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Bio-Computing & DNA Data Storage

The Human-Centered Future of Information

LAST UPDATED: December 12, 2025 at 5:47 PM

Bio-Computing & DNA Data Storage

GUEST POST from Art Inteligencia

We are drowning in data. The digital universe is doubling roughly every two years, and our current infrastructure — reliant on vast, air-conditioned server farms — is neither environmentally nor economically sustainable. This is where the most profound innovation of the 21st century steps in: DNA Data Storage. Rather than using the binary zeroes and ones of silicon, we leverage the four-base code of life — Adenine (A), Cytosine (C), Guanine (G), and Thymine (T) — to encode information. This transition is not merely an improvement; it is a fundamental shift that aligns our technology with the principles of Human-Centered Innovation by prioritizing sustainability, longevity, and density.

The scale of this innovation is staggering. DNA is the most efficient information storage system known. Theoretically, all the world’s data could be stored in a volume smaller than a cubic meter. This level of density, combined with the extreme longevity of DNA (which can last for thousands of years when properly preserved), solves the two biggest crises facing modern data: decay and footprint. We must unlearn the limitation of physical space and embrace biology as the ultimate hard drive. Bio-computing, the application of molecular reactions to perform complex calculations, is the natural, faster counterpart to this massive storage potential.

The Three Pillars of the Bio-Data Revolution

The convergence of biology and information technology is built on three revolutionary pillars:

1. Unprecedented Data Density

A single gram of DNA can theoretically store over 215 petabytes (215 million gigabytes) of data. Compared to a standard hard drive, which requires acres of physical space to house that much information, DNA provides an exponential reduction in physical footprint. This isn’t just about saving space; it’s about decentralizing data storage and dramatically reducing the need for enormous, vulnerable, power-hungry data centers. This density makes truly long-term archival practical for the first time.

2. Extreme Data Longevity

Silicon-based media, such as hard drives and magnetic tape, are ephemeral. They require constant maintenance, migration, and power to prevent data loss, with a shelf life often measured in decades. DNA, in contrast, has proven its stability over millennia. By encapsulating synthetic DNA in glass or mineral environments, the stored data becomes essentially immortal, eliminating the costly and energy-intensive practice of data migration every few years. This shifts the focus from managing hardware to managing the biological encapsulation process.

3. Low Energy Footprint

Traditional data centers consume vast amounts of electricity, both for operation and, critically, for cooling. The cost and carbon footprint of this consumption are rapidly becoming untenable. DNA data storage requires energy primarily during the initial encoding (synthesis) and subsequent decoding (sequencing) stages. Once stored, the data is inert, requiring zero power for preservation. This radical reduction in operational energy makes DNA storage an essential strategy for any organization serious about sustainable innovation and ESG goals.

Leading the Charge: Companies and Startups

This nascent but rapidly accelerating industry is attracting major players and specialized startups. Large technology companies like Microsoft and IBM are deeply invested, often in partnership with specialized biotech firms, to validate the technology and define the industrial standard for synthesis and sequencing. Microsoft, in collaboration with the University of Washington, was among the first to successfully encode and retrieve large files, including the entire text of the Universal Declaration of Human Rights. Meanwhile, startups are focusing on making the process more efficient and commercially viable. Twist Bioscience has become a leader in DNA synthesis, providing the tools necessary to write the data. Other emerging companies like Catalog are working on miniaturizing and automating the DNA storage process, moving the technology from a lab curiosity to a scalable, automated service. These players are establishing the critical infrastructure for the bio-data ecosystem.

Case Study 1: Archiving Global Scientific Data

Challenge: Preserving the Integrity of Long-Term Climate and Astronomical Records

A major research institution (“GeoSphere”) faced the challenge of preserving petabytes of climate, seismic, and astronomical data. This data needs to be kept for over 100 years, but the constant migration required by magnetic tape and hard drives introduced a high risk of data degradation, corruption, and enormous archival cost.

Bio-Data Intervention: DNA Encapsulation

GeoSphere partnered with a biotech firm to conduct a pilot program, encoding its most critical reference datasets into synthetic DNA. The data was converted into A, T, C, G sequences and chemically synthesized. The resulting DNA molecules were then encapsulated in silica beads for long-term storage.

The physical volume required to store the petabytes of data was reduced from a warehouse full of tapes to a container the size of a shoebox.
The data was found to be chemically stable with a projected longevity of over 1,000 years without any power or maintenance.

The Innovation Impact:

The shift to DNA storage solved GeoSphere’s long-term sustainability and data integrity crisis. It demonstrated that DNA is the perfect medium for “cold” archival data — vast amounts of information that must be kept secure but are infrequently accessed. This validated the role of DNA as a non-electronic, permanent archival solution.

Case Study 2: Bio-Computing for Drug Discovery

Challenge: Accelerating Complex Molecular Simulations in Pharmaceutical R&D

A pharmaceutical company (“BioPharmX”) was struggling with the computational complexity of molecular docking — simulating how millions of potential drug compounds interact with a target protein. Traditional silicon supercomputers required enormous time and electricity to run these optimization problems.

Bio-Data Intervention: Molecular Computing

BioPharmX explored bio-computing (or molecular computing) using DNA strands and enzymes. By setting up the potential drug compounds as sequences of DNA and allowing them to react with a synthesized protein target (also modeled in DNA), the calculation was performed not by electrons, but by molecular collision and selection.

Each possible interaction became a physical, parallel chemical reaction taking place simultaneously in the solution.
This approach solved the complex Traveling Salesman Problem (a key metaphor for optimization) faster than traditional electronic systems because of the massive parallelism inherent in molecular interactions.

The Innovation Impact:

Bio-computing proved to be a highly efficient, parallel processing method for solving specific, combinatorial problems related to drug design. This allowed BioPharmX to filter billions of potential compounds down to the most viable candidates in a fraction of the time, dramatically accelerating their R&D pipeline and showcasing the power of biological systems as processors.

Conclusion: The Convergence of Life and Logic

The adoption of DNA data storage and the development of bio-computing mark a pivotal moment in the history of information technology. It is a true embodiment of Human-Centered Innovation, pushing us toward a future where our most precious data is stored sustainably, securely, and with a life span that mirrors humanity’s own. For organizations, the question is not if to adopt bio-data solutions, but when and how to begin building the competencies necessary to leverage this biological infrastructure. The future of innovation is deeply intertwined with the science of life itself. The next great hard drive is already inside you.

“If your data has to last forever, it must be stored in the medium that was designed to do just that.”

Frequently Asked Questions About Bio-Computing and DNA Data Storage

1. How is data “written” onto DNA?

Data is written onto DNA using DNA synthesis machines, which chemically assemble the custom sequence of the four nucleotide bases (A, T, C, G) according to a computer algorithm that converts binary code (0s and 1s) into the base-four code of DNA.

2. How is the data “read” from DNA?

Data is read from DNA using standard DNA sequencing technologies. This process determines the exact sequence of the A, T, C, and G bases, and a reverse computer algorithm then converts this base-four sequence back into the original binary code for digital use.

3. What is the current main barrier to widespread commercial adoption?

The primary barrier is the cost and speed of the writing (synthesis) process. While storage density and longevity are superior, the current expense and time required to synthesize vast amounts of custom DNA make it currently viable only for “cold” archival data that is accessed very rarely, rather than for “hot” data used daily.

Your first step into bio-data thinking: Identify one dataset in your organization — perhaps legacy R&D archives or long-term regulatory compliance records — that has to be stored for 50 years or more. Calculate the total cost of power, space, and periodic data migration for that dataset over that time frame. This exercise will powerfully illustrate the human-centered, sustainable value proposition of DNA data storage.

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 credit: Google Gemini

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Stealing From the Garden of Eden

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Stealing From the Garden of Eden

GUEST POST from Greg Satell

The story of the Garden of Eden is one of the oldest in recorded history, belonging not only to the world’s three major Abrahamic faiths of Judaism, Christianity and Islam, but also having roots in Greek and Sumerian mythology. It’s the ultimate origin archetype: We were once pure, innocent and good, but then were corrupted in some way and cast out.

As Timothy Snyder points out in his excellent course on The Making of Modern Ukraine, this template of innocence, corruption and expulsion often leads us to a bad place, because it implies that anything we do to remove that corrupting influence would be good and just. When you’re fighting a holy war, the ends justify the means.

The Eden myth is a favorite of demagogues, hucksters and con artists because it is so powerful. We’re constantly inundated with scapegoats— the government, big business, tech giants, the “billionaire” class, immigrants, “woke” society — to blame for our fall from grace. We need to learn to recognize the telltale signs that someone is trying to manipulate us.

The Assertion Of Victimhood

In 1987, a rather drab and dull Yugoslavian apparatchik named Slobodan Milošević was visiting Kosovo field, the site of the Serbs humiliating defeat at the hands of the Ottoman empire in 1389. While meeting with local leaders, he heard a commotion outside and found police beating back a huge crowd of Serbs and Montenegrins.

“No one should dare to beat you again!” Milošević is reported to have said and, in that moment, that drab apparatchik was transformed into a political juggernaut who left death and destruction in his path. For the first time since World War II, a genocide was perpetrated in Europe and the term ethnic cleansing entered the lexicon.

In Snyder’s book, Bloodlands, which chronicled the twin horrors of Hitler and Stalin, he points out that if we are to understand how humans can do such atrocious things to other humans, we first need to understand that they saw themselves as the true victims. When people believe that their survival is at stake, there is very little they won’t assent to.

The assertion of victimhood doesn’t need to involve life and death. Consider the recent Twitter Files “scandal,” in which the social media giant’s new owner leaked internal discussions about content moderation. The journalists who were given access asserted that those discussions amounted to an FBI-Big Tech conspiracy to censor important information. They paint sinister pictures of dark forces working to undermine our access to information.

When you read the actual discussions, however, what you see is a nuanced discussion about how to balance a number of competing values. How do we balance national security and public safety with liberty and free speech? At what point does speech become inciteful and problematic? Where should lines be drawn?

The Dehumanization Of An Out-group

Demagogues, hucksters and con men abhor nuance because victimhood requires absolutes. The victim must be completely innocent and the perpetrator must be purely evil for the Eden myth sleight of hand to work. There are no innocent mistakes, only cruelty and greed will serve to build the narrative.

Two years after Milošević political transformation at Kosooe field he returned there to commemorate the 600 anniversary of the Battle of Kosovo, where he claimed that “the Serbs have never in the whole of their history conquered and exploited others.” Having established that predicate, the stage was set for the war in Bosnia and the atrocities that came with it.

Once you establish complete innocence, the next step is to dehumanize the out-group. The media aren’t professionals who make mistakes, they are “scum who spread lies.” Tech giants aren’t flawed organizations, but ones who deliberately harm the public. Public servants like Anthony Fauci and philanthropists like Bill Gates are purported to engage in nefarious conspiracies that undermine the public well-being.

The truth is, of course, that nothing is monolithic. People have multiple motivations, some noble, others less so. Government agencies tend to attract mission-driven public servants, but can also be prone to overreach and abuse of power. Entrepreneurs like Elon Musk can have both benevolent aspirations to serve mankind and problematic character flaws.

It is no accident that the states in the US with the fewest immigrants tend to have the most anti-immigrant sentiment. The world is a messy place, which is why real-world experience undermines the Manichean worldview that demagogues, hucksters and con artists need to prepare the ground for what comes next.

The Vow For Retribution

It is now a matter of historical record what came of Milošević. After the horrors of the genocides his government perpetrated, his regime was brought down in the Bulldozer Revolution, the first of a string of Color Revolutions that spread across Eastern Europe. He was then sent to The Hague to stand trial, where would die in his prison cell.

Milošević made a common mistake (and one Vladimir Putin is repeating today). Successful demagogues, hucksters and con artists know to never make good on their vows for retribution. In order to serve its purpose, the return to Eden must remain aspirational, a fabulous yonder that will never be truly attained. Once you actually try to get there, it will be exposed as a mirage.

Yet politicians who vow to bring down evil corporations can depend on a steady stream of campaign contributions. In much the same way, entrepreneurs and entrepreneurs who rail against government bureaucrats can be enthusiastically invited to speak to the media and at investor conferences.

It is a ploy that has continued to be effective from antiquity to the present-day because it strikes at our primordial tendencies toward tribalism and justice, which is why we can expect it to continue. It’s a pattern that recurs with such metronomic regularity precisely because we are so vulnerable to it.

Being Aware Is Half The Battle

In my friend Bob Burg’s wonderful book, Adversaries into Allies, he makes the distinction between persuasion and manipulation. Bob says that persuasion involves helping someone to make a decision by explaining the benefits of a particular course of action, while manipulation takes advantage of negative emotions, such as anger, fear and greed.

So it shouldn’t be surprising that those who want to manipulate us tell origin stories in which we were once innocent and good until a corrupting force diminished us. It is that narrative that allows them to assert victimhood, dehumanize an out-group and promise, if given the means, that they will deliver retribution and a return to our rightful place.

These are the tell-tale signs that reveal demagogues, hucksters and con artists. It doesn’t matter if they are seeking backing for a new technology, belief in a new business model or public office, there will always be an “us” and a “them” and there can never be a “we together,” because “they,” are trying to deceive us, take what is rightfully ours and rob us of our dignity.

Yet once we begin to recognize those signs, we can use those emotional pangs as markers that alert us to the need to scrutinize claims more closely, seek out a greater diversity of perspectives and examine alternative narratives. We can’t just believe everything we think. It is the people who are telling us things that we want to be true that are best able to deceive us.

Those who pursue evil and greed always claim that they are on the side of everything righteous and pure. That’s what we need to watch out for most.

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

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What the Heck is Electrofermentation?

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The Convergence of Biology, Technology, and Human-Centered Innovation

What the Heck is Electrofermentation?

GUEST POST from Art Inteligencia

For centuries, the principles of manufacturing have been rooted in a linear, resource-intensive model: extract, produce, use, and dispose. In this paradigm, our most creative biological processes, like fermentation, have been limited by their own inherent constraints—slow yields, inconsistent outputs, and reliance on non-renewable inputs like sugars. But as a human-centered change and innovation thought leader, I see a new convergence emerging, one that promises to rewrite the rules of industry. It’s a profound synthesis of biology and technology, a marriage of microbes and micro-currents. I’m talking about electrofermentation, and it’s not just a scientific breakthrough; it’s a paradigm shift that enables us to produce the goods of the future in a way that is smarter, cleaner, and fundamentally more sustainable. This is about using electricity to guide and accelerate nature’s most powerful processes, turning waste into value and inefficiency into a new engine for growth.

The Case for a ‘Smarter’ Fermentation

Traditional fermentation, from brewing beer to creating biofuels, is an impressive but imperfect process. It is a biological balancing act, often limited by thermodynamic and redox imbalances that reduce yield and produce unwanted byproducts. Think of it as a chef trying to cook a complex dish without being able to precisely control the heat or the ingredients. This lack of fine-tuned control leads to waste and inefficiency, a costly reality in a world where every resource counts.

Electrofermentation revolutionizes this by introducing electrodes directly into the microbial bioreactor. This allows scientists to apply an electric current that acts as an electron source or sink, providing a powerful, precise control mechanism. This subtle electrical “nudge” steers the microbial metabolism, overcoming the natural limitations of traditional fermentation. The result is a process that is not only more efficient but also more versatile. It enables us to use unconventional feedstocks, such as industrial waste gases or CO₂, and convert them into valuable products with unprecedented speed and yield. It’s the difference between guessing and knowing, between a linear process and a circular one.

The Startups and Companies Leading the Charge

This revolution is already underway, driven by a new generation of companies and startups that are harnessing the power of electrofermentation to solve some of the world’s most pressing problems. At the forefront is LanzaTech, a company that has pioneered a process to recycle carbon emissions. They are essentially retrofitting breweries onto industrial sites like steel mills, using their proprietary microbes to ferment waste carbon gases into ethanol and other valuable chemicals. In the food sector, companies like Arkeon are redefining what we eat. They are building a new food system from the ground up by using microbes to convert CO₂ and hydrogen into sustainable proteins. And in the materials science space, innovators are exploring how this technology can create everything from biodegradable plastics to advanced biopolymers, all from non-traditional and renewable sources. These are not just scientific curiosities; they are real-world ventures creating scalable, impactful solutions that are actively building a circular economy.

Case Study 1: LanzaTech – Turning Pollution into Products

The Challenge:

Industrial emissions from steel mills and other heavy industries are a major contributor to climate change. These waste gases—rich in carbon monoxide (CO) and carbon dioxide (CO₂)—are a significant liability, but they also represent a vast, untapped resource. The challenge was to find a commercially viable way to capture these emissions and transform them into something valuable, rather than simply releasing them into the atmosphere.

The Electrofermentation Solution:

LanzaTech developed a gas fermentation process that uses a special strain of bacteria (Clostridium autoethanogenum) that feeds on carbon-rich industrial gases. This is a form of electrofermentation where the microbes use the electrons from the gas to power their metabolism. The process diverts carbon from being a pollutant and, through a biological synthesis, converts it into useful products. It’s like a biological recycling plant that fits onto a smokestack. The bacteria consume the waste gas, and in return, they produce fuels and chemicals like ethanol, which can then be used to make sustainable aviation fuel, packaging, and household goods. The key to its success is the precision of the fermentation process, which maximizes the conversion of waste carbon to valuable products.

The Human-Centered Result:

LanzaTech’s innovation is a powerful example of a human-centered approach to a global problem. It’s a technology that not only addresses a critical environmental challenge but also creates new economic opportunities and supply chains. By turning industrial emissions from a “bad” into a “good,” it redefines our relationship with waste. It’s a move away from a linear, extractive economy and toward a circular, regenerative one, proving that sustainability can be a catalyst for both innovation and profit. It has commercial plants in operation, showing that this is not just a theoretical solution but a scalable reality.

Case Study 2: Arkeon – The Future of Food from Air

The Challenge:

The global food system is under immense pressure. Rising populations, climate change, and resource-intensive agricultural practices are straining our ability to feed everyone sustainably. The production of protein, in particular, has a significant environmental footprint, requiring vast amounts of land and water and generating substantial greenhouse gas emissions. The challenge is to find a new, highly efficient, and sustainable source of protein that is not dependent on traditional agriculture.

The Electrofermentation Solution:

Arkeon is using a form of electrofermentation to create a protein-rich biomass from air. Their process involves using specialized microbes called archaea, which thrive in extreme environments and can be “fed” on CO₂ and hydrogen gas. By using an electrical current to power this process, Arkeon can precisely control the microbial activity to produce amino acids, the building blocks of protein, with incredible efficiency. This innovative process decouples food production from agricultural land, water, and sunlight, making it a highly resilient and sustainable source of nutrition. It’s a closed-loop system where waste (CO₂) is the primary input, and a high-value, functional protein powder is the output.

The Human-Centered Result:

Arkeon’s work is a powerful human-centered innovation because it tackles one of the most fundamental human needs: food security. By developing a method to create protein from waste gases, the company is not only providing a sustainable alternative but also building a more resilient food system. This technology could one day enable localized, decentralized food production, reducing reliance on complex supply chains and making communities more self-sufficient. It is a bold, forward-looking solution that envisions a future where the air we breathe can be a source of sustainable, high-quality nutrition for everyone.

Conclusion: The Dawn of a New Industrial Revolution

Electrofermentation is far more than a technical trick. It represents a paradigm shift from a linear, extractive model to a circular, regenerative one. By converging biology and technology, we are unlocking the ability to produce what we need, not from the earth’s finite resources, but from the waste and byproducts of our own civilization. It is a testament to the power of human-centered innovation, where the goal is not just to build a better widget but to create a better world. For leaders, the question is not if this will impact your industry, but how you will embrace it. The future belongs to those who see waste not as a liability, but as a feedstock, and who are ready to venture beyond the traditional. This is the dawn of a new industrial revolution, and it’s powered by a jolt of electricity and a microbe’s silent work, promising a more sustainable and abundant future for us all.

This video provides a concise overview of LanzaTech’s carbon recycling process, which is a key example of electrofermentation in action.

Image credit: Pixabay

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Top 10 Human-Centered Change & Innovation Articles of August 2025

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Top 10 Human-Centered Change & Innovation Articles of August 2025 Drum 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 August’s ten most popular innovation posts:

The Nordic Way of Leadership in Business — by Stefan Lindegaard
Science Says You Shouldn’t Waste Too Much Time Trying to Convince People — by Greg Satell
A Manager’s Guide to Employee Engagement — by David Burkus
Decoding the Code of Life – Human-Centered Innovation in Synthetic Biology — by Art Inteligencia
Why Innovators Can’t Ignore the Quantum Revolution — by Art Inteligencia
Performance Reviews Don’t Have to Suck — by David Burkus
Why Explainable AI is the Key to Our Future – The Unseen Imperative — by Art Inteligencia
Goals Require Belief to be Achievable — by Mike Shipulski
The Future is Rotary – Human-Centered Innovation in Rotating Detonation Engines — by Art Inteligencia
The Killer Strategic Concept You’ve Never Heard Of – You Really Need to Know About Schwerpunkt! — by Greg Satell

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

Do We Really Need Managers? — by David Burkus
Building Psychological Safety – Team Dynamics Explained — by Stefan Lindegaard
3 Reasons Why Bad Business Thinking Exists — by Greg Satell
Turning Around Declining Customer Satisfaction — by Shep Hyken
Three Executive Decisions for Strategic Foresight Success or Failure — by Robyn Bolton

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!

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 four years:

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Five Unsung Scientific Discoveries Driving Future Innovation

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Five Unsung Scientific Discoveries Driving Future Innovation

GUEST POST from Art Inteligencia

In the relentless pursuit of progress, the headlines often gravitate towards the monumental—AI breakthroughs, space exploration milestones, or widely publicized medical cures. Yet, beneath the surface, a vibrant ecosystem of lesser-known scientific discoveries is quietly brewing, each holding immense potential to reshape industries, solve pressing global challenges, and fundamentally alter our human experience. As a human-centered change and innovation thought leader, I believe it’s not just important, but *critical*, to shine a light on these unsung heroes of scientific advancement. Beyond the captivating, yet often abstract, idea of “freezing light,” here are five scientific breakthroughs poised to drive profound innovation, which you might not yet be fully aware of.

1. “Magic State” Distillation in Quantum Computing

The Discovery:

While the broad concept of quantum computing is a familiar frontier, a specific, less-heralded breakthrough known as “magic state distillation” is fundamentally critical. This advanced technique allows quantum computers to generate highly entangled quantum states (the “magic states”) from imperfect or noisy ones. Essentially, it’s a method for error reduction that makes large-scale, fault-tolerant quantum computation a significantly more tangible reality. This isn’t merely an incremental improvement; it’s a foundational step towards building truly powerful and reliable quantum machines capable of tackling previously intractable problems.

Innovation Potential:

This breakthrough dramatically accelerates the timeline for practical quantum computing, unlocking possibilities across numerous sectors:

Drug Discovery & Materials Science: Simulating molecular interactions with unprecedented accuracy, leading to the rapid design and development of novel drugs, advanced catalysts, and revolutionary materials.
Artificial Intelligence: Powering next-generation AI algorithms capable of solving complex optimization problems and performing pattern recognition currently beyond the reach of even the most powerful classical supercomputers.
Financial Modeling: Optimizing intricate financial portfolios, risk assessments, and market predictions with vastly greater precision and speed.

It transforms quantum computing from a theoretical marvel into a practical, industry-redefining tool, poised to revolutionize everything from healthcare to finance.

2. Advanced Bionic Limbs with Direct Neural/Muscular Integration

The Discovery:

Moving beyond conventional prosthetics, recent advancements have enabled bionic limbs that directly integrate with a user’s nervous system and residual muscles. This groundbreaking connection allows for truly intuitive control, where the prosthetic limb responds seamlessly to the user’s thoughts and intentions, eliminating the need for cumbersome manual inputs. This innovation extends beyond mere movement; it’s about restoring a profound sense of proprioception (the body’s inherent awareness of its position in space) and even tactile feedback, making the prosthetic feel like a natural, integrated extension of the body.

Innovation Potential:

The implications of this human-machine interface are vast and extend far beyond aiding amputees:

Human Augmentation: Developing sophisticated exoskeletons for industrial workers, significantly enhancing physical capabilities for specialized tasks, or providing unparalleled assistance to individuals with severe mobility impairments.
Rehabilitation & Therapy: Revolutionizing physical therapy by providing real-time, precise feedback and facilitating more natural movement patterns for accelerated recovery.
Virtual Reality & Gaming: Creating incredibly immersive and haptically rich experiences where digital interactions feel physically real, blurring the lines between the virtual and physical worlds.

This technology is fundamentally paving the way for a future where human-machine interfaces are not just functional, but seamless, intuitive, and profoundly enhance human capabilities.

3. Metamaterials: Engineering the Impossible

The Discovery:

Metamaterials are a class of artificially engineered materials designed with properties not found in nature. Their unique, often counter-intuitive characteristics arise not from their chemical composition, but from their meticulously designed sub-wavelength microscopic structures. By precisely manipulating these architectures, scientists can control waves (be it light, sound, or heat) in unprecedented ways, leading to phenomena like “negative refraction” or perfect absorption. Think of them as materials whose fundamental properties are defined by their intricate structural design, rather than solely by their atomic makeup.

Innovation Potential:

The applications stemming from metamaterials are truly revolutionary and span diverse sectors:

Advanced Optics: Creating ultra-thin, highly efficient lenses for next-generation cameras and sensors, or even developing the foundational components for “invisibility cloaks” that precisely bend light around objects.
Wireless Communication: Drastically enhancing 5G and future wireless networks by improving signal reception, significantly reducing interference, and enabling far more efficient data transmission.
Medical Imaging: Improving the resolution, sensitivity, and safety of MRI machines and other diagnostic tools, leading to earlier, more accurate, and less invasive diagnoses.
Energy Harvesting: Designing highly efficient materials that can more effectively capture, concentrate, and convert solar or thermal energy into usable power.

Metamaterials offer a completely new paradigm for material design, empowering us to engineer properties previously considered impossible, opening doors to unimaginable technological advancements.

4. Living Building Materials (Bio-Integrated Construction)

The Discovery:

This groundbreaking and rapidly evolving field involves the deliberate integration of living organisms (such as specific strains of bacteria, fungi, or algae) directly into traditional building materials. Imagine bricks that can literally grow themselves, concrete that possesses the remarkable ability to self-heal its own cracks, or walls that actively absorb carbon dioxide from the atmosphere. These bio-integrated materials leverage natural biological processes to provide dynamic functions that inert, conventional materials simply cannot, offering profoundly sustainable and adaptive solutions for the future of construction.

Innovation Potential:

The impact on architecture, urban planning, and environmental sustainability is truly enormous:

Sustainable Construction: Drastically reducing the carbon footprint of buildings by utilizing materials that actively sequester CO2, require significantly less energy to produce, and can even be cultivated on-site from renewable resources.
Self-Healing Infrastructure: Creating resilient roads, bridges, and buildings that automatically repair minor damage, thereby extending their operational lifespan, drastically reducing maintenance costs, and enhancing safety.
Improved Indoor Air Quality: Designing walls that actively filter indoor pollutants, regulate humidity, or even produce oxygen, effectively transforming buildings into living, breathing, and healthier ecosystems.
Resource Efficiency: Developing innovative materials that can be “grown” from waste products or require minimal energy-intensive processing, promoting a circular economy in construction.

This represents a fundamental paradigm shift from static, inert structures to dynamic, biologically active, and self-sustaining built environments.

5. Precision Synthetic Biology (Beyond CRISPR’s Initial Scope)

The Discovery:

While CRISPR gene editing has deservedly garnered widespread recognition, the broader, more expansive field of precision synthetic biology pushes the boundaries even further. It involves the deliberate design and meticulous engineering of entirely new biological systems (such as cells, microbes, or enzymes) to perform novel functions or produce new materials and chemicals with unprecedented accuracy, efficiency, and control. This isn’t just about editing existing genes; it’s about building entirely new biological circuits and metabolic pathways from scratch, or precisely reprogramming organisms to act as tiny, highly efficient, and sustainable factories.

Innovation Potential:

The implications of this ability to program life itself are vast and truly transformative:

Sustainable Manufacturing: Producing advanced biofuels, fully biodegradable plastics, and high-value industrial chemicals from renewable resources using engineered microbes, significantly reducing our reliance on petrochemicals and minimizing environmental impact.
Novel Materials: Bio-fabricating materials with properties superior to conventionally manufactured ones, such as self-healing textiles, bio-inspired super-strong, lightweight composites, or even living sensors.
Food & Agriculture: Engineering crops to be inherently more drought-resistant, more nutrient-dense, or to produce their own fertilizers, fundamentally addressing global food security challenges. This also includes developing sustainable alternative proteins and lab-grown cellular agriculture products.
Advanced Therapeutics: Creating “smart” cells that can precisely detect and treat diseases within the human body, or producing vaccines and therapeutics more rapidly, affordably, and at scale.

Precision synthetic biology empowers us to program life itself, ushering in an entirely new era of bio-innovation that promises to reshape countless aspects of our world.

The Unseen Drivers of Tomorrow’s World

These five scientific discoveries, while perhaps not yet household names, represent the absolute cutting edge of human inquiry and ingenuity. They are the quiet, yet powerful, engines of future innovation, each with the profound capacity to spawn entirely new industries, provide elegant solutions to humanity’s grandest challenges, and fundamentally improve the human condition. As leaders, innovators, and conscious citizens, our collective role is not only to recognize these remarkable advancements but to actively foster the environments where they can transition seamlessly from laboratory breakthroughs to tangible, real-world impact. By understanding, championing, and strategically investing in these unsung scientific frontiers, we can truly shape a more innovative, sustainable, and profoundly human-centered future for all. 🔬🌟

Image credit: Gemini

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Freezing Light and Turning it into a Solid

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Freezing Light and Turning it into a Solid

GUEST POST from Art Inteligencia

Imagine holding a beam of light in your hand, not as a fleeting shimmer, but as a tangible object. Sounds impossible, right? Yet, as an innovation thought leader, I’m constantly scanning the horizon for breakthroughs that shatter our perceptions of what’s possible. Few concepts ignite my imagination quite like the audacious idea of freezing light and transforming it into something akin to a solid or even a “super liquid.” This isn’t just theoretical musing; cutting-edge science is making incredible strides towards manipulating light in ways previously confined to science fiction.

Traditionally, light—composed of photons—is thought of as a wave that travels at the fastest speed in the universe, passing through everything without interaction. But what if we could make photons “stick” together? What if we could slow them down, halt them, and then coax them into entirely new states of matter? This seemingly fantastical endeavor is precisely what researchers are achieving, primarily by forcing photons into strong interactions with specially prepared atomic systems or engineered materials. It’s a fundamental redefinition of light’s behavior.

The “Solid” State of Light: Forming Photonic Molecules

Picture light behaving like a crystal, with photons not just propagating, but forming stable, bound structures. This remarkable feat is becoming a reality. Scientists have demonstrated situations where individual photons, usually independent entities, begin to bind together, acting like “molecules of light.” This binding occurs when photons are made to interact intensely within a specific medium. One groundbreaking method involves firing photons into an extremely cold cloud of rubidium atoms. Instead of simply passing through, the photons effectively transfer their energy to the atoms, which then relay that energy in a kind of quantum bucket brigade. This process dramatically slows the photons down, making them appear to navigate an incredibly thick, viscous substance. Crucially, when two such photons enter the cloud, they don’t just slow independently; they exit together, demonstrating a newfound “stickiness” – a strong interaction previously thought impossible for light in free space. This collective, bound behavior is what gives light a solid-like quality, where a collection of photons acts as a coherent, stable entity. Think of it like water molecules freezing into ice; here, photons are forming similar, if ephemeral, bonds.

The “Super Liquid” State of Light: Flowing Without Resistance

Now, let’s pivot from a rigid solid to something that flows with zero friction and perfect coherence – a superfluid. This incredible quantum phenomenon, often seen in ultra-cold helium, is also being explored in the realm of light. Scientists have successfully created systems where light behaves as a “superfluid of polaritons.” Polaritons are fascinating hybrid quasi-particles, a blend of light and matter, formed when photons strongly couple with electronic excitations within a material, often at extremely low temperatures. In these precise conditions, these polaritons can condense into a macroscopic quantum state known as a Bose-Einstein condensate. Once condensed, this “super liquid” light can flow without any resistance, and even sustain persistent currents indefinitely, much like a perpetual motion machine for light. This revolutionary state promises the potential for lossless transmission and manipulation of information, far surpassing the limitations of conventional electronics. It’s the ultimate expression of quantum coherence applied to light, enabling entirely new forms of optical circuitry and communication.

Practical Applications: Beyond the Bleeding Edge

This is where the true innovation potential of these discoveries comes into sharp focus. While currently confined to highly specialized laboratory environments, the ability to fundamentally manipulate light opens up staggering possibilities across numerous industries. We’re talking about fundamental shifts in how we store, transmit, and process information. The implications span across numerous industries:

Quantum Computing and Communication:

The ability to precisely manipulate individual photons and create stable, interacting light structures is a cornerstone for quantum computing. Imagine using qubits (the basic unit of quantum information) made of light, offering unprecedented processing speeds and inherent resilience to decoherence. “Frozen” or “solid” light could serve as quantum memory, storing delicate quantum states for extended durations, a critical bottleneck in current quantum computer designs. For quantum communication, super-fluid light could enable perfectly efficient, lossless transmission of quantum information over vast distances, potentially revolutionizing secure data transfer methods like quantum key distribution.

Ultra-Efficient Data Storage:

If we can reliably “freeze” and retrieve information encoded in the quantum state of trapped photons, we could witness the birth of optical data storage with capacities that dwarf anything available today. Instead of storing data as magnetic bits or electronic charges, imagine encoding petabytes of information in incredibly small, three-dimensional volumes using light itself. This could lead to storage devices with densities orders of magnitude greater than current technologies, transforming everything from cloud computing to personal devices.

Novel Sensing and Metrology:

The extreme sensitivity and unparalleled control over light at these quantum levels could lead to entirely new forms of sensors. Think about detectors capable of identifying single photons with near-perfect efficiency, or instruments that can measure incredibly subtle changes in magnetic fields, gravitational waves, or even biomolecules with unprecedented precision. “Solid” or “super liquid” light could also be used to create ultra-precise atomic clocks or quantum gyroscopes, significantly enhancing navigation systems, geological surveying, and fundamental physics experiments.

New Materials and Energy Technologies:

While more speculative, the principles behind creating light-matter hybrids and precisely manipulating photon interactions could inspire the development of entirely new classes of materials. Imagine materials whose optical properties can be dynamically controlled and even programmed, leading to advancements in everything from smart windows that adapt to light conditions to new forms of optical computing hardware. In energy, could we harness these light manipulation techniques to dramatically improve solar energy conversion, perhaps by “trapping” photons more effectively for enhanced energy transfer, or even creating new forms of light-driven power generation?

Challenges and The Innovation Horizon

Of course, the journey from these groundbreaking laboratory demonstrations to widespread practical applications is fraught with significant challenges. Maintaining the ultra-low temperatures required for many of these phenomena, scaling up these delicate quantum systems, and engineering robust, real-world devices are immense hurdles. Yet, these challenges are precisely what drive innovation.

As a human-centered change leader, I see not just technological advancements but a profound paradigm shift in how we interact with and utilize one of the most fundamental forces of the universe. The ability to control light at such an intimate, quantum level opens doors to innovations that are currently only limited by our collective imagination. The key to unlocking these future applications lies in continued, audacious investment in basic research, fostering deep interdisciplinary collaboration between physicists, engineers, and computer scientists, and embracing a culture of relentless experimentation. We need to empower the boldest thinkers to explore these frontiers, not just for the immediate return on investment, but for the profound and transformative societal impact they could bring. The future of light, it seems, is far from ethereal; it’s becoming increasingly tangible, solid, and incredibly fluid in its potential to reshape our world. 🚀

Image credit: Gemini

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Contemporary Science versus Natural Language

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Contemporary Science versus Natural Language

GUEST POST from Geoffrey A. Moore

Item 1. The fastest human-created spacecraft goes 165,000 mph. Pretty amazing. But for it to travel one light year would take roughly 3000 years—basically, the length of recorded human history. The closest star system that hosts an earth-like planet (Alpha Centauri) is 4.4 light years away. Thus, it would take today’s fastest vehicle 14,000 years to make a one-way trip. On our earth, 14,000 years ago humanity’s most sophisticated technology was a stone axe. Thus, while we love to talk about space travel outside the solar system, as well as aliens in UFOs coming to Earth, neither is remotely possible, not now, not ever.

Item 2. There are 30 trillion cells in the average human body. There are 100 trillion atoms in a typical human cell. That means there are three thousand trillion trillion atoms, give or take, in you or me. Atoms are so small that it is not clear any words we have would apply to how they actually operate. Particle and wave are two of the ones we end up using the most. Neither of them, however, can coherently explain something as simple as the double-slit experiment.

Item 3. The metabolic reactions that support all life are mind-bogglingly fast. Take mitochondria for example. They are the organelles that produce the bulk of our ATP, the energy molecule that drives virtually all life’s chemical reactions. Of the 30 trillion cells in your body, on average each one uses around 10 million molecules of ATP per second and can recycle all its ATP in less than a minute. There is simply no way to imagine something happening a million times per second simultaneously in thirty million different places inside your own body.

Item 4. Craig Venter has been quoted as saying, “If you don’t like bacteria, you’re on the wrong planet. This is the planet of the bacteria.” In one-fifth of a teaspoon of seawater, there are a million bacteria (and perhaps 10 million viruses). The human microbiome, which has staked out territory all over our body, in our gut, mouth, skin, and elsewhere, harbors upwards of three thousand kinds of bacteria, comprising some 3 million distinct genes, which they swap with each other wherever they congregate. How in the world are we supposed to keep track of that?

Okay, okay. So what’s your point?

The point is that contemporary science engages with reality across a myriad of orders of magnitude, from the extremely small to the extremely large, somewhere between sixty and one hundred all told. Math can manage this brilliantly. Natural languages cannot. All of which means: philosophers beware!

Philosophers love analogies, and well they should. They make the abstract concrete. They enable us to transport a strategy from a domain where it has been proven effective and test its applicability in a completely different one. Such acts of imagination are the foundation of discovery, the springboard to disruptive innovation. But to work properly they have to be credible. That means they must stand up to the kind of pressure testing that determines the limits to which they can be applied, the boundaries beyond which they must not stretch. This is where the orders of magnitude principle comes in.

It is not credible that there could be a cause that is a million million times smaller than its effect. Yes, it is theoretically conceivable that via a cascading set of emergent relationships, one could build a chain from such an A to such a B, but the amount of coordination that would be required to lever something up a million million times is just ridiculously improbable. So, when philosophers refer to the uncertainty principles embedded in quantum mechanics, and then infer or imply that such uncertainty permeates human affairs, or when they trace consciousness down to quantum fluctuations in messenger RNA, when, in short, they are correlating things that are more than a trillion, trillion times different in size and scope, then they are misusing both the mathematics of science and the resources of natural language. We simply have to stay closer to home.

That’s what I think. What do you think?

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The Breakthrough Lifecycle

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The Breakthrough Lifecycle

GUEST POST from Greg Satell

Many experts suspect that the COVID crisis is receding into the background. It is, of course, hard to know for sure. There will continue to be debate and we will still need to have some mitigating measures in place. Still, for the most part, people are back at work, kids are in school, and relatively normal routines have returned.

Generations from now, historians will most likely still question what lessons are to be gleaned from the past few years. Should we strengthen our multilateral institutions or have they become so sclerotic that they need to be dismantled? Is the rise of populist nationalism a harbinger for the future or a flash in the pan?

One thing I don’t expect to be hotly debated, in fact seems perfectly clear even now, is that science saved us. Untold thousands, working mostly anonymously in labs around the world, created a vaccine of astonishing efficacy in record time. It is these types of breakthroughs that change the course of history and, if we can embrace their power, lead us to a better future.

A Seemingly Useless Idea

The MRNA technology that led to the Moderna and Pfizer-BioNTech vaccines have the potential to revolutionize medical science. It can rapidly reprogram the machinery in our cells to manufacture things that can potentially cure or prevent a wide range of diseases, from cancer to malaria, vastly more efficiently than anything we’ve ever seen before.

Yet while revolutionary, it is not at all a new idea. In fact Katalin Karikó, who pioneered the approach, published her first paper on mRNA-based therapy way back in 1990. Unfortunately, she wasn’t able to win grants to fund her work and, by 1995, things came to a head. She was told that she could either direct her energies in a different way, or be demoted.

This type of thing is not unusual. Jim Allison, who won the Nobel Prize for his work on cancer immunotherapy, had a very similar experience when he had his breakthrough, despite having already become a prominent leader in the field. “It was depressing,” he told me. “I knew this discovery could make a difference, but nobody wanted to invest in it.”

The truth is that the next big thing always starts out looking like nothing at all. Things that really change the world always arrive out of context for the simple reason that the world hasn’t changed yet.

Overcoming Resistance

Humans tend to see things in a linear fashion. It is easier for us to imagine a clear line of cause and effect, like a row of dominoes falling into each other, rather than a series of complex interactions and feedback loops. So it shouldn’t be surprising that, in hindsight, breakthrough ideas seem so obvious that only the most dim-witted would deny their utility.

When we think of something like, say, electricity, we often just assume that it was immediately adopted and the world simply changed overnight. After all, who could deny the superiority of an efficient electric motor over a big, noisy steam engine? Yet as the economist Paul David explained in a famous paper, it took 40 years for it to really take hold.

There are a few reasons why this is the case. The first is switching costs. A new technology almost always has to replace something that already does the job. Another problem involves establishing a learning curve. People need to figure out how to unlock the potential of the new technology. To bring about any significant change you first have to overcome resistance.

With electricity, the transition happened slowly. It wouldn’t have made sense to immediately tear down steam-powered factories and replace them. At first, only new plants used the electricity. Yet it wasn’t so much the technology itself, but how people learned to use it to re-imagine how factories functioned that unlocked a revolution in productivity gains.

In the case of mRNA technology, no one had seen a mRNA vaccine work, so many favored more traditional methods. Johnson & Johnson and AstraZeneca, for example, used a more traditional DNA-based approach using adenoviruses that was much better understood, rather than take a chance on a newer, unproven approach.

We seem to be at a similar point now with mRNA and other technologies, such as CRISPR. They’ve been proven to be viable, but we really don’t understand them well enough yet to unlock their full potential.

Building Out The Ecosystem

When we look back through history, we see a series of inventions. It seems obvious to us that things like the internal combustion engine and electricity would change the world. Still, as late as 1920, roughly 40 years after they were invented, most American’s lives remained unchanged. For practical purposes, the impact of those two breakthroughs were negligible.

What made the difference wasn’t so much the inventions themselves, but the ecosystems that form around them. For internal combustion engines it took a separate networks to supply oil, to build roads, manufacture cars and ships and so on. For electricity, entire industries based on secondary inventions, such as household appliances and radios, needed to form to fully realize the potential of the underlying technology.

Much of what came after could scarcely have been dreamed of. Who could have seen how transportation would transform retail? Or how communications technologies would revolutionize warfare? Do you really think anybody looked at an IBM mainframe in the 1960s and said, “Gee, this will be a real problem for newspapers some day?”

We can expect something similar to happen with mRNA technology. Once penicillin hit the market in 1946, a “golden age” of antibiotics ensued, resulting in revolutionary new drugs being introduced every year between 1950 and 1970. We’ve seen a similar bonanza in cancer immunotherapies since Jim Allison’s breakthrough.

In marked contrast to Katalin Karikó’s earlier difficulty in winning grants for her work, the floodgates have now opened as pharma companies are now racing to develop mRNA approaches for a myriad of diseases and maladies.

The Paradox Of New Paradigms

The global activist Srdja Popović once told me that when a revolution is successful, it’s difficult to explain the previous order, because it comes to be seen as unbelievable. Just as it’s hard to imagine a world without electricity, internal combustion or antibiotics today, it will be difficult to explain our lives today to future generations.

In much the same way, we cannot understand the future through linear extrapolation. We can, of course, look at today’s breakthroughs in things like artificial intelligence, synthetic biology and quantum computing, but what we don’t see is the second or third order effects, how they will shape societies and how societies will choose to shape them.

Looking at Edison’s lightbulb would tell you nothing about radios, rock music and the counterculture of the 60s, much like taking a ride in Ford’s “Model T” would offer little insight into the suburbs and shopping malls his machine would make possible. Ecosystems are, by definition, chaotic and non-linear.

What is important is that we allow for the unexpected. It was not obvious to anyone that Katalin Karikó could ever get her idea to work, but she shouldn’t have had to risk her career to make a go of it. We’re enormously lucky that she didn’t, as so many others would have, taken an easier path. It is, in the final analysis, that one brave decision that we have to thank for what promises to be brighter days ahead.

All who wander are not lost.

— Article courtesy of the Digital Tonto blog
— Image credits: Pixabay

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Uber Economy is Killing Innovation, Prosperity and Entrepreneurship

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Uber Economy is Killing Innovation, Prosperity and Entrepreneurship

GUEST POST from Greg Satell

Today, it seems that almost everyone wants to be the “Uber” of something, and why not? With very little capital investment, the company has completely disrupted the taxicab industry and attained a market value of over $100 billion. In an earlier era, it would have taken decades to have created that kind of impact on a global scale.

Still, we’re not exactly talking about Henry Ford and his Model T here. Or even the Boeing 707 or the IBM 360. Like Uber, those innovations quickly grew to dominance, but also unleashed incredible productivity. Uber, on the other hand, gushed red ink for more than a decade despite $25 billion invested. In 2021 it lost more than $6 billion, the company made progress in 2022 but still lost money, and it was only in 2023 that they finally made a profit.

The truth is that we have a major problem and, while Uber didn’t cause it, the company is emblematic of it. Put simply, a market economy runs on innovation. It is only through consistent gains in productivity that we can create real prosperity. The data and evidence strongly suggests that we have failed to do that for the past 50 years. We need to do better.

The Productivity Paradox Writ Large

The 20th century was, for the most part, an era of unprecedented prosperity. The emergence of electricity and internal combustion kicked off a 50-year productivity boom between 1920 and 1970. Yet after that, gains in productivity mysteriously disappeared even as business investment in computing technology increased, causing economist Robert Solow to observe that “You can see the computer age everywhere but in the productivity statistics.”

When the internet emerged in the mid-90’s things improved and everybody assumed that the mystery of the productivity paradox had been resolved. However, after 2004 productivity growth disappeared once again. Today, despite the hype surrounding things such as Web 2.0, the mobile Internet and, most recently, artificial intelligence, productivity continues to slump.

Take a closer look at Uber and you can begin to see why. Compare the $25 billion invested in the ride-sharing company with the $5 billion (worth about $45 billion today) IBM invested to build its System 360 in the early 1960s. The System 360 was considered revolutionary, changed computing forever and dominated the industry for decades.

Uber, on the other hand, launched with no hardware or software that was particularly new or revolutionary. In fact, the company used fairly ordinary technology to dis-intermediate relatively low-paid taxi dispatchers. The money invested was largely used to fend off would-be competitors through promoting the service and discounting rides.

Maybe the “productivity paradox” isn’t so mysterious after all.

Two Paths To Profitability

Anybody who’s ever taken an Economics 101 course knows that, under conditions of perfect competition, the forces of supply and demand are supposed to drive markets toward equilibrium. It is at this magical point that prices are high enough to attract supply sufficient to satisfy demand, but not any higher.

Unfortunately for anyone running a business, that equilibrium point is the same point at which economic profit disappears. So to make a profit over the long-term, managers need to alter market dynamics either through limiting competition, often through strategies such as rent seeking and regulatory capture, or by creating new markets through innovation.

As should be clear by now, the digital revolution has been relatively ineffective at creating meaningful innovation. Economists Daron Acemoglu and Pascual Restrepo refer to technologies like Uber, as well as things like automated customer service, as “so-so technologies,” because they displace workers without significantly increasing productivity.

Joseph Schumpeter pointed out long ago, market economies need innovation to fuel prosperity. Without meaningful innovation, managers are left with only strategies that limit innovation, undermine markets and impoverish society, which is what largely seems to have happened over the past few decades.

The Silicon Valley Doomsday Machine

The arrogance of Silicon Valley entrepreneurs seems so outrageous—and so childishly naive— that it is scarcely hard to believe. How could an industry that has produced so little in terms of productivity seem so sure that they’ve been “changing the world” for the better. And how have they made so much money?

The answer lies in something called increasing returns. As it turns out, under certain conditions, namely high up-front investment, negligible marginal costs, network effects and “winner-take-all markets,” the normal laws of economics can be somewhat suspended. In these conditions, it makes sense to pump as much money as possible into an early Amazon, Google or Facebook.

However this seemingly happy story has a few important downsides. First, to a large extent these technologies do not create new markets as much as they disrupt or displace old ones, which is one reason why productivity gains are so meager. Second, the conditions apply to a small set of products, namely software and consumer gadgets, which makes the Silicon Valley model a bad fit for many groundbreaking technologies.

Still, if the perception is that you can make a business viable by pumping a lot of cash into it, you can actually crowd-out a lot of good businesses with bad, albeit well-funded ones. In fact, there is increasing evidence that is exactly what is happening. Rather than an engine of prosperity, Silicon Valley is increasingly looking like a doomsday machine.

Returning To An Innovation Economy

Clearly, we cannot continue “Ubering” ourselves to death. We must return to an economy fueled by innovation, rather than disruption, which produces the kind of prosperity that lifts all boats, rather than outsized profits for a meager few. It is clearly in our power to do that, but we must begin to make better choices.

First, we need to recognize that innovation is something that people do, but instead of investing in human capital, we are actively undermining it. In the US, food insecurity has become an epidemic on college campuses. To make matters worse, the cost of college has created a student debt crisis, essentially condemning our best and brightest to decades of indentured servitude. To add insult to injury, healthcare costs continue to soar. Should we be at all surprised that entrepreneurship is in decline?

Second, we need to rebuild scientific capital. As Vannevar Bush once put it, “There must be a stream of new scientific knowledge to turn the wheels of private and public enterprise.” To take just one example, it is estimated that the $3.8 billion invested in the Human Genome Project generated nearly $800 billion of economic activity as of 2011. Clearly, we need to renew our commitment to basic research.

Finally, we need to rededicate ourselves to free and fair markets. In the United States, by almost every metric imaginable, whether it is industry concentration, occupational licensing, higher prices, lower wages or whatever else you want to look at capitalism has been weakened by poor regulation and oversight. Not surprisingly, innovation has suffered.

Perhaps most importantly, we need to shift our focus from disrupting markets to creating them, from “The Hacker Way”, to tackling grand challenges and from a reductionist approach to an economy based on dignity and well being. Make no mistake: The “Uber Economy” is not the solution, it’s the problem.

— Article courtesy of the Digital Tonto blog
— Image credits: Pixabay

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Don’t ‘Follow the Science’, Follow the Scientific Method

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Don't 'Follow the Science', Follow the Scientific Method

GUEST POST from Pete Foley

The scientific method is probably the most useful thing I’ve learnt in my life. It is a near universal tool that can be used in so many ways and so many places. It unleashes a whole world of assisted critical thinking that is invaluable to innovators, but also in our personal lives. Teaching it to individuals or teams who are not trained as scientists is one of the most powerful and enabling things we can do for them. And teaching it to kids, as opposed to endless facts and data that they can easily access from the web is something we should do far more of.

Recruiting Skills not Expertise: When I was involved in recruiting, I always valued PhD’s and engineers. Sometimes that was for their unique, specialized knowledge. But more often than not it was more for the critical thinking skills they had acquired while gaining that specialized knowledge. In today’s rapidly evolving world, specific knowledge typically has a relatively short shelf-life. But the cognitive framework embodied by the scientific method is a tool for life, and one that can be reapplied in so many ways. .

Don’t Follow the Science, Follow the Process: All too often today the scientific method gets confused with ‘following the science’. The scientific process is almost infinitely useful, but blindly ‘following the science’ is often far less so, and can be counter productive. The scientific method is a process that helps us to evaluate information, challenge assumptions, and in so doing, get us closer to truth. Sometimes it confirms our existing ideas, sometimes it improves them, and sometimes it completely replaces them. But it is grounded in productive and informed skepticism, and this is at the heart of why science is constantly evolving.

‘Follow the Science’ in many ways the opposite. It assumes someone in a position of power already has the right answer. At it’s best it means blindly follow the consensus of today’s experts. All too often it really means ‘do as you are told’. Frequently the people saying this are not the experts themselves, but are instead evoking third party expertise to support their viewpoint. That of course is the opposite of science. It’s often well intended, but not always good advice.

Science is not a Religion: At the heart of this is a fundamental misunderstanding of science, and scientists. In today’s media and social media, all too often science and scientists are presented with a quasi-religious reverence, and challenging the current view is framed as heretical. How often do you here the framing ‘scientists tell us… ‘ as a way of validating a position?

This is understandable. The sheer quantity and complexity of information we are faced with in our everyday lives is increasingly unmanageable, while big challenges like climate unimaginably complex. I find it almost impossible to keep up with my own interests, let alone everything that is happening. And some topics are so technical that they simply require translation by experts. When someone announces they’ve discovered the Higgs boson particle, it’s not really practical for any of us to pop over to the local particle accelerator and check for ourselves. So expertise is clearly an important part of any decision chain. But experts come with their own biases. An engineer naturally tends to see problems and through, an engineering lens, a chemist through a chemical one.

Science in Support of an Agenda: One danger with the ‘follow the science’ mantra is that it is often used to reinforce a belief, opinion, or even agenda. I’ve seen this all too often in my work life, with the question, ‘can you find me a paper that supports ‘x’. This is often benign, in that someone passionately believes something, and wants to find evidence to support it. But this is fundamentally the wrong question, and of course, completely ‘unscientific’.

The scientific literature is filled with competing theories, disproven or outdated ideas, and bad science. If you look for literature to support an idea you can usually find it, even if it’s wrong. Scientists are not gods. They make mistakes, they run poor experiments, and they are subject to confirmation biases, ego, and other human frailties. There is a good reason for the phrase that science evolves one death at a time. Science, like virtually every human organization is hierarchical, and a prestigious scientist can advance a discipline, but can also slow it down by holding onto a deeply held belief. And mea culpa, I know from personal experience that it’s all too easy to fall in love with a theory, and resist evidence to the contrary.

Of course, some theories are more robust than others. Both consensus and longevity are therefore important considerations. Some science is so well established, and supported by so much observation that it’s unlikely that it will fundamentally change. For example, we may still have a great deal to learn about gravity, but for practical purposes, apples will still drop from trees.

Peer Review: Policing the literature is hard. Consensus is right until its not. Another phrase I often hear is ‘peer reviewed’, in the context that this makes the paper ‘right’. Of course, peer review is valuable, part of the scientific process, and helps ensure that content has quality, and has been subject to a high level of rigor. If one person says it, it can be a breakthrough or utter nonsense. If a lot of smart people agree, it’s more likely to be ‘right’. But that is far from guaranteed, especially if they share the same ingoing assumptions. Scientific consensus has historically embraced many poor theories; a flat earth, or the sun revolving around the earth are early examples. More tragically, I grew up with the thalidomide generation in Europe. On an even bigger scale, the industrial revolution gave us so much, but also precipitated climate change. And on a personal level, I’ve just been told by my physician to take a statin, and I am in the process of fighting my way through rapidly growing and evolving literature in order to decide if that is the right decision. So next time you see a scientist, or worse, a politician, journalist, or a random poster on Twitter claim they own scientific truth, enjoin you to ‘follow the science’, or accuse someone else of being a science denier, treat it with a grain of sodium chloride.

They may of course be right, but the more strident they are, or the less qualified, the less likely they are to really understand science, and hence what they are asking you to follow. And the science they pick is quite possibly influenced by their own goals, biases or experience. Of course, practically we cannot challenge everything. We need to be selective, and the amount of personal effort we put into challenging an idea will depend upon how important it is to us as individuals.

Owning your Health: Take physicians as an example. At some time or other, we’ve all looked to a physician for expert advise. And there is a good reason to do so. They work very hard to secure deep knowledge of their chosen field, and the daily practice of medicine gives then a wealth of practical as well as well as theoretical knowledge. But physicians are not gods either. The human body is a very complex system, physicians have very little time with an individual patient (over the last 10 years, the average time a physician spends with a patient has shrunk to a little over 15 minutes), the field is vast and expanding, and our theories around how to diagnose and treat disease are constantly evolving. In that way, medicine is a great example of the scientific method in action, but also how transient ‘scientific truths’ can be.

I already mentioned my current dilemma with statins. But to give an even more deeply personal example, neither my wife or I would be alive today if we’d blindly followed a physicians diagnosis.

I had two compounding and comparatively rare conditions that combined to appear like a more common one. The physician went with the high probability answer. I took time to dig deeper and incorporate more details. Together we got to the right answer, and I’m still around!

This is a personal and pragmatic example of how valuable the scientific process can be. My health is important, so I chose to invest considerable time in the diagnosis I was given, and challenge it productively, instead of blindly accepting an expert opinion. My physicians had far more expertise than I did, but I had far more time and motivation. We ultimately complemented each other by partnering, and using the scientific method both as a process, and as a way to communicate.

The Challenge of Science Communication: To be fair, science communication is hard. It requires communicating an often complex concept with sufficient simplicity for it to be understandable, often requires giving guidance, while also embracing appropriate uncertainty. Nowhere was this more evident than in the case of Covid 19, where a lot of ‘follow the science’, and ‘science denier’ language came from. At the beginning of the pandemic, the science was understandably poorly developed, but we still had to make important decisions on often limited data. At first we simply didn’t understand even the basics like the transmission vectors (was it airborne or surface, how long did it survive outside of the body, etc). I find it almost surreal to think back to those early months, how little we knew, the now bizarre clean room protocols we used on our weekly shopping, and some of the fear that has now faded into the past.

But because we understood so little, we made a lot of mistakes. The over enthusiastic use of ventilators may have killed some patients, although that is still a hotly debated topic. Early in the pandemic masks, later to become a controversial and oddly politically charged topic, masks were specifically not recommended by the US government for the general public. Who knows how many people contracted the disease by following this advice? It was well intentioned, as authorities were trying to prevent a mask shortage for health workers. But it was also mechanistically completely wrong.

At the time I used simple scientific reasoning, and realized this made little sense. If the virus was transmitted via an airborne vector, a mask would help. If it wasn’t, it would do no harm, at least as long as I didn’t subtract from someone with greater need. By that time the government had complete control of the mask supply chain anyway, so that was largely a moot point. Instead I dug out a few old N95 masks that had been used for spray painting and DIY, and used them outside of the house (hospitals would not accept donations of used masks). I was lambasted with ‘follow the science’ by at least one friend for doing so, but followed an approach with high potential reward and virtually zero downside. I’ll never know if that specifically worked, but I didn’t get Covid, at least not until much later when it was far less dangerous.

Science doesn’t own truth: Unlike a religion, good science doesn’t pretend to own ultimate truths. But unfortunately it can get used that way. Journalists, politicians, technocrats and others sometimes weaponize (selective) science to support an opinion. Even s few scientists who have become frustrated with ‘science deniers’ can slip into this trap.

Science is a Journey: I should clarify that the scientific method is more of a journey, not so much a single process. To suggest is is a single ‘thing’ so is probably an unscientific simplification in its own right. It’s more a way of thinking that embraces empiricism, observation, description, productive skepticism, and the use of experimentation to test and challenge hypothesis. It also helps us to collaborate and communicate with experts in different areas, creating a common framework for collaboration, rather than blindly following directions or other expert opinions.

It can be taught, and is incredibly useful. But like any tool, it requires time and effort to become a skilled user. But if we invest in it, it can be extraordinarily valuable, both in innovation and life. It’s perhaps not for every situation, as that would mire us in unmanageable procrastination. But if something is important, it’s an invaluable tool.

Image credits: Pixabay

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