Every Disaster Has a Beginning: In Search of Anomaly Zero
In 2012, when 15-year old Jack Andraka’s uncle died of pancreatic cancer, he decided to look into it. He found that the current test for pancreatic cancer was over 60 years old, cost over $800, and wasn’t very reliable.
For this reason over 85% of pancreatic cancer cases were detected too late, when the chances of survival were only 2%.
As a bright and inspired young mind, Jack was able to devise a far better testing procedure, which he took to the researchers at Johns Hopkins University.
The result is a new dipstick-type diagnostic test that uses a paper sensor, similar to that of the diabetic test strip. This strip tests for cancer biomarkers in blood or urine, is over 90% accurate and only costs 3 cents per test.
Jack’s ingenious test strip will soon be used for early testing of other diseases as well. But this line of thinking doesn’t just apply to the medical arena.
- We can’t stop a hurricane after its reached full intensity.
- We can’t stop an avalanche after it’s halfway down the mountain.
- We can’t stop a tidal wave after it already in motion.
- We can’t stop a war once the bombs start dropping.
- We can’t stop a plague once it’s reached several continents.
As tiny humans battling the giant forces of nature, we need to do battle when the problems are still small. Jack was able to push the discovery of pancreatic cancer far closer to Anomaly Zero. Anomaly Zero is the first detectable sign that something is wrong.
Every major disaster in the world begins with the shifting of a single molecule, a spark of electrical energy, or some synapse firing in a different way.
We may not be able to spot that first sign of change, but can get far closer than what we detect today. So what exactly is Anomaly Zero and how close can we actually get to it and intervene before major damage begins?
The Butterfly Effect
In 1969, chaos theorist Edward Lorenz used the theoretical example of a butterfly’s wings flapping, where that simple movement became the root cause of a hurricane forming several weeks later on the other side of the planet. This has become known as the butterfly effect.
This type of cause and effect relationship, in chaos theory, is used to describe a nonlinear system where the true sequence of events is so complex that it can only be sorted out after the fact.
Anomaly Zero is different than that. Using an interventionist’s mindset, Anomaly Zero is the theoretical earliest possible point where danger can be confirmed as a real threat. In virtually all cases, it remains theoretical because we are a long ways from both understanding it and figuring out ways to track it.
The primary point of this discussion is simply to move the earliest red flags of detection far closer to the point of origin so most disasters can be averted.
Defining a Minimum Detectable Change
When a forest fire starts, it’s relatively easy to put out the flames when it only covers a few square feet. Once it grows to an entire acre, it becomes far more difficult to contain.
At the same time, not all fires build momentum and turn into disasters. Fires in campgrounds, being carefully monitored by campers, rarely get out of control. So just scouting for fires in a forest will produce lots of meaningless data points, otherwise known as statistical noise.
With enough data points, certain disorders will cause an emerging situation to be flagged, first as noteworthy, something that needs to be monitored, and something that may eventually be upgraded to a dangerous condition.
If we think about change as measured along a 1,000-mile long yardstick, Anomaly Zero is at the beginning, and today’s early warning systems are at the end. Our goal should be to determine the earliest possible point that we can detect a problem?
How can we detect danger earlier, much earlier, while the situation is still controllable?
Everything I’ve discussed so far is about building awareness, and using this added awareness to halt something negative from happening. In this context it becomes easier to visualize a far better early warning system for detecting:
- Natural Disasters
- Health Issues
- Disease Outbreaks
- Infrastructure Failures
- Environmental Dangers
- Deviant Behavior
- Much more
When it comes to spotting deviant behavior, we have the potential for intervening and removing the worst of the worst very quickly. Here’s an example.
One of the most notorious serial killers of all times was Pedro Alonso Lopez, known as the “Monster of the Andes,” who butchered enough people to fill a small town. After killing around 100 tribal women in Peru in the 1970s, he was apprehended by tribal forces that were just about ready to execute him when they were convinced by an American missionary to take him to the police instead.
Unfortunately, the police then just let him go, after which Lopez travelled to Ecuador, where he proceeded to kill about 3-4 girls a week, claiming that girls in Ecuador were “more gentle, trusting, and innocent”. This carried on until he was caught in 1980, but police were still unsure as to his guilt. But as luck would have it, a flash flood uncovered a mass grave that had hidden many of his victims, which then led to his arrest.
Once again, for some unexplainable reason, the Ecuadorian government decided to release him in 1998, deporting him to Columbia. Lopez allegedly said that he was being released for “good behavior”. His whereabouts today is unknown.
As we increase our awareness of what’s happening in society, the odds of this kind of deviant behavior being overlooked are dramatically reduced. In most cases, mass murderers like Lopez or Ted Bundy will be red flagged and caught after the first death rather than dozens or hundreds of deaths later.
But what if these types of disasters could be spotted before anyone died? Is there a data-driven version of Minority Report justice that might actually make sense without relying on mystical “precogs” to guide our way?
Like a single pixel on a trillion pixel image, we quickly lose our ability to find significance in a single point. But it is exactly that, a tiny little signal on the masterpiece of life that determines what happens next.
Every disaster has a lifecycle with a definable beginning, middle, and end. As with every statistical bell curve, the size and shape of the curve represents the overall impact on society.
But disasters are not inevitable. Human intervention can make a huge difference, and the sooner the better.
We are currently building a massive digital infrastructure with the ability to monitor and assess changes happening anywhere in the world in real time. As we move into the big data era, our awareness of pre-disaster conditions will grow exponentially.
Once we can sense an impending disaster, we will need to create response mechanisms capable of mitigating whatever forces are in play.
I’m certainly not deluded into thinking we can eliminate all or even most of the catastrophes we’ll be facing over the coming years. But we have an obligation to deal with these problems in a far better fashion than we currently are.
And all of this can happen if we focus our attention on the nano-size events happening at Anomaly Zero.
Please take a few moments to weigh in on this topic. I’d love to hear what you think.
Every Disaster Has a Beginning: In Search of Anomaly Zero
I was thoroughly intrigued when I found out the Colorado School of Mines in Golden, Colorado was offering a degree in asteroid mining.
Yes, the idea of extracting water, oxygen, minerals, and metals from an asteroid sounds like science fiction to most people, but it’s not that far away. In fact, Colorado School of Mines’ newly launched “Space Resources” program will help people get in on the ground floor.
After thinking about the proactive nature of this approach, it became abundantly clear how backward thinking most colleges have become.
When colleges decide on a new degree program, they must first recruit instructors, create a new curriculum, and attract students. As a result, the talent churned out of these newly minted programs is the product of a 6-7 year pipeline.
For this reason, anticipatory-thinking institutions really need to be setting their sights on what business and industries will need 7-10 years from now.
The Risk-Averse Nature of Education
When Harvard professor Clayton M. Christensen released his best-selling book, The Innovator’s Dilemma, his core message that disruptive change is the path to success, was only partially embraced by higher education.
While many were experimenting with MOOCs and smart whiteboards, changes in the subject matter of their courses still evolved at the traditional pace of discovery.
This is not to say colleges are not innovative. Rather, the demands of today’s emerging tech environment are forcing business and industries to shift into an entirely new gear. And that most definitely includes our academic institutions.
From a management perspective, it’s far easier to oversee a contained system where all variables are constrained. But during times of change, we tend to give far more power to the “unleashers,” who are determined to test the status quo and release ideas and trial balloons to see what works.
For this reason, managers and creatives often find themselves on opposing sides, and the winners of these warring factions often determine what we as consumers see as the resulting ripples of change.
Offering Pilot Programs
When Facebook bought Oculus Rift in March 2014 for $2 billion, the job boards went crazy, as there was an instant uptick in the demand for VR designers, engineers, and experience creators. But no one was teaching VR, and certainly not the Oculus Rift version of it.
Colleges have a long history of being blindsided by new technologies:
- When eBay launched, no one was teaching ecommerce strategies
- When Myspace launched, no one was teaching social networking
- When Google launched, no one was teaching online search engine strategies
- When Uber launched, no one was teaching sharing economy business models
- When Apple first opened their App Store, no one was teaching smart phone app design
- When Amazon first allowed online storefronts, no one was teaching the Amazon business model
- When YouTube first offered ways to monetize videos, no one was teaching it
Since most academic institutions are only willing to put their name on programs with long-term viability, the endorsement of half-baked agendas does not come easy. However, that is exactly what needs to be done.
Colleges can no longer afford to remain comfortably behind the curve.
52 Future College Degrees
As a way of priming your thinking on this matter, here are 52 future degrees that forward-thinking colleges could start offering today:
- Space Exploration – space tourism planning and management
- Space Exploration – planetary colony design and operation
- Space Exploration – next generation space infrastructure
- Space Exploration – advanced cosmology and non-earth human habitats
- Bioengineering with CRISPR – policy and procedural strategies
- Bioengineering with CRISPR – advanced genetic engineering systems
- Bioengineering with CRISPR – operational implementations and system engineering
- Bioengineering with CRISPR – ethical regulation and oversight
- Smart City – autonomous traffic integration
- Smart City – mixed reality modeling
- Smart City – autonomous construction integration
- Smart City – next generation municipal planning and strategy
- Autonomous Agriculture – robotic systems
- Autonomous Agriculture – drone systems
- Autonomous Agriculture – supply chain management
- Autonomous Agriculture – systems theory and integration
- Swarmbot – design, theory, and management
- Swarmbot – system engineering and oversight
- Swarmbot – municipal system design
- Swarmbot – law enforcement and advanced criminology systems
- Cryptocurrency – digital coin economics
- Cryptocurrency – crypto-banking system design
- Cryptocurrency – regulatory systems and oversight
- Cryptocurrency – forensic accounting strategies
- Blockchain – design, systems, and applications
- Blockchain – blockchain for biological systems
- Blockchain – large-scale integration structures
- Blockchain – municipal system design strategies
- Global Systems – system planning, architecture, and design
- Global Systems – large-scale integration strategies
- Global Systems – operational systems checks and balance
- Global Systems – governmental systems in a borderless digital world
- Unmanned Aerial Vehicle - drone film making
- Unmanned Aerial Vehicle – command center operations
- Unmanned Aerial Vehicle – municipal modeling and planning systems
- Unmanned Aerial Vehicle – emergency response systems
- Mixed Reality - experiential retail
- Mixed Reality – three-dimensional storytelling
- Mixed Reality – game design
- Mixed Reality – therapeutic systems and design
- Advanced Reproductive Systems – designer baby strategies, planning, and ethics
- Advanced Reproductive Systems – surrogate parenting policy and approaches
- Advanced Reproductive Systems – organic nano structures
- Advanced Reproductive Systems – clone engineering and advanced processes
- Artificial Intelligence – data management in an AI environment
- Artificial Intelligence – advanced human-AI integration
- Artificial Intelligence – streaming AI data services
- Artificial Intelligence – advanced marketing with AI
- Quantum Computing – data strategies in a quantum-connected world
- Quantum Computing – quantum-level encryption and security
- Quantum Computing – quantum computing implementation strategies
- Quantum Computing – AI-quantum system integration
More so than any time in history, we have a clear view of next generation technologies. Naturally, we’re still a long way from 100% clarity, but for most of the technologies listed above, the shifting tectonic plates of change can be felt around the world.
Without taking decisive action, colleges run the risk of being circumvented by new types of training systems that can meet market demands in a fraction of the time it takes traditional academia to react.
The ideas I’ve listed are a tiny fraction of what’s possible when it comes to emerging tech degrees. Should colleges stick their neck out like Colorado School of Mines and offer degrees that may not be immediately useful? Adding to that question, how many college degrees are immediately useful today?
I’d love to hear your thoughts on this topic.