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Satchu's Rich Wrap-Up
 
 
Tuesday 28th of January 2020
 
Afternoon,
Africa

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Macro Thoughts

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You Are Now Remotely Controlled @nytimes @shoshanazuboff
Africa


The debate on privacy and law at the Federal Trade Commission was
unusually heated that day. Tech industry executives “argued that they
were capable of regulating themselves and that government intervention
would be costly and counterproductive.”
Civil libertarians warned that the companies’ data capabilities posed
“an unprecedented threat to individual freedom.”
One observed, “We have to decide what human beings are in the
electronic age. Are we just going to be chattel for commerce?” A
commissioner asked, ‘‘Where should we draw the line?” The year was
1997.
The line was never drawn, and the executives got their way.
Twenty-three years later the evidence is in.
The fruit of that victory was a new economic logic that I call
“surveillance capitalism.”
Its success depends upon one-way-mirror operations engineered for our
ignorance and wrapped in a fog of misdirection, euphemism and
mendacity.
It rooted and flourished in the new spaces of the internet, once
celebrated by surveillance capitalists as “the world’s largest
ungoverned space.”
But power fills a void, and those once wild spaces are no longer
ungoverned. Instead, they are owned and operated by private
surveillance capital and governed by its iron laws.
The rise of surveillance capitalism over the last two decades went
largely unchallenged. “Digital” was fast, we were told, and stragglers
would be left behind.
It’s not surprising that so many of us rushed to follow the bustling
White Rabbit down his tunnel into a promised digital Wonderland where,
like Alice, we fell prey to delusion.
In Wonderland, we celebrated the new digital services as free, but now
we see that the surveillance capitalists behind those services regard
us as the free commodity. We thought that we search Google, but now we
understand that Google searches us.
We assumed that we use social media to connect, but we learned that
connection is how social media uses us. We barely questioned why our
new TV or mattress had a privacy policy, but we’ve begun to understand
that “privacy” policies are actually surveillance policies.
And like our forebears who named the automobile “horseless carriage”
because they could not reckon with its true dimension, we regarded the
internet platforms as “bulletin boards” where anyone could pin a note.
Congress cemented this delusion in a statute, Section 230 of the 1996
Communications Decency Act, absolving those companies of the
obligations that adhere to “publishers” or even to “speakers.”
The belief that privacy is private has left us careening toward a
future that we did not choose, because it failed to reckon with the
profound distinction between a society that insists upon sovereign
individual rights and one that lives by the social relations of the
one-way mirror.
The lesson is that privacy is public — it is a collective good that is
logically and morally inseparable from the values of human autonomy
and self-determination upon which privacy depends and without which a
democratic society is unimaginable.
Still, the winds appear to have finally shifted. A fragile new
awareness is dawning as we claw our way back up the rabbit hole toward
home.
Surveillance capitalists are fast because they seek neither genuine
consent nor consensus. They rely on psychic numbing and messages of
inevitability to conjure the helplessness, resignation and confusion
that paralyze their prey.
Democracy is slow, and that’s a good thing. Its pace reflects the tens
of millions of conversations that occur in families, among neighbors,
co-workers and friends, within communities, cities and states,
gradually stirring the sleeping giant of democracy to action.
These conversations are occurring now, and there are many indications
that lawmakers are ready to join and to lead.
This third decade is likely to decide our fate. Will we make the
digital future better, or will it make us worse? Will it be a place
that we can call home?
Epistemic inequality is not based on what we can earn but rather on
what we can learn. It is defined as unequal access to learning imposed
by private commercial mechanisms of information capture, production,
analysis and sales.
It is best exemplified in the fast-growing abyss between what we know
and what is known about us.
Twentieth-century industrial society was organized around the
“division of labor,” and it followed that the struggle for economic
equality would shape the politics of that time.
Our digital century shifts society’s coordinates from a division of
labor to a “division of learning,” and it follows that the struggle
over access to knowledge and the power conferred by such knowledge
will shape the politics of our time.
The new centrality of epistemic inequality signals a power shift from
the ownership of the means of production, which defined the politics
of the 20th century, to the ownership of the production of meaning.
The challenges of epistemic justice and epistemic rights in this new
era are summarized in three essential questions about knowledge,
authority and power: Who knows? Who decides who knows? Who decides who
decides who knows?
During the last two decades, the leading surveillance capitalists —
Google, later followed by Facebook, Amazon and Microsoft — helped to
drive this societal transformation while simultaneously ensuring their
ascendance to the pinnacle of the epistemic hierarchy.
They operated in the shadows to amass huge knowledge monopolies by
taking without asking, a maneuver that every child recognizes as
theft.
Surveillance capitalism begins by unilaterally staking a claim to
private human experience as free raw material for translation into
behavioral data. Our lives are rendered as data flows.
Early on, it was discovered that, unknown to users, even data freely
given harbors rich predictive signals, a surplus that is more than
what is required for service improvement.
It isn’t only what you post online, but whether you use exclamation
points or the color saturation of your photos; not just where you walk
but the stoop of your shoulders; not just the identity of your face
but the emotional states conveyed by your “microexpressions”; not just
what you like but the pattern of likes across engagements.
Soon this behavioral surplus was secretly hunted and captured, claimed
as proprietary data.
The data are conveyed through complex supply chains of devices,
tracking and monitoring software, and ecosystems of apps and companies
that specialize in niche data flows captured in secret.
For example, testing by The Wall Street Journal showed that Facebook
receives heart rate data from the Instant Heart Rate: HR Monitor,
menstrual cycle data from the Flo Period & Ovulation Tracker, and data
that reveal interest in real estate properties from Realtor.com — all
of it without the user’s knowledge.
These data flows empty into surveillance capitalists’ computational
factories, called “artificial intelligence,” where they are
manufactured into behavioral predictions that are about us, but they
are not for us.
Instead, they are sold to business customers in a new kind of market
that trades exclusively in human futures.
Certainty in human affairs is the lifeblood of these markets, where
surveillance capitalists compete on the quality of their predictions.
This is a new form of trade that birthed some of the richest and most
powerful companies in history.
In order to achieve their objectives, the leading surveillance
capitalists sought to establish unrivaled dominance over the 99.9
percent of the world’s information now rendered in digital formats
that they helped to create.
Surveillance capital has built most of the world’s largest computer
networks, data centers, populations of servers, undersea transmission
cables, advanced microchips, and frontier machine intelligence,
igniting an arms race for the 10,000 or so specialists on the planet
who know how to coax knowledge from these vast new data continents.
With Google in the lead, the top surveillance capitalists seek to
control labor markets in critical expertise, including data science
and animal research, elbowing out competitors such as start-ups,
universities, high schools, municipalities, established corporations
in other industries and less wealthy countries.
In 2016, 57 percent of American computer science Ph.D. graduates took
jobs in industry, while only 11 percent became tenure-track faculty
members. It’s not just an American problem.
In Britain, university administrators contemplate a “missing
generation” of data scientists. A Canadian scientist laments, “the
power, the expertise, the data are all concentrated in the hands of a
few companies.”
Google created the first insanely lucrative markets to trade in human
futures, what we now know as online targeted advertising, based on
their predictions of which ads users would click.
Between 2000, when the new economic logic was just emerging, and 2004,
when the company went public, revenues increased by 3,590 percent.
This startling number represents the “surveillance dividend.”
It quickly reset the bar for investors, eventually driving start-ups,
apps developers and established companies to shift their business
models toward surveillance capitalism.
The promise of a fast track to outsized revenues from selling human
futures drove this migration first to Facebook, then through the tech
sector and now throughout the rest of the economy to industries as
disparate as insurance, retail, finance, education, health care, real
estate, entertainment and every product that begins with the word
“smart” or service touted as “personalized.
Even Ford, the birthplace of the 20th-century mass production economy,
is on the trail of the surveillance dividend, proposing to meet the
challenge of slumping car sales by reimagining Ford vehicles as a
“transportation operating system.”
As one analyst put it, Ford “could make a fortune monetizing data.
They won’t need engineers, factories or dealers to do it. It’s almost
pure profit.”
Surveillance capitalism’s economic imperatives were refined in the
competition to sell certainty. Early on it was clear that machine
intelligence must feed on volumes of data, compelling economies of
scale in data extraction.
Eventually it was understood that volume is necessary but not
sufficient. The best algorithms also require varieties of data —
economies of scope. This realization helped drive the “mobile
revolution” sending users into the real world armed with cameras,
computers, gyroscopes and microphones packed inside their smart new
phones.
In the competition for scope, surveillance capitalists want your home
and what you say and do within its walls. They want your car, your
medical conditions, and the shows you stream; your location as well as
all the streets and buildings in your path and all the behavior of all
the people in your city.
They want your voice and what you eat and what you buy; your
children’s play time and their schooling; your brain waves and your
bloodstream. Nothing is exempt.
Unequal knowledge about us produces unequal power over us, and so
epistemic inequality widens to include the distance between what we
can do and what can be done to us.
Data scientists describe this as the shift from monitoring to
actuation, in which a critical mass of knowledge about a machine
system enables the remote control of that system.
Now people have become targets for remote control, as surveillance
capitalists discovered that the most predictive data come from
intervening in behavior to tune, herd and modify action in the
direction of commercial objectives.
This third imperative, “economies of action,” has become an arena of
intense experimentation. “We are learning how to write the music,” one
scientist said, “and then we let the music make them dance.”
This new power “to make them dance” does not employ soldiers to
threaten terror and murder. It arrives carrying a cappuccino, not a
gun.
It is a new “instrumentarian” power that works its will through the
medium of ubiquitous digital instrumentation to manipulate subliminal
cues, psychologically target communications, impose default choice
architectures, trigger social comparison dynamics and levy rewards and
punishments — all of it aimed at remotely tuning, herding and
modifying human behavior in the direction of profitable outcomes and
always engineered to preserve users’ ignorance.
We saw predictive knowledge morphing into instrumentarian power in
Facebook’s contagion experiments published in 2012 and 2014, when it
planted subliminal cues and manipulated social comparisons on its
pages, first to influence users to vote in midterm elections and later
to make people feel sadder or happier.
Facebook researchers celebrated the success of these experiments
noting two key findings: that it was possible to manipulate online
cues to influence real world behavior and feelings, and that this
could be accomplished while successfully bypassing users’ awareness.
In 2016, the Google-incubated augmented reality game, Pokémon Go,
tested economies of action on the streets. Game players did not know
that they were pawns in the real game of behavior modification for
profit, as the rewards and punishments of hunting imaginary creatures
were used to herd people to the McDonald’s, Starbucks and local pizza
joints that were paying the company for “footfall,” in exactly the
same way that online advertisers pay for “click through” to their
websites.
In 2017, a leaked Facebook document acquired by The Australian exposed
the corporation’s interest in applying “psychological insights” from
“internal Facebook data” to modify user behavior.
The targets were 6.4 million young Australians and New Zealanders. “By
monitoring posts, pictures, interactions and internet activity in real
time,” the executives wrote, “Facebook can work out when young people
feel ‘stressed,’ ‘defeated,’ ‘overwhelmed,’ ‘anxious,’ ‘nervous,’
‘stupid,’ ‘silly,’ ‘useless’ and a ‘failure.’”
This depth of information, they explained, allows Facebook to pinpoint
the time frame during which a young person needs a “confidence boost”
and is most vulnerable to a specific configuration of subliminal cues
and triggers.
The data are then used to match each emotional phase with appropriate
ad messaging for the maximum probability of guaranteed sales.
Facebook denied these practices, though a former product manager
accused the company of “lying through its teeth.” The fact is that in
the absence of corporate transparency and democratic oversight,
epistemic inequality rules. They know. They decide who knows. They
decide who decides.
The public’s intolerable knowledge disadvantage is deepened by
surveillance capitalists’ perfection of mass communications as
gaslighting.
 Two examples are illustrative. On April 30, 2019 Mark Zuckerberg made
a dramatic announcement at the company’s annual developer conference,
declaring, “The future is private.”
A few weeks later, a Facebook litigator appeared before a federal
district judge in California to thwart a user lawsuit over privacy
invasion, arguing that the very act of using Facebook negates any
reasonable expectation of privacy “as a matter of law.”
In May 2019 Sundar Pichai, chief executive of Google, wrote in The
Times of his corporations’s commitment to the principle that “privacy
cannot be a luxury good.”
Five months later Google contractors were found offering $5 gift cards
to homeless people of color in an Atlanta park in return for a facial
scan.
Facebook’s denial invites even more scrutiny in light of another
leaked company document appearing in 2018.
The confidential report offers rare insight into the heart of
Facebook’s computational factory, where a “prediction engine” runs on
a machine intelligence platform that “ingests trillions of data points
every day, trains thousands of models” and then “deploys them to the
server fleet for live predictions.”
Facebook notes that its “prediction service” produces “more than 6
million predictions per second.” But to what purpose?
In its report, the company makes clear that these extraordinary
capabilities are dedicated to meeting its corporate customers’ “core
business challenges” with procedures that link prediction,
microtargeting, intervention and behavior modification.
For example, a Facebook service called “loyalty prediction” is touted
for its ability to plumb proprietary behavioral surplus to predict
individuals who are “at risk” of shifting their brand allegiance and
alerting advertisers to intervene promptly with targeted messages
designed to stabilize loyalty just in time to alter the course of the
future.
That year a young man named Christopher Wylie turned whistle-blower on
his former employer, a political consultancy known as Cambridge
Analytica.
“We exploited Facebook to harvest millions of people’s profiles,”
Wylie admitted, “and built models to exploit what we knew about them
and target their inner demons.”
Mr. Wylie characterized those techniques as “information warfare,”
correctly assessing that such shadow wars are built on asymmetries of
knowledge and the power it affords.
Less clear to the public or lawmakers was that the political firm’s
strategies of secret invasion and conquest employed surveillance
capitalism’s standard operating procedures to which billions of
innocent “users” are routinely subjected each day.
Mr. Wylie described this mirroring process, as he followed a trail
that was already cut and marked. Cambridge Analytica’s real innovation
was to pivot the whole undertaking from commercial to political
objectives.
In other words, Cambridge Analytica was the parasite, and surveillance
capitalism was the host.
Thanks to its epistemic dominance, surveillance capitalism provided
the behavioral data that exposed the targets for assault.
Its methods of behavioral microtargeting and behavioral modification
became the weapons. And it was surveillance capitalism’s lack of
accountability for content on its platform afforded by Section 230
that provided the opportunity for the stealth attacks designed to
trigger the inner demons of unsuspecting citizens.
It’s not just that epistemic inequality leaves us utterly vulnerable
to the attacks of actors like Cambridge Analytica. The larger and more
disturbing point is that surveillance capitalism has turned epistemic
inequality into a defining condition of our societies, normalizing
information warfare as a chronic feature of our daily reality
prosecuted by the very corporations upon which we depend for effective
social participation.
They have the knowledge, the machines, the science and the scientists,
the secrets and the lies. All privacy now rests with them, leaving us
with few means of defense from these marauding data invaders.
Without law, we scramble to hide in our own lives, while our children
debate encryption strategies around the dinner table and students wear
masks to public protests as protection from facial recognition systems
built with our family photos.
In the absence of new declarations of epistemic rights and
legislation, surveillance capitalism threatens to remake society as it
unmakes democracy.
From below, it undermines human agency, usurping privacy, diminishing
autonomy and depriving individuals of the right to combat.
From above, epistemic inequality and injustice are fundamentally
incompatible with the aspirations of a democratic people.
We know that surveillance capitalists work in the shadows, but what
they do there and the knowledge they accrue are unknown to us. They
have the means to know everything about us, but we can know little
about them.
Their knowledge of us is not for us. Instead, our futures are sold for
others’ profits. Since that Federal Trade Commission meeting in 1997,
the line was never drawn, and people did become chattel for commerce.
Another destructive delusion is that this outcome was inevitable — an
unavoidable consequence of convenience-enhancing digital technologies.
The truth is that surveillance capitalism hijacked the digital medium.
There was nothing inevitable about it.
American lawmakers have been reluctant to take on these challenges for
many reasons. One is an unwritten policy of “surveillance
exceptionalism” forged in the aftermath of the Sept. 11 terrorist
attacks, when the government’s concerns shifted from online privacy
protections to a new zeal for “total information awareness.”
In that political environment the fledgling surveillance capabilities
emerging from Silicon Valley appeared to hold great promise.
Surveillance capitalists have also defended themselves with lobbying
and forms of propaganda intended to undermine and intimidate
lawmakers, confounding judgment and freezing action.
These have received relatively little scrutiny compared to the damage
they do. Consider two examples:
The first is the assertion that democracy threatens prosperity and
innovation. Former Google chief executive Eric Schmidt explained in
2011, “we took the position of ‘hands off the internet.’
You know, leave us alone … The government can make regulatory mistakes
that can slow this whole thing down, and we see that and we worry
about it.”
This propaganda is recycled from the Gilded Age barons, whom we now
call “robbers.” They insisted that there was no need for law when one
had the “law of survival of the fittest,” the “laws of capital” and
the “law of supply and demand.”
Paradoxically, surveillance capital does not appear to drive
innovation. A promising new era of economic research shows the
critical role that government and democratic governance have played in
innovation and suggests a lack of innovation in big tech companies
like Google. Surveillance capitalism’s information dominance is not
dedicated to the urgent challenges of carbon-free energy, eliminating
hunger, curing cancers, ridding the oceans of plastic or flooding the
world with well paid, smart, loving teachers and doctors. Instead, we
see a frontier operation run by geniuses with vast capital and
computational power that is furiously dedicated to the lucrative
science and economics of human prediction for profit.
The second form of propaganda is the argument that the success of the
leading surveillance capitalist firms reflects the real value they
bring to people. But data from the demand side suggest that
surveillance capitalism is better understood as a market failure.
Instead of a close alignment of supply and demand, people use these
services because they have no comparable alternatives and because they
are ignorant of surveillance capitalism’s shadow operations and their
consequences. Pew Research Center recently reported that 81 percent of
Americans believe the potential risks of companies’ data collection
outweigh the benefits, suggesting that corporate success depends upon
coercion and obfuscation rather than meeting people’s real needs.
In his prizewinning history of regulation, the historian Thomas McCraw
delivers a warning. Across the centuries regulators failed when they
did not frame “strategies appropriate to the particular industries
they were regulating.”
Existing privacy and antitrust laws are vital but neither will be
wholly adequate to the new challenges of reversing epistemic
inequality.
These contests of the 21st century demand a framework of epistemic
rights enshrined in law and subject to democratic governance.
Such rights would interrupt data supply chains by safeguarding the
boundaries of human experience before they come under assault from the
forces of datafication.
The choice to turn any aspect of one’s life into data must belong to
individuals by virtue of their rights in a democratic society.
This means, for example, that companies cannot claim the right to your
face, or use your face as free raw material for analysis, or own and
sell any computational products that derive from your face.
The conversation on epistemic rights has already begun, reflected in a
pathbreaking report from Amnesty International.
On the demand side, we can outlaw human futures markets and thus
eliminate the financial incentives that sustain the surveillance
dividend.
This is not a radical prospect. For example, societies outlaw markets
that trade in human organs, babies and slaves.
In each case, we recognize that such markets are both morally
repugnant and produce predictably violent consequences.
Human futures markets can be shown to produce equally predictable
outcomes that challenge human freedom and undermine democracy. Like
subprime mortgages and fossil fuel investments, surveillance assets
will become the new toxic assets.
In support of a new competitive landscape, lawmakers will need to
champion new forms of collective action, just as nearly a century ago
legal protections for the rights to organize, to strike and to bargain
collectively united lawmakers and workers in curbing the powers of
monopoly capitalists.
Lawmakers must seek alliances with citizens who are deeply concerned
over the unchecked power of the surveillance capitalists and with
workers who seek fair wages and reasonable security in defiance of the
precarious employment conditions that define the surveillance economy.
Anything made by humans can be unmade by humans. Surveillance
capitalism is young, barely 20 years in the making, but democracy is
old, rooted in generations of hope and contest.
Surveillance capitalists are rich and powerful, but they are not
invulnerable. They have an Achilles heel: fear.
They fear lawmakers who do not fear them. They fear citizens who
demand a new road forward as they insist on new answers to old
questions:
Who will know? Who will decide who knows? Who will decide who decides?
Who will write the music, and who will dance?
Shoshana Zuboff (@ShoshanaZuboff) is professor emerita at Harvard
Business School and the author of “The Age of Surveillance
Capitalism.”

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"It's no use fighting elections on the facts; it's all about emotions."
Africa


“We just put information into the bloodstream to the internet and then
watch it grow, give it a little push every now and again over time to
watch it take shape. And so this stuff infiltrates the online
community and expands but with no branding – so it’s unattributable,
untraceable.”

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27-JAN-2020 :: #WuhanCoronavirus #nCoV2019 #coronavirus
Law & Politics


President Xi warned The Corona virus is 'accelerating' [and the]
country [is] facing 'grave situation'.
At the last count [Sunday 26th January 2020], more than 2,000 people
globally have been infected., the vast majority of them in China,
where 56 people have died from the disease.
[I, for one, believe this number is massively undercounted. Some
reports speak to 100,000 infections in China] It looks like it started
around December 1st and that it can take up to 23 days to show
symptoms.
Curiously, "Bill Gates kept telling us a pandemic was coming, in Oct
2019 he ran a simulation of a Coronavirus pandemic, just three months
later the real Coronavirus pandemic begins." @HenryMakow.
In an article carried in Business Insider in October last year  Bill
Gates said the following
thinks a coming disease could kill 30 million people within 6 months -
and Gates presented a simulation by the Institute for Disease Modeling
that found that a new flu like the one that killed 50 million people
in the 1918 pandemic would now most likely kill 30 million people
within six months.
The likelihood that such a disease will appear continues to rise. New
pathogens emerge all the time as the world population increases and
humanity encroaches on wild environments.
It's becoming easier and easier for individual people or small groups
to create weaponized diseases that could spread like wildfire around
the globe.
According to Gates, a small non-state actor could build an even
deadlier form of smallpox in a lab.
So who had ‘mutated bat-snake flu’ as their top market risk for 2020?
tweeted @tracyalloway.
The Precise origins of the Corona virus are yet to be established with
Wiley's Journal of Medical Virology saying it may be may be
snake-to-human transmission and some even pointing the Finger at the
Wuhan Institute of Virology and the Wuhan bio-safety level four
(BSL-4) laboratory and surmising that the only explanation left is
artificial DNA modification, possibly by the Wuhan Institute of
Virology, which since 2007 has collected samples from thousands of
bats across the country and done genetic experiments with them.
What is clear is that the CCP suppressed information until we reached
a Groucho Marx ''Who Ya Gonna Believe, Me or Your Own Eyes'' moment.
Epidemiologists speak of Tipping Points. Malcolm Gladwell described
the ''Tipping Point''  as the name given to that moment in an epidemic
when a virus reaches critical mass. It's the boiling point. It's the
moment on the graph when the line starts to shoot straight upwards. In
an article in 2014 about Ebola I called it the moment of ''escape
velocity'' and wrote ''viruses exhibit non-linear and exponential
characteristics'' The Mathematics is the basic reproduction number of
the infection (R_0), which represents how many People each person
infected with the coronavirus is passing the disease on to. A number
of less than 1, means the virus dies out.
For a Frame of Reference, the typical R0 attack rate for the seasonal
flu is around an R0=1.28. The 2009 flu pandemic R0=1.48. The 1918
Spanish Flu =1.80. The R0 range is somewhere between 2.00-2.6 with Dr.
Eric Ding speaking of 3.8 over the weekend.
@DrEricDing tweeted the new coronavirus is a 3.8!!! How bad is that
reproductive R0 value? It is thermonuclear pandemic level bad - never
seen an actual virality coefficient outside of Twitter in my entire
career [before adjusting his calculations lower to 2.5]
Each person infected with coronavirus is passing the disease on to
between two and three other people on average at current transmission
rates, according to two separate scientific analyses of the epidemic.
Ferguson’s team suggest as many as 4,000 people in Wuhan were already
infected by Jan. 18 and that on average each case was infecting two or
three others.
A second study by researchers at Britain’s Lancaster University also
calculated the contagion rate at 2.5 new people on average being
infected by each person already infected.
''Should the epidemic continue unabated in Wuhan, we predict (it) will
be substantially larger by Feb. 4,” the scientists wrote.
They estimated that the central Chinese city of Wuhan where the
outbreak began in December will alone have around 190,000 cases of
infection by Feb. 4., and that “infection will be established in other
Chinese cities, and importations to other countries will be more
frequent.”
The Lancet now reports that the coronavirus is contagious even when
*no symptoms*: specifically: “crucial to isolate patients...
quarantine contacts as early as possible because asymptomatic
infection appears possible”
The overarching Point is that whether its 2.5 or 3.8 this is off the
charts. The CCP is building hospitals in a record breaking 7 days but
who will man them? China has locked down a total of 47m of its
Citizens.
Given the new hyperconnectedness of the World [For example, did you
know there is a daily Ethiopian Flight between Wuhan and Addis Abeba -
As of Thursday Ethiopian Airlines, which has multiple daily passenger
and cargo flights to China and Africa’s busiest airport hub, said it
was waiting for guidance from Ethiopia’s Health Ministry on how to
respond], I have to assume that the Corona virus is already in Africa
but just not diagnosed. Thats a racing certainty.
Paul Virilio wrote ''With every natural disaster, health scare, and
malicious rumor now comes the inevitable “information bomb”–live feeds
take over real space, and technology connects life to the immediacy of
terror, the ultimate expression of speed''
And in his book City of panic he described The city reconstructed
through the use mediatized panic.
Markets bought Gold and G7 Bonds on Friday as Investors dived into
Safe Havens, Nest week we could see these moves turn parabolic.
“But it is a curve each of them feels, unmistakably. It is the
parabola. They must have guessed, once or twice -guessed and refused
to believe -that everything, always, collectively, had been moving
toward that purified shape latent in the sky, that shape of no
surprise, no second chance, no return.’’

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The earliest case became ill on 1 December and had no reported link to the seafood market, the authors report. "No epidemiological link was found between the first patient and later cases"
Law & Politics


As confirmed cases of a novel virus surge around the world with
worrisome speed, all eyes have so far focused on a seafood market in
Wuhan, China, as the origin of the outbreak. But a description of the
first clinical cases published in The Lancet on Friday challenges that
hypothesis.The paper, written by a large group of Chinese researchers
from several institutions, offers details about the first 41
hospitalized patients who had confirmed infections with what has been
dubbed 2019-novel coronavirus (2019-nCoV). The earliest case became
ill on 1 December and had no reported link to the seafood market, the
authors report. “No epidemiological link was found between the first
patient and later cases,” they state. Their data also show that in
total, 13 of the 41 cases had no link to the marketplace either.
“That’s a big number, 13, with no link,” says Daniel Lucey, an
infectious disease specialist at the University of Georgetown
Earlier reports from Chinese health authorities and the World Health
Organization said the first patient had onset of symptoms on 8
December—and those reports simply said “most” cases had links to the
seafood market, which was closed on 1 January.
Lucey says if the new data are accurate, the first human infections
must have occurred in November—if not earlier—because there is an
incubation time between infection and symptoms surfacing. If so, the
virus possibly spread silently between people in Wuhan and perhaps
elsewhere before the cluster of cases from the city’s now infamous
Huanan Seafood Wholesale Market was discovered in late December. “The
virus came into that marketplace before it came out of that
marketplace,” Lucey asserts.

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"Notably, the new coronavirus provides a new lineage for almost half of its genome" - basically it's saying it's completely brand new to #coronavirus subgenus. @DrEricDing
Law & Politics


“Notably,  the  new  coronavirus  provides  a  new  lineage  for
almost  half  of  its  genome,  with  no  close  genetic
relationships  to  other  viruses  within  the  subgenus  of
sarbecovirus.” —> basically it’s saying it’s completely brand new to
#coronavirus subgenus.

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Very strange: new mystery middle segment that has no #coronavirus history "This genomic part comprises also half of the spike region encoding a multifunctional protein responsible also for virus entry into host cells[30,31]" DrEricDing/
Law & Politics


Very strange: So what is in this new mystery middle segment that
has no #coronavirus history? The study authors continue: “This genomic
part comprises also half of the spike region encoding a
multifunctional protein responsible also  for virus entry into host
cells[30,31]”.

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BOTTOMLINE: 1) Seafood market not source. 2) RNA #coronavirus mutates really fast. 3) has unusual middle segment never seen before in any coronavirus. 5) mystery middle segment encodes protein responsible for entry into host cells. @DrEricDing
Law & Politics


BOTTOMLINE: 1) Seafood market not the source. 2) This RNA
#coronavirus mutates really fast. 3) 🧬 has unusual middle segment
never seen before in any coronavirus. 4) Not from recent mixing. 5)
That mystery middle segment encodes protein responsible for entry into
host cells.

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The early outbreak data largely follows the exponential growth. We estimated that the mean R0 ranges from 3.30 (95%CI: 2.73-3.96) to 5.47 (95%CI: 4.16-7.10) associated with 0-fold to 2-fold increase in the reporting rate
Law & Politics


The early outbreak data largely follows the exponential growth. We
estimated that the mean R0 ranges from 3.30 (95%CI: 2.73-3.96) to 5.47
(95%CI: 4.16-7.10) associated with 0-fold to 2-fold increase in the
reporting rate. With rising report rate, the mean R0 is likely to be
below 5 but above 3. Conclusion: The mean estimate of R0 for the
2019-nCoV ranges from 3.30 (95%CI: 2.73-3.96) to 5.47 (95%CI:
4.16-7.10), and significantly larger than 1. Our findings indicate the
potential of 2019-nCoV to cause outbreaks.

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20 OCT 14 :: it is about its 'escape velocity' viruses exhibit non-linear and exponential characteristics. EBOLA #WuhanCoronavirus
Law & Politics


“It is a numbers game, the more cases you have the more likely there
are going to be mutations that could change the virus in a significant
way,” said David Sanders, a professor of biological sciences at Purdue
University who studies Ebola.
“The more it persists, the more likely we are going to be thrown a curve.”

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Clearly, we are dealing with an extreme fat-tailed process owing to an increased connectivity, which increases the spreading in a nonlinear way
Law & Politics


Fat tailed processes have special attributes, making conventional
risk-management approaches inadequate.
The general (non-naive) precautionary principle [3] delineates
conditions where actions must be taken to reduce risk of ruin, and
traditional cost-benefit analyses must not be used.
These are ruin problems where, over time, exposure to tailevents leads
to a certain eventual extinction. While thereis a very high
probability for humanity surviving a single such event, over time,
there is eventually zero probability of surviving repeated exposures
to such events.
While repeated risks can be taken by individuals with a limited life
expectancy, ruin exposures must never be taken at the systemic and
collective level. In technical terms, the precautionary principle
applies when traditional statistical averages are invalid because
risks are not ergodic
Spreading rate:
Historically based estimates of spreading rates for pandemics in
general, and for the current one in particular, underestimate the rate
of spread because of the rapid increases in transportation
connectivity over recent years.
This means that expectations of the extent of harm are under-estimates
both because events are inherently fat tailed, and because the tail is
becoming fatter as connectivity increases.Global connectivity is at an
all-time high, with China one of the most globally connected
societies.
Fundamentally,viral contagion events depend on the interaction of
agents in physical space, and with the forward-looking uncertainty
that novel outbreaks necessarily carry, reducing connectivity
temporarily to slow flows of potentially contagious individuals is the
only approach that is robust against misestimations in the properties
of a virus or other pathogen.
Reproductive ratio:
Estimates of the virus’s reproductive ratio R0 —the number of cases
one case generates on average over the course of its infectious period
in an otherwise uninfected population—are biased downwards.
This property comes from fat-tailedness [4] due to individual
‘superspreader’ events. Simply, R0 is estimated from an average which
takes longer to converge as it is itself a fat-tailed variable.
Mortality rate:
Mortality and morbidity rates are also downward biased, due to the lag
between identified cases,deaths and reporting of those deaths.
Increasingly Fatal Rapidly Spreading Emergent Pathogens:
With increasing transportation we are close to a transition to
conditions in which extinction becomes certain both because of rapid
spread and because of the selective dominance of increasingly worse
pathogens. [5]
Asymmetric Uncertainty:
Properties of the virus that are uncertain will have substantial
impact on whether policies implemented are effective. For instance,
whether contagious asymptomatic carriers exist.
These uncertainties make it un-clear whether measures such as
temperature screening at major ports will have the desired impact.
Practically all the uncertainty tends to make the problem potentially
worse, not better, as these processes are convex to uncertainty.
Fatalism and inaction:
Perhaps due to these challenges, a common public health response is
fatalistic, accepting what will happen because of a belief that
nothing can be done.
This response is incorrect as the leverage of correctly selected
extraordinary interventions can be very high.
Conclusion:
Standard individual-scale policy approaches such as isolation, contact
tracing and monitoring are rapidly(computationally) overwhelmed in the
face of mass infection,and thus also cannot be relied upon to stop a
pandemic.
Multi-scale population approaches including drastically pruning
contact networks using collective boundaries and social behavior
change, and community self-monitoring, are essential.
Together, these observations lead to the necessity of a precautionary
approach to current and potential pandemic outbreaks that must include
constraining mobility patterns in the early stages of an outbreak,
especially when little is known about the true parameters of the
pathogen.
It will cost something to reduce mobility in the short term, but to
fail do so will eventually cost everything—if not from this event,
then one in the future.

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The point is that you can be wrong a zillion times; doesn't matter if all it takes is once to hit extinction. @nntaleb
Law & Politics


It's remarkable how pple who learn statistics become dangerously
stupid, like this "professor"  @AlexColangeloCar accidents are
thin-tailed, never multiplicative

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We are committing $10 million in emergency funds and corresponding support to assist frontline responders in China and Africa in their efforts to contain the global spread of 2019-nCoV (coronavirus). @gatesfoundation
Law & Politics


SEATTLE, January 26, 2020 – The Bill & Melinda Gates Foundation today
announced that it is immediately committing $10 million in emergency
funds and corresponding technical support to help frontline responders
in China and Africa accelerate their efforts to contain the global
spread of 2019-nCoV.
The foundation is committing $5 million to the 2019-nCoV response in
China and is already working with a range of Chinese public and
private sector partners to accelerate national and international
cooperation in areas of critical need, including efforts to identify
and confirm cases, safely isolate and care for patients and accelerate
the development of treatments and vaccines.
Partners include the National Health Commission and Chinese Center for
Disease Control and Prevention, the National Natural Science
Foundation of China and various research institutes affiliated with
the Chinese Academy of Sciences, Xiamen University and Sinopharm China
National Biotec Group.
The foundation is also immediately committing $5 million to assist the
Africa Centers for Disease Control and Prevention in scaling up public
health measures against 2019-nCoV among African Union member states.
These measures will include technical support to implement the
screening and treatment of suspected cases, laboratory confirmation of
2019-nCoV diagnoses and the safe isolation and care of identified
cases.

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Currency Markets at a Glance WSJ
World Currencies


Euro 1.1020
Dollar Index 97.94
Japan Yen 108.86
Swiss Franc 0.9687
Pound 1.3018
Aussie 0.6745
India Rupee 71.3330
South Korea Won 1179.53
Brazil Real 4.2078
Egypt Pound 15.7904
South Africa Rand 14.6060

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Sell oil on rips @TCommodity 53.12
Commodities


Emerging Markets

Frontier Markets

Sub Saharan Africa

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The Republic of Congo's public debt may exceed $12.5 billion, more than a third higher than previous @IMFNews estimates, @Global_Witness @business
Africa


The debt could further complicate Congo’s three-year, $449 million
loan program it began with the IMF in July.
The Washington-based lender has already postponed its first review of
the program while Congo restructures external commercial debt, an IMF
spokesman said by email Friday before it had seen the Global Witness
report.
The London-based group says as much as $3.3 billion owed by Congo and
state-owned oil company Societe Nationale des Petroles du Congo, or
SNPC, was previously undisclosed, based on an analysis of documents
and contracts that were released under conditions of the IMF bailout.
Global Witness’s analysis shows “a government that is mismanaging the
primary source of sovereign wealth today, while mortgaging off what
will remain of that finite resource for the generations of tomorrow.”
Millions of dollars are also missing from SNPC accounts, according to
the report.
Calls to Congo’s government spokesman and the SNPC weren’t answered
when Bloomberg sought comment.
Congo, rated Caa2 by Moody’s Investors Service, or eight steps below
investment grade, has one Eurobond outstanding.
The amortizing bond totals $295 million and has a final maturity of
2029. It yields 9.5% and has made investors a total return of 20% in
the past year, according to data compiled by Bloomberg, almost double
the average for emerging-market sovereign dollar debt.
The IMF stepped in in July after low oil prices had devastated the
economy of Congo, which is sub-Saharan Africa’s third-largest crude
producer.
The loans came with increased transparency requirements for the
government and SNPC, which “does not meet international benchmarks for
sound corporate governance,” according to the IMF.
Between 2012 and 2018, the company made only $123 million in profits
despite $5.7 billion worth of sales, Global Witness said.
The group also questioned the fairness of some of Congo and SNPC’s
contracts, which allow oil companies to write off millions in expenses
that are not always audited.
“Congo’s representatives have agreed to subsidize the business
overheads of some of the largest oil companies in the world,” the
report said.
Of the debts Global Witness said it found, SNPC owes at least $2.7
billion to companies including Total SA, Eni SpA, and Chevron Corp.
The government owes another $606 million to banks for loans secured by
oil, it said.
Chevron’s Congo operations did not immediately respond to an emailed
request for comment. Total said in a statement Monday that the terms
of its Congo projects were “not uncommon” in the industry.
“Total does not finance Republic of Congo other than as expressly
reported in our obligatory annual public financial reporting of
payments made to governments,” it said.
Eni said in an email Monday that the money due to its Congo subsidiary
was to reimburse the company for advances made to SNPC for operating
and capital costs.
“Such amount will be gradually reimbursed in kind by SNPC, which is a
contractual practice widespread in the industry,” it said. “No
interest rate is applicable as reimbursement will be in kind.”

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Gabon Set to Test Demand for African High-Yield Dollar Debt @markets
Africa


Gabon is starting investor meetings Monday for a planned Eurobond sale
that will test demand for hard-currency debt from one of the
lowest-rated issuers in the region.
The sale comes amid record debt sales by emerging-market borrowers
this year as a lull in trade tensions and a rally in U.S. Treasuries
spur demand for higher-yielding assets.
Average yields on Eurobonds from sub-Saharan Africa are 2.5 percentage
points higher than the emerging-market average, promising potentially
juicy returns for investors willing to take on the added risk.
Gabon, rated seven levels below investment-grade by Moody’s Investors
Service, mandated Deutsche Bank AG, JPMorgan Chase & Co. and Standard
Bank Group Ltd. to manage its benchmark-sized sale.
Ghana, rated just one step higher at B3, named five banks including
JPMorgan earlier this month for a $3 billion deal. They would be the
first issuers from the continent to tap international markets this
year.
“The African Eurobond universe generally has become a bit scarce,”
said Jibran Qureishi, an economist at Nairobi-based Stanbic Holdings
Plc. “Those kind of bonds are going to be popular among hard-currency
investors.”
Yields on Gabon’s Eurobonds due 2025 fell to a record low of 5.23%
last week. The yield jumped 5 basis points on Monday as increasing
concern over the spread of the deadly coronavirus gripped global
markets.
Dollar debt from sub-Saharan African sovereigns has returned 1.5% this
month, more than double the 0.6% average of emerging-market issuers.
Average yields fell as low as 6.43% in January, from a high of 7.65% a
year ago, even as the Institute of International Finance warned that
African nations’ debt loads may be unsustainable, partly due to
issuance of Eurobonds in a low-interest-rate environment.
Countries in the region, excluding South Africa, face Eurobond
repayments of about $75 billion over the next 10 years while slowing
growth is putting increasing strain on governments’ finances, IIF
economists Benjamin Hilgenstock and Elina Ribakova wrote in a report.
Ghana, along with Nigeria, Kenya, Angola and Zambia face the heaviest
repayment burdens, they wrote. Ghana’s Eurobonds due 2029 climbed 30
basis points on Monday to 7.43%, after falling to a record low on Jan.
13.
Those on Kenya’s 2028 dollar securities hit a record low on Jan. 17,
but have since retraced 26 basis points to 6.05%.

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Unexpected heavy rains in the second half of 2019 caused some crop damage and food inflation reached 23.8% in December, the highest in almost three years.
Africa


“Because of the bad rains we had in the last quarter of 2019 we expect
inflation in the first quarter of 2020 to be slightly above our
medium-term benchmark of 5%,” Rwangombwa said in an interview Friday
in the capital, Kigali.
However, the rate will remain inside the target band of 2% to 8%, he said.
The central bank uses the urban inflation rate as the headline
indicator that it targets, although the majority of Rwanda’s
population of 12 million live in rural areas.
Urban inflation reached reached 6.9% in November, the highest level in
more than two years, before slowing to 6.7% in December. The rural
inflation rate is more than double that.
Rwangombwa said. Economic growth is projected at 8%, “if we don’t get
unusual pressures on any of our sectors,”

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@sbmbankkenya has filed a petition to liquidate @eacables after the company defaulted on a Sh285mn loan. @BD_Africa
Africa


SBM Bank (Kenya) Limited has filed a petition to liquidate East
African Cables   after the company defaulted on a Sh285 million loan.
The legal action has been taken under the Insolvency Act 2015 which
provides directions for resolving companies unable to pay their
obligations.
EA Cables is part of a group of companies owned by investment firm
TransCentury  and which have struggled to pay various creditors
including bondholders and banks.
The cable manufacturer’s biggest lenders, the Kenyan and Tanzanian
branches of Standard Bank Plc, last year agreed to take a haircut on
Sh1.56 billion and were paid Sh1.6 billion as final settlement.
EA Cables took new loans from Equity Bank and used the amounts to pay
off StanChart . It disclosed negotiations with Equity Bank  to also
settle the remaining claims by SBM (Sh285 million) and Ecobank Kenya
(Sh161 million).

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@eacables share price data
Africa


Closing Price:           2.37
Total Shares Issued:          253125000.00
Market Capitalization:        599,906,250
EPS:             1.92
PE:                 1.234

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by Aly Khan Satchu (www.rich.co.ke)
 
 
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January 2020
 
 
 
 
 
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