to tell you about two games of chess the first happened in one thousand nine hundred and ninety seven in which garry kasparov a human lost to 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 twenty years on and the greatest change in how we relate to computers is the ipad not hal the second game was a freestyle
their ability to coach and manipulate their computers to deeply explorespecific positions effectively counteracted the superior chess knowledge of the grandmasters and 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 artificialintelligence over the last fifty years it 's a sexy vision for sure many have embraced it it 's become the dominant school of thought in computer science but as we enter the era of big data of network systems of open platforms and embedded technology
i 'm talking about j c r licklider 's human computer symbiosis perhaps better termed intelligence augmentation i a licklider was a computer science titan who had a profound effect on the development of technology and the internet
his vision was to enable man and machine to cooperate in making decisions controlling complex situations without the inflexible dependence on predetermined programs
note that word cooperate licklider encourages us not 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 non linear approaches our creativity iterative hypotheses all very difficult if possible at all for computers to do licklider 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 we 're terrible at scale computation and volume we require high end talentmanagement to keep the rock band together and playing licklider foresaw computers doing all the routinizable 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 field brute force simply isn 't enough
foldit a game created by computer scientists illustrates the value of the approach
non technical non biologist amateurs play a video game in which they visually rearrange the structure of the protein allowing the computer to manage the atomic forces and interactions and identify structural issues this approach beat supercomputers fifty percent of the time and tied thirty percent of the time
foldit recently made a notable and major scientific discovery by deciphering the structure of the mason pfizer monkey virus a protease that had eluded determination for over ten years was solved was by three players in a matter of days perhaps the first major scientific advance to come from playing a video game
last year on the site of the twin towers the nine eleven memorial opened it displays the names of the thousands of victims using a beautiful concept called meaningful adjacency it places the names next to each other based on their relationships to one another friends families coworkers when you put it all together it 's quite a computational challenge
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 underlyingframework humans used that framework to design the final result
so in this case a computer had evaluated millions of possible layouts managed 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 's vision everywhere whether it 's augmented reality in your iphone or gps in your car 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 spent all of your time on the interface between man and machine specifically on designing away the friction in the interaction
and minimizing friction turns out to be the decisive 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 your credit card your 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 into 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 and organized crime has a lot in common with this audiencebrilliant people relentlessly resourceful entrepreneurial spirit
there 's a whole class of problems like this ones with adaptive adversaries they rarely if ever present with a repeatable pattern that 's discernable to computers instead there 's some inherentcomponent 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 and new behaviors but 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 artificialintelligence 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 terrorist 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 them in one place something that 's been nearly impossible to do before to some 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 intents so let 's explore through a couple of examples the impact that technologies built to drive human computer symbiosis have had in recent time
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
hugely important since between two thousand and three and two thousand and seven iraq had one thousand three 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 time frame 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 twenty percent of the foreign fighters were from libya fifty percent of those from a single town in libya hugely important since prior statistics put that figure at three percent
it also helped to hone in on a figure of rising importance in al qaeda abu yahya al libi a senior cleric in the libyan islamic fighting group in march of two thousand and seven he gave a speech after which there was a surge in participationamongst 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 ultimatelyresponsible 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 cheating would be jihadists in january two thousand and ten a devastating seven point zero earthquake struck haiti third deadliest earthquake of all time left one million people ten percent of the population homeless
one seemingly small aspect of the overall relief effort became increasingly important as the delivery of food and water started rolling january and february are 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 earthquakeleadership inside
so the question is which camps are at risk how many people are in these camps what 's the timeline for flooding and given very limited resources and infrastructure how do we prioritize the relocation
the human goal here was to identify camps for relocation based on priority need
the computer had to integrate a vast amount of geospacial information social media data and relief organization information to answer this question
by implementing a superior process what was otherwise a task for forty people over three months became a simple job for three people in forty hours
all victories for human computer symbiosis we 're more than fifty years into licklider 's vision for the future and the data suggests that we should be quite excited about tackling this century 's hardest problems man and machine in cooperation together thank you
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