The rise of humancomputer cooperation Shyam Sankar
I’d like to tell you about two games of
chess the first happened in 1997 which
Garry Kasparov a human lost a deep-blue
a machine to many this was the dawn of a
new era one where man would be dominated
by machine but here we are 20 years on
and the greatest change in how we relate
to computers is the iPad not how the
second game was a freestyle chess
tournament in 2005 and which man and
machine could enter together as partners
rather than adversaries if they so chose
at first the results were predictable
even a supercomputer was beaten by a
grandmaster with a relatively weak
laptop the surprise came at the end who
won not a grandmaster with the
supercomputer but actually two American
amateurs using three relatively weak
laptops their ability to coach and
manipulate their computers to deeply
explore specific positions effectively
counteracted the superior chess
knowledge of the grandmasters in the
superior computational power of other
adversaries this is an astonishing
result average men average machines
beating the best man the best machine
and anyways isn’t it supposed to be man
versus machine instead it’s about
cooperation and the right type of
cooperation we’ve been paying a lot of
attention to Marvin Minsky’s vision for
artificial intelligence over the last 50
years it’s a sexy vision for sure many
of embraces become the dominant school
of thought computer science but as we
enter the era of big data of network
systems of open platforms and embedded
technology I’d like to suggest it’s time
to reevaluate an alternative vision that
was actually developed around the same
time I’m talking about JCR Licklider z'
human-computer symbiosis perhaps better
termed intelligence augmentation I a
wick lighter was a computer science
Titan who had a profound effect on the
development of technology in the
Internet his vision was to enable man
and machine to cooperate in making
decisions in controlling complex
situations without the inflexible
dependence on predetermined programs
note that word cooperate Lickliter
encourages us
to take a toaster and make it data from
Star Trek but to take a human and make
her more capable humans are so amazing
how we think our nonlinear approaches
our creativity iterative hypotheses all
very difficult if possible all for
computers to do Lickliter intuitively
realized this contemplating humans
setting the goals formulating the
hypotheses determining the criteria and
performing the evaluation of course in
other ways humans are so limited were
terrible at scale computation and volume
we require high-end talent management to
keep the rock band together and playing
Licklider for saw computers doing all of
the routinize herbal work that was
required to prepare the way for insights
and decision-making silently without
much fanfare this approach has been
compiling victories beyond chess protein
folding a topic that shares the
incredible expansiveness of chess there
are more ways of folding a protein than
there are atoms in the universe this is
a world-changing problem with huge
implications for our ability to
understand and treat disease and for
this task supercomputer fueled brute
force simply isn’t enough fully a game
created by computer scientists
illustrates the value of the approach
non technical non biologists amateurs
play a video game in which they visually
arranged the structure of the protein
allowing the computer to manage the
atomic forces and interactions and
identify structural issues this approach
beats supercomputers 50% of the time and
tied 30% of the time folded recently
made a notable and major scientific
discovery by deciphering the structure
of the Mason Fischer monkey virus a
protease that had eluded determination
for ever 10 years was solved by three
players in a matter of days perhaps the
first major scientific advance to come
from playing the video game last year on
the side of the twin towers a 9/11
memorial opened it displays the names of
the thousands of victims using a
beautiful concept called meaningful
adjacency places the names and next to
each other based on the relationships to
one another friends families co-workers
when you put it all together it’s quite
a computational challenge 3,500 victims
1,800 to JCCC requests the importance of
the overall physical specifications in
the final aesthetics when first reported
by the media
full credit for such a feat was given to
an algorithm from the New York City
design firm local projects the truth is
a bit more nuanced while an algorithm
was used to develop the underlying
framework humans use that framework to
design the final result so in this case
a computer I’ve evaluated millions of
possible layouts manage a complex
relational system and kept track of a
very large set of measurements and
variables allowing the humans to focus
on design and compositional choices so
the more you look around you the more
you see Licklider vision everywhere
whether it’s augmented reality in your
iPhone or GPS in your car or
human-computer symbiosis is making us
more capable so if you want to improve
human-computer symbiosis what can you do
you can start by designing the human
into the process instead of thinking
about what a computer will do to solve
the problem design the solution around
what the human will do as well when you
do this you’ll quickly realize that you
spend all of your time on the interface
between man and machine specifically on
designing away the friction in the
interaction in fact this friction is
more important than the power of the man
or the power of the machine in
determining overall capability that’s
why two amateurs with a few laptops
handily beat a supercomputer and a
grandmaster what Kasparov calls
processes a byproduct of friction the
better the process the less the friction
and minimizing friction turns out to be
this isof variable or take another
example Big Data every interaction we
have in the world is recorded by an
ever-growing array of sensors your phone
credit card computer the result is big
data and it actually presents us with an
opportunity to more deeply understand
the human condition the major emphasis
of most approaches to big data focus on
how do I store this data how do I search
this data how do i process this data
these are necessary but insufficient
questions the imperative is not to
figure out how to compute but what to
compute how do you impose human
intuition on data at this scale again we
start by designing the human to the
process when PayPal was first starting
as a business their biggest challenge
was not how do I send money back and
forth online it was how do I do that
without being defrauded by organized
crime why so challenging because while
computers can learn to detect and
identify fraud based on patterns they
can’t learn to do that based on patterns
they’ve never seen before an organized
crime has a lot in common with this
audience brilliant people relentlessly
resourceful entrepreneurial spirit and
one huge and important difference
purpose and so while computers alone can
catch all about the cleverest fraudsters
catching the cleverest it’s the
difference between success and failure
there’s a whole class of problems like
this ones with adaptive adversaries they
rarely if ever present with the
repeatable pattern that’s discernable to
computers instead there’s some inherent
component of innovation or disruption
and increasingly these problems are
buried in big data for example terrorism
terrorists are always adapting in minor
and major ways to new circumstances
and despite what you might see on TV
these adaptations and the detection of
them are fundamentally human computers
don’t detect novel patterns or new
behaviors or humans do humans using
technology testing hypotheses searching
for insight by asking machines to do
things for them Osama bin Laden was not
caught by artificial intelligence he was
caught by dedicated resourceful
brilliant people in partnerships with
various technologies as appealing as it
might sound you cannot algorithmically
data-mine your way to the answer there
is no find terrorists button and the
more data we integrate from a vast
variety of sources across a wide variety
of data formats from very disparate
systems the less effective data mining
can be instead people will have to look
at data and search for insight and as
Licklider foresaw long ago the key to
great results here is the right type of
cooperation and as Kasparov realized
that means minimizing friction at the
interface now this approach makes
possible things like combing through all
available data from very different
sources identifying key relationships
and putting of that in one place
something that’s been nearly impossible
to do before the salm this has
terrifying privacy and civil liberties
implications to others it foretells of
an era of greater privacy and civil
liberties protections but privacy and
civil liberties are of fundamental
importance that must be acknowledged and
they can’t be swept aside even with the
best of intense so let’s explore through
a couple of examples the impact that
technologies built to drive
human-computer symbiosis have had in
recent time in October 2007 US and
coalition forces raided an al Qaeda safe
house in the city of Sinjar on the
Syrian border of Iraq they found a
treasure trove of documents 700
biographical sketches of foreign
fighters these foreign fighters had left
their families in the Gulf the Levant in
North Africa
to join al-qaeda in Iraq these records
were human resource forms the foreign
fighters filled them out as they joined
the organization it turns out that
al-qaeda too is not without its
bureaucracy they answered questions like
who recruited you what’s your hometown
what occupation do you seek and that
last question a surprising insight was
revealed the vast majority of foreign
fighters were seeking to become suicide
bombers for martyrdom hugely important
since between 2003 and 2007 Iraq had
thirteen hundred and eighty two suicide
bombings a major source of instability
analyzing this data was hard the
originals were sheets of paper in Arabic
that had to be scanned and translated
the friction in the process did not
allow for meaningful results in an
operational timeframe using humans PDFs
and tenacity alone the researchers had
to lever up their human minds with
technology to dive deeper to explore
non-obvious hypotheses and in fact
insights emerged 20% of the foreign
fighters were from Libya 50% of those
from a single town in Libya hugely
important since prior statistics but
that figure at 3% it also helped to hone
in on a figure of rising importance in
Al Quaida Abu Yahya al-libi a senior
cleric in the Libyan Islamic fighting
group in March of 2007 he gave a speech
after worship was a surge and
participation amongst Libyan foreign
fighters perhaps most clever of all
though and least obvious by flipping the
data on its head the researchers were
able to deeply explore the coordination
networks in Syria that were ultimately
responsible for receiving and
transporting the foreign fighters to the
border these were networks of
mercenaries not ideologues who were in
the coordination business for profit for
example they charged Saudi foreign
fighters substantially more than Libyans
money that would have otherwise gone to
al Qaeda
perhaps the adversary would disrupt
their own network if they knew they were
cheating would-be jihadists in January
2010 a devastating 7.0 earthquake struck
Haiti third deadliest earthquake of all
time left 1 million people 10% of the
population homeless one seemingly small
aspect of the overall relief ever became
increasingly important as the delivery
of food and water soccer rolling January
and February the dry months in Haiti yet
many of the camps had developed standing
water the only institution with detailed
knowledge of Haiti’s floodplains
had been leveled in the earthquake
leadership inside so the question is
which camps are at risk
how many people in these camps what’s
the timeline for flooding and give it
very limited resources infrastructure
how do we prioritize the relocation the
data was incredibly disparate US Army
had detailed knowledge for only a small
section of the country there was data
online from a 2006 environmental risk
conference others geospatial data not
have been integrated the human goal here
was to identify camps for relocation
based on priority need the computer had
to integrate a vast amount of geospatial
information social media data and relief
organization information to answer this
question by implementing a superior
process what was otherwise a task for 40
people over three months became a simple
job for three people in 40 hours all
victories for human-computer symbiosis
were more than 50 years into lick
lighters vision for the future and the
data suggest that we should be quite
excited about tackling this century’s
hardest problems man and machine in
cooperation together thank you