Category Archives: Systems

Complex adaptive systems, forecasting systems, systems design, systems architecture, modules, modular systems, modular design, system design patterns, forecasting systems that mine big data

The Dying Algorithm

CREDIT: NYT Article on the Dying Algorithm

This Cat Sensed Death. What if Computers Could, Too
By Siddhartha Mukherjee
Jan. 3, 2018

Of the many small humiliations heaped on a young oncologist in his final year of fellowship, perhaps this one carried the oddest bite: A 2-year-old black-and-white cat named Oscar was apparently better than most doctors at predicting when a terminally ill patient was about to die. The story appeared, astonishingly, in The New England Journal of Medicine in the summer of 2007. Adopted as a kitten by the medical staff, Oscar reigned over one floor of the Steere House nursing home in Rhode Island. When the cat would sniff the air, crane his neck and curl up next to a man or woman, it was a sure sign of impending demise. The doctors would call the families to come in for their last visit. Over the course of several years, the cat had curled up next to 50 patients. Every one of them died shortly thereafter.
No one knows how the cat acquired his formidable death-sniffing skills. Perhaps Oscar’s nose learned to detect some unique whiff of death — chemicals released by dying cells, say. Perhaps there were other inscrutable signs. I didn’t quite believe it at first, but Oscar’s acumen was corroborated by other physicians who witnessed the prophetic cat in action. As the author of the article wrote: “No one dies on the third floor unless Oscar pays a visit and stays awhile.”
The story carried a particular resonance for me that summer, for I had been treating S., a 32-year-old plumber with esophageal cancer. He had responded well to chemotherapy and radiation, and we had surgically resected his esophagus, leaving no detectable trace of malignancy in his body. One afternoon, a few weeks after his treatment had been completed, I cautiously broached the topic of end-of-life care. We were going for a cure, of course, I told S., but there was always the small possibility of a relapse. He had a young wife and two children, and a mother who had brought him weekly to the chemo suite. Perhaps, I suggested, he might have a frank conversation with his family about his goals?

But S. demurred. He was regaining strength week by week. The conversation was bound to be “a bummah,” as he put it in his distinct Boston accent. His spirits were up. The cancer was out. Why rain on his celebration? I agreed reluctantly; it was unlikely that the cancer would return.

When the relapse appeared, it was a full-on deluge. Two months after he left the hospital, S. returned to see me with sprays of metastasis in his liver, his lungs and, unusually, in his bones. The pain from these lesions was so terrifying that only the highest doses of painkilling drugs would treat it, and S. spent the last weeks of his life in a state bordering on coma, unable to register the presence of his family around his bed. His mother pleaded with me at first to give him more chemo, then accused me of misleading the family about S.’s prognosis. I held my tongue in shame: Doctors, I knew, have an abysmal track record of predicting which of our patients are going to die. Death is our ultimate black box.

In a survey led by researchers at University College London of over 12,000 prognoses of the life span of terminally ill patients, the hits and misses were wide-ranging. Some doctors predicted deaths accurately. Others underestimated death by nearly three months; yet others overestimated it by an equal magnitude. Even within oncology, there were subcultures of the worst offenders: In one story, likely apocryphal, a leukemia doctor was found instilling chemotherapy into the veins of a man whose I.C.U. monitor said that his heart had long since stopped.

But what if an algorithm could predict death? In late 2016 a graduate student named Anand Avati at Stanford’s computer-science department, along with a small team from the medical school, tried to “teach” an algorithm to identify patients who were very likely to die within a defined time window. “The palliative-care team at the hospital had a challenge,” Avati told me. “How could we find patients who are within three to 12 months of dying?” This window was “the sweet spot of palliative care.” A lead time longer than 12 months can strain limited resources unnecessarily, providing too much, too soon; in contrast, if death came less than three months after the prediction, there would be no real preparatory time for dying — too little, too late. Identifying patients in the narrow, optimal time period, Avati knew, would allow doctors to use medical interventions more appropriately and more humanely. And if the algorithm worked, palliative-care teams would be relieved from having to manually scour charts, hunting for those most likely to benefit.

Avati and his team identified about 200,000 patients who could be studied. The patients had all sorts of illnesses — cancer, neurological diseases, heart and kidney failure. The team’s key insight was to use the hospital’s medical records as a proxy time machine. Say a man died in January 2017. What if you scrolled time back to the “sweet spot of palliative care” — the window between January and October 2016 when care would have been most effective? But to find that spot for a given patient, Avati knew, you’d presumably need to collect and analyze medical information before that window. Could you gather information about this man during this prewindow period that would enable a doctor to predict a demise in that three-to-12-month section of time? And what kinds of inputs might teach such an algorithm to make predictions?
Avati drew on medical information that had already been coded by doctors in the hospital: a patient’s diagnosis, the number of scans ordered, the number of days spent in the hospital, the kinds of procedures done, the medical prescriptions written. The information was admittedly limited — no questionnaires, no conversations, no sniffing of chemicals — but it was objective, and standardized across patients.

These inputs were fed into a so-called deep neural network — a kind of software architecture thus named because it’s thought to loosely mimic the way the brain’s neurons are organized. The task of the algorithm was to adjust the weights and strengths of each piece of information in order to generate a probability score that a given patient would die within three to 12 months.

The “dying algorithm,” as we might call it, digested and absorbed information from nearly 160,000 patients to train itself. Once it had ingested all the data, Avati’s team tested it on the remaining 40,000 patients. The algorithm performed surprisingly well. The false-alarm rate was low: Nine out of 10 patients predicted to die within three to 12 months did die within that window. And 95 percent of patients assigned low probabilities by the program survived longer than 12 months. (The data used by this algorithm can be vastly refined in the future. Lab values, scan results, a doctor’s note or a patient’s own assessment can be added to the mix, enhancing the predictive power.)

So what, exactly, did the algorithm “learn” about the process of dying? And what, in turn, can it teach oncologists? Here is the strange rub of such a deep learning system: It learns, but it cannot tell us why it has learned; it assigns probabilities, but it cannot easily express the reasoning behind the assignment. Like a child who learns to ride a bicycle by trial and error and, asked to articulate the rules that enable bicycle riding, simply shrugs her shoulders and sails away, the algorithm looks vacantly at us when we ask, “Why?” It is, like death, another black box.

Still, when you pry the box open to look at individual cases, you see expected and unexpected patterns. One man assigned a score of 0.946 died within a few months, as predicted. He had had bladder and prostate cancer, had undergone 21 scans, had been hospitalized for 60 days — all of which had been picked up by the algorithm as signs of impending death. But a surprising amount of weight was seemingly put on the fact that scans were made of his spine and that a catheter had been used in his spinal cord — features that I and my colleagues might not have recognized as predictors of dying (an M.R.I. of the spinal cord, I later realized, was most likely signaling cancer in the nervous system — a deadly site for metastasis).
It’s hard for me to read about the “dying algorithm” without thinking about my patient S. If a more sophisticated version of such an algorithm had been available, would I have used it in his case? Absolutely. Might that have enabled the end-of-life conversation S. never had with his family? Yes. But I cannot shake some inherent discomfort with the thought that an algorithm might understand patterns of mortality better than most humans. And why, I kept asking myself, would such a program seem so much more acceptable if it had come wrapped in a black-and-white fur box that, rather than emitting probabilistic outputs, curled up next to us with retracted claws?

Siddhartha Mukherjee is the author of “The Emperor of All Maladies: A Biography of Cancer” and, more recently, “The Gene: An Intimate History.”

Regulatory State and Redistributive State

Will Wilkinson is a great writer, and spells out here two critical aspects of government:

The regulatory state is the aspect of government that protects the public against abuses of private players, protects property rights, and creates well-defined “corridors” that streamline the flows of capitalism and make it work best. It always gets a bad rap, and shouldn’t. The rap is due to the difficulty of enforcing regulations on so many aspects of life.

The redistributive state is the aspect of government that deigns to shift income and wealth from certain players in society to other players. The presumption is always one of fairness, whereby society deems it in the interests of all that certain actors, e.g. veterans or seniors, get preferential distributions of some kind.

He goes on to make a great point. These two states are more independent of one another than might at first be apparent. So it is possible to dislike one and like another.

Personally, I like both. I think both are critical to a well-oiled society with capitalism and property rights as central tenants. My beef will always go to issues of efficiency and effectiveness?

On redistribution, efficiency experts can answer this question: can we dispense with the monthly paperwork and simply direct deposit funds? Medicare now works this way, and the efficiency gains are remarkable.

And on regulation, efficiency experts can answer this question: can private actors certify their compliance with regulation, and then the public actors simple audit from time to time? Many government programs work this way, to the benefit of all.

ON redistribution, effectiveness experts can answer this question: Is the homeless population minimal? Are veterans getting what they need? Are seniors satisfied with how government treats them?

On regulation, effectiveness experts can answer this question: Is the air clean? Is the water clean? Is the mortgage market making food loans that help people buy houses? Are complaints about fraudulent consumer practices low?

CREDIT: VOX Article on Economic Freedom by Will Wilkinson

By Will Wilkinson
Sep 1, 2016

American exceptionalism has been propelled by exceptionally free markets, so it’s tempting to think the United States has a freer economy than Western European countries — particularly those soft-socialist Scandinavian social democracies with punishing tax burdens and lavish, even coddling, welfare states. As late as 2000, the American economy was indeed the freest in the West. But something strange has happened since: Economic freedom in the United States has dropped at an alarming rate.

Meanwhile, a number of big-government welfare states have become at least as robustly capitalist as the United States, and maybe more so. Why? Because big welfare states needed to become better capitalists to afford their socialism. This counterintuitive, even paradoxical dynamic suggests a tantalizing hypothesis: America’s shabby, unpopular safety net is at least partly responsible for capitalism’s flagging fortunes in the Land of the Free. Could it be that Americans aren’t socialist enough to want capitalism to work? It makes more sense than you might think.

America’s falling economic freedom

From 1970 to 2000, the American economy was the freest in the West, lagging behind only Asia’s laissez-faire city-states, Hong Kong and Singapore. The average economic freedom rating of the wealthy developed member countries of the Organization for Economic Cooperation and Development (OECD) has slipped a bit since the turn of the millennium, but not as fast as America’s.
“Nowhere has the reversal of the rising trend in the economic freedom been more evident than in the United States,” write the authors of Fraser Institute’s 2015

Economic Freedom of the World report, noting that “the decline in economic freedom in the United States has been more than three times greater than the average decline found in the OECD.”

The economic freedom of selected countries, 1999 to 2016. Heritage Foundation 2016 Index of Economic Freedom

The Heritage Foundation and the Canadian Fraser Institute each produce an annual index of economic freedom, scoring the world’s countries on four or five main areas, each of which breaks down into a number of subcomponents. The main rubrics include the size of government and tax burdens; protection of property rights and the soundness of the legal system; monetary stability; openness to global trade; and levels of regulation of business, labor, and capital markets. Scores on these areas and subareas are combined to generate an overall economic freedom score.

The rankings reflect right-leaning ideas about what it means for people and economies to be free. Strong labor unions and inequality-reducing redistribution are more likely to hurt than help a country’s score.

So why should you care about some right-wing think tank’s ideologically loaded measure of economic freedom? Because it matters. More economic freedom, so measured, predicts higher rates of economic growth, and higher levels of wealth predict happier, healthier, longer lives. Higher levels of economic freedom are also linked with greater political liberty and civil rights, as well as higher scores on the left-leaning Social Progress Index, which is based on indicators of social justice and human well-being, from nutrition and medical care to tolerance and inclusion.

The authors of the Fraser report estimate that the drop in American economic freedom “could cut the US historic growth rate of 3 percent by half.” The difference between a 1.5 percent and 3 percent growth rate is roughly the difference between the output of the economy tripling rather than octupling in a lifetime. That’s a huge deal.
Over the same period, the economic freedom scores of Canada and Denmark have improved a lot. According to conservative and libertarian definitions of economic freedom, Canadians, who enjoy a socialized health care system, now have more economic freedom than Americans, and Danes, who have one of the world’s most generous welfare states, have just as much.
What the hell’s going on?

The redistributive state and the regulatory state are separable

To make headway on this question, it is crucial to clearly distinguish two conceptually and empirically separable aspects of “big government” — the regulatory state and the redistributive state.

The redistributive state moves money around through taxes and transfer programs. The regulatory state places all sorts of restrictions and requirements on economic life — some necessary, some not. Most Democrats and Republicans assume that lots of regulation and lots of redistribution go hand in hand, so it’s easy to miss that you can have one without the other, and that the relationship between the two is uneasy at best. But you can’t really understand the politics behind America’s declining economic freedom if you fail to distinguish between the regulatory and fiscal aspects of the economic policy.

Standard “supply-side” Republican economic policy thinking says that cuts in tax rates and government spending will unleash latent productive potential in the economy, boosting rates of growth. And indeed, when taxes and government spending are very high, cuts produce gains by returning resources to the private sector. But it’s important to see that questions about government control versus private sector control of economic resources are categorically different from questions about the freedom of markets.

Free markets require the presence of good regulation, which define and protect property rights and facilitate market processes through the consistent application of clear law, and an absence of bad regulation, which interferes with productive economic activity. A government can tax and spend very little — yet still stomp all over markets. Conversely, a government can withdraw lots of money from the economy through taxes, but still totally nail the optimal balance of good and bad regulation.

Whether a country’s market economy is free — open, competitive, and relatively unmolested by government — is more a question of regulation than a question of taxation and redistribution. It’s not primarily about how “big” its government is. Republicans generally do support a less meddlesome regulatory approach, but when they’re in power they tend to be much more persistent about cutting taxes and social welfare spending than they are about reducing economically harmful regulatory frictions.

If you’re as worried about America’s declining economic freedom as I am, this is a serious problem. In recent years, the effect of cutting taxes and spending has been to distribute income upward and leave the least well-off more vulnerable to bad luck, globalization, “disruptive innovation,” and the vagaries of business cycles.
If spending cuts came out of the military’s titanic budget, that would help. But that’s rarely what happens. The least connected constituencies, not the most expensive ones, are the first to get dinged by budget hawks. And further tax cuts are unlikely to boost growth. Lower taxes make government seem cheaper than it really is, which leads voters to ask for more, not less, government spending, driving up the deficit. Increasing the portion of GDP devoted to paying interest on government debt isn’t a growth-enhancing way to return resources to the private sector.

Meanwhile, wages have been flat or declining for millions of Americans for decades. People increasingly believe the economy is “rigged” in favor of the rich. As a sense of economic insecurity mounts, people anxiously cast about for answers.

Easing the grip of the regulatory state is a good answer. But in the United States, its close association with “free market” supply-side efforts to produce growth by slashing the redistributive state has made it an unattractive answer, even with Republican voters. That’s at least part of the reason the GOP wound up nominating a candidate who, in addition to promising not to cut entitlement spending, openly favors protectionist trade policy, giant infrastructure projects, and huge subsidies to domestic manufacturing and energy production. Donald Trump’s economic policy is the worst of all possible worlds.

This is doubly ironic, and doubly depressing, once you recognize that the sort of big redistributive state supply-siders fight is not necessarily the enemy of economic freedom. On the contrary, high levels of social welfare spending can actually drive political demand for growth-promoting reform of the regulatory state. That’s the lesson of Canada and Denmark’s march up those free economy rankings.

The welfare state isn’t a free lunch, but it is a cheap date

Economic theory tells you that big government ought to hurt economic growth. High levels of taxation reduce the incentive to work, and redistribution is a “leaky bucket”: Moving money around always ends up wasting some of it. Moreover, a dollar spent in the private sector generally has a more beneficial effect on the economy than a dollar spent by the government. Add it all up, and big governments that tax heavily and spend freely on social transfers ought to hurt economic growth.

That matters from a moral perspective — a lot. Other things equal, people are better off on just about every measure of well-being when they’re wealthier. Relative economic equality is nice, but it’s not so nice when relatively equal shares mean smaller shares for everyone. Just as small differences in the rate at which you put money into a savings account can lead to vast differences in your account balance 40 years down the road, thanks to the compounding nature of interest, a small reduction in the rate of economic growth can leave a society’s least well-off people much poorer in absolute terms than they might have been.

Here’s the puzzle. As a general rule, when nations grow wealthier, the public demands more and better government services, increasing government spending as a percentage of GDP. (This is known as “Wagner’s law.”) According to standard growth theory, ongoing increase in the size of government ought to exert downward pressure on rates of growth. But we don’t see the expected effect in the data. Long-term national growth trends are amazingly stable.

And when we look at the family of advanced, liberal democratic countries, countries that spend a smaller portion of national income on social transfer programs gain very little in terms of growth relative to countries that spend much more lavishly on social programs. Peter Lindert, an economist at the University of California Davis, calls this the “free lunch paradox.”

Lindert’s label for the puzzle is somewhat misleading, because big expensive welfare states are, obviously, expensive. And they do come at the expense of some growth. Standard economic theory isn’t completely wrong. It’s just that democracies that have embraced generous social spending have found ways to afford it by minimizing and offsetting its anti-growth effects.

If you’re careful with the numbers, you do in fact find a small negative effect of social welfare spending on growth. Still, according to economic theory, lunch ought to be really expensive. And it’s not.

There are three main reasons big welfare states don’t hurt growth as much as you might think. First, as Lindert has emphasized, they tend to have efficient consumption-based tax systems that minimize market distortions.
When you tax something, people tend to avoid it. If you tax income, as the United States does, people work a little less, which means that certain economic gains never materialize, leaving everyone a little poorer. Taxing consumption, as many of our European peers do, is less likely to discourage productive moneymaking, though it does discourage spending. But that’s not so bad. Less consumption means more savings, and savings puts the capital in capitalism, financing the economic activity that creates growth.

There are other advantages, too. Consumption taxes are usually structured as national sales taxes (or VATs, value-added taxes), which are paid in small amounts on a continuous basis, are extremely cheap to collect (and hard to avoid), while being less in-your-face than income taxes, which further mitigates the counterproductively demoralizing aspect of taxation.

Big welfare states are also more likely to tax addictive stuff, which people tend to buy whatever the price, as well as unhealthy and polluting stuff. That harnesses otherwise fiscally self-defeating tax-avoiding behavior to minimize the costs of health care and environmental damage.
Second, some transfer programs have relatively direct pro-growth effects. Workers are most productive in jobs well-matched to their training and experience, for example, and unemployment benefits offer displaced workers time to find a good, productivity-promoting fit. There’s also some evidence that health care benefits that aren’t linked to employment can promote economic risk-taking and entrepreneurship.

Fans of open-handed redistributive programs tend to oversell this kind of upside for growth, but there really is some. Moreover, it makes sense that the countries most devoted to these programs would fine-tune them over time to amplify their positive-sum aspects.

This is why you can’t assume all government spending affects growth in the same way. The composition of spending — as well as cuts to spending — matters. Cuts to efficiency-enhancing spending can hurt growth as much as they help. And they can really hurt if they increase economic anxiety and generate demand for Trump-like economic policy.

Third, there are lots of regulatory state policies that hurt growth by, say, impeding healthy competition or closing off foreign trade, and if you like high levels of redistribution better than you like those policies, you’ll eventually consider getting rid of some of them. If you do get rid of them, your economic freedom score from the Heritage Foundation and the Fraser Institute goes up.
This sort of compensatory economic liberalization is how big welfare states can indirectly promote growth, and more or less explains why countries like Canada, Denmark, and Sweden have become more robustly capitalist over the past several decades. They needed to be better capitalists to afford their socialism. And it works pretty well.

If you bundle together fiscal efficiency, some offsetting pro-growth effects, and compensatory liberalization, you can wind up with a very big government, with very high levels of social welfare spending and very little negative consequences for growth. Call it “big-government laissez-faire.”

The missing political will for genuine pro-growth reform

Enthusiasts for small government have a ready reply. Fine, they’ll say. Big government can work through policies that offset its drag on growth. But why not a less intrusive regulatory state and a smaller redistributive state: small-government laissez-faire. After all, this is the formula in Hong Kong and Singapore, which rank No. 1 and No. 2 in economic freedom. Clearly that’s our best bet for prosperity-promoting economic freedom.

But this argument ignores two things. First, Hong Kong and Singapore are authoritarian technocracies, not liberal democracies, which suggests (though doesn’t prove) that their special recipe requires nondemocratic government to work. When you bring democracy into the picture, the most important political lesson of the Canadian and Danish rise in economic freedom becomes clear: When democratically popular welfare programs become politically nonnegotiable fixed points, they can come to exert intense pressure on fiscal and economic policy to make them sustainable.

Political demand for economic liberalization has to come from somewhere. But there’s generally very little organic, popular democratic appetite for capitalist creative destruction. Constant “disruption” is scary, the way markets generate wealth and well-being is hard to comprehend, and many of us find competitive profit-seeking intuitively objectionable.

It’s not that Danes and Swedes and Canadians ever loved their “neoliberal” market reforms. They fought bitterly about them and have rolled some of them back. But when their big-government welfare states were creaking under their own weight, enough of the public was willing, thanks to the sense of economic security provided by the welfare state, to listen to experts who warned that the redistributive state would become unsustainable without the downsizing of the regulatory state.

A sound and generous system of social insurance offers a certain peace of mind that makes the very real risks of increased economic dynamism seem tolerable to the democratic public, opening up the political possibility of stabilizing a big-government welfare state with growth-promoting economic liberalization.

This sense of baseline economic security is precisely what many millions of Americans lack.

Learning the lesson of Donald Trump
America’s declining economic freedom is a profoundly serious problem. It’s already putting the brakes on dynamism and growth, leaving millions of Americans with a bitter sense of panic about their prospects. They demand answers. But ordinary voters aren’t policy wonks. When gripped by economic anxiety, they turn to demagogues who promise measures that make intuitive economic sense, but which actually make economic problems worse.

We may dodge a Trump presidency this time, but if we fail to fix the feedback loop between declining economic freedom and an increasingly acute sense of economic anxiety, we risk plunging the world’s biggest economy and the linchpin of global stability into a political and economic death spiral. It’s a ridiculous understatement to say that it’s important that this doesn’t happen.

Market-loving Republicans and libertarians need to stare hard at a framed picture of Donald Trump and reflect on the idea that a stale economic agenda focused on cutting taxes and slashing government spending is unlikely to deliver further gains. It is instead likely to continue to backfire by exacerbating economic anxiety and the public’s sense that the system is rigged.

If you gaze at the Donald long enough, his fascist lips will whisper “thank you,” and explain that the close but confusing identification of supply-side fiscal orthodoxy with “free market” economic policy helps authoritarian populists like him — but it hurts the political prospects of regulatory state reforms that would actually make American markets freer.

Will Wilkinson is the vice president for policy at the Niskanen Center.

Neo.Life

This beta site NeoLife link beyond the splash pagee is tracking the “neobiological revolution”. I wholeheartedly agree that some of our best and brightest are on the case. Here they are:

ABOUT
NEO.LIFE
Making Sense of the Neobiological Revolution
NOTE FROM THE EDITOR
Mapping the brain, sequencing the genome, decoding the microbiome, extending life, curing diseases, editing mutations. We live in a time of awe and possibility — and also enormous responsibility. Are you prepared?

EDITORS

FOUNDER

Jane Metcalfe
Founder of Neo.life. Entrepreneur in media (Wired) and food (TCHO). Lover of mountains, horses, roses, and kimchee, though not necessarily in that order.
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EDITOR
Brian Bergstein
Story seeker and story teller. Editor at NEO.LIFE. Former executive editor of MIT Technology Review; former technology & media editor at The Associated Press
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ART DIRECTOR
Nicholas Vokey
Los Angeles-based graphic designer and animator.
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CONSULTANT
Saul Carlin
founder @subcasthq. used to work here.

EDITOR
Rachel Lehmann-Haupt
Editor, www.theartandscienceoffamily.com & NEO.LIFE, author of In Her Own Sweet Time: Egg Freezing and the New Frontiers of Family

Laura Cochrane
“To oppose something is to maintain it.” — Ursula K. Le Guin

WRITERS

Amanda Schaffer
writes for the New Yorker and Neo.life, and is a former medical columnist for Slate. @abschaffer

Mallory Pickett
freelance journalist in Los Angeles

Karen Weintraub
Health/Science journalist passionate about human health, cool researcher and telling stories.

Anna Nowogrodzki
Science and tech journalist. Writing in Nature, National Geographic, Smithsonian, mental_floss, & others.
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Juan Enriquez
Best-selling author, Managing Director of Excel Venture Management.

Christina Farr
Tech and features writer. @Stanford grad.

NEO.LIFE
Making sense of the Neobiological Revolution. Get the email at www.neo.life.

Maria Finn
I’m an author and tell stories across multiple mediums including prose, food, gardens, technology & narrative mapping. www.mariafinn.com Instagram maria_finn1.

Stephanie Pappas
I write about science, technology and the things people do with them.

David Eagleman
Neuroscientist at Stanford, internationally bestselling author of fiction and non-fiction, creator and presenter of PBS’ The Brain.

Kristen V. Brown
Reporter @Gizmodo covering biotech.

Thomas Goetz

David Ewing Duncan
Life science journalist; bestselling author, 9 books; NY Times, Atlantic, Wired, Daily Beast, NPR, ABC News, more; Curator, Arc Fusion www.davidewingduncan.com

Dorothy Santos
writer, editor, curator, and educator based in the San Francisco Bay Area about.me/dorothysantos.com

Dr. Sophie Zaaijer
CEO of PlayDNA, Postdoctoral fellow at the New York Genome Center, Runway postdoc at Cornell Tech.

Andrew Rosenblum
I’m a freelance tech writer based in Oakland, CA. You can find my work at Neo.Life, the MIT Technology Review, Popular Science, and many other places.

Zoe Cormier

Diana Crow
Fledgling science journalist here, hoping to foster discussion about the ways science acts as a catalyst for social change #biology

Ashton Applewhite
Calling for a radical aging movement. Anti-ageism blog+talk+book

Grace Rubenstein
Journalist, editor, media producer. Social/bio science geek. Tweets on health science, journalism, immigration. Spanish speaker & dancing fool.

Science and other sundries.

Esther Dyson
Internet court jEsther — I occupy Esther Dyson. Founder @HICCup_co https://t.co/5dWfUSratQ http://t.co/a1Gmo3FTQv

Jessica Leber
Freelance science and technology journalist and editor, formerly on staff at Fast Company, Vocativ, MIT Technology Review, and ClimateWire.

Jessica Carew Kraft
An anthropologist, artist, and naturalist writing about health, education, and rewilding. Mother to two girls in San Francisco.

Corby Kummer
Senior editor, The Atlantic, five-time James Beard Journalism Award winner, restaurant reviewer for New York, Boston, and Atlanta magazines

K McGowan
Journalist. Reporting on health, medicine, science, other excellent things. T: @mcgowankat

Rob Waters
I’m a journalist living in Berkeley. I write about health, science, social justice and policy. Father of 1. From Detroit.
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Yiting Sun
writes for MIT Technology Review and Neo.life from Beijing, and was based in Accra, Ghana, in 2014 and 2015.
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Michael Hawley
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Richard Sprague
Curious amateur. Years of near-daily microbiome experiments. US CEO of AI healthcare startup http://airdoc.com
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Bob Parks ✂
Connoisseur of the slap dash . . . maker . . . runner . . . writer of Outside magazine’s Gear Guy blog . . . freelance writer and reporter.

CREDIT: https://medium.com/neodotlife/review-of-daytwo-microbiome-test-deacd5464cd5

Microbiome Apps Personalize EAT recommendations

Richard Sprague provides a useful update about the microbiome landscape below. Microbiome is exploding. Your gut can be measured, and your gut can influence your health and well-being. But now …. these gut measurements can offer people a first: personalized nutrition information.

Among the more relevant points:

– Israel’s Weitzman Institute is the global leader academically. Eran Elinav, a physician and immunologist at the Weizmann Institute and one of their lead investigators (see prior post).
– The older technology for measuring the gut is called “16S” sequencing. It tell you at a high level which kinds of microbes are present. It’s cheap and easy, but 16S can see only broad categories,
– The companies competing to measure your microbiome are uBiome, American Gut, Thryve, DayTwo and Viome. DayTwo and Viome offer more advanced technology (see below).
– The latest technology seems to be “metagenomic sequencing”. It is better because it is more specific and detailed.
– By combining “metagenomic sequencing” information with extensive research about how certain species interact with particular foods, machine-learning algorithms can recommend what you should eat.
– DayTwo offers a metagenomic sequencing for $299, and then combines that with all available research to offer personalized nutrition information.
– DayTwo recently completed a $12 million financing round from, among others, Mayo Clinic, which announced it would be validating the research in the U.S.
– DayTwo draws its academic understandings from Israel’s Weitzman Institute. The app is based on more than five years of highly cited research showing, for example, that while people on average respond similarly to white bread versus whole grain sourdough bread, the differences between individuals can be huge: what’s good for one specific person may be bad for another.

CREDIT: Article on Microbiome Advances

When a Double-Chocolate Brownie is Better for You Than Quinoa

A $299 microbiome test from DayTwo turns up some counterintuitive dietary advice.

Why do certain diets work well for some people but not others? Although several genetic tests try to answer that question and might help you craft ideal nutrition plans, your DNA reveals only part of the picture. A new generation of tests from DayTwo and Viome offer diet advice based on a more complete view: they look at your microbiome, the invisible world of bacteria that help you metabolize food, and, unlike your DNA, change constantly throughout your life.
These bugs are involved in the synthesis of vitamins and other compounds in food, and they even play a role in the digestion of gluten. Artificial sweeteners may not contain calories, but they do modify the bacteria in your gut, which may explain why some people continue to gain weight on diet soda. Everyone’s microbiome is different.

So how well do these new tests work?
Basic microbiome tests, long available from uBiome, American Gut, Thryve, and others, based on older “16S” sequencing, can tell you at a high level which kinds of microbes are present. It’s cheap and easy, but 16S can see only broad categories, the bacterial equivalent of, say, canines versus felines. But just as your life might depend on knowing the difference between a wolf and a Chihuahua, your body’s reaction to food often depends on distinctions that can be known only at the species level. The difference between a “good” microbe and a pathogen can be a single DNA base pair.

New tests use more precise “metagenomic” sequencing that can make those distinctions. And by combining that information with extensive research about how those species interact with particular foods, machine-learning algorithms can recommend what you should eat. (Disclosure: I am a former “citizen scientist in residence” at uBiome. But I have no current relationship with any of these companies; I’m just an enthusiast about the microbiome.)

I recently tested myself with DayTwo ($299) to see what it would recommend for me, and I was pleased that the advice was not always the standard “eat more vegetables” that you’ll get from other products claiming to help you eat healthily. DayTwo’s advice is much more specific and often refreshingly counterintuitive. It’s based on more than five years of highly cited research at Israel’s Weizmann Institute, showing, for example, that while people on average respond similarly to white bread versus whole grain sourdough bread, the differences between individuals can be huge: what’s good for one specific person may be bad for another.

In my case, whole grain breads all rate C-. French toast with challah bread: A.

The DayTwo test was pretty straightforward: you collect what comes out of your, ahem, gut, which involves mailing a sample from your time on the toilet. Unlike the other tests, which can analyze the DNA found in just a tiny swab from a stain on a piece of toilet paper, DayTwo requires more like a tablespoon. The extra amount is needed for DayTwo’s more comprehensive metagenomics sequencing.

Since you can get a microbiome test from other companies for under $100, does the additional metagenomic information from DayTwo justify its much higher price? Generally, I found the answer is yes.

About two months after I sent my sample, my iPhone lit up with my results in a handy app that gave me a personalized rating for most common foods, graded from A+ to C-. In my case, whole grain breads all rate C-. Slightly better are pasta and oatmeal, each ranked C+. Even “healthy” quinoa — a favorite of gluten-free diets — was a mere B-. Why? DayTwo’s algorithm can’t say precisely, but among the hundreds of thousands of gut microbe and meal combinations it was trained on, it finds that my microbiome doesn’t work well with these grains. They make my blood sugar rise too high.

So what kinds of bread are good for me? How about a butter croissant (B+) or cheese ravioli (A-)? The ultimate bread winner for me: French toast with challah bread (A). These recommendations are very different from the one-size-fits-all advice from the U.S. Department of Agriculture or the American Diabetes Association.

I was also pleased to learn that a Starbucks double chocolate brownie is an A- for me, while a 100-calorie pack of Snyder’s of Hanover pretzels gets a C-. That might go against general diet advice, but an algorithm determined that the thousands of bacterial species inside me tend to metabolize fatty foods in a way that results in healthier blood sugar levels than what I get from high-carb foods. Of course, that’s advice just for me; your mileage may vary.

Although the research behind DayTwo has been well-reviewed for more than five years, the app is new to the U.S., so the built-in food suggestions often seem skewed toward Middle Eastern eaters, perhaps the Israeli subjects who formed the original research cohort. That might explain why the app’s suggestions for me include lamb souvlaki with yogurt garlic dip for dinner (A+) and lamb kabob and a side of lentils (A) for lunch. They sound delicious, but to many American ears they might not have the ring of “pork ribs” or “ribeye steak,” which have the same A+ rating. Incidentally, DayTwo recently completed a $12 million financing round from, among others, Mayo Clinic, which announced it would be validating the research in the U.S., so I expect the menu to expand with more familiar fare.

Fortunately you’re not limited to the built-in menu choices. The app includes a “build a meal” function that lets you enter combinations of foods from a large database that includes packaged items from Trader Joe’s and Whole Foods.

There is much more to the product, such as a graphical rendering of where my microbiome fits on the spectrum of the rest of the population that eats a particular food. Since the microbiome changes constantly, this will help me see what is different when I do a retest and when I try Viome and other tests.

I’ve had my DayTwo results for only a few weeks, so it’s too soon to know what happens if I take the app’s advice over the long term. Thankfully I’m in good health and reasonably fit, but for now I’ll be eating more strawberries (A+) and blackberries (A-), and fewer apples (B-) and bananas (C+). And overall I’m looking forward to a future where each of us will insist on personalized nutritional information. We all have unique microbiomes, and an app like DayTwo lets us finally eat that way too.

Richard Sprague is a technology executive and quantified-self enthusiast who has worked at Apple, Microsoft, and other tech companies. He is now the U.S. CEO of an AI healthcare startup, Airdoc.

====================APPENDIX: Older Posts about the microbiome =========

Microbiome Update
CREDIT: https://www.wsj.com/articles/how-disrupting-your-guts-rhythm-affects-your-health-1488164400?mod=e2tw A healthy community of microbes in the gut maintains regular daily cycles of activities. A healthy community of microbes in the gut maintains regular daily cycles of activities.PHOTO: WEIZMANN INSTITUTE By LARRY M. GREENBERG Updated Feb. 27, 2017 3:33 p.m. ET 4 COMMENTS New research is helping to unravel the mystery of how […]

Vibrant Health measures microbiome

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Microbiome Update
My last research on this subject was in August, 2014. I looked at both microbiomes and proteomics. Today, the New York Times published a very comprehensive update on microbiome research: Link to New York Time Microbiome Article Here is the article itself: = = = = = = = ARTICLE BEGINS HERE = = = […]

Microbiomes
Science is advancing on microbiomes in the gut. The key to food is fiber, and the key to best fiber is long fibers, like cellulose, uncooked or slightly sauteed (cooking shortens fiber length). The best vegetable, in the view of Jeff Leach, is a leek. Eating Well Article on Microbiome = = = = = […]

Arivale Launches LABS company
“Arivale” Launched and Moving Fast. They launched last month. They have 19 people in the Company and a 107 person pilot – but their plans are way more ambitious than that. Moreover: “The founders said they couldn’t envision Arivale launching even two or three years ago.” Read on …. This is an important development: the […]

Precision Wellness at Mt Sinai
My Sinai announcement Mount Sinai to Establish Precision Wellness Center to Advance Personalized Healthcare Mount Sinai Health System Launches Telehealth Initiatives Joshua Harris, co-Founder of Apollo Global Management, and his wife, Marjorie has made a $5 million gift to the Icahn School of Medicine at Mount Sinai to establish the Harris Center for Precision Wellness. […]

Proteomics
“Systems biology…is about putting together rather than taking apart, integration rather than reduction. It requires that we develop ways of thinking about integration that are as rigorous as our reductionist programmes, but different….It means changing our philosophy, in the full sense of the term” (Denis Noble).[5] Proteomics From Wikipedia, the free encyclopedia For the journal […]

Marketing Automation Software

Pardot believes they are perfecting lead generation through supplemental technologies.

See Pardot Website

Salesforce.com believes in the idea enough to buy them.

At a high level, this is about accepting that most leads are not “hot”, Pardot offers a way to nurture all warm leads and monitor whether they are moving toward cold or hot. If hot, the Pardot nurtures tha relationship in a way most relevant to the lead. They call this Smarter lead generation and effortless email marketing.

My friend Andrew M is a Salesforce expert and swears by them.

World’s biggest battery installation

JAMESTOWN, Australia—Tesla Inc. Chief Executive Elon Musk may have overpromised on production of the company’s latest electric car, but he is delivering on his audacious Australian battery bet.

An enormous Tesla-built battery system—storing electricity from a new wind farm and capable of supplying 30,000 homes for more than an hour—will be powered up over the coming days, the government of South Australia state said Thursday. Final tests are set to be followed by a street party that Mr. Musk, founder of both Tesla and rocket maker Space Exploration Technologies Corp., or SpaceX, was expected to attend.

Success would fulfill the risky pledge Mr. Musk made in March, to deliver a working system in “100 days from contract signature or it is free.” He was answering a Twitter challenge from Australian IT billionaire and environmentalist Mike Cannon-Brookes to help fix electricity problems in South Australia—which relies heavily on renewable energy—after crippling summer blackouts left 1.7 million people without power, some for weeks.

Mr. Cannon-Brookes then brokered talks between Mr. Musk and Australian Prime Minister Malcolm Turnbull, who has faced criticism from climate groups for winding back renewable-energy policies in favor of coal. South Australia notwithstanding, the country’s per-person greenhouse emissions are among the world’s highest.

South Australia’s government has yet to say how much the battery will cost taxpayers, although renewable-energy experts estimate it at US$50 million. Tesla says the system’s 100-megawatt capacity makes it the world’s largest, tripling the previous record array at Mira Loma in Ontario, Calif., also built by Tesla and U.S. power company Edison.

On-Demand Work

The New York Times article below refers to a mega-trend: on-demand work. The author refers to it as a “tectonic shift in how jobs are structured“.

The focus of the article is Liveops, but this is only illustrative of this larger trend. https://www.liveops.com. Their competitor is https://workingsolutions.com .

On their front page, LiveOps says: “It’s a highly skilled workforce of virtual agents who flex to meet customer needs.”

On-demand work is exploding in customer service call centers and sales.

Some points I found interesting:

Roughly 3,000,000 Americans find work this way – as independent contractors working on a virtual basis.

Since 2001, apparently the move to outsource call centers to India has reversed. Today, the focus is on quality, and so the new trend is toward employing American workers, on a contract basis, and on a virtual basis.

They are only paid while on the phone. This is roughly 75% of the time they “commit” (“commits” are made in half hour blocks)

Top performers get the first call. “Performance-Based Routing, so the top-performing agents on your programs get more calls. By aligning our agents’ incentives with your goals, each agent who answers the call will be invested in your business objectives. What’s more, you won’t be paying call centers for idle time.”

Clients hire LiveOp. In this article, TruStage Insurance is the client.

Liveops CEO is Greg Hanover. Their competitor, Working Solutions, was founded in 1996. LiveOps says they have 20,000 agents, which they refer to as “Liveops Nation”.

“We hand-pick our agents for their great phone voices and warm and friendly personalities.”

“Scalable and flexible contract center outsourcing – leveraging an on-demand distributed network.”

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CREDIT: https://www.nytimes.com/2017/11/11/business/economy/call-center-gig-workers.html?smid=nytcore-ipad-share&smprod=nytcore-ipad
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Plugging Into the Gig Economy, From Home With a Headset

A company called Liveops has become the
Uber of call centers by doting on its agents.
But is the work liberating, or dehumanizing?
By NOAM SCHEIBERNOV. 11, 2017

DURHAM, N.C. — The gathering in a private dining room at a Mexican restaurant had the fervent energy of a megachurch service, or maybe an above-average “Oprah” episode — a mix of revival-style confession and extravagant empathy. There were souls to be won.

“By the end of the day, Kelly’s going to be an agent,” the group’s square-jawed leader said. “Kelly went through the process a while ago, then life happens, now she’s back. Her commitment to me that she made earlier, she looked me right in the eyes and told me she’s going to be an agent.”
Paradise, for these pilgrims, lies at one end of a phone line.

The company behind this spectacle, Liveops, had invited several dozen freelance call-center agents to a so-called road show. Some of them may have answered your customer-service calls to Home Depot or AAA. All were among the more than 100,000 agents who work as independent contractors through on-demand platforms like the one Liveops operates, which uses big data, algorithms and gamelike techniques to match its agents to clients. What Uber is to cars, Liveops is to call centers.

The agents are part of a tectonic shift in how jobs are structured. More companies are pushing work onto freelancers, temps, contractors and franchisees in the quest for an ever more nimble profit-making machine. It is one reason a job category seemingly headed offshore forever — customer service representatives — has been thriving in call centers and home offices across the United States, supporting roughly three million workers.

While critics of the arrangement cite rising insecurity, some of Liveops’ star agents — like Emmett Jones in Chicago, who knows of his rivals primarily as numbers on a leader board — say the opportunity has been transformative.

The earnest gratitude of the agents assembled here, not far from the Raleigh-Durham Airport, affirmed that. To them, Liveops is a sustaining force, a way to earn a living while being present at home. A few had driven hours to attend. Many brought friends and family members who were considering joining “Liveops Nation,” too.

There were icebreakers (“Liveops Nation Bingo”). Gift-card raffles (“$150?” the chief executive quipped. “Who approved these things?”). Free enchiladas. Everyone was invited to schmooze.
“John, I heard your story about how you got to us is pretty great,” said the master of ceremonies, an impossibly sunny woman named Tara. “Would you mind telling all these people?”
When the mic came to John, a former insurance claims adjuster with a gray beard and several earrings, there was a sense of imminent revelation.

“I was working in another glass box over near here for six years,” he began. “I reached the point where it was either jump off the roof or walk out the front door.” The other agents laughed knowingly.

He continued: “My commute now is I walk down the hall, close the bedroom door behind me.” More laughter.
Then John’s voice softened: “This is good, this is good. I get paid for when I’m working, instead of souring when you get paid for 40 hours and work some more. So, I’m here.”
“Awesome,” Tara said, applause drowning her out. “I feel like John’s story mimics a lot of what we hear from people.”
According to Greg Hanover, a longtime Liveops official who became chief executive this summer, the company’s goal is to make agents feel as if they’re part of a movement, not just earning a wage.

“Where we want to be with this is what Mary Kay has done, multilevel marketing companies,” Mr. Hanover said, referring to the cosmetics distributor and its independent sales force. “The direction we need to head in for the community within Liveops Nation is that the agents are so happy, so satisfied with the purpose and meaning there, that they’re telling their story.”

It’s an ambition that feels almost radical compared with Uber, whose best-known exercise in worker outreach is a video of its former chief executive berating a driver. It was heartening to discover that on-demand work could be both financially viable and emotionally fulfilling.

That is, until I began to speak with Mr. Jones and some of his Liveops competitors. The more you talk with them, the more you detect a kind of Darwinian struggle behind the facade of community and self-actualization. You start to wonder: Is there really such a thing as a righteous gig-economy job, even if the company is as apparently well intentioned as Liveops? Or is there something about the nature of gig work that’s inescapably dehumanizing?

Just the Right Tone
Mr. Jones, who lives in Chicago, was the top rated Liveops agent for an insurer called TruStage for much of this year.
An AT&T technician for decades, he decided that he needed to be at home not long after his wife was diagnosed with vertigo in 2008. “I can’t work and be worried about how she’s doing,” he said.

A few years later, when his daughter told him of a friend who worked with Liveops, he was eager to sign up — but refused to send in his required voice test until it was close to perfect. “I must have did the voice test four or five times,” he said. “I wanted to make sure I gave the right tone that they were looking for.”

As a Liveops agent, Mr. Jones sells life policies to callers, often those who have just seen a television commercial for TruStage insurance. He estimates that he works roughly 40 hours each week, beginning around 8 most mornings, and that he makes about $20 an hour. He is such a valued worker that TruStage invited him to its headquarters earlier this year for a two-day visit by an elite group of agents, in which executives pumped them for insights about how to increase sales.

Roughly two decades ago, Liveops and its competitors typically connected callers to psychic hotlines, and in some cases less reputable services. Such businesses had frequent spikes in call volume, making it helpful to have an on-demand work force that could be abruptly ramped up.

“The only thing people were interested in was the abandonment rate” — that is, the number of people who would hang up in frustration from being kept on hold — said Kim Houlne, the chief executive of a Liveops rival called Working Solutions, which she founded in 1996.

The call center industry took a hit during the 2001 recession, when cost consciousness unleashed a wave of outsourcing to India. But within 10 years, many companies decided that the practice, known as offshoring, had been oversold. The savings on wages were often wiped out by lost business from enraged customers, who preferred to communicate with native English speakers.
“People don’t feel comfortable,” Ms. Houlne said, alluding to the overseas agents.

By the early part of this decade, quality was in fashion. The enormous amounts of data that companies like Liveops and Working Solutions collect allowed them to connect callers to the best possible agent with remarkable precision, while allowing big clients to avoid the overhead of a physical call center and full-time workers.

Today, in addition to sales calls, Liveops agents handle calls from people trying to file insurance claims, those in need of roadside assistance, even those with medical or financial issues relating to prescription drugs. The agents must obtain a certification before they can handle such calls, which sometimes takes weeks of online coursework.

Liveops goes to great lengths to attend to their needs, addressing technical-support issues, even answering agents’ emails to the chief executive within 24 hours.

Mr. Jones, like many of his fellow agents, thinks of himself as helping others in need. He said that many families will gather around a table after a loved one has died to discuss the burial. If the deceased relative had no insurance, he said, “A lot of times that table is going to clear.” If, on the other hand, he had even $2,000 in life insurance — the minimum that TruStage sells — “the family members are more inclined to say, ‘He did what he could, let me see what I could do to help out.’ You end up with $5,000 to $6,000. You can do a decent burial rather than none at all.”

Still, there is undeniably a brass-tacks quality to the work. Shortly after we hung up, I turned my attention to an assignment due that afternoon, only to receive more calls from Mr. Jones’s number. When I finally answered, he apologized for interrupting me, then came to the point. “I have a question for you,” he said. “Do you have life insurance?”

‘Where the Price Point Is’
Like Uber, Liveops expends considerable effort calculating demand for its agents. For example, if an auto insurance company is running a commercial on ESPN, Liveops will ask the company’s media buyer — that is, the intermediary that placed the ad — to predict how many calls such an ad is likely to generate. Liveops will adjust that prediction, using its own data showing how many calls similar ads have produced from similar audiences during a comparable time of year.

And like Uber, the Liveops focuses on “utilization” — in the Liveops case, the percentage of working agents actually on a call. Depending on the client, Liveops strives for rates of 65 percent to 75 percent. Lower than that and the agents, who make money only when they’re on a call, will complain that they’re not busy enough. Significantly higher and the system is vulnerable to a sudden increase in demand that could tie up the phone lines and keep callers waiting.

Liveops asks agents to schedule themselves in half-hour blocks, known as “commits,” for the upcoming week. If the company expects demand to be higher than the number of commits, it sends agents a message urging them to sign up. (Uber does something similar, except without formal scheduling.) Sometimes it will even offer financial incentives, like a bump in the rate earned for each minute they’re on a call, or a raffle-type scheme in which people accumulate tickets for the giveaway of an iPad or a cruise.

Again like Uber, Liveops relentlessly tests the effectiveness of these tools. Referring to financial incentives, Jon Brown, the Liveops senior director of client services, said, “We’ve zeroed in on exactly what we need for an agent to go from 10 to 15 commits, from 15 commits to 20 commits. We know where the price point is, what drives behavior.”

And then there are the performance metrics. Liveops agents are rated according to what are called key performance indicators, which, depending on the customer, can include the number of sales they make, their success at upselling customers, and whether a caller would recommend the service based on their interaction.

Liveops makes clear that its agents’ ability to earn more money is closely tied to performance. “You’ve heard the term meritocracy?” said a Liveops official named Aimee Matolka at the North Carolina event. “When a call comes in, it routes in to that best agent. Yes, our router is that smart. You guys want to be that agent, I know you do. Otherwise you wouldn’t be here.”

It allows the agents to track their rankings obsessively through internal leader boards. (Liveops officials say that while the pressures of the job can preoccupy agents, it is up to them how much time to invest.)

“I lost the No. 1 spot, now I’m No. 2,” Mr. Jones said in early August, acknowledging that he checks his ranking frequently. “I thought about researching to find out who it is — you always want to know who’s the competition — but I said leave it.”

He added: “I’m a competitive person. We just toggle back and forth. If they see me jump back in, they work harder. They want that spot back.”

‘This Is My Phone Call’
My flight to Bangor, Me., was due after 9 p.m., and apparently sensing my unease with the North Country, the firefighter seated next to me asked if I had to far to drive when we landed. “About three hours north,” I confessed. “Watch out for moose,” he said. I assured him I’d driven around deer before. He stopped me short: If you hit a deer, you’ll kill them, he said. If you hit a moose, they’ll kill you.

I found Troy Carter, the agent who had recently surpassed Emmett Jones, at his home in Fort Fairfield the next day, wearing jeans, a button-down short-sleeve shirt, and a New England Patriots hat. There were no shoes on his feet, only white socks.

Like Mr. Jones, Mr. Carter said Liveops had been a blessing, allowing him to earn a living in a part of Maine so remote that my cellphone carrier welcomed me to Canada shortly after I pulled into his driveway.

When I told Mr. Carter that I had been in touch with his top competitor, he quickly pulled up the latest monthly rankings of Liveops agents selling TruStage insurance. He pointed out that while Mr. Jones, whom he recognized only by his identification number, 141806, had more sales — 87 to his 82 — he had far fewer paid sales, charged at the time of purchase rather than by invoice.

“The real thing is the paid application rate — they want it around 95 percent,” Mr. Carter said. “He has 87 sales, but only 65 percent paid, compared to my 94 percent.” This, he explained, was why he enjoyed the right to call himself the top agent for the month.

Mr. Carter is what you might call a serial entrepreneur. He once started an art supply website that folded within a few months, and a penny auction site called Bid Tree that foundered for lack of a marketing budget.

He sees Liveops, on which he spends 40 to 50 hours per week, as of a piece with these entrepreneurial efforts. In fact, it is something of a family business. His wife, Lori, handles incoming calls while he’s busy with customers. “I’m a housewife/secretary/receptionist,” she said. Even Mr. Carter’s 9-year-old son, Logan, plays a role. “At nighttime, he says the last part of his prayer based on how many sales I did today,” Mr. Carter said. “If it was a lot of sales, he’ll pray, ‘Dear Lord, help my dad get the same amount of sales tomorrow.’”

Though Liveops agents work from a script, Mr. Carter, like Mr. Jones, adds his own flourishes. Before asking a caller’s gender, as he is required to do, he will say, “Now I already know the answer to this question, but please confirm if you’re male or female.” Upon receiving the answer, he will pause momentarily before saying, “I told you I already knew the answer,” and break into a laugh.

He might make this identical joke, with identical timing, dozens of times in a workday. “It’s like a comedian has a little pause before a joke,” he told me. “It relaxes them right off.”

Even with these touches, results can vary widely. Two days earlier, Mr. Carter had made seven sales, only a few shy of his record. The day I turned up, he managed only one. He said some callers had the impression they could receive $25,000 of insurance for $9.95 per month — the commercial mentions both figures — and begged off when Mr. Carter told them that
Mr. Carter has done research on how to comport himself, including watching an instructional YouTube video by the former stockbroker who was the subject of the movie “The Wolf of Wall Street.” He believes the key is to come off as the alpha presence. “The one that asks the most questions is the one in control,” he said. “If they ask me questions — ‘How are you doing?’ — I’ll come back, ‘The question is how are you doing?’ This is my phone call, as much as I can make it.”

But on this day he repeatedly ran up against the limits of his powers. Even those who remained interested after 10 or 15 minutes of painstaking back-and-forth often demurred when Mr. Carter asked them for payment information. “This one guy was outside in a wheelchair,” Mr. Carter said of a caller who couldn’t produce his credit card. “He didn’t want to go in and get it. I said, ‘I’m fine waiting,’ but I can’t push him.”

These setbacks only seem to make Mr. Carter focus more. At one point, he made a swiping motion between his face and his headset with his index finger and middle finger. “They recommend that you keep the microphone two fingers away,” he said. “I’m always doing that — checking that it’s two fingers. I’ll do that for the rest of my life.”

It seemed, all in all, like a grueling way to make the slightly more than $30,000 that Mr. Carter estimates he takes in before taxes. “The good thing is he can take hours off,” Lori told me. “But then he can lose his spot. It’s always a fight for the top.”

I was reminded of the Alec Baldwin monologue from the movie “Glengarry Glen Ross,” except that the prize for having the most sales wouldn’t be a Cadillac, it would be a set of steak knives, because the Liveops analytics team had calculated that agents would give nearly as much effort for a prize worth a small fraction of the cost.

Of course, unlike the salesmen in that movie, the Liveops agents can’t really be fired — the third prize — because they weren’t employees to begin with.

A while later, Mr. Carter described a recent initiative in which agents were promised a bonus if 95 percent of their collective sales were paid up front. “I knew it wasn’t going to work as soon as they said it,” he told me, because a handful of agents with low paid rates could ruin everyone else’s chances.

“They did do a pullover sweatshirt for the top two,” he added, brightening. “I was second, so that’s coming.”

A version of this article appears in print on November 12, 2017, on Page BU1 of the New York edition with the headline: Paradise at the End of a Phone Line. Order Reprints| Today’s Paper|Subscribe

Quantified Water Movement (QWM)

Think FITBITS for water. The Quantified Water Movement (QWM) is here to stay, with devices that make real-time monitoring of water quality in streams, rivers, lakes and oceans for less than $1,000 per device.

The Stroud Water Research Center in Pennsylvania is leading the way, along with other center of excellence around the world. Stroud has been leading the way on water for fifty years. It is an elite water quality study organization, renowned for its globally relevant science and scientist excellence. Find out more at www.stroudcenter.org.

As a part of this global leadership in the study of water quality, Stroud is advancing the applied technologies that comprise the “quantified water movement” – the real-time monitoring of water quality in streams, rivers, lakes and oceans.

QWM is very much like the “quantified self movement”(see Post on QSM. QSM takes full advantage of low cost sensor and communication technology to “quantify my self”. In other words, I can dramatically advance my understanding about my own personal well-being win areas like exercise, sleep, glucose levels in blood, etc This movement already has proven that real-time reporting on metrics is possible at a very low cost, and on a one-person-at-a-time scale. Apple Watch and FITBIT are examples of commercial products arising out of QSM.

In the same way, QWM takes full advantage of sensors and communication technology to provide real-time reporting on water quality for a given stream, lake, river, or ocean. While still in a formative stage. QWM uses the well-known advances in sensor, big data, and data mining technology to monitor water quality on a real-time basis. Best of all, this applied technology has now reached an affordable price point.

For less than $1,000 per device, it is now possible to fully monitor any body of water, and to report out the findings in a comprehensive dataset. Many leaders believe that less than $100 is possible very soon.

The applied technology ends up being a simple “data logger” coupled with a simple radio transmitter.

Examples of easy-to-measure metrics are:

1. water depth
2. conductivity (measures saltiness or salinity)
3. dissolved oxygen (supports fish and beneficial bacteria)
4. turbidity (a sign of runoff from erosion. Cloudy water actually abrades fish, and prevent fish from finding food)

Training now exists, thanks to Stroud, that is super simple. For example, in one hour, you can learn the capability of this low cost equipment, and the science as to why it is important.

In a two day training, citizen scientists and civil engineers alike can learn how to program their own data logger, attach sensors to the data logger, and deploy and maintain the equipment in an aquatic environment.

All of this and more is illuminated at www.enviroDIY.org.

Alzheimer’s Genetic Risk Assessment

CREDIT: NPR article

CREDIT: Bill Gates 11.13.17 Blog Post on Alzheimer’s

FDA Approves Marketing Of Consumer Genetic Tests For Some Conditions

April 7, 20171:40 PM ET
JESSICA BODDY

23andMe is now allowed to market tests that assess genetic risks for 10 health conditions, including Parkinson’s and late-onset Alzheimer’s diseases.
Meredith Rizzo/NPR
The U.S. Food and Drug Administration approved 23andMe’s personal genetic test for some diseases on Thursday, including Alzheimer’s, Parkinson’s and celiac diseases.
The tests assess genetic risk for the conditions but don’t diagnose them, the FDA says. The agency urges consumers to use their results to “help to make decisions about lifestyle choices or to inform discussions with a health care professional,” according to a press release about the decision.
Jeffrey Shuren, the director of the FDA’s Center for Devices and Radiological Health, wrote, “it is important that people understand that genetic risk is just one piece of the bigger puzzle, it does not mean they will or won’t ultimately develop a disease.” Other known factors that can play into the development of disease include diet, environment and tobacco use.

SHOTS – HEALTH NEWS
23andMe Bows To FDA’s Demands, Drops Health Claims
The FDA has previously scolded the company for marketing the personal genetic testing kits without the agency’s consent. In 2013, the agency told 23andMe to stop selling its personal genome kits in the United States until they gained FDA approval by proving they were accurate.
The company agreed to work with the FDA, as we reported, and a recent FDA review of peer-reviewed studies found more consistent links between certain gene variants and 10 diseases, the FDA says.
As a result, the FDA is now allowing 23andMe to market tests that assess genetic risks for the following 10 diseases or conditions:
▪ Parkinson’s disease, a nervous system disorder impacting movement 

▪ Late-onset Alzheimer’s disease, a progressive brain disorder that destroys memory and thinking skills 

▪ Celiac disease, a disorder resulting in the inability to digest gluten 

▪ Alpha-1 antitrypsin deficiency, a disorder that raises the risk of lung and liver disease 

▪ Early-onset primary dystonia, a movement disorder involving involuntary muscle contractions and other uncontrolled movements 

▪ Factor XI deficiency, a blood clotting disorder 

▪ Gaucher disease type 1, an organ and tissue disorder 

▪ Glucose-6-phosphate dehydrogenase deficiency, also known as G6PD, a red blood cell condition 

▪ Hereditary hemochromatosis, an iron overload disorder 

▪ Hereditary thrombophilia, a blood clot disorder 


The company’s $199 Health and Ancestry test is available directly to consumers, without seeing a physician or genetic counselor. Consumers’ DNA is extracted from a saliva sample. After mailing in their sample, people can see their results online.
“This is an important moment for people who want to know their genetic health risks and be more proactive about their health,” said Anne Wojcicki, the CEO and co-founder of 23andMe, in a company press release.
Sharon Terry, the CEO of the Genetic Alliance, a nonprofit organization that advocates for health care for people with genetic disorders, likens it to another consumer test. “Women learn they are pregnant using a test directly marketed to them and buy it off the shelf in a drugstore,” she told NPR. “In 10 years we will marvel that this is an ‘advance’ at all. Imagine pregnancy tests being only available through a doctor!”
Robert Green, a professor of medicine at Harvard Medical School, says people should be able to access genetic information in whatever way is best for them. “Some people really want this [genetic] information on their own, and others want it through their physician,” he said. “Both those channels are legitimate. People should just be aware that this information is complicated.”
But some are still concerned about whether the genes in question actually correspond to a higher risk of disease reliably enough to warrant direct-to-consumer marketing and testing, as opposed to genetic testing with the guidance of a professional.

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Some health professionals worry that consumers will “take the results and run,” as Mary Freivogel put it. Freivogel, a certified genetic counselor and the president of the National Society of Genetic Counselors, added that genetics are just “one piece to the story when it comes to developing a disease.”
Freivogel said speaking with a genetic counselor before getting tested for disease is important. “Direct-to-consumer testing takes away a pre-test conversation,” she said, where counselors can help patients think about questions like: “What do you want to know? What are you going to do with this information? Is it something you’re prepared to know, or is it going to just make you anxious?”
And it isn’t clear what consumers should do with their newly calculated disease risk, especially for conditions like Alzheimer’s for which there isn’t a cure or even a course of action to prevent the disease.
What’s more, having the genes is not the same as having the diseases the genes are associated with. A person may have genes that are associated with Alzheimer’s, for example, but that doesn’t mean he or she will ever get the disease. Conversely, some people develop Alzheimer’s without the identified risk genes.
The Alzheimer’s Association does not recommend routine genetic testing for the disease in the general population because it can’t “productively guide medical treatment.”
A genetic test result for Alzheimer’s is “not going to provide useful information even if you’re at an increased risk,” said Keith Fargo, director of scientific programs at the Alzheimer’s Association. “It’s not like there’s a drug you can take right now [to prevent the disease] or a lifestyle change you can make that you shouldn’t make anyway,” such as exercising and eating right to keep your brain healthy.
John Lehr, the CEO of the Parkinson’s Foundation, says personal genetic tests can help identify risk for Parkinson’s disease. But, he wrote in a statement following the FDA’s announcement, the foundation recommends “that people who are interested in testing first seek guidance from their doctors and from genetic counselors to understand what the process may mean for them and their families.”