OVERVIEW1 OF THE GLOBAL BUSINESS COURSE
SEPTEMBER 2015
(first draft incomplete)
Professor Robin Matthews
1
I summarize just part of the course and indicate how my contribution links with Dr Au Yeung
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OVERVIEW OF GLOBAL BUSINESS
INTRODUCTION
I think it will be helpful to provide an overview of the global business course (2nd - 5th). I
hope this will help you to prepare your brief for the assignment and to relate some of the
global issues raised on the course. I reproduce some of the slides we used in this paper and
remind you of the fuller presentations we have given you. I refer to them below and also
relate the various themes in the overview to some readings. You have the course text [13] and
general recommended readings and access to my dropbox. I will indicate some references and
refer to them by numbers in the reference list. In appendix 1 some papers, especially on the
role of IT in managerial work globally, are reproduced.
Figure I summarizes the essential themes of the course.
Figure 1
A complex adaptive system consists of a large number of interacting variables (large N).
Interaction means that they are interdependent. A complex system adapts to changes in the
system’s environment; hence a complex adaptive system (CAS). It evolves and new and
often unpredicted changes emerge. Sometimes CAS self organize to a critical or tipping
point when changes on all scales are possible. This is described as self ordered criticality
(SOC). [12, 8]
See Kevin Kelly (12) and Malcolm Glad well (8) not only for outlines of the concepts in
figure 1 but explanations of how they are interrelated and also related to other concepts such
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as path dependence and economies of scale and scope. Strategies for gaining scale and scope
economies are also associated with the idea of leveraging assets and more fundamentally,
leveraging capabilities. Carlesi et al. (5) see leveraging capabilities as natural ownership;
their idea being that possession of certain assets and capabilities enables organizations to
diversify and gain economies of scope and scale in new but related markets and products.
Complex behaviour of large systems with large numbers of inter dependent variables (large
N), in nature, business, piles of sand grains (sand piles), ecological systems, and the global
economy for example, often gravitate to a situation where they are poised at a critical state (a
tippling point) where small disturbances including butterfly effects, infectious losses of
confidence, may lead to avalanches, earthquakes, or revolutions or trigger bubble bursts in
Lehmann, Madoff or Northern Rock type financial collapses.
Per Bak as far as I know is the originator of the sand pile thought experiment which links
with those systems self organize (gravitate) to a critical state. From this comes the idea of
management at the edge of chaos associated with Kauffman and popularized by McKinsey.
Kauffman and Beinhocker [(4)] apply ideas from complexity to management.
A critical state may be a take-off point when poor countries become EM’s, software
companies reach a critical mass or some individual or group is at the point of scientific
advance, innovation or innovation
Concepts in figure 1 are interrelated in ways I have indicated above. They are related also to
concepts such as Black Swans (power laws), singularity, punctuated equilibrium and phase
transitions. The characteristic aspect shared by all these concepts is the idea of a sudden,
dramatic change, a break with the past, a renaissance, a new way of looking at the world or a
mind shift. provide in various ways, illustrations of all the above concepts and indicate their
applications to global business.
The idea of connectedness and interdependence is perhaps best illustrated by networks.
Networks consist of vertices (nodes) and edges (links) that connect them. Viewing an
organization (or a group of organizations) as a network as in figure 1, there is a choice as to
which properties. Vertices (A, B, .....) in figure 2, may refer to coalitions within organizations
(teams, projects, value chains), or between them (supply chains, alliances, mergers).
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Networks complexity and grammar
Networks are way of illustrating complexity and globalisation and the concept of
organizational grammar or the grammar of networks; nodes or vertices being the phenomena
we are discussing, the morphology or parts of speech in a system and edges being the nature
of the linkages between them.
Figure 2
In figure 2; (a) is an undirected network in which all the nodes are the same size and
significance and the vertices are undirected, that is they link in both directions; in (b) nodes
are distinct, they may for example refer to different phenomenon are of different types; in (c)
both the nodes and the strength of connections have different weights; in (d) edges are
directed.
Nodes in (b) may be business functions, structures, individuals, teams and hierarchies,
operations all linked to a central hub, and some linked to each other and some not in hard or
soft systems or architectures.
Normally decisions in large organizations are distributed. Not a single decision or strategy,
but numerous decisions or strategies taking place concurrently and consecutively and
presenting enormous co-ordination problems even in small scale organizations like families
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or small teams, and increasing in complexity as the size of organizations increase. Such was
the too big to fail problem in the financial crisis that began in 2008.
Figure 3 illustrates the complexity and connectivity of the global financial system in the early
twenty first century. The size of the nodes is proportional to the size of banking systems in
various countries; there are many connections, some strong (thick lines) involving large
financial connections between financial systems, some relatively weak. Some systems
connected, some are outliers. Some systems, the US and UK financial systems are connected
to many other systems. Some indeed most of them have relatively few connections. This
property, known as a small world property seems to be a feature of real world systems as they
evolve.
The small world property of systems is closely related to power laws, or Black Swans as
power laws are also described. A power law describes a situation in which some nodes, a
very few of them are connected to many others and the vast majority of nodes are connected
to few others.
Figure 3
The outer dynamics of organizations can be considered as networks; linked macro-economic,
technological, demographic, social, political, ecological factors (to list only a few). Global
businesses are particularly complex networks. They are coalitions of business units, projects,
teams, partnerships and so on.
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Managing at the edge of chaos
Kauffman is the originator of ‘managing at the edge of chaos, the idea being that if things are
too ordered and structured then organizations are frozen into their current system state and
find it difficult to break out of it by innovation, new thinking, reorientation of strategies of the
past into new areas. On the other hand, if they are in a state of chaos everything is in flux and
it is difficult or impossible either to attain stability. There is, according to Kauffman a point
between order and chaos, the ‘edge of chaos’ where organizations become both flexible and
controllable. Kauffman’s explanation of this, I find unsatisfactory. It is based on how much
interconnected organizations are. If assets and/capabilities are too interconnected then they
become chaotic. If there is a small degree of interconnectedness then they become too fixed.
The edge of chaos, he says exists when no part of a system is connected to more than 2 other
parts. I think is unreal. Organizations that remain stable and successful are much more
connected than that. For this reason I introduced the idea of grammar as a stabilising factor.
The current phase of globalisation
Globalisation is not a new phenomenon. There have been many phases. The current phase
represents an evolution of the late nineteenth early twentieth phase punctuated by the
economic blowback of world wars (WW1 and WW2), depression and protectionism. Calling
both WW’s world wars is significant. Twentieth century warfare was global. In the cold war
(CW) period the process of globalisation resumed with, for example, the United Nations, the
World Bank, the IMF, and in the developed nations and beginning in the late 50’s the Age of
High Mass Consumption.
But globalisation truly took off in the 1970’s and 80’s, initiated by internationalising money
via flexible (or flexibly managed) exchange rates by the Nixon Administration in the USA,
which enabled foreign direct investment (FDI). Financial deregulation further deregulated
money. Advances in science led a technological revolution based on information,
communication and biotechnology. International finance, technology, and competition
interacted in the positive feedback loop, illustrated in figure 2, as firms sought cheap labour,
global demand and lucrative international investment opportunities.
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Figure 4
Poor nations became emerging nations (EM’s). USA consumption, fed by sovereign wealth
funds (SWF’s) sustained demand up to the global recession beginning in 2008. [15]
As a result of bailout monetary policies, global recession did not descend into global
depression, though this recession endured for a longer period than the depression of the
1930’s. Repercussions are still with us; the crises in the Eurozone and overcapacity in China.
To an extent, Chinese investment demand compensated for falling USA demand. But the
impacts of world recession led to world overcapacity (in relation to demand); and slowdown
in growth worldwide. [21]
The global economy as a complex adaptive system
Many aspects of the global economy can be described as networks; of coalitions within
coalitions ranging from the massive coalitions such as the world wide world wide web
(WWW) itself which embraces intranets that exist within formal and informal organizations,
including social, business, market, religious networks.
The direction of the economy emerges from the interaction of many dispersed and
interdependent units (firms, institutions, people, demographics, urbanization, cultures,
religions, ethnicities personalities and so on) in parallel. The action of any one unit depends
on the state and action of others units. The global economy has many levels of interaction;
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coalitions at many levels ranging from teams to business units and mergers. Tangled
interactions (associations, communications) occur within and between levels. Coalitions are
building blocks. They are recombined and revised continually as the system accumulates
experience and adapts. There are many niches created by new technologies that can be
exploited by adaptation. Thus large and small local and global firms coexist and coevolve on
the global economy; glocalisation.
There is no universal super-competitor, such as the USA or China or massive corporation or
institution that can fill all niches; often they are helpless, global terrorism for example. There
are so many niches serving many purposes and needs the system operates far from
equilibrium or optimum. Despite the talk about progress and world growth recent
developments have seen a resurgence of real politique; struggle for resources, struggle for
dominance.
Demographics
On average the global growth rate between 1964 and 2014 was 3.8%. Exceptional world
growth in the late 20th and early 21st century is often credited to science based technology, but
the biggest contributor was the increase in world population and urbanisation. For the first
time, worldwide urban population exceeds rural population. The global labour force has risen
fourfold over the past two decades and developed nations (DM’s) access the increasing
labour supply globally, through trade, offshoring and outsourcing, alliances, joint ventures
and migration.
The EM’s
During the 1990s the contribution of the emerging economies averaged 40%, rising to 58%
for the years between 2000 and 2007. According to the IMF almost three-quarters of global
growth in 2015 comes from China and other EM’s.
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Informationalism
What is new about informationalism? Production is information, transmitted from sender to
receiver; information in resources combined, transformed into goods or services and
transmitted to consumers to feed needs, utility, satisfaction, desire and craving. Money is
information. Informationalism is the result of the exponential speed and scale of
developments in information, media, communication and bio technologies. Such technologies
have shaped globalisation and modern capitalism. They have created new industries and
influenced all industries (global and domestic) and opened up new possibilities ranging from
conceivable possibilities such as Google implants in the brain and barely conceivable event
horizons or technological singularity.
Many aspects of life in Europe in the 1940’s and 50’s would have been recognisable to
people in the 1870’s or 80’s. In comparison, life in 2011 is radically different from the
1960’s. The comparison can be illustrated by Moore’s law of integrated circuits named after
Gordon Moore, of Intel; the idea being that innovation in microchips gives exponential
increase in chip technology, such that every two years you get twice as much power and
memory for the same price: hence the transformation of many aspects of industries, work and
life over the last 30 years or so and the emergence of a new phase of globalisation, and
capitalism. The WWW enables information to be communicated, accessed and shared over
the Internet using one of many protocols including HTTP. The WWW Web uses browsers,
for example Explorer, Bing, and Firefox, to access web pages, containing sound, graphics,
videos as well as text. Web pages are linked by hyperlinks. Web documents also contain
graphics, sounds, text and video.
The Internet is made up of networks within networks, connecting millions of computers and
enabling communication between them using a variety of protocols or languages to transmit
information.
Global recession
The global economy seemed to gravitate to SOC in 2008. As with the tower Babel, the
network of communication broke down and the positive feedback system that had brought a
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long global upswing from the 1990’s to 2007, with global growth averaging around 4% per
annum mostly concentrated in emerging nations. This was followed by a long recession, the
effects of which are still with us, resulting in a global loss of between $60 and $200 trillion
[16, 18, 22]
Figure 5
THE EVOLUTION OF INDUSTRIES AND FIRMS
Industries are in a constant state of flux. Flux, change and evolution take many forms. [14,
17]
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Corporations may appear at the macro level may appear to be stable, but their inner coalition
structure is constantly changing. Macroscopically they may appear stable but microscopically
they are replete with change and restructuring.
The more macroscopic (coarse grained) the change, the more it is noticed by observers of
organizations. Internally change may be experienced as trauma. Sometimes change at the
macro level is so dramatic that it appears as a phase transition; utter change into something
quite different, as for example the transformation of ice into liquid and gas in response to
temperature increases.
Coalitions
Coalition refers to a formal or informal relationship between individuals or groups. It
includes formal pacts, treaties, covenants, alliances and informal relationships, partnerships,
marriages, clubs, societies, unions, peace movements, faith movements and occupy Wall
Street. NATO, the EU, the UN, the Eurozone, the ILO, the IMF, East African Community
(EAC), West African Economic and Monetary Union (UEMOA), the UAE, ASEAN, the
Union of South American Nations (USAN), and OPEC, are but a few examples of
international and regional coalitions. Generally coalitions are formed to balance their own
and each other’s interests through cooperation.
Central to the global business course is the insight that the evolution of institutions and
corporates public and private, small and large, that is organizations generally, takes place
through the formation and re- formation of coalitions.
Organizations are composed of coalitions within coalitions, integrated hierarchies of
activities. At the base of the hierarchy coalitions of
fundamental tasks within teams and
coalitions of the teams that make up the firm’s projects and combined into coalitions of
projects in business units. Corporations are coalitions of business units. Mergers are
coalitions of firms or corporations. Corporations are coalitions, as supply chains, joint
ventures, partnerships and alliances.
The process of forming larger and more complex coalitions, as we ascend the hierarchy of the
organization matrix, opens up of new possibilities: new synergies from the coalitions that
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emerge that are the basis of evolution at different levels of hierarchy. Thus the organization
matrix approach encompasses evolution at industry level, the sector level and the firm and
intra firm level.
Evolution of firms and industries and leveraging capabilities
New Darwinism maintains that evolution takes place at the genetic level. Evolution
represents a change in the genetic structure of a population. Natural selection operates on the
phenotype. For example within species competition for scarce resources in a challenging
environment leads some members of a population reproducing more successfully than others,
because of their relatively favourable genetic structure. As environmental conditions change,
reproductive success may be favoured by a different genetic structure. Thus the genetic
structure of populations change. [20]
Is there a corresponding process in firms and industries? I think so. But the analogy should
not be overextended. The phenotype level corresponds to a firm’s performance (financial
ratios, sales, profit and so on). Core capabilities correspond to the genetic level of
organizations. The process of becoming global is one of leveraging core capabilities
internationally.
As with biological populations there is usually not a one to one relationship between genes
and characteristics (phenotypes). Rather relationships between groups of genes determine
characteristics. Similarly core capabilities are founded upon linkages of assets, synergies
between them. Assets may be tangible or intangible, or more realistically complex mixes of
tangible and intangible assets; physical and human capital, facilities, structures, hierarchies,
infrastructure, brands, reputation, trust, culture mind sets and personalities. All these form
part of grammar that I describe below.[18]
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Country specific and firm specific advantages
Global business theory is a subset of international trade theory, focussing on firms that
developed business internationally. The East India Company is an early example. Unilever,
Proctor and Gamble, Mars, and the giant oil companies are early examples. Developments in
statistical and econometric analysis publication of national and international trade and FDI
statistics, enabled scholars to identify country specific advantages (CSA’s) as motivators of
firms to become international and multi-national enterprises (MNE’s). MNE’s can leverage
advantages of scale (economies of scale) and diversification based on core capabilities
(economies of scope) and increasing returns from developing networks of related products
internationally (demand increasing economies of scale. These scale, scope and demand
increasing economies of internationalising are summarized under the blanket heading of firm
specific advantages (FSA’s).[21]
The idea of CSA’s has been significantly extended by network and complexity theory.
Emergence of new firms and industries in a country are path dependent on the extent to
which countries produce a diversity of products and services; the greater the variety of their
industrial base, the greater the opportunity for a country to develop new products and
services. Long steps into entirely new varieties into new areas are much more difficult than
short steps that extend and link their product base via small innovations.[5]
The gravity equation
Distance remains a key factor as summarized by the gravity equation which states that the
value of trade between nations (TAB) is positively related to their respective gross national
products (GNPA and GNPB) and inversely related to the distance that separates them DAB.
[6,9]
TAB
(GNPA ) a .  GNPB 

DAB
b
1
a  b 1
Clearly the gravity equation (1) is a simplification, though regression coefficient estimation
(relating TAB to GNPA, GNPB and DAB equations appear to be significant and a = b = 1.
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Are the relationships in the gravity equation stronger if we take into account international
business theories of FSA’s and CFA’s; as in equation (2)? Further research may reveal new
hypotheses embedded in (2).2
 (GNPA ).  GNPB 

VAB  G 
, CFAi , FSAj , u 
DAB


 2
i = 1, 2, ….., n; j = 1, 2, ……,m
Expression (2) makes the value of trade between country A and B is determined (a function
of the gravity equation and country specific advantages CFAi and firm specific advantages
FSAj ‘s and a random factors u. The subscripts indicate that there are a variety of CFAi ’s
and FSAj ’s.
Responsiveness and integration
So far our summary focuses on advantages of scale of itself (scale scope and demand
increasing economies of scale). The shorthand for such advantages are integration
advantages. Detailed case studies reveal the importance of corporate responsiveness to
aspects of grammar that distinguish, some of which are shared globally and some of which
are unique to one national market or another. Responsiveness can refer to responsiveness to
national and local laws, regulations, customs and demographics. These represent
responsiveness to unique formal conditions. Informal, difficult to measure, and elusive local
and national conditions may be much more significant; national cultures, traditions, customs,
norms, personalities and mind sets.
Two by two matrices are popular in management studies. One such matrix is the integration
responsiveness matrix developed by Ghoshal and Bartlett (G&B). Transnational businesses
are said to be strong in both respects. Multinationals are according to G&B relatively strong
on responsiveness. Global businesses are relatively strong on integration.
2
The exponents a and b are omitted in (2). Maybe the the exponents when (2) is estimated differ from 1.
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Of course at a general level, G&B’s categorization into integration and responsiveness is
quite broad-brush. Their later work deconstructs organizations into sub coalitions; business
functions, divisions and subsidiaries of businesses. This allows for mixed emphasis; R&D
may be centralised and integrated, marketing, branding, promotion may be partly centralised
to gain integration advantages.[2, 10, 20,]
Figure 6
The integration responsiveness grid reproduced from Bartlett and Ghoshal 1985
Grammar
I summarize formal and informal rules with the term grammar. Individual organizations have
their own (organizational) grammar. The variety of ways in which integration and
responsiveness is expressed are also determined by grammar.
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Figure 7
References
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1. Arthur, Brian. "The Second Economy." Mckinsey.
http://www.mckinsey.com/insights/strategy/the_second_economy.
2. Bartlett, Christopher A., and Sumantra Ghoshal. Transnational Management: Text,
Cases, and Readings in Cross-border Management. Chicago: Irwin, 1995.
3. Bartlett, Christopher. "Global Strategies for MNCs: Christopher A. Bartlett &
Sumantra Ghoshal." Global Strategies for MNCs: Christopher A. Bartlett & Sumantra
Ghoshal. Accessed September 15, 2015.
http://www.businessmate.org/Article.php?ArtikelId=13.
4. Beinhocker, Eric. "Adaptable Corporation." Mckinsey. www.synetzinternational.com/Artikel_Adaptable_corporation_McK.pdf.
5. Berraby, David. "Between Chaos and Order: What Complexity Theory Can Teach
Business." Strategy+business. Accessed September 15, 2015. http://www.strategybusiness.com/article/15099?gko=73fbc.
6. Carlesi, L., D. Verster, and F. Wenger. "The New Dynamics of Managing the
Corporate Portfolio." The New Dynamics of Managing the Corporate Portfolio.
Accessed September 15, 2015.
http://www.mckinsey.com/insights/corporate_finance/the_new_dynamics_of_managi
ng_the_corporate_portfolio.
7. CHEYNEY, THOMAS. "The Gravity Equation in International Trade: An
Explanation." NBER. Accessed September 15, 2015.
http://www.nber.org/papers/w19285.
8. "The End Of Globalization (ebook) by Alan Rugman." EBooks.com. Accessed
September 12, 2015. http://www.ebooks.com/783679/the-end-ofglobalization/rugman-alan/.
9. Gladwell, Malcolm. The Tipping Point: How Little Things Can Make a Big
Difference. Boston: Little, Brown, 2000.
10. "THE GRAVITY MODEL OF TRADE." Wikipedia. Accessed September 15, 2015.
http://en.wikipedia.org/wiki/Gravity_model_of_trade.
11. Harzing, Anne-Wil. "An Empirical Analysis and Extension of the Bartlett and
Ghoshal Typology of Multinational Companies." Journal of International Business
Studies J Int Bus Stud 31, no. 1 (2000): 101-20.
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12. Haussman, Ricardo. "Networks Understanding Networks, Pt. 4: Ricardo Hausmann."
MITLABS. Accessed September 15, 2015.
http://www.youtube.com/watch?v=496ujSBhVpM.
13. Kauffman, Stuart. "Kauffman -- The Origins of Order: Self-Organization and
Selection in Evolution -- 1993." Kauffman -- The Origins of Order: Self-Organization
and Selection in Evolution -- 1993. Accessed September 15, 2015.
http://groups.lis.illinois.edu/amag/langev/cited2/kauffmanthinsoforderselfonevolution.
html.
14. "Kevin Kelly’s NEW RULES FOR THE NEW ECONOMY." Kevin Kelly’s NEW
RULES FOR THE NEW ECONOMY. Accessed September 15, 2015. http://www.cspartner.com/Kevin%20Kelly.htm.
15. Lasserre, Philippe. Global Strategic Management. New York: Palgrave Macmillan,
2003.
16. Lemmons, Aurelie. "Managing Churn to Maximise Profits."
Www.hbs.edu/faculty/Pages/download.aspx?name=14-020.pdf.
http://hbswk.hbs.edu/item/7350.html.
17. Manyika, James, et al.. "Global Flows in the Digital Age." Global Flows in a Digital
Age: How Trade, Finance, People, and Data Connect the World Economy.
http://www.mckinsey.com/insights/globalization/global_flows_in_a_digital_age.
18. Matthews, Robin, and Issam Tlemsani. "The Financial Tower of Babel: Roots of
Crisis." I J Islam Mid East Fin and Mgt International Journal of Islamic and Middle
Eastern Finance and Management 3, no. 4 (2010): 334-50.
19. Matthews, Robin. "The Eurozone as a Koan." Robindcmatthews.com. Accessed
September 15, 2015. http://robindcmatthews.com/blogs/18.
20. Matthews, Robin. Is Global Singularity coming? 4th World Conference on Global
Civilisation 2013.
21. "The New Dynamics of Managing the Corporate Portfolio." The New Dynamics of
Managing the Corporate Portfolio. Accessed September 12, 2015.
http://www.mckinsey.com/insights/corporate_finance/the_new_dynamics_of_managi
ng_the_corporate_portfolio.
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22. "New Rules for the New Economy by Kevin Kelly - Read EBook." Scribd. Accessed
September 12, 2015. https://www.scribd.com/book/190939688/New-Rules-for-theNew-Economy.
23. "On the Origin of Strategies." "" by Beinhocker, Eric D. Accessed September 12,
2015. https://www.questia.com/library/journal/1G1-59427148/on-the-origin-ofstrategies.
24. "On the Origin of Strategies." "" by Beinhocker, Eric D. Accessed September 15,
2015. https://www.questia.com/library/journal/1G1-59427148/on-the-origin-ofstrategies.
25. Paul Krugman, and Robin Wells. "Why the Slump Continues." New York Review of
Books. http://www.nybooks.com/articles/archives/2010/sep/30/slump-goes-why/.
26. Rugman, Alan, Alain Verbeke, and Wenlong Yuan. "Re-conceptualizing Bartlett and
Ghoshal's Classification of National Subsidiary Roles in the Multinational
Enterprise." Journal of Management Studies, 2010.
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International Business Theory and Beyond." Management International Review
Manag Int Rev 51, no. 6 (2011): 755-86.
28. Rugman, Alan M., and Alain Verbeke. "A New Perspective on the Regional and
Global Strategies of Multinational Services Firms." Handbook of Research on
International Strategic Management, 2012, 257-70.
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http://gladwell.com/the-tipping-point/.
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2013. www.mckinsey.com/.../hal_varian_on_how_the_web_challenges_manag...
APPENDIX 1
Miscellaneous papers from the web
Some papers that might be of interest
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For further materials see my website Robindcmatthews.com
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APPENDIX 1
Hal Varian on how the Web challenges managers
Google’s chief economist says executives in wired organizations need a sharper
understanding of how technology empowers innovation.
JANUARY 2009
Source: Business Technology Office
More than ten years into the widespread business adoption of the Web, some managers still
fail to grasp the economic implications of cheap and ubiquitous information on and about
their business. Hal Varian, professor of information sciences, business, and economics at the
University of California at Berkeley, says it’s imperative for managers to gain a keener
understanding of the potential for technology to reconfigure their industries. Varian, currently
serving as Google's chief economist, compares the current period to previous times of
industrialization when new technologies combined to create ever more complex and valuable
systems—and thus reshaped the economy.
Varian spoke with McKinsey’s James Manyika, a director in the San Francisco office, in
Napa, California, in October 2008. Watch the video or read the transcript of his comments
below.
Hal Varian on how the Web challenges managers
Google’s chief economist on how technology empowers innovation.
Launch Interactive
Back to top
On flexible innovation
We’re in the middle of a period that I refer to as a period of “combinatorial innovation.” So if
you look historically, you’ll find periods in history where there would be the availability of a
different component parts that innovators could combine or recombine to create new
inventions. In the 1800s, it was interchangeable parts. In 1920, it was electronics. In the
1970s, it was integrated circuits.
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Now what we see is a period where you have Internet components, where you have software,
protocols, languages, and capabilities to combine these component parts in ways that create
totally new innovations. The great thing about the current period is that component parts are
all bits. That means you never run out of them. You can reproduce them, you can duplicate
them, you can spread them around the world, and you can have thousands and tens of
thousands of innovators combining or recombining the same component parts to create new
innovation. So there’s no shortage. There are no inventory delays. It’s a situation where the
components are available for everyone, and so we get this tremendous burst of innovation
that we’re seeing.
On corporations and work
The question is, “What are other periods where we saw technology influence the way
organizations work?” One nice example comes from the works of Alfred Chandler, where he
describes how the telegraph and the railroad had a big impact on the development of the
modern corporation. And this was a synergistic operation: one, you had to have a large
organization to manage these technologies, and two, you had to have the communications and
transportation infrastructure to enable the management at a distance.
So I think now, with what we’re seeing with mobility, we’re going to have a totally different
concept of what it means to go to work. The work goes to you, and you’re able to deal with
your work at any time and any place, using the infrastructure that’s now become available.
At the base, there’s the innovation infrastructure making better, faster, cheaper networks.
There’s the improvement in the human–computer interface because the big challenge in
mobile communication has always been dealing with this—quite limited—interface. But
then, the kinds of innovations I think will arise on top of that will be innovations in how work
is done. And that’s going to be one of the most exciting aspects, in my opinion.
If you look at the beginning of the 20th century, we saw the rise of mass production. Henry
Ford and the entire team were down on the factory floor raising this, lowering that, speeding
up the assembly line, changing the way things were built, and were able to extract far more
efficiencies than were available before. I think the same thing is happening now with digital
technology. When we’re all networked, we all have access to the same documents, to the
same capabilities, to this common infrastructure, and we can improve the way work—
intellectual work, knowledge work—flows through the organization. And again, in my
opinion, that will lead to a substantial advantage in terms of productivity.
On free goods and value
Back in the early days of the Web, every document had at the bottom, “Copyright 1997. Do
not redistribute.” Now every document has at the bottom, “Copyright 2008. Click here to
send to your friends.” So there’s already been a big revolution in how we view intellectual
property. So it’s not so much the question of what’s owned or what’s not owned. It’s a
question of how can you leverage the assets you have to realize the most value.
I think that the availability of these very inexpensive platforms you’re creating, in
disseminating content, means that it’s become intensely competitive. The content is as
valuable as it ever was, it’s just the competition that’s pushed the prices down to something
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that approximates zero. So it’s not something that the content producers necessarily embrace,
but it’s something they’re forced into by the nature of the technological change.
In these models, there is typically a revenue-generating component somewhere in the value
chain. And most commonly today we’re seeing it on the advertising side. To look at this from
a historical perspective, it’s really not so new. If you look at the 1920s, the technological
question in the ’20s was, “How can we build a business model around broadcast radio?” And
nobody really had a good idea. And back in the mid-1990s we asked, “How can we build a
business model around the Internet?” And the preferred model at the time was a
micropayments system. That never happened, for some reasons, but what did happen instead
is we moved into the advertising model, and the advertising’s model been phenomenally
successful.
We have to look at today’s economy and say, “What is it that’s really scarce in the Internet
economy?” And the answer is attention. [Psychologist] Herb Simon recognized this many
years ago. He said, “A wealth of information creates a poverty of attention.” So being able to
capture someone’s attention at the right time is a very valuable asset. And Google really has
built an entire business around this, because we’re capturing your attention when you’re
doing a search for something you’re interested in. That’s the ideal time to show you an
advertisement for a product that may be related or complimentary to what your search is all
about.
On workers and managers
I keep saying the sexy job in the next ten years will be statisticians. People think I’m joking,
but who would’ve guessed that computer engineers would’ve been the sexy job of the 1990s?
The ability to take data—to be able to understand it, to process it, to extract value from it, to
visualize it, to communicate it—that’s going to be a hugely important skill in the next
decades, not only at the professional level but even at the educational level for elementary
school kids, for high school kids, for college kids. Because now we really do have essentially
free and ubiquitous data. So the complimentary scarce factor is the ability to understand that
data and extract value from it.
I think statisticians are part of it, but it’s just a part. You also want to be able to visualize the
data, communicate the data, and utilize it effectively. But I do think those skills—of being
able to access, understand, and communicate the insights you get from data analysis—are
going to be extremely important. Managers need to be able to access and understand the data
themselves.
You always have this problem of being surrounded by “yes men” and people who want to
predigest everything for you. In the old organization, you had to have this whole army of
people digesting information to be able to feed it to the decision maker at the top. But that’s
not the way it works anymore: the information can be available across the ranks, to everyone
in the organization. And what you need to ensure is that people have access to the data they
need to make their day-to-day decisions. And this can be done much more easily than it could
be done in the past. And it really empowers the knowledge workers to work more effectively.
On computer monitoring and risks
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One of the really interesting phenomena that’s been going on in the last 20 years is what I call
“computer-mediated transactions.” So now, in the middle of almost every transaction from
person to person or organization to organization, there’s a computer. And the computer can
monitor that transaction, record the information, collect the data, and assure that the
transaction is carried out the way it was intended to be carried out. So one of the subtle
implications of this is you can now write contracts and make contracts enforceable that
simply weren’t enforceable before.
Let me give you an example. Suppose you go rent a car and they say, “Hey, we’ll give you
$10 off if you don’t go over the speed limit.” Well, that might sound like a good deal, but
what’s to keep you from going over the speed limit? Well, the answer is now they’ve got a
transponder in the trunk and it will monitor your behavior and charge you accordingly. And
the same thing happens with semitrucks: virtually every semi on the road today has a
computer in it. And that computer improves the logistics. It monitors the performance of the
driver and it helps things get to the consumer more quickly. So there are a lot of capabilities
of that sort that allow you to contract on terms that were just not available to you before.
[At the same time,] you get a new technology in and people are excited about the positive
sides of it. Then you see there are also some negative aspects. And you’ll have a regulatory
infrastructure that arises to deal with those. I think everybody is very excited about the
intended aspects of this technology—the fact that you can personalize, the fact that you can
monitor, the fact that you can provide products that are more closely suited to a consumer’s
interests and needs. What people are worried about are the unintended consequences, the
downsides, the negative sides, the security, the identity theft, the possibility of extortion or
embarrassment. These are the problems: not what people want to do but what could happen if
these technologies weren’t appropriately managed.
On reshaping industries
We’re obviously going to see enormous change in the traditional marketing industry. You
look at TV, you look at print, you look at radio and other media of that sort. On the Internet,
we’ve learned to measure advertising effectiveness, and the challenge now is to move those
same effectiveness measures over to the offline media.
That can be done. I think we’re going to see vast improvements in how those industries
function in the future. And in general, if we look at service industries—well, everybody I
think is in agreement that we’re going to see lots of efficiency improvements in services,
because we do have this network capability. We have the technological infrastructure. We
can improve communication flows. The second beneficiaries of that will be with service
industries who’ve already seen a lot of advances in manufacturing productivity. And the
tough nut is the one we’re working on cracking now.
What I actually work on to a large extent is a current feeding of the auction model that we
have at Google. As you know, all of our ads are sold by auction. That’s a relatively novel
pricing mechanism in the ad world. And there’re a lot of intricacies that involve how you
manage that. We’d like to extend that model to the offline world: to radio, TV, print, and
other media. It’s a model that was enabled by the Internet. It’s not something you could’ve
done without that information technology there. And it’s a great model for all sorts of
resource allocation issues.
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I think the people who originally designed the model way back in 2001 had a very, very
useful insight. They recognized that the content provider has impressions to sell. So you’ve
got some space in your TV show. You’ve got some space on your page. You’ve got some
space that’s available to put an ad. But what the advertiser wants to pay for is clicks or
conversions or visits. So they don’t really care how many impressions they show. Normally,
what they care about is getting people into their store and, ultimately, getting people to
purchase. So you have to build a system that allows the publisher to sell impressions but the
advertiser to buy clicks. And I think we’ve managed to accomplish that in a nice, elegant
way.
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BECOMING MORE STRATEGIC: THREE TIPS FOR ANY EXECUTIVE
You don’t need a formal strategy role to help shape your organization’s strategic direction.
Start by moving beyond frameworks and communicating in a more engaging way.
JULY 2012 • Michael Birshan and Jayanti Kar
Source: Strategy Practice
In This Article


About the authors
Comments (10)
We are entering the age of the strategist. As our colleagues Chris Bradley, Lowell Bryan, and
Sven Smit have explained in “Managing the strategy journey,” a powerful means of coping
with today’s more volatile environment is increasing the time a company’s top team spends
on strategy. Involving more senior leaders in strategic dialogue makes it easier to stay ahead
of emerging opportunities, respond quickly to unexpected threats, and make timely decisions.
This is a significant change. At a good number of companies, corporate strategy has long
represented the bland aggregation of strategies that individual business unit heads put
forward.1 At others, it’s been the domain of a small coterie, perhaps led by a chief strategist
who is protective of his or her domain—or the exclusive territory of a CEO.
Rare is the company, though, where all members of the top team have well-developed
strategic muscles. Some executives reach the C-suite because of functional expertise, while
others, including business unit heads and even some CEOs, are much stronger on execution
than on strategic thinking. In some companies, that very issue has given rise to the position of
chief strategy officer—yet even a number of executives playing this role disclosed to us, in a
series of interviews we conducted over the past year, that they didn’t feel adequately prepared
for it.
This article draws on those interviews, as well as our own and our colleagues’ experience
working with numerous executives developing strategies, adapting planning approaches, and
running strategy capability-building programs. We offer three tips that any executive can act
on to become more strategic. They may sound deceptively simple, but our interviews and
experience suggest that they represent foundational skills for any strategist and that putting
them into practice requires real work. We’ve also tried, through examples, to present practical
ways of acting on each suggestion and to show how doing so often means augmenting
experience-based instincts with fresh perspectives.
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1. Understand what strategy really means in your industry
By the time executives have reached the upper echelons of a company, almost all of them
have been exposed to a set of core strategy frameworks, whether in an MBA or executive
education program, corporate training sessions, or on the job. Part of the power of these
frameworks is that they can be applied to any industry.
But that’s also part of the problem. General ideas can be misleading, and as strategy becomes
the domain of a broader group of executives, more will also need to learn to think
strategically in their particular industry context. It is not enough to do so at the time of a
major strategy review. Because strategy is a journey, executives need to study, understand,
and internalize the economics, psychology, and laws of their industries, so that context can
guide them continually.
For example, being able to think strategically in the high-tech industry involves a nuanced
understanding of strategy topics such as network effects, platforms, and standards. In the
utilities sector, it involves mastery of the economic implications of (and room for strategic
maneuvers afforded by) the regulatory regime. In mining, leaders must understand the
strategic implications of cost curves, game theory, and real-options valuation; further, they
must know and be sensitive to the stakeholders in their regulatory and societal environment,
many of whom can directly influence their opportunities to create value.
There is a rich and specialized literature on strategy in particular industries that many
executives will find helpful.2 Tailored executive education courses can also be beneficial. We
know organizations that have taken management teams off-site to focus not on setting
strategy but on deepening their understanding of how to be a strategist in their industries. For
example, one raw-materials player headquartered in Europe took its full leadership team to
Asia for a week, in hopes of shaking up the team’s thinking. Executives explored in depth 20
trends that would shape the industry over the next decade, discussing both the trends
themselves and their implications for the supply of and demand for the organization’s
products.3 They also looked across their industry’s full value chain to understand who was
making money and why—and how the trends would change that. A number of the executives
in the discussion were surprised by how much value certain specialized intermediaries were
capturing and others by how the organization was losing out to competitors that were
financing retailers to hold their inventory. The executive team emerged with a clearer
appreciation of where the opportunities were in its industry and with ideas to capture them.
Building this kind of industry understanding should be an ongoing process not just because
we live in an era of more dynamic management4 but also because of the psychology of the
individual. Experience-based instincts about “the way things work” heavily influence all of
us, making it hard, without systematic effort, to take advantage of emerging strategic insights
or the real lessons of an industry’s history. War games or other experiential exercises are one
way executives can help themselves to look at their industry landscape from a new vantage
point.5
2. Become expert at identifying potential disrupters
Expanding the group of executives engaged in strategic dialogue should boost the odds of
identifying company or industry-disrupting changes that are just over the horizon—the sorts
of changes that make or break companies.
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But those insights don’t emerge magically. Consider, for example, technological disruption.
For many executives, the rise up the corporate ladder requires a deep understanding of
industry-specific technologies—those embedded in a company’s products, for example, or in
manufacturing techniques—but much less knowledge of cross-cutting technology trends,
such as the impact of sensors and the burgeoning “Internet of Things.”6 Moreover, many
senior executives are happy to delegate thinking about such technology issues to their
company’s chief information officer or chief technology officer. Yet it’s exactly such crosscutting trends that are most likely to upend value chains, transform industries, and
dramatically shift profit pools and competitive advantage.
So what to do? Some executives choose to spend a week or two visiting a technology hub,
such as Silicon Valley, to meet companies, investors, and academics. Others ask a more
technophile member of the team to keep abreast of the issues and brief them periodically. We
know a number of executives who have developed “reverse mentoring” relationships with
younger and more junior colleagues (or even their children) that focus on technology and
innovation. And of course, there’s no substitute for seeing what your customers are doing
with technology: during several store visits, an executive at a baby care retailer saw mothers
compare the prices of products on their smartphones at the store and leave if they could get a
better deal elsewhere. The store visits brought home how modern mothers research their
buying decisions, the interaction between mobile technology and store visits, and the
importance of advertising a price-matching scheme to keep tech-savvy customers buying in
stores.
Nascent competitors are another easy-to-overlook source of disruption. Senior strategic
thinkers are of course well aware of the need to keep an eye on the competition, and many
companies have roles or teams focused on competitor intelligence. However, in our
experience, often too many resources—including mental energy—are devoted to following
the activities of long-standing competitors rather than less conventional ones that may pose
an equivalent (or greater) strategic threat.
For example, suppose you are an executive at an oil company with assets in the UK
Continental Shelf. It is natural for the competitors that you meet regularly at board meetings
of Oil & Gas UK, the regional industry association, to be more top of mind than Asian
players that have only just acquired their first positions in the region. And that’s exactly why
many long-standing industry leaders were surprised when Korea National Oil Corporation
(KNOC), South Korea’s national oil company, clinched a hostile takeover of Dana Petroleum
in late 2010, in what was to be the largest oil and gas transaction in the United Kingdom in
several years. The transaction was a harbinger of future investments by less traditional
players in the North Sea oil and gas industry. Similar dynamics prevail in mining: developedworld majors (such as Anglo American, BHP Billiton, and Rio Tinto), which have long
competed with one another globally, now must also take into account players from Brazil,
China, India, and elsewhere.
Picking up weak competitive signals is more often than not a result of careful practice: a
systematic updating of competitive insights as an ongoing part of existing strategic
processes.7 Executives with diverse backgrounds can boost the quality of dialogue by
contributing to—and insisting on—issue-based competitive analyses. Who is well-positioned
to play in emerging business areas? If new technologies are involved, what are they, and who
else might master them? Who seems poorly positioned, and what does that mean for
competitive balance in the industry or for acquisition opportunities? Focusing competitive
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reviews on questions like these often yields insights of significantly greater value than would
be possible through the more common practice of periodically examining competitors’
financial and operating results. It also helps push the senior team away from linear,
deterministic thinking and toward a more contingent, scenario-based mind-set that’s better
suited to today’s fast-moving strategy environment.
3. Develop communications that can break through
A more adaptive strategy-development process places a premium on effective
communications from all the executives participating. The strategy journey model described
by our colleagues, for example, involves meeting for two to four hours every week or two to
discuss strategy topics and requires each executive taking part to flag issues and lead the
discussion about them.
In such an environment, time spent looking for better, more innovative ways to communicate
strategy—to make strategic insights cut through the day-to-day morass of information that
any executive receives—is rarely wasted. This requires discipline, as it is always tempting to
invest in further analysis so that the executive has a deeper grasp of the issues rather than in
communications design to ensure that everybody has a good grasp of them. It also may
require building new skills; indeed, developing messages that can break through the clutter is
becoming a required skill for the modern strategist.8
Experiential exercises are one way of boosting the effectiveness of strategic communications
within a top team. A strategist we know at a shoe manufacturer wanted to illustrate the point
that many of his company’s products were both unattractive and expensive. He started with a
two-by-two matrix. So far, so predictable. But his matrix was built using masking tape on the
floor of the executive suite, and the shoes were real ones from the company and its
competitors. His colleagues had to classify the shoes right there and then—and he made his
point. Similarly, we know another strategist who spent an afternoon cutting the labels off
samples of men’s boxer shorts. She wanted the board members to put them in order of price
so they could see how their perceptions of quality were driven by brands and not
manufacturing standards.
We would add that as strategy becomes more of a real-time journey, it’s important to figure
out ways to support discussions with data that’s engaging and easy to manipulate. To the
extent possible, executives need to be able to push on data and its implications “in the
moment,” instead of raising questions and then waiting two weeks for a team of analysts to
come back with answers. Ideally, in fact, anyone in a room could drill into thoughtfully
visualized data with the flick of a finger on a tablet computer. The proliferation of tactile
mobile devices and new software tools that help make spreadsheets more visual and
interactive should facilitate more dynamic, data-driven dialogue.
Executives hoping to become more strategic should look for opportunities to innovate in their
communication of data, while prodding their organizations to institutionalize such
capabilities. Breakthroughs abound—look no further than the interactive visualizations in the
New York Times in the United States or the Guardian in the United Kingdom; the 2006
TED.com video “Hans Rosling shows the best stats you’ve ever seen”; Generation
Grownup’s interactive tool Name Voyager, which examines the popularity of baby names
over time (see babynamewizard.com/voyager); or Kiva.org’s Intercontinental Ballistic
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Microfinance visualization of loan-funding and repayment flows. But few companies have
kept up.
It’s not enough to increase the number and diversity of executives engaged in setting strategy.
Many of those leaders also must enhance their own strategic capabilities. We hope these three
tips help them get started.
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http://www.youtube.com/watch?v=1uIzS1uCOcE&hd=1 and/or
http://www.youtube.com/watch?v=IsFShIWlSkE&hd=1
THE SINGULARITY
A Talk With Ray Kurzweil [3.24.01]
Topic:
CULTURE
Introduction By: John Brockman
I once spent a few days with the late dolphinologist John C. Lilly, M.D. Talking about
advanced intelligence in other species. I asked him, "How can you say that dolphins are more
intelligent than we are? Isn’t knowledge tautological? How can we know more than we do
know? Who would know it, except us?"
We are entering a new era. I call it "the Singularity." It's a merger between human
intelligence and machine intelligence is going to create something bigger than itself. It's the
cutting edge of evolution on our planet. One can make a strong case that it's actually the
cutting edge of the evolution of intelligence in general, because there's no indication that it's
occurred anywhere else. To me that is what human civilization is all about. It is part of our
destiny and part of the destiny of evolution to continue to progress ever faster, and to grow
the power of intelligence exponentially.To contemplate stopping that — to think human
beings are fine the way they are — is a misplaced fond remembrance of what human beings
used to be. What human beings are is a species that has undergone a cultural and
technological evolution, and it's the nature of evolution that it accelerates, and that its
powers grow exponentially, and that's what we're talking about. The next stage of this will be
to amplify our own intellectual powers with the results of our technology.
Introduction
Ray Kurzweil posits that we will soon be facing a similar question through the merger of
human and machine intelligence. "One response is not to want to be enhanced," he says, "not
to have nanobots. A lot of people say that they just want to stay a biological person. But what
will the Singularity look like to people who want to remain biological? The answer is that
they really won't notice it, except for the fact that machine intelligence will appear to
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biological humanity to be their transcendent servants....there's a lot that, in fact, biological
humanity won't actually notice."
Kurzweil, an inventor and entrepreneur , has been pushing the technological envelope for
years in his field of pattern recognition. Among his many accomplishments, he developed the
technology behind the flatbed scanner, and he is a leading expert in speech recognition. In his
radical view of the future the operant word is....exponential. For example, "One application of
sending billions of nanobots into the brain is full-immersion virtual reality. If you want to be
in real reality, the nanobots sit there and do nothing, but if you want to go into virtual reality,
the nanobots shut down the signals coming from my real senses, replace them with the
signals I would be receiving if I were in the virtual environment, and then my brain feels as if
it's in the virtual environment. And you can go there yourself — or, more interestingly you
can go there with other people — and you can have everything from sexual and sensual
encounters to business negotiations, in full-immersion virtual reality environments that
incorporate all of the senses."
— JB
RAY KURZWEIL was the principal developer of the first omni-font optical character
recognition, the first print-to-speech reading machine for the blind, the first CCD flat-bed
scanner, the first text-to-speech synthesizer, the first music synthesizer capable of recreating
the grand piano and other orchestral instruments, and the first commercially marketed large
vocabulary speech recognition. He has successfully founded, developed, and sold four AI
businesses in OCR, music synthesis, speech recognition, and reading technology. All of these
technologies continue today as market leaders.
Kurzweil received the $500,000 Lemelson-MIT Prize, the world's largest award in invention
and innovation. He also received the 1999 National Medal of Technology, the nation's
highest honor in technology, from President Clinton in a White House ceremony. He has also
received scores of other national and international awards, including the 1994 Dickson Prize
(Carnegie Mellon University's top science prize), Engineer of the Year from Design News,
Inventor of the Year from MIT, and the Grace Murray Hopper Award from the Association
for Computing Machinery. He has received ten honorary Doctorates and honors from three
U.S. presidents. He has received seven national and international film awards. He is the
author of The Age of Intelligent Machines, and The Age of Spiritual Machines, When
Computers Exceed Human Intelligence.
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Ray Kurzweil 's Edge Bio Page
THE REALITY CLUB: John McCarthy, Forrest Sawyer respond to Ray Kurzweil;
Kurzweil answers McCarthy
THE SINGULARITY
[RAY KURZWEIL:] My interest in the future really stems from my interest in being an
inventor. I've had the idea of being an inventor since I was five years old, and I quickly
realized that you had to have a good idea of the future if you're going to succeed as an
inventor. It's a little bit like surfing; you have to catch a wave at the right time. I quickly
realized the world quickly becomes a different place than it was when you started by the time
you finally get something done. Most inventors fail not because they can't get something to
work, but because all the market's enabling forces are not in place at the right time.
So I became a student of technology trends, and have developed mathematical models about
how technology evolves in different areas like computers, electronics in general,
communication storage devices, biological technologies like genetic scanning, reverse
engineering of the human brain, miniaturization, the size of technology, and the pace of
paradigm shifts. This helped guide me as an entrepreneur and as a technology creator so
that I could catch the wave at the right time.
This interest in technology trends took on a life of its own, and I began to project some of
them using what I call the law of accelerating returns, which I believe underlies technology
evolution to future periods. I did that in a book I wrote in the 1980s, which had a road map of
what the 1990s and the early 2000's would be like, and that worked out quite well. I've now
refined these mathematical models, and have begun to really examine what the 21st century
would be like. It allows me to be inventive with the technologies of the 21st century, because
I have a conception of what technology, communications, the size of technology, and our
knowledge of the human brain will be like in 2010, 2020, or 2030. If I can come up with
scenarios using those technologies, I can be inventive with the technologies of the future. I
can't actually create these technologies yet, but I can write about them.
One thing I'd say is that if anything the future will be more remarkable than any of us can
imagine, because although any of us can only apply so much imagination, there'll be
thousands or millions of people using their imaginations to create new capabilities with these
future technology powers. I've come to a view of the future that really doesn't stem from a
preconceived notion, but really falls out of these models, which I believe are valid both for
theoretical reasons and because they also match the empirical data of the 20th century.
One thing that observers don't fully recognize, and that a lot of otherwise thoughtful people
fail to take into consideration adequately, is the fact that the pace of change itself has
accelerated. Centuries ago people didn't think that the world was changing at all. Their
grandparents had the same lives that they did, and they expected their grandchildren would
do the same, and that expectation was largely fulfilled.
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Today it's an axiom that life is changing and that technology is affecting the nature of society.
But what's not fully understood is that the pace of change is itself accelerating, and the last 20
years are not a good guide to the next 20 years. We're doubling the paradigm shift rate, the
rate of progress, every decade. This will actually match the amount of progress we made in
the whole 20th century, because we've been accelerating up to this point. The 20th century
was like 25 years of change at today's rate of change. In the next 25 years we'll make four
times the progress you saw in the 20th century. And we'll make 20,000 years of progress in
the 21st century, which is almost a thousand times more technical change than we saw in the
20th century.
Specifically, computation is growing exponentially. The one exponential trend that people
are aware of is called Moore's Law. But Moore's Law itself is just one method for bringing
exponential growth to computers. People are aware that we're doubling the power of
computation every 12 months because we can put twice as many transistors on an integrated
circuit every two years. But in fact, they run twice as fast and double both the capacity and
the speed, which means that the power quadruples.
What's not fully realized is that Moore's Law was not the first but the fifth paradigm to bring
exponential growth to computers. We had electro-mechanical calculators, relay-based
computers, vacuum tubes, and transistors. Every time one paradigm ran out of steam another
took over. For a while there were shrinking vacuum tubes, and finally they couldn't make
them any smaller and still keep the vacuum, so a whole different method came along. They
weren't just tiny vacuum tubes, but transistors, which constitute a whole different approach.
There's been a lot of discussion about Moore's Law running out of steam in about 12 years
because by that time the transistors will only be a few atoms in width and we won't be able to
shrink them any more. And that's true, so that particular paradigm will run out of steam.
We'll then go to the sixth paradigm, which is massively parallel computing in three
dimensions. We live in a 3-dimensional world, and our brains organize in three dimensions,
so we might as well compute in three dimensions. The brain processes information using an
electrochemical method that's ten million times slower than electronics. But it makes up for
this by being three-dimensional. Every intra-neural connection computes simultaneously, so
you have a hundred trillion things going on at the same time. And that's the direction we're
going to go in. Right now, chips, even though they're very dense, are flat. Fifteen or twenty
years from now computers will be massively parallel and will be based on biologically
inspired models, which we will devise largely by understanding how the brain works.
We're already being significantly influenced by it. It's generally recognized, or at least
accepted by a lot of observers, that we'll have the hardware to manipulate human intelligence
within a brief period of time — I'd say about twenty years. A thousand dollars of computation
will equal the 20 million billion calculations per second of the human brain. What's more
controversial is whether or not we will have the software. People acknowledge that we'll have
very fast computers that could in theory emulate the human brain, but we don't really know
how the brain works, and we won't have the software, the methods, or the knowledge to
create a human level of intelligence. Without this you just have an extremely fast calculator.
But our knowledge of how the brain works is also growing exponentially. The brain is not of
infinite complexity. It's a very complex entity, and we're not going to achieve a total
understanding through one simple breakthrough, but we're further along in understanding the
principles of operation of the human brain than most people realize. The technology for
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scanning the human brain is growing exponentially, our ability to actually see the internal
connection patterns is growing, and we're developing more and more detailed mathematical
models of biological neurons. We actually have very detailed mathematical models of several
dozen regions of the human brain and how they work, and have recreated their methodologies
using conventional computation. The results of those re-engineered or re-implemented
synthetic models of those brain regions match the human brain very closely.
We're also literally replacing sections of the brain that are degraded or don't work any more
because of disabilities or disease. There are neural implants for Parkinson's Disease and wellknown cochlear implants for deafness. There's a new generation of those that are coming out
now that provide a thousand points of frequency resolution and will allow deaf people to hear
music for the first time. The Parkinson's implant actually replaces the cortical
neurons themselves that are destroyed by that disease. So we've shown that it's feasible to
understand regions of the human brain, and reimplement those regions in conventional
electronics computation that will actually interact with the brain and perform those functions.
If you follow this work and work out the mathematics of it. It's a conservative scenario to
say that within 30 years — possibly much sooner — we will have a complete map of the
human brain, we will have complete mathematical models of how each region works, and we
will be able to re-implement the methods of the human brain, which are quite different than
many of the methods used in contemporary artificial intelligence.
But these are actually similar to methods that I use in my own field — pattern recognition —
which is the fundamental capability of the human brain. We can't think fast enough to
logically analyze situations very quickly, so we rely on our powers of pattern recognition.
Within 30 years we'll be able to create non-biological intelligence that's comparable to human
intelligence. Just like a biological system, we'll have to provide it an education, but here we
can bring to bear some of the advantages of machine intelligence: Machines are much faster,
and much more accurate. A thousand-dollar computer can remember billions of things
accurately — we're hard-pressed to remember a handful of phone numbers.
Once they learn something, machines can also share their knowledge with other machines.
We don't have quick downloading ports at the level of our intra-neuronal connection patterns
and our concentrations of neurotransmitters, so we can't just download knowledge. I can't just
take my knowledge of French and download it to you, but machines can. So we can educate
machines through a process that can be hundreds or thousands of times faster than the
comparable process in humans. It can provide a 20-year education to a human-level machine
in maybe a few weeks or a few days and then these machines can share their knowledge.
The primary implication of all this will be to enhance our own human intelligence. We're
going to be putting these machines inside our own brains. We're starting to do that now with
people who have severe medical problems and disabilities, but ultimately we'll all be doing
this. Without surgery, we'll be able to introduce calculating machines into the blood stream
that will be able to pass through the capillaries of the brain. These intelligent, blood-cell-sized
nanobots will actually be able to go to the brain and interact with biological neurons. The
basic feasibility of this has already been demonstrated in animals.
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One application of sending billions of nanobots into the brain is full-immersion virtual
reality. If you want to be in real reality, the nanobots sit there and do nothing, but if you want
to go into virtual reality, the nanobots shut down the signals coming from my real senses,
replace them with the signals I would be receiving if I were in the virtual environment, and
then my brain feels as if it's in the virtual environment. And you can go there yourself — or,
more interestingly you can go there with other people — and you can have everything from
sexual and sensual encounters to business negotiations, in full-immersion virtual reality
environments that incorporate all of the senses.
People will beam their own flow of sensory experiences and the neurological correlates of
their emotions out into the Web, the way people now beam images from web cams in their
living rooms and bedrooms. This will enable you to plug in and actually experience what it's
like to be someone else, including their emotional reactions, a´ la the plot concept of Being
John Malkovich. In virtual reality you don't have to be the same person. You can be someone
else, and can project yourself as a different person.
Most importantly, we'll be able to enhance our biological intelligence with non-biological
intelligence through intimate connections. This won't mean just having one thin pipe between
the brain and a non-biological system, but actually having non-biological intelligence in
billions of different places in the brain. I don't know about you, but there are lots of books I'd
like to read and Web sites I'd like to go to, and I find my bandwidth limiting. So instead of
having a mere hundred trillion connections, we'll have a hundred trillion times a million.
We'll be able to enhance our cognitive pattern recognition capabilities greatly, think faster,
and download knowledge.
If you follow these trends further, you get to a point where change is happening so rapidly
that there appears to be a rupture in the fabric of human history. Some people have referred to
this as the "Singularity." There are many different definitions of the Singularity, a term
borrowed from physics, which means an actual point of infinite density and energy that's kind
of a rupture in the fabric of space-time.
Here, that concept is applied by analogy to human history, where we see a point where this
rate of technological progress will be so rapid that it appears to be a rupture in the fabric of
human history. It's impossible in physics to see beyond a Singularity, which creates an event
boundary, and some people have hypothesized that it will be impossible to characterize
human life after the Singularity. My question is what human life will be like after the
Singularity, which I predict will occur somewhere right before the middle of the 21st century.
A lot of the concepts we have of the nature of human life — such as longevity — suggest a
limited capability as biological, thinking entities. All of these concepts are going to undergo
significant change as we basically merge with our technology. It's taken me a while to get my
own mental arms around these issues. In the book I wrote in the 1980s,The Age of Intelligent
Machines, I ended with the spectre of machines matching human intelligence somewhere
between 2020 and 2050, and I basically have not changed my view on that time frame,
although I left behind my view that this is a final spectre. In the book I wrote ten years
later, The Age of Spiritual Machines, I began to consider what life would be like past the
point where machines could compete with us. Now I'm trying to consider what that will mean
for human society.
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One thing that we should keep in mind is that innate biological intelligence is fixed. We have
10^(26) calculations per second in the whole human race and there are ten billion human
minds. Fifty years from now, the biological intelligence of humanity will still be at that same
order of magnitude. On the other hand, machine intelligence is growing exponentially, and
today it's a million times less than that biological figure. So although it still seems that human
intelligence is dominating, which it is, the crossover point is around 2030 and non-biological
intelligence will continue its exponential rise.
This leads some people to ask how can we know if another species or entity is more
intelligent that we are? Isn't knowledge tautological? How can we know more than we do
know? Who would know it, except us?
One response is not to want to be enhanced, not to have nanobots. A lot of people say that
they just want to stay a biological person. But what will the Singularity look like to people
who want to remain biological? The answer is that they really won't notice it, except for the
fact that machine intelligence will appear to biological humanity to be their transcendent
servants. It will appear that these machines are very friendly are taking care of all of our
needs, and are really our transcendent servants. But providing that service of meeting all of
the material and emotional needs of biological humanity will comprise a very tiny fraction of
the mental output of the non-biological component of our civilization. So there's a lot that, in
fact, biological humanity won't actually notice.
There are two levels of consideration here. On the economic level, mental output will be the
primary criterion. We're already getting close to the point that the only thing that has value is
information. Information has value to the extent that it really reflects knowledge, not just raw
data. There are a few products on this table — a clock, a camera, tape recorder — that are
physical objects, but really the value of them is in the information that went into their design:
the design of their chips and the software that's used to invent and manufacture them. The
actual raw materials — a bunch of sand and some metals and so on — is worth a few pennies,
but these products have value because of all the knowledge that went into creating them.
And the knowledge component of products and services is asymptoting towards 100 percent.
By the time we get to 2030 it will be basically 100 percent. With a combination of
nanotechnology and artificial intelligence, we'll be able to create virtually any physical
product and meet all of our material needs. When everything is software and information, it'll
be a matter of just downloading the right software, and we're already getting pretty close to
that.
On a spiritual level, the issue of what is consciousness is another important aspect of this,
because we will have entities by 2030 that seem to be conscious, and that will claim to have
feelings. We have entities today, like characters in your kids' video games, that can make that
claim, but they are not very convincing. If you run into a character in a video game and it
talks about its feelings, you know it's just a machine simulation; you're not convinced that it's
a real person there. This is because that entity, which is a software entity, is still a million
times simpler than the human brain.
In 2030, that won't be the case. Say you encounter another person in virtual reality that looks
just like a human but there's actually no biological human behind it — it's completely an AI
projecting a human-like figure in virtual reality, or even a human-like image in real reality
using an android robotic technology. These entities will seem human. They won't be a million
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times simpler than humans. They'll be as complex as humans. They'll have all the subtle cues
of being humans. They'll be able to sit here and be interviewed and be just as convincing as a
human, just as complex, just as interesting. And when they claim to have been angry or
happy it'll be just as convincing as when another human makes those claims.
At this point, it becomes a really deeply philosophical issue. Is that just a very clever
simulation that's good enough to trick you, or is it really conscious in the way that we assume
other people are? In my view there's no real way to test that scientifically. There's no machine
you can slide the entity into where a green light goes on and says okay, this entity's
conscious, but no, this one's not. You could make a machine, but it will have philosophical
assumptions built into it. Some philosophers will say that unless it's squirting impulses
through biological neurotransmitters, it's not conscious, or that unless it's a biological human
with a biological mother and father it's not conscious. But it becomes a matter of
philosophical debate. It's not scientifically resolvable.
The next big revolution that's going to affect us right away is biological technology, because
we've merged biological knowledge with information processing. We are in the early stages
of understanding life processes and disease processes by understanding the genome and how
the genome expresses itself in protein. And we're going to find — and this has been apparent
all along — that there's a slippery slope and no clear definition of where life begins. Both
sides of the abortion debate have been afraid to get off the edges of that debate: that life starts
at conception on the one hand or it starts literally at birth on the other. They don't want to get
off those edges, because they realize it's just a completely slippery slope from one end to the
other.
But we're going to make it even more slippery. We'll be able to create stem cells without ever
actually going through the fertilized egg. What's the difference between a skin cell, which has
all the genes, and a fertilized egg? The only differences are some proteins in the eggs and
some signalling factors that we don't fully understand, yet that are basically proteins. We will
get to the point where we'll be able to take some protein mix, which is just a bunch of
chemicals and clearly not a human being, and add it to a skin cell to create a fertilized egg
that we can then immediately differentiate into any cell of the body. When I go like this and
brush off thousands of skin cells, I will be destroying thousands of potential people. There's
not going to be any clear boundary.
This is another way of saying also that science and technology are going to find a way around
the controversy. In the future, we'll be able to do therapeutic cloning, which is a very
important technology that completely avoids the concept of the fetus. We'll be able to take
skin cells and create, pretty directly without ever going through a fetus, all the cells we need.
We're not that far away from being able to create new cells. For example, I'm 53 but with my
DNA, I'll be able to create the heart cells of a 25-year-old man, and I can replace my heart
with those cells without surgery just by sending them through my blood stream. They'll take
up residence in the heart, so at first I'll have a heart that's one percent young cells and 99
percent older ones. But if I keep doing this every day, a year later, my heart is 99 percent
young cells. With that kind of therapy we can ultimately replenish all the cell tissues and the
organs in the body. This is not something that will happen tomorrow, but these are the kinds
of revolutionary processes we're on the verge of.
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If you look at human longevity — which is another one of these exponential trends — you'll
notice that we added a few days every year to the human life expectancy in the 18th century.
In the 19th century we added a few weeks every year, and now we're now adding over a
hundred days a year, through all of these developments, which are going to continue to
accelerate. Many knowledgeable observers, including myself, feel that within ten years we'll
be adding more than a year every year to life expectancy.
As we get older, human life expectancy will actually move out at a faster rate than we're
actually progressing in age, so if we can hang in there, our generation is right on the edge.
We have to watch our health the old-fashioned way for a while longer so we're not the last
generation to die prematurely. But if you look at our kids, by the time they're 20, 30, 40 years
old, these technologies will be so advanced that human life expectancy will be pushed way
out.
There is also the more fundamental issue of whether or not ethical debates are going to stop
the developments that I'm talking about. It's all very good to have these mathematical models
and these trends, but the question is if they going to hit a wall because people, for one reason
or another — through war or ethical debates such as the stem cell issue controversy — thwart
this ongoing exponential development.
I strongly believe that's not the case. These ethical debates are like stones in a stream. The
water runs around them. You haven't seen any of these biological technologies held up for
one week by any of these debates. To some extent, they may have to find some other ways
around some of the limitations, but there are so many developments going on. There are
dozens of very exciting ideas about how to use genomic information and proteonic
information. Although the controversies may attach themselves to one idea here or there,
there's such a river of advances. The concept of technological advance is so deeply ingrained
in our society that it's an enormous imperative. Bill Joy has gotten around — correctly —
talking about the dangers, and I agree that the dangers are there, but you can't stop ongoing
development.
The kinds of scenarios I'm talking about 20 or 30 years from now are not being developed
because there's one laboratory that's sitting there creating a human-level intelligence in a
machine. They're happening because it's the inevitable end result of thousands of little steps.
Each little step is conservative, not radical, and makes perfect sense. Each one is just the next
generation of some company's products. If you take thousands of those little steps — which
are getting faster and faster — you end up with some remarkable changes 10, 20, or 30 years
from now. You don't see Sun Microsystems saying the future implication of these
technologies is so dangerous that they're going to stop creating more intelligent networks and
more powerful computers. Sun can't do that. No company can do that because it would be out
of business. There's enormous economic imperative.
There is also a tremendous moral imperative. We still have not millions but billions of people
who are suffering from disease and poverty, and we have the opportunity to overcome those
problems through these technological advances. You can't tell the millions of people who are
suffering from cancer that we're really on the verge of great breakthroughs that will save
millions of lives from cancer, but we're cancelling all that because the terrorists might use
that same knowledge to create a bioengineered pathogen.
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This is a true and valid concern, but we're not going to do that. There's a tremendous belief in
society in the benefits of continued economic and technological advance. Still, it does raise
the question of the dangers of these technologies, and we can talk about that as well, because
that's also a valid concern.
Another aspect of all of these changes is that they force us to re-evaluate our concept of what
it means to be human. There is a common viewpoint that reacts against the advance of
technology and its implications for humanity. The objection goes like this: we'll have very
powerful computers but we haven't solved the software problem. And because the software's
so incredibly complex, we can't manage it.
I address this objection by saying that the software required to emulate human intelligence is
actually not beyond our current capability. We have to use different techniques — different
self-organizing methods — that are biologically inspired. The brain is complicated but it's not
that complicated. You have to keep in mind that it is characterized by a genome of only 23
million bytes. The genome is six billion bits — that's eight hundred million bytes — and
there are massive redundancies. One pretty long sequence called ALU is repeated 300
thousand times. If you use conventional data compression on the genomes (at 23 million
bytes, a small fraction of the size of Microsoft Word), it's a level of complexity that we can
handle. But we don't have that information yet.
You might wonder how something with 23 million bytes can create a human brain that's a
million times more complicated than itself. That's not hard to understand. The genome creates
a process of wiring a region of the human brain involving a lot of randomness. Then, when
the fetus becomes a baby and interacts with a very complicated world, there's an evolutionary
process within the brain in which a lot of the connections die out, others get reinforced, and it
self-organizes to represent knowledge about the brain. It's a very clever system, and we don't
understand it yet, but we will, because it's not a level of complexity beyond what we're
capable of engineering.
In my view there is something special about human beings that's different from what we see
in any of the other animals. By happenstance of evolution we were the first species to be able
to create technology. Actually there were others, but we are the only one that survived in this
ecological niche. But we combined a rational faculty, the ability to think logically, to create
abstractions, to create models of the world in our own minds, and to manipulate the world.
We have opposable thumbs so that we can create technology, but technology is not just tools.
Other animals have used primitive tools, but the difference is actually a body of knowledge
that changes and evolves itself from generation to generation. The knowledge that the human
species has is another one of those exponential trends.
We use one stage of technology to create the next stage, which is why technology accelerates,
why it grows in power. Today, for example, a computer designer has these tremendously
powerful computer system design tools to create computers, so in a couple of days they can
create a very complex system and it can all be worked out very quickly. The first computer
designers had to actually draw them all out in pen on paper. Each generation of tools creates
the power to create the next generation.
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So technology itself is an exponential, evolutionary process that is a continuation of the
biological evolution that created humanity in the first place. Biological evolution itself
evolved in an exponential manner. Each stage created more powerful tools for the next, so
when biological evolution created DNA it now had a means of keeping records of its
experiments so evolution could proceed more quickly. Because of this, the Cambrian
explosion only lasted a few tens of millions of years, whereas the first stage of creating DNA
and primitive cells took billions of years. Finally, biological evolution created a species that
could manipulate its environment and had some rational faculties, and now the cutting edge
of evolution actually changed from biological evolution into something carried out by one of
its own creations, Homo sapiens, and is represented by technology. In the next epoch this
species that ushered in its own evolutionary process — that is, its own cultural and
technological evolution, as no other species has — will combine with its own creation and
will merge with its technology. At some level that's already happening, even if most of us
don't necessarily have them yet inside our bodies and brains, since we're very intimate with
the technology—it's in our pockets. We've certainly expanded the power of the mind of the
human civilization through the power of its technology.
We are entering a new era. I call it "the Singularity." It's a merger between human
intelligence and machine intelligence that is going to create something bigger than itself. It's
the cutting edge of evolution on our planet. One can make a strong case that it's actually the
cutting edge of the evolution of intelligence in general, because there's no indication that it's
occurred anywhere else. To me that is what human civilization is all about. It is part of our
destiny and part of the destiny of evolution to continue to progress ever faster, and to grow
the power of intelligence exponentially. To contemplate stopping that — to think human
beings are fine the way they are — is a misplaced fond remembrance of what human beings
used to be. What human beings are is a species that has undergone a cultural and
technological evolution, and it's the nature of evolution that it accelerates, and that its powers
grow exponentially, and that's what we're talking about. The next stage of this will be to
amplify our own intellectual powers with the results of our technology.
What is unique about human beings is our ability to create abstract models and to use these
mental models to understand the world and do something about it. These mental models have
become more and more sophisticated, and by becoming embedded in technology, they have
become very elaborate and very powerful. Now we can actually understand our own minds.
This ability to scale up the power of our own civilization is what's unique about human
beings.
Patterns are the fundamental ontological reality, because they are what persists, not anything
physical. Take myself, Ray Kurzweil. What is Ray Kurzweil? Is it this stuff here? Well, this
stuff changes very quickly. Some of our cells turn over in a matter of days. Even our
skeleton, which you think probably lasts forever because we find skeletons that are centuries
old, changes over within a year. Many of our neurons change over. But more importantly, the
particles making up the cells change over even more quickly, so even if a particular cell is
still there the particles are different. So I'm not the same stuff, the same collection of atoms
and molecules that I was a year ago.
But what does persist is that pattern. The pattern evolves slowly, but the pattern persists. So
we're kind of like the pattern that water makes in a stream; you put a rock in there and you'll
see a little pattern. The water is changing every few milliseconds; if you come a second later,
it's completely different water molecules, but the pattern persists. Patterns are what have
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resonance. Ideas are patterns, technology is patterns. Even our basic existence as people is
nothing but a pattern. Pattern recognition is the heart of human intelligence. 99 percent of our
intelligence is our ability to recognize patterns.
There's been a sea change just in the last several years in the public understanding of the
acceleration of change and the potential impact of all of these technologies — computer
technology, communications, biological technology — on human society. There's really been
tremendous change in popular public perception in the past three years because of the
onslaught of stories and news developments that document and support this vision. There are
now several stories every day that are significant developments and that show the escalating
power of these technologies.
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