On your way back from work one day – in a shared, driverless car – you get a message from your doctor. She says she’s noticed your temperature readings detected by your smart socks, smart shirt, and smart pants increased by an average of 1F. Your smartwatch indicates you’ve been exercising 25% less. She explains how in Arizona – you were there last week for business – people have exhibited similar trends. She expects you may develop flu symptoms in the next few days, and recommends you come in for a check-up this afternoon.
In Joanna Kavenna’s new book “Zed”, behemoth technology giants run governments. They monitor the populace and control everything. In her book, Kavenna paints a pessimistic picture. She highlights how data used incorrectly hurts society. However, I believe individual and public good arises from such large amounts of data.
In this opinion piece, I explore the potential benefits of collection. Many of these technologies already exist today to varying degrees of maturity and consumer access. I give my opinion on how we will use huge amounts of data to help, rather than hurt or control, individuals and society. In a future blog, I plan to explore security, privacy, and other considerations needed to help ensure this data is shared, protected, and utilized appropriately.
Today, we have portable communication devices that Michio Kaku, the physicist and popular author, says “has more computer power than all of NASA back in 1969, when it placed two astronauts on the moon.” We call these portable devices cell phones.
In addition to cell phones, wearable technologies – known simply as wearables – are smart electronic devices worn closely to and/or on the surface of the skin. One third of all Americans have wearables that collect movement, heart rate, and oxygen levels.
Traditionally these devices have been marketed as entertainment. Only recently have wearables potential for meaningful personal and population health begun to emerge.
Wearable technology will one day be included in shirts, dresses, shoes, hats, and other clothing. We will have tiny sensors embedded in our organs, allowing a real-time measurement of organ function by electrodes measuring our internal functions. Trillions of data points will be collected hundreds of times per second on you, me, our neighbors, and the world.
Data Collected Today
We already collect huge amounts of data. In the medical world, we have electronic healthcare records, giant database registries chronologizing our medical history. They store our test results and past surgeries. They also store insights, notes, and final diagnosis from healthcare providers. Medical diagnostic studies house detailed physiological information over brief periods of time. Smartwatches created by Apple, Garmin, FitBit, and many others are already collecting massive amounts of physiological data.
The question now is what we do with that data.
We have the opportunity to interpret the information collected from wearable devices to help both individuals and society. We are seeing examples of this during the current COVID-19 pandemic with organizations across the world collaborating to analyze large amounts of temporal data, interpret the patterns, and triage those findings.
The outputs are helping governments, NGOs, and private institutions make informed decisions about resource allocation, proper procedural interventions, and create meaningful policies and legislation. What we’re seeing today is only the very tip of the iceberg.
Taking the Nation’s Temperature
In recent years, we have seen connected thermometers be used to track the spread of seasonal flu faster than the CDC and they are now being used to indicate growing hot spots for coronavirus. Real-time data from the source provides information much faster than lagging indicators like diagnosis or treatment in a healthcare facility.
The CDC and private healthcare technology companies track temperature changes geospatially and temporally. Individual data points analyzed together help them understand what’s happening to the community. They use this information to track the population’s average temperatures overtime. This shows when people are getting sick and represents the spread of a disease or a virus.
In the future, what will hospitals do with this information? Clinicians and administrators will ensure open bed space at their hospitals ahead of increased admissions. They will order resupplies of personal protective equipment (PPE) way ahead of leading indicators. Today, once doctor visits, emergency room triage, and hospital admissions have increased, hospitals play catch-up to contain and react to health emergencies.
What is Waveform AI?
Feverishness tracked in real-time signifies a meaningful physiological change. Something is going on – but what? Maybe it’s a hot day. Maybe more people are exercising. By taking into account many different pieces of information collected about each one of us, we can understand how all of this ties together.
That’s where Waveform AI comes into the picture.
Waveform AI is a cutting-edge and ever-evolving methodology in computer science and statistics. Researchers modeled Waveform AI on how our own brains work. It mimics the feedback mechanisms our brains’ neurons use to communicate, store information, and interpret our surroundings. This allows them to analyze time-sampled data across a multitude of variables.
For example, today this technology is used in industrial applications to predict when a knob or socket needs to be replaced in a chemical plant. In medicine, the technology is applied to the analysis of medical procedural test data. At EnsoData, we currently use the technology to expedite the diagnosis of sleep disorders.
By utilizing Waveform AI to interpret data collected by wearables, implantables, and other devices, we can understand individual status and relationships between people over time, in ways the human brain cannot.
Observing how temperature relates to location information over time – or how it relates to chemical levels in the body, heart rate, skin humidity, arterial oxygen saturation, or air quality – we find these variables are affected by one another and can draw insights from them.
And there are thousands, tens thousands, millions and even trillions of data points and variables – physiologically, spatially, environmentally – that interact with each other at all times. Waveform AI dynamically attributes different weights and values to each variable, elucidating how these variables influence each other.
By attributing these variables to quantifiable outcomes we will help individuals understand how their actions and physiology affect their life, their well-being, and the people around them. Individuals will make meaningful lifestyle changes based on the personal information provided by their medical providers and by the devices themselves. You will obtain a level of personalized medicine only dreamed of by medical doctors today.
The same variables at the community level will allow institutions, government agencies, medical providers, NGOs, etc. to intervene and help get ahead of the world-wide adverse events.
The algorithms will not always recognize patterns with known outcomes. Rather, some Waveform analysis will alert these groups to meaningful abnormalities. Technology embedded with Waveform AI will tell people that something is happening. It won’t always know what that something is.
Empowering People with Waveform AI
In the future, more information will be collected constantly through many of the devices we use today. Waveform AI will allow researchers and policymakers to analyze and understand this data in meaningful ways. Waveform AI empowers humans to do what computers cannot. Researchers will intervene using creativity, emotion, empathy, value, and judgement – things AI and computers can’t do.
“Zed” is the last alphabet of the greek alphabet, coined by Kavenna as the unexplainable, the unpredictable. It’s what algorithms can’t predict. It’s the very thing giving us our lifeblood and our essence. In a sense, it’s what makes us human. It’s what makes the world intrinsically unknowable.
By understanding the rest of the alphabet, collecting time-sampled data hundreds of times per second, and correlating that to known outcomes, we can better learn from our mistakes and make the world a better place. And understand when we can’t know, when we don’t know, and ultimately empower us to be what we are: human.