by Rodger Malcolm Mitchell, www.nofica.com
Your privacy vs. your lifespan might seem like a strange alternative, something like baseball vs. celery, but in fact, it is one of the great questions of today and of tomorrow.
DISCOVER MAGAZINE, October 2016 edition:
Eric Dishman, a former Intel executive now at the National Institutes of Health, was a 19-year-old college sophomore when he was diagnosed with a rare form of kidney cancer.
Over the course of the next 23 years, he would receive 62 different kinds of chemotherapy, immunotherapy and radiation. Some slowed the tumor’s growth, but never for long. The cancer spread from his left kidney to right kidney.
Just when it seemed Dishman had run out of options, a chance encounter in 2012 with a scientist working for a now-defunct genome-testing company presented an opportunity he couldn’t refuse.
He had his cancerous tissue sequenced, a process that would compare his cancer’s mutated DNA with a healthy patient’s genome.
This would let doctors look for genetic mutations and other abnormalities that support cancer growth, and to use that information to devise a treatment strategy.
Dishman says he was “literally at death’s door,” when he got the call from his doctor. Computer scientists and data crunchers analyzed Dishman’s genetic data and pinpointed a drug – for pancreatic cancer – that targeted the unique features of his cancer.
This experimental drug homes in on the abnormal gene suspected to cause Dishman’s disease.
Within three months of starting treatment, he was cancer-free and eligible for the kidney transplant that ultimately saved his life.
Finding the differences among the myriad of different cancers, and then locating the single drug that will attack one specific cancer, requires massive amounts of information about massive numbers of people.
Today’s medicine esentially is a “one-size-fits-all” process. Have a pain? Take ibuprofen or one of a dozen other common pain relievers, regardless of your physical, mental and emotional uniqueness.
If that doesn’t work, try something else. Keep trying, until you find something that works, even though it may cause unpleasant side effects, and even though it stops working in a short time.
Many people suffer and/or die while their doctors search and search for a treatment, and even then, who knows if the “treatment that works” is the best treatment?
Tomorrow’s medicine would know exactly what treatment works best for YOU. No experimentation needed.
But in order for that to become a reality, first, you must tell the scientists everything about you – and that means EVERYTHING – your lifestyle (where you live and have lived, what you’ve eaten, drunk, and smoked, your age, your diseases throughout your life), plus all your relative’s lifestyles, your genome, your epigenome, their genomes, and epigenomes, etc., and you will update this constantly changing information every day of your life.
Everyone else in the world must do the same, to create a gigantic human database that can be used to find individual cures, not only for cancer, but presumably for all other human ailments.
Medical perfection, the medicine of the future – all we need are big enough computers:
Brian Druker, the director of the Knight Cancer Institute at Oregon Health and Science University (said) “You really need a dataset of 500,000 or a million people to start seeing patterns.”
Intel and OHSU have teamed up through a new, open-source platform called the Collaborative Cancer Cloud (CCC).
Today, when Druker wants to gain insight from patient data beyond his own institution, he must do so manually, by phone or email. It’s a painstaking process that can take weeks or months.
Though the CCC has just launched, its goal is to make this happen in less than a day by 2020 as more cancer centers join and share data.
“You get sequenced in the morning,” says Druker. “Your data is then compared against millions of other patients. By the end of the day, your doctor can say, ‘Yes, we have found the treatment for you and the data to support that choice.’
“You can’t tell a patient to be patient. They need treatments today,” he added.
If you have cancer, or some other intractable disease, or simply are frightened about growing infirm and dying, you want this personalized treatment, now. But . . .
Many scientists cite patient privacy concerns, particularly given the recent spate of data breaches within health care organizations.
And data detached from names can still sometimes be used to identify supposedly anonymous patients.
Somewhere, in the “cloud,” you as an individual will exist as a stream of data, accessible by people you don’t know.
These people will be able to control your life, as though you are a puppet on strings.
More from the October 2016 Discover Magazine, By Cathy O’Neil
Credit scores are one of the formulas that determine our world. They often work against us, from job prospects to how long we’re on hold.
In the 50s, a mathematician named Earl Isaac and his engineer friend, Bill Fair, devised a model they called Fair, Isaac, and Corporation (FICO) to evaluate the risk of an individual defaulting on a loan.
This FICO score was fed by a formula that looked only at a borrower’s finances – mostly his or her debt load and bill-paying record.
Since Fair and Isaac’s pioneering days, the use of scoring has proliferated wildly. Today, we’re added up in every conceivable way as statisticians and mathematicians patch together a mishmash of data, from our ZIP codes and internet surfing patterns to our recent purchases (e-scoring).
Consider the nasty feedback loop e-scores create.
There’s a very high chance the e-scoring system will give the borrower from the rough section of East Oakland a low score.
Lots of people default there. So the credit card offer popping up will be targeted to a riskier demographic. That means less available credit and higher interest rates for those who are already struggling.
Fair and Isaac’s great advance was to (analyze) relevant financial data, like past bill-paying behavior. They focused their analysis on the individual – not on other people with similar attributes.
E-scores, by contrast, carry out thousands of “people like you” calculations.
And if enough of these “similar” people turn out to be deadbeats or, worse, criminals, that individual will be treated accordingly.
According to a survey by the Society for Human Resource Management, nearly half of America’s employers screen potential hires by looking at their credit reports.
Some of them check the credit status of current employees as well, especially when they’re up for a promotion.
The practice of using credit scores in hirings and promotions creates a dangerous poverty cycle. After all, if you can’t get a job because of your credit record, that record will likely get worse, making it even harder to land work.
Bottom line: Big Data can cure your diseases. It can find what you want and help you avoid what you don’t want.
But it can widen the gap between the rich and the rest, making permanent a worldwide caste system, dominated by those few elite having access to your data.
You can lead a perfect life, but if “people like you” lead imperfect lives, you will be tarred with the same brush, and no matter what you do, you will not be able to escape.
You will be who they say you are.
So we ask again:
“Which is more important to you: Your privacy or your life?”
