what if a generation from now companies
are unrecognizable now a number of years
ago I did a project with a large
Association focused on the media
industry at a time when it was just
beginning to experience the early stages
of disruption at that time I remember
having a conversation with one very
senior record exec who said that he
wasn’t worried about new tools like
Napster opening up a Pandora’s box of
change because quote CD sales have never
been higher well in retrospect we know
how that turned out
when when’s the last time you bought a
CD right now it’s very easy to look back
on an executive who completely missed
the way that something like digital
music would turn his whole industry
upside down and kind of roll our eyes
but the thing is people still get caught
in familiar frameworks and I would argue
that the shifts facing us now are
actually much bigger than those were
that we’re facing him then some of you
may have already heard some of the
predictions being made by tech industry
gurus like Elon Musk Eric Schmidt and
Bill Gates as they’ve tried to alert
people to the implications of some of
the technologies that their companies
are developing now words like robot a
cessation of work and even jobs
apocalypse are being thrown around and
they’re not exactly comforting if you’re
thinking in terms of your own personal
job security right the thing is if these
forecasts are even partially right then
we’re going to need to rethink the
frameworks we use to get things done on
just about every level and in a sense
that’s been the focus of my career
working along with partners to try to
track new thinking about the ways that
businesses could be structured and to
prototype new systems by combining
emerging technologies and emerging ideas
to get things done in new ways basically
you can kind of think as trying to
stress test the tools that we might use
to build future businesses now along
those lines some of the things that are
becoming possible now are enough to give
you goosebumps
things are moving quickly and there are
a number of factors in play but I want
to talk about two in particular just as
examples one is platforms and the other
is machine learning
so platforms are digital matchmaking
systems they’re all over the news right
now as discussions about companies like
uber Airbnb and lyft play out across the
headlines incidentally for context it’s
worth noting that uber is now the third
largest employer on earth by total
number of paychecks issued now because
these systems are good at matching
people with resources including Human
Resources they’re already having an
impact on for example hospitality taxi
services even consulting you know areas
where this kind of matching is critical
actually there’s a whole series of
platforms growing up right now around
the idea of connecting freelancers of
all kinds to all kinds of work a site
called upwork is the biggest of these
and covers everything from accounting to
graphic design now I expect to see more
of this kind of work
matching moving forward machine learning
on the other hand is a particularly
powerful kind of artificial intelligence
and is the technology at the heart of
for example Siri the iPhone personal
assistant or Watson the computer that
you may remember winning jeopardy a
number of years ago now some of the work
we’re doing suggests that while both
machine learning and platforms are very
powerful on their own their power could
really be unlocked when they’re combined
to give you a sense of where this could
be pushing companies I want to describe
one series of experiments that we’ve
been doing to try to test the limits and
see if it’s possible for a machine to
actually bring people together to get
work done we were particularly
interested in automating the management
of complex research processes we wanted
to create a push button system a kind of
Robo manager able to run workflows from
end to end ideally at a quality level
the same as or higher than those using
traditional approaches now the system
works with human assistants to
restructure these workflows like an
evolving assembly line
from a human resource standpoint it’s
the system that tries to find just the
right person for each job using those
freelancing platforms we mentioned and
machine learning so the Robo manager
will actually go out and try to find
talented people hire them give them a
digital workspace and then route them
colleagues to either team up answer any
questions or review their work in
essence what this had created is an
evolving assembly line for knowledge
work so what does this mean for the
project of rethinking companies and the
ways that we get things done well for me
the most exciting implication here is a
very big one for more than a generation
we’ve watched as a series of problems
too big for today’s organizational
systems to handle has piled up one on
top of another
slowly seizing up our economic
environmental and political systems with
a string of crises we can’t fully fix
think climate change or the financial
crisis but what if we’re now on the
threshold of being able to build
organizational power tools that are
actually able to scale to meet these
kinds of challenges and it’s not only
for profits that’ll be reshaped in the
wake of these you can imagine for
example somebody sitting down at a
terminal and writing a computer program
that’s able to save fight hunger it
could do this by intelligently
soliciting donations online and then
using these to acquire and then route
resources to the places where an AI
suggests they would do the most good
similarly can you imagine what our
disaster response say responding to all
of the fires we’ve been having would
look like if it was coordinated by the
same kind of technology that lyft uses
to route cards very soon I suspect we
will be relying on software to find both
emergency responders and the equipment
they need and to orchestrate them to do
the most good one thing we need to
understand here is how deep this
disruption goes and what we need to do
to adapt here a couple of fundamental
issues come to mind first we need to
rethink at an individual level jobs jobs
are not the only way to organize work
and already smart platforms are
moving away from something that looks
like jobs towards something that looks
more like workflows at an organizational
level we’re going to need to rethink the
concept of companies now companies are
not the only way to organize work and
we’re originally developed mostly to
coordinate industrial processes moving
forward it seems that we’re on the
threshold of organizations as a kind of
technology and a technology on the verge
of disruption at that now not too much
further out it’s possible to imagine for
example companies that behave like the
more benevolent cousins of today’s
ransomware computer viruses businesses
in this world could be pieces of
software designed to go out bring
together the resources necessary to make
things and to get things done so for
example what if twenty years from now
not only most cars but most companies
are actually self-driving in some sense
what if instead of facing a world of
inevitable technological unemployment as
robots take all of our jobs we actually
have the opportunity now to build
systems that are able to identify and
enhance the best talents that each of us
have to offer what if a generation from
now the world’s best leaders are you
know kind of like the world’s best chess
and go players today not people at all
but pieces of software in our lifetimes
organizational technologies are going to
dramatically expand the realm of
possibility and for me at least that’s
the kind of thing that can give you
goosebumps thank you
are unrecognizable now a number of years
ago I did a project with a large
Association focused on the media
industry at a time when it was just
beginning to experience the early stages
of disruption at that time I remember
having a conversation with one very
senior record exec who said that he
wasn’t worried about new tools like
Napster opening up a Pandora’s box of
change because quote CD sales have never
been higher well in retrospect we know
how that turned out
when when’s the last time you bought a
CD right now it’s very easy to look back
on an executive who completely missed
the way that something like digital
music would turn his whole industry
upside down and kind of roll our eyes
but the thing is people still get caught
in familiar frameworks and I would argue
that the shifts facing us now are
actually much bigger than those were
that we’re facing him then some of you
may have already heard some of the
predictions being made by tech industry
gurus like Elon Musk Eric Schmidt and
Bill Gates as they’ve tried to alert
people to the implications of some of
the technologies that their companies
are developing now words like robot a
cessation of work and even jobs
apocalypse are being thrown around and
they’re not exactly comforting if you’re
thinking in terms of your own personal
job security right the thing is if these
forecasts are even partially right then
we’re going to need to rethink the
frameworks we use to get things done on
just about every level and in a sense
that’s been the focus of my career
working along with partners to try to
track new thinking about the ways that
businesses could be structured and to
prototype new systems by combining
emerging technologies and emerging ideas
to get things done in new ways basically
you can kind of think as trying to
stress test the tools that we might use
to build future businesses now along
those lines some of the things that are
becoming possible now are enough to give
you goosebumps
things are moving quickly and there are
a number of factors in play but I want
to talk about two in particular just as
examples one is platforms and the other
is machine learning
so platforms are digital matchmaking
systems they’re all over the news right
now as discussions about companies like
uber Airbnb and lyft play out across the
headlines incidentally for context it’s
worth noting that uber is now the third
largest employer on earth by total
number of paychecks issued now because
these systems are good at matching
people with resources including Human
Resources they’re already having an
impact on for example hospitality taxi
services even consulting you know areas
where this kind of matching is critical
actually there’s a whole series of
platforms growing up right now around
the idea of connecting freelancers of
all kinds to all kinds of work a site
called upwork is the biggest of these
and covers everything from accounting to
graphic design now I expect to see more
of this kind of work
matching moving forward machine learning
on the other hand is a particularly
powerful kind of artificial intelligence
and is the technology at the heart of
for example Siri the iPhone personal
assistant or Watson the computer that
you may remember winning jeopardy a
number of years ago now some of the work
we’re doing suggests that while both
machine learning and platforms are very
powerful on their own their power could
really be unlocked when they’re combined
to give you a sense of where this could
be pushing companies I want to describe
one series of experiments that we’ve
been doing to try to test the limits and
see if it’s possible for a machine to
actually bring people together to get
work done we were particularly
interested in automating the management
of complex research processes we wanted
to create a push button system a kind of
Robo manager able to run workflows from
end to end ideally at a quality level
the same as or higher than those using
traditional approaches now the system
works with human assistants to
restructure these workflows like an
evolving assembly line
from a human resource standpoint it’s
the system that tries to find just the
right person for each job using those
freelancing platforms we mentioned and
machine learning so the Robo manager
will actually go out and try to find
talented people hire them give them a
digital workspace and then route them
colleagues to either team up answer any
questions or review their work in
essence what this had created is an
evolving assembly line for knowledge
work so what does this mean for the
project of rethinking companies and the
ways that we get things done well for me
the most exciting implication here is a
very big one for more than a generation
we’ve watched as a series of problems
too big for today’s organizational
systems to handle has piled up one on
top of another
slowly seizing up our economic
environmental and political systems with
a string of crises we can’t fully fix
think climate change or the financial
crisis but what if we’re now on the
threshold of being able to build
organizational power tools that are
actually able to scale to meet these
kinds of challenges and it’s not only
for profits that’ll be reshaped in the
wake of these you can imagine for
example somebody sitting down at a
terminal and writing a computer program
that’s able to save fight hunger it
could do this by intelligently
soliciting donations online and then
using these to acquire and then route
resources to the places where an AI
suggests they would do the most good
similarly can you imagine what our
disaster response say responding to all
of the fires we’ve been having would
look like if it was coordinated by the
same kind of technology that lyft uses
to route cards very soon I suspect we
will be relying on software to find both
emergency responders and the equipment
they need and to orchestrate them to do
the most good one thing we need to
understand here is how deep this
disruption goes and what we need to do
to adapt here a couple of fundamental
issues come to mind first we need to
rethink at an individual level jobs jobs
are not the only way to organize work
and already smart platforms are
moving away from something that looks
like jobs towards something that looks
more like workflows at an organizational
level we’re going to need to rethink the
concept of companies now companies are
not the only way to organize work and
we’re originally developed mostly to
coordinate industrial processes moving
forward it seems that we’re on the
threshold of organizations as a kind of
technology and a technology on the verge
of disruption at that now not too much
further out it’s possible to imagine for
example companies that behave like the
more benevolent cousins of today’s
ransomware computer viruses businesses
in this world could be pieces of
software designed to go out bring
together the resources necessary to make
things and to get things done so for
example what if twenty years from now
not only most cars but most companies
are actually self-driving in some sense
what if instead of facing a world of
inevitable technological unemployment as
robots take all of our jobs we actually
have the opportunity now to build
systems that are able to identify and
enhance the best talents that each of us
have to offer what if a generation from
now the world’s best leaders are you
know kind of like the world’s best chess
and go players today not people at all
but pieces of software in our lifetimes
organizational technologies are going to
dramatically expand the realm of
possibility and for me at least that’s
the kind of thing that can give you
goosebumps thank you
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