made quantum computing possible and a few years later the company’s Deep Blue supercomputer would beat Garry Kasparov at chess.

Many change management schemes advise to create a “sense of urgency” and creating a “burning platform” atmosphere. Yet Gerstner understood that employees were perfectly aware of how dire the situation was. What they needed wasn’t more fear, but to see a path forward. Terrified people don’t make good decisions. They’re also more likely to head for the exit than to work for the future.

Don’t get me wrong, you don’t want to sugarcoat things. You need to be frank, honest and paint a clear picture. Gerstner made it plain that day that there would be changes. Yet by rooting his message in shared values, he was able to create a sense of safety around the change conversation. The scientists were able to see that they could, in fact, be heroes in the story of IBM’s future. As it turned out, they would be.

Creating A Dilemma Rather Than A Conflict

Once you start being explicit about your values you will inevitably find that not everyone shares them and that was certainly true at IBM. For example, Wladawsky-Berger told me that “IBM had always valued competitiveness, but we had started to compete with each other internally rather than working together to beat the competition. Lou put a stop to that and even let go of some senior executives who were known for infighting.”

A simple truth is that whenever we set out to make a significant impact, there will always be those who will work to undermine what we are trying to achieve in ways that are dishonest, underhanded and deceptive. Yet when that happens we need to be careful not to get sucked into a conflict, which will likely take us off course and discredit what we’re trying to achieve. Instead, we need to learn to design a dilemma.

Dilemma actions have been used for at least a century—famous examples include Gandhi’s Salt March, King’s Birmingham Campaign and Alice Paul’s Silent Sentinels—but more recently codified by the global activist, Srdja Popović. They are just as effective in an organizational context, using an opponent’s resistance against them.

One of the great things about dilemma actions is that you approach them exactly the same way you approach building allies—by identifying a shared purpose. Once you do that, you can design a constructive act rooted in that shared purpose that advances your agenda. That forces your opponent to make a choice: they can either disrupt the act and violate the shared value or they can let it go forward and allow change to proceed.

For example, I was once running a transformation project that was being impeded by a Sales Director hogging accounts. Although it was agreed that she would distribute her clients, she never got around to it. So I set up a meeting with a key account and one of our salespeople. When she tried to disrupt the meeting, she violated the shared value we had established and was dismissed from her position. Everything fell into place after that.

Forging A Shared Purpose

Change always begins with a grievance—there’s something people don’t like and they want it to change. Yet the status quo always has inertia on its side and never yields its power gracefully. That’s why it’s so important to forge a shared purpose, because people need a common mission they can believe in to see themselves as stakeholders in a shared future.

The reason so many organizations find themselves unable to pursue a purpose isn’t because they don’t want to, but because it is so hard. Purpose doesn’t begin with a single step, but with a diverging path. To honor a value we need to be willing to incur costs and constraints. We must choose one direction at the expense of another, or stay mired and lost, unable to move forward.

That’s why the change conversation needs to focus on what you value. Values are how an enterprise honors its mission. They represent choices of what an organization will and will not do, what it rewards and what it punishes and how it defines success and failure. Perhaps most importantly, values will determine an enterprise’s relationships with other stakeholders, how it collaborates and what it can achieve.

Perhaps most importantly, shared values enable a shared identity, which is what you need for change to last. The goal of a revolution, as Srdja Popović once explained to me, is not a constant state of disruption, but eventually to become mainstream, to be mundane and ordinary. That can only be done if change is built on common ground.

— Article courtesy of the Digital Tonto blog
— Image credit: Google Gemini

Subscribe to Human-Centered Change & Innovation WeeklySign up here to join 17,000+ leaders getting Human-Centered Change & Innovation Weekly delivered to their inbox every week.

Why Change Doesn’t Have to Start at the Top

Leave a reply

Why Change Doesn't Have to Start at the Top

GUEST POST from Greg Satell

In 2004 I found myself running a major news organization during the Orange Revolution in Ukraine. It was one of those moments when the universe opens up, reveals a bit of itself and you realize the world doesn’t work the way you thought it did. What struck me at the time was that nobody with any conventional form of power had any ability to shape events at all.

One of the myths that is constantly repeated is that change needs to start at the top. Clearly that is not true. It wasn’t true of the Color Revolutions that spread across Eastern Europe. Nor was it true of social movements like the fight for LGBT rights. Despite what you may have heard, it doesn’t hold true for organizations either.

What is true is that if you are going to bring about genuine change you need to influence institutions and that means you need, at some point, to involve senior leaders, but it rarely starts with them. The myth that change has to start at the top is a copout — a reason to do nothing when you can do something. Make no mistake. Change can come from anywhere.

Weaving Webs of Influence

Movements, as the name implies, are kinetic. They start somewhere and they end up somewhere else. That’s one reason why why so many successful change efforts become misunderstood. People look back at an event like the 1963 March on Washington and think that’s what made the civil rights movement successful. Nothing could be further from the truth. That wasn’t what built the movement, it was part of the end game.

Consider that the first “March on Washington,” the Woman Suffrage Procession of 1913, was a disaster. None of the others since 1963 did much either. The civil rights march came after nearly a decade of boycotts, sit-ins, Freedom Rides and other tactics that built the movement before it finally found its moment. Still, it’s the moment that people remember.

In much the same way, whenever we see a successful transformation we look to the actions of leaders. We see a CEO who gave a speech, a marketer who came up with a big product idea or an engineer who took a project in a new direction. These events are real, but they rarely, if ever, appear out of nowhere. They are products of webs of influence.

When we look more closely, we inevitably find that the CEO was inspired to give the pivotal speech from a conversation he had with his daughter. The marketer got the initial idea for the campaign from a junior team member. Or the engineer changed the direction of the project after a fateful encounter he had in the cafeteria.

Our decisions are the product of complex systems. Anything can start anywhere. Don’t let anyone tell you differently.

Going to Where the Energy Is

Transformations, in retrospect, often seem inevitable, even obvious. Yet they don’t start out that way. The truth is that it is small groups, loosely connected, but united by a common purpose that drives transformation. So the first thing you want to do is identify your apostles — people who are already excited about the possibilities for change.

For example, in his efforts to reform the Pentagon, Colonel John Boyd began every initiative by briefing a group of collaborators he called the “Acolytes,” who would help hone and sharpen the ideas. He then moved on to congressional staffers, elected officials and the media. By the time general officers were aware of what he was doing, he had too much support to ignore.

In a similar vein, a massive effort to implement lean manufacturing methods at Wyeth Pharmaceuticals began with one team at one factory, but grew to encompass 17,000 employees across 25 sites worldwide and cut manufacturing costs by 25%. The campaign that overthrew Serbian dictator Slobodan Milošević started with just 5 kids in a coffee shop.

One advantage to starting small is that you can identify your apostles informally, even through casual conversations. In skills-based transformations, change leaders often start with workshops and see who seems enthusiastic or comes up after the session. Your apostles don’t need to have senior positions or special skills, they just have to be passionate.

There’s something about human nature that, when we’re passionate about an idea, makes us want to go convince the skeptics. Don’t do that. Start with people who want your idea to succeed. If you feel the urge to convince or persuade, that’s a sign that you either have the wrong idea or the wrong people.

“You have to go where the energy is,” John Gadsby, who built a movement for process improvement inside Procter & Gamble that has grown to encompass 60,000 employees, told me. “We’ll choose energy and excitement and enthusiasm over the right position, or the person at the right leadership level, or the person whose job it is supposed to be to do that.”

Mobilizing People To Influence Institutions

In the early 1990s, writer and activist Jeffrey Ballinger published a series of investigations about Nike’s use of sweatshops in Asia. People were shocked by the horrible conditions that workers — many of them children — were subjected to. In most cases, the owners lived outside the countries where the factories were located and had little contact with their employees.

At first, Nike’s CEO, Phil Knight, was defiant. “I often reacted with self-righteousness, petulance, anger. On some level I knew my reaction was toxic, counterproductive, but I couldn’t stop myself,” he would later write in his memoir, Shoe Dog. He pointed out that his company didn’t own the factories, that he’d worked with the owners to improve conditions and that the stories, as gruesome as they were, were exceptions.

The simple truth is that change rarely, if ever, starts at the top because it is people with power that create the status quo. They are attached to what they’ve built and take pride in their accomplishments, just like the rest of us. That’s why, to bring about genuine change — change that lasts — you need to mobilize people to influence institutions (or those, like Knight, who yield institutional power).

Eventually, that’s what happened at Nike. The protests took their toll. “We had to admit,” Knight remembered, “We could do better.” Going beyond its own factories, the company established the Fair Trade Labor Association and published a comprehensive report of its own factories. Today, the company’s track record may not be perfect, but it’s become more a part of the solution than a part of the problem.

Change Is Never Top-Down Or Bottom-Up

At a pivotal moment during the height of the civil rights movement, Robert Kennedy, Attorney General of the United States and brother to the President, would turn to the activist John Lewis and say, “’John, the people, the young people of the SNCC, have educated me. You have changed me. Now I understand.”

Lewis, just a young kid in his twenties at the time, was himself the product of webs of influence. He was shaped by mentors like Jim Lawson and Keller Miller Smith, as well as by peers such as Diane Nash, Bernard Lafayette and James Bevel. They, in turn, influenced others to get out, protest and shape the minds of people like Robert Kennedy.

As I explain in Cascades, transformation isn’t top-down or bottom-up, but happens from side-to-side. You can find the entire spectrum — from active support to active resistance — at every level. The answer doesn’t lie in any specific strategy or initiative, but in how people are able to internalize the need for change and transfer ideas through social bonds.

Change never happens all at once and can’t simply be willed into existence. The best way to do that is to empower those who already believe in change to bring in those around them. That’s what’s key to successful transformations. A leader’s role is not to plan and direct action, but to inspire and empower belief.

— Article courtesy of the Digital Tonto blog
— Image credit: Unsplash

Subscribe to Human-Centered Change & Innovation WeeklySign up here to join 17,000+ leaders getting Human-Centered Change & Innovation Weekly delivered to their inbox every week.

Will our opinion still really be our own in an AI Future?

2 Replies

Will our opinion still really be our own in an AI Future?

GUEST POST from Pete Foley

Intuitively we all mostly believe our opinions are our own.  After all, they come from that mysterious thing we call consciousness that resides somewhere inside of us. 

But we also know that other peoples opinions are influenced by all sorts of external influences. So unless we as individuals are uniquely immune to influence, it begs at the question; ‘how much of what we think, and what we do, is really uniquely us?’  And perhaps even more importantly, as our understanding of behavioral modification techniques evolves, and the power of the tools at our disposal grows, how much mental autonomy will any of us truly have in the future?

AI Manipulation of Political Opinion: A recent study from the Oxford Internet Institute (OII) and the UK AI Security Institute (AISI) showed how conversational AI can meaningfully influence peoples political beliefs. https://www.ox.ac.uk/news/2025-12-11-study-reveals-how-conversational-ai-can-exert-influence-over-political-beliefs .  Leveraging AI in this way potentially opens the door to a step-change in behavioral and opinion manipulation inn general.  And that’s quite sobering on a couple of fronts.   Firstly, for many today their political beliefs are deeply tied to our value system and deep sense of self, so this manipulation is potentially profound.  Secondly, if AI can do this today, how much more will it be able to do in the future?

A long History of Manipulation: Of course, manipulation of opinion or behavior is not new.  We are all overwhelmed by political marketing during election season.  We accept that media has manipulated public opinion for decades, and that social media has amplified this over the last few decades. Similarly we’ve all grown up immersed in marketing and advertising designed to influence our decisions, opinions and actions.  Meanwhile the rise in prominence of the behavioral sciences in recent decades has provided more structure and efficiency to behavioral influence, literally turning an art into a science.  Framing, priming, pre-suasion, nudging and a host of other techniques can have a profound impact on what we believe and what we actually do. And not only do we accept it, but many, if not most of the people reading this will have used one or more of these channels or techniques.  

An Art and a Science: And behavioral manipulation is a highly diverse field, and can be deployed as an art or a science.   Whether it’s influencers, content creators, politicians, lawyers, marketers, advertisers, movie directors, magicians, artists, comedians, even physicians or financial advisors, our lives are full of people who influence us, often using implicit cues that operate below our awareness. 

And it’s the largely implicit nature of these processes that explains why we tend to intuitively think this is something that happens to other people. By definition we are largely unaware of implicit influence on ourselves, although we can often see it in others.   And even in hindsight, it’s very difficult to introspect implicit manipulation of our own actions and opinions, because there is often no obvious conscious causal event. 

So what does this mean?  As with a lot of discussion around how an AI future, or any future for that matter, will unfold, informed speculation is pretty much all we have.  Futurism is far from an exact science.  But there are a couple of things we can make pretty decent guesses around.

1.  The ability to manipulate how people think creates power and wealth.

2.  Some will use this for good, some not, but given the nature of humanity, it’s unlikely that it will be used exclusively for either.

3.  AI is going to amplify our ability to manipulate how people think.  

The Good news: Benevolent behavioral and opinion manipulation has the power to do enormous good.  Whether it’s mental health and happiness (an increasingly challenging area as we as a species face unprecedented technology driven disruption), health, wellness, job satisfaction, social engagement, important for many of us, adoption of beneficial technology and innovation and so many other areas can benefit from this.  And given the power of the brain, there is even potential for conceptual manipulation to replace significant numbers of pharmaceuticals, by, for example, managing depression, or via preventative behavioral health interventions.   Will this be authentic? It’s probably a little Huxley dystopian, but will we care?  It’s one of the many ethical connundrums AI will pose us with.

The Bad News.  Did I mention wealth and power?  As humans, we don’t have a great record of doing the right thing when wealth and power come into the equation.  And AI and AI empowered social, conceptual and behavioral manipulation has potential to concentrate meaningful power even more so than today’s tech driven society.  Will this be used exclusively for good, or will some seek to leverage for their personal benefit at the expense of the border community?   Answers on a postcard (or AI generated DM if you prefer).

What can and should we do?  Realistically, as individuals we can self police, but we obviously also face limits in self awareness of implicit manipulations.  That said, we can to some degree still audit ourselves.  We’ve probably all felt ourselves at some point being riled up by a well constructed meme designed to amplify our beliefs.   Sometimes we recognize this quickly, other times we may be a little slower. But just simple awareness of the potential to be manipulated, and the symptoms of manipulation, such as intense or disproportionate emotional responses, can help us mitigate and even correct some of the worst effects. 

Collectively, there are more opportunities.  We are better at seeing others being manipulated than ourselves.  We can use that as a mirror, and/or call it out to others when we see it.  And many of us will find ourselves somewhere in the deployment chain, especially as AI is still in it’s early stages.  For those of us that this applies to, we have the opportunity to collectively nudge this emerging technology in the right direction. I still recall a conversation with Dan Ariely when I first started exploring behavioral science, perhaps 15-20 years ago.  It’s so long ago I have to paraphrase, but the essence of the conversation was to never manipulate people to do something that was not in there best interest.  

There is a pretty obvious and compelling moral framework behind this. But there is also an element of enlightened self interest. As a marketer working for a consumer goods company at the time, even if I could have nudged somebody into buying something they really didn’t want, it might have offered initial success, but would likely come back to bite me in the long-term.  They certainly wouldn’t become repeat customers, and a mixture of buyers remorse, loss aversion and revenge could turn them into active opponents.  This potential for critical thinking in hindsight exists for virtually every situation where outcomes damage the individual.   

The bottom line is that even today, we already ave to continually ask ourselves if what we see is real, if our beliefs are truly our own, or have they been manipulated? Media and social media memes already play the manipulation game.   AI may already be better, and if not, it’s only a matter of time before it is. If you think we are politically polarized now, hang onto your hat!!!  But awareness is key.  We all need to stay aware, be conscious of manipulation in ourselves and others, and counter it when we see it occurring for the wrong reasons.

Image credits: Google Gemini

Subscribe to Human-Centered Change & Innovation WeeklySign up here to join 17,000+ leaders getting Human-Centered Change & Innovation Weekly delivered to their inbox every week.

Fearless Fashionistas Are Staying Ahead of Change

Leave a reply

Why Aren’t You?

Fearless Fashionistas Are Staying Ahead of Change

GUEST POST from Janet Sernack

As a fashion and lifestyle conceptualist and analyst for a major Australian department store group during the pre-Internet era, I co-created, with the GM of Marketing and GM of Women’s, Men’s, Children’s Apparel and Accessories, a completely new role. I took on the responsibility of forecasting and predicting customer, lifestyle, and fashion trends two to three years ahead of the present. While forecasting involves estimating future events or trends based on historical and statistical data, making predictions involves forming educated guesses or projections that do not necessarily rely on such data. Both forecasting and predictive skills are vital for developing strategic foresight—an organized and systematic approach to exploring plausible futures and anticipating, better preparing for, and staying ahead of change.

In this exciting new role, I had to ensure that my forecasts and predictions did not cause people to become anxious and tense, leading to poor or conflicting decisions involving millions of dollars. Instead, I needed to make sure that my forecasts convinced people that the well-researched information had been collected, captured, analyzed, and synthesized effectively. To ensure that the discovery of new marketing concepts is prompted by the development of strategic foresight, which enables people to make informed, million-dollar investment decisions by staying ahead of change.

This was before the revolutions in Design Thinking and Strategic Foresight. It taught me the fundamentals of agile and adaptive thinking processes, as well as the importance of creating and capturing value by viewing it from the customer’s perspective. It was initiated through rigorous research that involved framing the domain and scanning for trends by mentally moving back and forth among many scenarios, making links, connections, and unlikely associations. The information could then be actualized, analyzed, and synthesized to focus on evaluating a range of plausible futures as forecast scenarios. To envision the future by identifying the most promising or commercially viable trends in Australian marketing and merchandising, thereby supporting better policy-making across the organization, which consisted of forty-two department stores.

At the time, Australian fashion and lifestyle trends were considered six months behind those in Europe and the USA. This allowed me to utilize current and historical sales data, along with statistical methods, to create a solid foundation for the sales and marketing situation across various merchandise segments. Having completed a marketing degree as an adult learner, I applied and integrated marketing concepts and principles from product and fashion lifecycle management. Through being inventive, I built a fashion and lifestyle information system that had not previously existed, enabling the whole organization to stay ahead of change.  

I conducted backcasting research and built relationships with top Australian manufacturers that supplied our customers, gathering evidence and feedback that supported or challenged my approach to developing trend-tracking processes over a three-year period. I traveled widely four times a year to Europe and the USA to research the fashion and lifestyle value chain, visiting yarn, textile, couture, and ready-to-wear shows to explore, discover, identify, and validate emerging and diverging trends, providing context and evidence of their evolution and convergence. This was further tested and validated by analyzing and synthesizing the most critical and commercially successful fashion and lifestyle ranges marketed and merchandised at that time in major global department stores and leading retail outlets.

Formal research was also carried out through various channels, including desktop research, fashion and lifestyle forecasting services, as well as USA and European media, to gather customer insights that could then be identified, analyzed, synthesized, and developed and implemented into key fashion marketing and merchandising trends across the entire group of forty-two department stores. This enabled them to present a coordinated marketing and merchandising approach across all apparel to customers and stay ahead of change.

This was my journey into what is now known as strategic foresight, laying the vital foundations for developing my brain’s neuroplasticity and neuroelasticity, and becoming an agility shifter, with a prospective mind and adaptive thinking strategy that enables me to stay ahead of change.

Staying ahead of change

It took me many years to realize that I was chosen for this enviable role, not because of my deep knowledge and extensive experience, but for my intuitive and unconventional way of thinking. In Tomorrowmind, Dr Martin Seligman calls this ‘prospection’, an ability to metabolize the past with the present to envisage the future. He states that a prospective mind extracts the nutrients from the past and the present, then excretes the toxins and ballast to prepare for tomorrow. He defines prospection as “the mental process of projecting and evaluating future possibilities and then using these projections to guide thought and action.”

This develops the ability to stay ahead of change by anticipating and adapting to it, and includes many elements, such as:

  • Being able to adopt both a systemic and tactical approach, as well as a structured and detailed perspective alongside an agile and flexible view of the current reality or present state, simultaneously.
  • Sensing, connecting, perceiving, and linking operational patterns, and analyzing and synthesizing them within their context.
  • Generating, exploring, and unifying possibilities and options for selecting the most valuable commercial applications that match customers’ lifestyle needs and wants.
  • Unlearning and viewing the world with fresh eyes through sensing and perceiving it through a paradoxical lens, and cultivating a ‘both/and’ bird’s-eye perspective.
  • Opening your heart, mind, and will to relearning and learning, letting go of what may have worked in the past, focusing your emotional energy, towards learning new mindsets and mental models and relearning how to perceive the world differently.
  • Wondering and wandering into fresh and multiple perspectives underlie the development of a strategic foresight capability.

This approach helps shift your focus across the polarities of thought, from a fixed, binary, or linear and competitive approach to one that is neuro-scientifically grounded. It aims to foster your neuroplasticity and neuroelasticity within your brain, enabling the development of new and diverse perspectives that support prospective, strategic, critical, conceptual, complementary, and creative thinking processes necessary for staying ahead of change.

  • Improves strategic thinking

Strategic foresight aims to anticipate, analyze, synthesize, adapt to, and shape the factors relevant to a person, team, or company’s business, enabling it to perform and grow better than its competitors and stay ahead of change. It requires confidence, capacity, and competence to partner effectively and to think and act differently, using cutting-edge analytics, proven creative tools, and artificial intelligence (AI). This approach empowers, enables, and equips individuals with better, more risk-informed strategic thinking. It also provides a foundation for creative thinking by helping people better understand the options and alternatives available to them. Additionally, it identifies potential developments that could lead to building a competitive advantage at the individual, team, or organizational level, enabling them to stay ahead of change, innovate, and succeed in an uncertain business environment.  

  • Increases adaptability

In a recent article, ‘Navigating the Future with Strategic Foresight, the Boston Consulting Group stated:

“It’s not about gathering more data than everyone else but about being able to detect forward-looking signals, stretch perspectives, and interpret the data with fresh eyes. Uncertainty does not dissipate; rather, strategic foresight offers the clarity of direction that comes from greater confidence in data, assumptions, and analysis”.

The information gathered through strategic foresight enhances people’s ability and willingness to adapt their responses to uncertainty and unexpected situations and embrace change. It provides concrete evidence, in the form of data, assumptions, and analysis, to support people in being adaptive. This requires being open to unlearning, relearning, and learning, protecting you against anxiety, stress, and burnout, and helping you stay ahead of change and become resilient to create, invent, and innovate through chaos, uncertainty and disruption.

This is an excerpt from our upcoming book, “Anyone Can Learn to Innovate,” scheduled for publication in early 2026.

Please find out about our collective learning products and tools, including The Coach for Innovators, Leaders, and Teams Certified Program, presented by Janet Sernack. It is a collaborative, intimate, and profoundly personalized innovation coaching and learning program supported by a global group of peers over nine weeks. It can be customized as a bespoke corporate learning program.

It is a blended and transformational change and learning program that will give you a deep understanding of the language, principles, and applications of an ecosystem-focused, human-centric approach and emergent structure (Theory U) to innovation. It will also upskill people and teams and develop their future fitness within your unique innovation context. Please find out more about our products and tools.

Image Credit: Pixabay

Subscribe to Human-Centered Change & Innovation WeeklySign up here to join 17,000+ leaders getting Human-Centered Change & Innovation Weekly delivered to their inbox every week.

Making it Safe to Innovate

Leave a reply

Building Emotional Safety

Making it Safe to Innovate - Building Emotional Safety

GUEST POST from Janet Sernack

When my husband and I became accredited as foster parents for children in need, I thought my skills as a trainer and facilitator would help me navigate the challenges we faced. I quickly discovered that when children arrived at our home late at night, often physically injured and emotionally distraught due to a tragic accident or being separated from their families, their primary need was for emotional safety. This began my long and enlightening quest into what it truly means for someone to develop both emotional and psychological safety. To discover and explore why both emotional and psychological safety are crucial for people to survive, innovate and thrive in the post-pandemic, unstable, and uncertain world.

The whole issue of “safety” is a crucial one. Causing many people, especially those in the change, learning and coaching space, to stop, pause, retreat, and reflect upon how to personalize and contextualize it for ourselves and others we care about and interact with. Yet so few people understand the importance of creating safe environments, especially today when there is so much hatred and violence happening on many of our streets.

We all deserve to, and are entitled to, feel emotionally safe and secure in all aspects of our lives.

What does it mean to be safe?

Because safety: the condition of being protected from or unlikely to cause danger, risk, or injury, impacts everyone and everything in our entire world system. It is an essential element required for our survival, growth, and ability to navigate and innovate in the post-pandemic era. Safety is critical in enhancing people’s capacity to connect, belong, and engage in purposeful relationships, build happy families and secure communities, as well as produce creative, inventive, and innovative work that helps make the world a better place.

What is emotional safety?

Emotional safety exists in an environment where individuals feel valued, respected, and heard, regardless of their values, beliefs, or religious or cultural origins. It involves allowing people to feel safe and secure, nurturing vulnerability, and sharing personal thoughts and feelings without fear of having their words judged as “bad” or “wrong.” Without facing punishment, discrimination, persecution, diminishment, blame, shame, hatred, or violence by others.

It’s a space where it’s safe to say “I don’t know” or “I made a mistake” without being labelled as incompetent or “lacking” in some vital way.

  • Improving well-being, engagement and productivity

Emotional safety is a vital element of an emotionally and mentally healthy environment that fosters well-being, boosts engagement, and enhances productivity. In such an environment, individuals feel secure enough to express, explore, and share their thoughts and feelings about themselves, their colleagues, managers, leaders, and even their organization as a whole. People feel respected and trusted to share ideas, establish boundaries, and be accepted for who they are, what they believe in, flaws and all. 

  • Building mutuality

The intention is to build mutuality, defined by the American Psychological Association as:

“The tendency of relationship partners to think of themselves as members of a dyadic relationship rather than as distinct individuals. As close relationships, particularly romantic ones, develop over time, partners display increasing levels of mutuality, which may influence their affect, cognition, and behavior. In interdependence theory, the tendency of partners to depend equally on each other’s behavior for the attainment of desirable outcomes”.

We live in an interdependent, globalized world where developing emotionally safe, positive, and interactive mutual relationships across geographies, technologies, demographics, and functions is more important than ever. Mutuality lays the groundwork for creating a shared understanding that fosters a safe and open space for learning and effective interactions, based on cooperative, co-petitive, and collaborative relationships in the workplace.

  • Becoming attuned

Emotional intelligence, empathy, trust, and effective communication are vital for fostering emotional safety and form the basis for developing effective emotional regulation and management strategies. This enables us to attune to and connect with others with whom we wish to build relationships.

According to Dr. Dan Seigal:

“When we attune with others, we allow our internal state to shift, to come to resonate with the inner world of another. This resonance is at the heart of the important sense of “feeling felt” that emerges in close relationships. Children need attunement to feel secure and to develop well, and throughout our lives we need attunement to feel close and connected.”

As a foster carer, my ability and willingness to attune with them represented the most important gift I could offer the children. It allowed them to feel close and connected to someone who genuinely cared for them by simply providing the most basic essentials. With no judgement or strings attached, and with both detachment and empathy, it also provided them with crucial evidence that this could indeed continue to be possible for them in their future lives.

As a trainer, facilitator, and coach, these are the key ingredients for establishing an emotionally safe and effective learning intervention, particularly about the people side of innovation and in building an organization that fosters a culture of failure. 

Developing a psychologically safe culture

Emotional safety is closely linked to psychological safety, which is the belief that individuals can be themselves at work and share their opinions and ideas without fear of negative repercussions.  According to Dr Timothy Clarke at the Leaderfactor, psychological safety empowers individuals and teams to reach new levels of creativity, collaboration, and innovation by nurturing a culture of inclusion and vulnerability. It is a social condition where people feel accepted and secure enough to learn, contribute, and question the status quo, free from fear of embarrassment, marginalization, or punishment, by creating an environment founded on permission, safety, and trust.

  • Embodying a way of being

Creating this emotional state or culture is much harder than most people think. Most organizations believe it’s something they must achieve through process and system changes, rather than by embodying it as a way of being a manager, leader, trainer, or coach who creates:

  • Sanctuaries of inclusion—a space where individuals feel safe and are encouraged to express their feelings, thoughts, opinions, and ideas, fostering a profound sense of inclusion, connection, and belonging.
  • Safe containers – a space where individuals confidently disrupt conventional or habitual ways of doing things, step outside their comfort zones, and challenge the status quo, allowing dissonance, contradiction, paradox, and conflict as sources of creative tension to disrupt, differ, and deviate from the norm. 
  • Collective holding spaces—where individuals accept responsibility, take ownership, and are trusted to contribute to the entire system. By fostering co-creative, interdependent relationships both internally and externally, we work towards achieving the team’s and organization’s vision, mission, purpose, and collective goals.
  • Incubators and accelerators of innovation—where team members are free to emerge, diverge, and converge possibilities. They are empowered, enabled, and equipped to transform these into creative ideas and opportunities. Individuals and teams feel safe in unlearning, learning, and relearning new ways of being, thinking, and acting. This environment challenges the status quo by encouraging disruptive questions, taking calculated risks, and experimenting with new ideas within an authentic, fail-fast culture that promotes quick learning.

Benefits of emotional and psychological safety

  • Enhances individual, team, and collective engagement, connection, and belonging. It establishes a foundation for harnessing and mobilizing people’s collective intelligence in line with the organization’s vision, mission, and purpose. 
  • Promotes effective team collaboration, where individuals feel at ease sharing their ideas, opinions, and concerns. It cultivates an environment where diverse perspectives can be openly discussed alongside differing views: 
  • Inspires people to be emotionally energetic, agile, and adaptable in the face of uncertainty and chaos, as well as in a rapidly changing business landscape.

AI will continue to disrupt job stability and security.

Developing emotional and psychological safety is a key success factor that underpins a culture of innovation, as it creates the essential space for individuals to think and act differently. This is achieved through experimentation, learning from failures, and exploring new methods that lead to breakthrough ideas and innovative solutions, enabling individuals to survive and thrive in the age of AI.

  • Both job losses and opportunities

Fast Company shares that Anthropic CEO Dario Amodei has a stark warning for the developed world about job losses resulting from AI. The CEO told Axios that AI could wipe out half of all entry-level white-collar jobs. This could result in a 10% to 20% rise in the unemployment rate over the next one to five years, Amodei says. The losses could come from tech, finance, law, consulting, and other white-collar professions, with entry-level jobs being hit the hardest.

Just as the children we fostered needed emotional safety, we all require emotional safety when walking our city streets. Similarly, while at work, we all need a psychologically safe working environment rooted in mutuality and trust. This is what allows individuals to attune to each other, feel secure, bonded, and connected, fostering a sense of belonging and unity. This requires investing in the co-creation of emotionally and psychologically safe spaces that attract and retain top talent, enabling individuals to feel valued, as they truly matter, and helping them adapt, innovate, grow, perform and thrive in a post-pandemic, unstable, and uncertain world.

This is an excerpt from our upcoming book, “Anyone Can Learn to Innovate,” scheduled for publication in late 2025.

Please find out about our collective learning products and tools, including The Coach for Innovators, Leaders, and Teams Certified Program, presented by Janet Sernack. It is a collaborative, intimate, and profoundly personalized innovation coaching and learning program supported by a global group of peers over nine weeks. It can be customized as a bespoke corporate learning program.

It is a blended and transformational change and learning program that will give you a deep understanding of the language, principles, and applications of an ecosystem-focused, human-centric approach and emergent structure (Theory U) to innovation. It will also upskill people and teams and develop their future fitness within your unique innovation context. Please find out more about our products and tools.

Image Credit: Pixabay

Subscribe to Human-Centered Change & Innovation WeeklySign up here to join 17,000+ leaders getting Human-Centered Change & Innovation Weekly delivered to their inbox every week.

Focus your Emotional Energy Purposefully

1 Reply

Focus your Emotional Energy Purposefully

GUEST POST from Janet Sernack

When I exited my corporate career more than thirty-five years ago, I was privileged to be regarded and respected as the Fashion Direction Manager for the Grace Bros Department Store group, one of Australia’s most senior women in retail management. This launched my global reputation as a fashion and lifestyle marketing innovator. In this exciting role, I was responsible for designing and implementing a company-wide fashion information system for apparel, accessories, homeware, merchandising, and advertising.  This required me to focus my emotional energy on researching, analyzing, and conceptualizing global fashion and lifestyle trends and adapting them to suit the Australian consumer lifestyle.

It was a dream role before the invention of the Internet, the implosion of the mass media, and the dominance of fast fashion. It required our team to focus their emotional energy on intensively researching different global and diverse media sources, including yarn, textile, couture, designer, ready-to-wear shows, trade journals, magazines, and seasonal sales data. 

Generating creative thinking

Creativity is about connecting things, and in the fashion world, the best designers make the most unlikely connections to produce novel and wondrous creations. As my professional background included graphic and fashion design and marketing, I could further hone my associative (lateral and connective) thinking skills to think creatively and critically in this role. To focus my emotional energy and attention on guiding my intuition, values, and decisions on the needs and wants of buyers, merchandisers, marketers, and customers. To emerge, diverge and converge the key connections and patterns occurring globally in the fashion world and external complex fashion systems. I also learned the importance of being customer-focused and the value and role of being empathic with customers, manufacturers’ value chains and fashion information system users.

It was an incredibly emotional, physical, and stressful role, which required me to travel overseas four times a year to stay current on the different global fashion streams.

This caused my life to melt into being at work, the gym, or the airport.

Stress-induced exhaustion and burnout

This resulted in my first profound encounter with stress-induced exhaustion and burnout, which hit me right in the face one morning when my body refused to move, and I was unable to get out of bed.

I have also noticed that many of my global coaching clients have faced a similar challenge: stress-induced exhaustion and burnout. Fortunately, they can use the coaching partnership to unearth their particular pattern and unresourceful ways of being and learn how to focus their emotional energy to disrupt, dispute, and deviate from it into a more resourceful way of being and acting. However, it has shifted the coach’s role as a healer, making it even more critical in our current environment.

Focusing emotional energy on pursuing mattering, meaning and purposeful work

This ultimately manifests as a crisis and becomes a defining moment. In my case, I made a fundamental choice to focus emotional energy on pursuing meaning, mattering, and purposeful work, which still focuses my full attention and drives me today.

It created a “crack, “or an opening and threshold for making two fundamental choices: to embark on a healing journey to become the kind of person I wanted to be and to find a way to focus my emotional energy on making the difference I wanted to make in the world. 

This enabled me to use my knowledge, experience, and skills to establish Australia’s first design management consultancy.

What is emotional energy?

Emotional energy is the catalyst that fuels creativity, invention, and innovation.

Understanding and harnessing this energy inspires and motivates individuals to explore and embrace creative and critical thinking strategies, now in partnership with AI.

When a person’s emotional energy has contracted, it results in constrained, negative, pessimistic, and even catastrophic thinking habits, which have a toxic impact on the person’s identity and emotional and physical well-being.

This means there is no space, doorway, or threshold to take on anything new, novel, or different. Nor can they imagine what might be possible to evolve, advance, or transform their personal or professional lives in an uncertain future.

Emotional energy catalyses and directs your intrinsic motivation, conviction, hope, positivity, and optimism to approach your world purposefully, meaningfully, and differently.

When you are true to your calling or purpose, you will make extra efforts to be healthier, positively impact your well-being, and improve your resilience.

How does this apply to leadership in uncertain times?

“I think leaders need to remember that they are in the energy management business,” says Halsey. “Their role is to keep people focused, energized, and positive about themselves and their work. They may be unable to change external circumstances, but they can create a safe, nurturing, and empowering work environment. By setting clear goals, diagnosing individual needs, and providing the right leadership style, leaders can help their teams thrive—even in uncertain times.”

People want work to be less of a job and more of a calling.

According to Martin Seligman and Gabriella Rosen Kellerman in their book Tomorrowmind, a US-based research study that included two thousand employees of all ages, industries, tenures, and incomes, revealed that people craved more meaning at work regardless of sector or position. Everyone wanted work to be less of a job and more of a calling and gave their current jobs a rating of 49, which suggests that their “meaning cups” are only half full.

This search for meaning, mattering, and being of service to humanity in a different and value-adding way enables innovators, entrepreneurs and intrapreneurs to cultivate the emotional energy and develop the agility required to drive their creativity, invention and innovation endeavors. 

It is the most critical ingredient that motivates, empowers, enables, fuels and sustains innovators, entrepreneurs, and intrapreneurs to adapt, survive and thrive on the innovation roller coaster.

Channeling emotional energy meaningfully and purposefully

From my leadership training and coaching experience, I have learned that most people desperately want their lives to make sense and be meaningful and to know that who they are and what they do matters. It is possible to link meaning and mattering to being intentionally motivated and directed by your core values to make a difference and a contribution that provides value and significance to someone, a community, or society.  

  • Being purposeful

Being purposeful focuses your emotional energy, guides your life decisions influences your behaviors, shapes your goals, offers a sense of direction, and creates meaning. Rather than engaging in shallow, empty, or pointless activities, it gives you agency.

In our uncertain, volatile and disruptive world, it is crucial to think about your “purpose in life.” Be like an Entrepreneur and link your purpose as a guidepost to help you deal with uncertainty, navigate it better, mitigate the damaging effects of long-term stress, and become psychologically resilient.

People with a strong sense of purpose direct and focus their emotional energy on what really matters to them. They tend to be more agile and adaptive, hardier and resilient, and more able to refocus and recover quickly from adverse and catastrophic events.

According to McKinsey & Co.’s article “Igniting individual purpose in times of crisis,” purposeful people also live longer and healthier lives and are essential to employee experience. This results in higher levels of employee engagement, more substantial organizational commitment, and increased feelings of well-being. Like many entrepreneurs, people who find their purpose congruent with their jobs tend to get more meaning from their roles, making them more productive and more likely to outperform their peers.

How can you add more meaning, mattering and purpose?

Meaning is an outcome of purpose, and many people, due to their experience of the pandemic and hybrid workplace in a chaotic and uncertain world, are seeking to re-engage with their work and workplaces by focusing their emotional energy on improving their well-being and creating more purposeful, balanced, and meaningful lives.

This is a short section from our new book, “Conscious Innovation – Activating the Heart, Mind and Soul of Innovation”, which will be published in 2025.

Please find out more about our work at ImagineNation™.

Please find out about our collective learning products and tools, including The Coach for Innovators, Leaders, and Teams Certified Program, presented by Janet Sernack. It is a collaborative, intimate, and profoundly personalized innovation coaching and learning program supported by a global group of peers over 9-weeks. It can be customized as a bespoke corporate learning program.

It is a blended and transformational change and learning program that will give you a deep understanding of the language, principles, and applications of an ecosystem-focused, human-centric approach and emergent structure (Theory U) to innovation. It will also up-skill people and teams and develop their future fitness within your unique innovation context. Please find out more about our products and tools.

Image Credit: Unsplash

Subscribe to Human-Centered Change & Innovation WeeklySign up here to join 17,000+ leaders getting Human-Centered Change & Innovation Weekly delivered to their inbox every week.