IBM Watson™ made its debut in February 2011 when the Deep Question & Answer software system defeated two previous reigning human champions – Ken Jennings and Brad Rutter in a three-night special Jeopardy! showcase.

The event made for carnival headlines but most news reports failed to connect Watson’s performance with its intended application- to transform the nature of human productivity in an age of information-rich, context dependent and software-mediated work environments.

Watson is designed to augment (improve) our capacity to think through complex problems, ask the right questions,  judge possible solutions and make informed confident decisions based on real-world data that exists within our own memory banks and beyond.

Productivity and Life-long Learning via Personal Assistants
IBM Watson™ and Apple Siri™  are early signals of what might transform work and lifelong learning around software based personal assistants that push human beings to think more deeply and broadly about questions, answers and their personal confidence levels in making decisions.

IBM is leading the way in an emerging paradigm for software – based on improving human cognitive performance in an era of endless streams of data and changing contexts around the marketplace and collective industry knowledge base.

The next step for IBM’s Watson is to enter the workplace and help to transform the capacity of human work.  IBM’s public roadmap for Watson begins in three main industries: Healthcare, Finance and Customer Service.  But first, let’s explore why Watson matters….

Why Watson Matters…
Natural Language, Box in a Cloud, Focus on Answers & Honesty about Confidence Levels 

There are four things that matter with IBM Watson that are relevant to understanding the future of work and learning (machine and human):

1) Natural Language Matters
Watson is not alive.  It is not artificial intelligence.  But it can (better than any other system on Earth today) understand the nuanced elements of meaning created by natural language.

Forget about display screens, clicking with your mouse and typing on a keyboard.  Watson (and to a lesser degree – Siri) allow us  to engage us in conversation and overcome the ambiguity associated with human language.  Watson is an ideal ‘post screen’ interface that helps to lower the barrier to workplace applications where screens might not be conducive to workflow.

2) Knowledge in a Box Matters
The web revolutionized access to information, but has also led to a world with too much information — and at times –  too much inaccurate information.  The web is also limited in its capture of unstructured and private data.   So we can recognize a fundamental limitation to a purely ‘open’ web platform for advanced human augmentation systems. Knowledge requires filters for transparency, authentication and accountability.  There is benefit to controlling information in a silo that is constantly updated.

Watson is a self contained storage, retrieval, analysis systems.  Watson is a ‘box’ with a 15 trillion-byte memory capacity which allows IBM to be sure that the information output will be shaped by the input rather than extracting data from the open web.

The next step is putting the Box in the Cloud — and opening up a portal to non-supercomputing devices!!

3) Answers Matter
Today we search the web and receive a list of websites which we must read to find the answer.  Again, there are no filters to guide that process.  The website we choose was likely placed on the first page of a Google Search bar – or shared with us via social networks.

Watson does not give you a list of websites, it gives you the answer(s).

It might take years to change behavior– but in a not-so-distant future, our ‘search’ expectations are likely to shift to more answer oriented results.  Obviously there is tremendous potential for an upside and downside (e.g. narrow casting; critical thinking issues) to an answer engine web culture– but we can see other players such as Wolfram Alpha and Google validating the industry’s new direction towards ‘answers’ as the next step for search.

One wonders if Google and IBM become learning management systems in the end…

4) Confidence Matters
Watson knows that it is not perfect.  IBM recognizes that technology cannot deliver certainty on demand.

So Watson embraces uncertainty and is honest about its confidence level with each response.  For each question it receives, Watson assigns a ‘Confidence’ level (%) and chooses to respond – or not – based on the situation.

One can only dream of a world where humans approach real-world challenges filled with uncertainty – with answers that reflect our recognition that the answers – solutions – might not be perfectly clear.

Imagine a work environment where people are honest and transparent in their knowledge level – and confidence level to respond to a particular question!  Instead of giving answers to please our colleagues and customers we can envision a future world of work where uncertainty is dealt with using a range of possible answers given our best set of inputs.

….

Apple’s Siri is cute— but Watson is the real potential game-changer in these early days of software-mediated human performance!

Real World Applications for ‘Watson’-like Software Programs 

Healthcare Why healthcare?  It is impossible to know all new information in the world of life sciences.

IBM Watson – Commercial for Healthcare

IBM Watson – Future of Financial Services

IBM Watson – Call Centers 

Finance – Assist in providing humans with real-time market information.

Watson is not Alone

• Google is not shy about hiding its ‘real-time’ and ‘voice’ based interface innovations.  Google’s vision is to have the answer ‘as fast as you think’.
• Apple has recently launched Siri as a consumer grade personal assistant.
• Microsoft’s promotion of Bing is as a ‘decision engine’ – not a lowly search engine.
• Wolfram Alpha (and a number of other startups) are involved in this ‘answer engine’

Key Concepts:

• Natural Language Interface; Conversational Interface
• Analytics; Deep Analytics; Deep Question & Answer;
• Algorithms; Data;  Unstructured Data; Data-Information-Knowledge-Wisdom (DIKW)
• Parallel Processing; Distributed Computing; Multi-core; Scaling; Power 7 Platform;
• Augmentation; Intelligence Augmentation;  information processing augmentation

People

• Algo Team
• David Ferrucci
• Anant Jhingran

Video Resources

IBM Watson: Overview (20 min)

IBM – The Next Grand Challenge: Natural Language

IBM Watson on Ambiguity 

Science Behind IBM Watson

Manoj Saxena IOD Keynote – Putting IBM Watson to work

IBM Watson – Future of Financial Services Work

IBM Watson – Future of Customer Service 

Part One of Series:
The Future of Programming (for Non-Programmers)

Today we are witnessing the rise of the Programmer as one of the most important enabling actors in the global knowledge economy.

These individuals and communities who design and build software that power computing devices and networks that permeate our world might occupy ‘the’ drivers seat of change in the 21st century.  And yet – who they are – what they do – and how they do it remains a mystery to most people in the world.

Programmers have been behind many of the enabling ‘new economy’ dynamics of the early 21st century: bootstrapped startup culture, open source, social media and networks, platforms and networked-based business models, hacking and mash-ups, remote working and collaboration, real-time, data visualization, high frequency ‘algo’ trading, and radical transparency.

Most of these things emerged out of left-brained geek culture led by early adopter programmer communities.

Whether you embrace a ‘market-oriented‘, ‘techno-optimist‘ or ‘sustainable economy‘ worldview, it seems impossible to envision a 21st century of transformational social, economic and environmental change without a central Role of the Programmer.  We cannot expand capital markets, democratize access to information (or radical transparency), or scale an advanced cleantech world without software driving the entire process.

Programmers as Systems Designers

Looking beyond 2010 – programming has less to do with ‘web connected desktop computers’ and more to do with software reshaping every aspect of human society from financial trading markets to laboratory research, to monitoring natural ecosystems or our own self-direct learning.

Programmers are already moving forward to emerging industries -’smart’ infrastructure (energy/transportation), nanoscale materials design, robotics, education/learning systems, security/military, and all the so-called ’2.0′ versions of government,  healthcare, agriculture and food.

Software is the virtual lubricant for this yet to be built global system of systems – and we get nowhere without understanding (and embracing) the Programmer as a key enabling actor on the world stage.

The Left-Brained Future: Foundations of our Knowledge Economy

We are familiar with the popular professions associated with the supposed right brain Knowledge Economy – it is designers, entrepreneurs, and other ‘creatives’ who are celebrated.

Yet, that we can even indulge in more creative right brain economic activities, is only the result of typically left brained programmers automating the world and reducing the demand for human attention to the routine tasks.

The creative class workforce would not exist without the software-hardware infrastructure coded by geek class programmers.  Nor would many of our most celebrated companies and industries.

When Apple, Google, Facebook, or Twitter succeed it is because they have cultivated strong relationships with programmers (e.g. developers) who drive their platforms forward.

When an entrepreneur enters the market with a new concept, it is likely that the barriers to entry were knocked down by programmers who disrupted in the incumbent marketplace with new tools.

When a Wall Street company sees profits it is largely because programmers were involved in designing the analytic and analysis tools to shape investment strategies – or via high frequency trading ‘algos’ that dominate trading exchanges.

When a Biotechnology or Cleantech company announces a breakthrough product- it was likely built via simulation software tools designed by programmers.

We might not understand how it works, but software will likely shape the majority of  social and economic activities in the 21st century.  Our future will be programmed.

A Place in History?
My belief is that the Programmer will earn a spot in history – as relevant to social change as past archetype roles.

Every major era of massive social-economic change has seen new archetypes emerge as the symbols of transformation.  The Agricultural-Town era had the farmer and craftsman,  the Industrial Age had the factory owner and worker. Our information-rich and business oriented world is often embodied by the archetypes of CEO, banker, entrepreneur and the consumer.

But at the center of most all modern economic activity is the Programmer – those individuals and communities who design and build software that power computing devices and networks that will soon permeate most aspects of the planet.

Next up
This Series is designed to highlight how Programmers might transform our society, economies and environment. And to explore ways in which humanity might tap its inner geek to bring about more transformative change capable of breaking beyond today’s performance limits.

• Part One: Why the Future will be Programmed
• Part Two: Programmers as 21st Century Learners
• Part Three: Programmers  - From Social Web to Wisdom Web
• Part Four: Programmers and World of Finance & Capital Markets
• Part Five: Programmers – Governance, Power & Radical Transparency
• Part Six: Programmers – Smart Infrastructure & Situational Awareness
• Part Seven: Programmers – Science and Simulation
• Part Eight: The Rise of the Female Programmer
• Part Nine:  Programmers – Future of Work

Image (Thanks!):

Flickr by Sebestian Bergmann Creative Commons Attribution

Professional Futurists who work with clients are familiar with the perception pitfalls associated with forecasts and scenarios that deal with the impact of technology.

This is why framing forecasts and scenarios around demographics (life stage), cultural (lifestyle) and market structure transitions are more digestible frameworks for getting clients to challenge their assumptions about transformational changes to their business models.

Why is technology a hard pill to swallow?  A combination of reasons: risks of early adoption, costs associated with implementation and support, lack of  pull demand from existing consumers, accepting small market share profits even with fast growth prospects (et al).   And let’s not forget that technology solutions are sold by deeply embedded vendors who have their own varying self-interests in transitioning old vs new platforms.

A less eloquently stated reason is that the theme of technology (especially ‘digital’ and ‘web’ technology) just scares most people.  Even if we all agree that technology on its own is never a solution, and that there is always a tendency of over-hype it in the short-term, many people struggle to overcome strong negative emotional/gut responses to new technology platforms.

For most audiences technology seems too gimmicky…  too young and hip… too transparent and invasive… or too time consuming.   These are legitimate barriers for getting audiences to see real world applications for customers.

Technology should always be placed in the context of culture, market and regulatory structures.  Without this broader context it will always be easier to roll our eyes than to probe, explore and seek to understand.

To get us to this place of understanding the broader social context of technology we need framers like Kevin Kelly to bring context to the story of technology – past, present and future.

Kevin Kelly:Technology & Foresight Foundations of Social Change & Systems Thinking
Kevin Kelly has spent decades preparing a script to tell  the epic story of technology’s past, present and future.  As a Former Editor of the Whole Earth Review and past Editor of Wired he holds a very unique perspective that spans our recent historical era where technology has become a widely perceived mechanism (and ‘agent’) of change.

I prefer to see Kelly as an informed observer as much as he is arguably a techno-optimist.  And I believe his passion for understanding technology is rooted in the two pillars of foresight/futures studies: social change and systems thinking.

Social Change frameworks (e.g. Progress, Power & Conflict, Evo-Devo, et al) help us understand change and develop the right models for forecasting possible outcomes.  Systems thinking forces us to understand structure and relationships that shape feedback loops (e.g. vicious vs. virtuous) often associated with non-linear change.  Kelly is quick to point out the non-linear aspects of change shaped by emerging technology platforms.

Here are a few of Kevin Kelly’s public lectures on technology.  Each is a variation of his central exploration in understanding the fundamental nature of technology and life in the universe:

TEDxAmsterdam, 2010

Kevin Kelly: Predicting the next 5,000 days of the web
2007 EG conference

Let’s go back further… before TED had exploded in the mainstream world– and we see many of the same messages (and one-liners) that continue to shape Kevin Kelly’s investigation into the human and universal relationship with technology.

Kevin Kelly: How does technology evolve? Like we did

And finally a recent interview on historical foundations of Wired:

Kelly’s current blog Technium

Image Source: Porfolium Flickr Creative Commons

The good news is that the perceived value of ‘games-based learning‘ and ‘social learning‘ is starting to gain mainstream traction as a way of reconciling and bridging the worlds of formal (institutional) and informal learning that stretches from learner experiences within schools and workplaces – to our activities at home and while we are within the physical world.

The bad news is that most conversations about ‘the future‘ simply extend present day notions of ‘games’ and ‘social web’ experiences into the future – rather than explore new assumptions about how both might evolve in the years ahead.

In other words, the future of learning management systems is NOT World or Warcraft or Facebook!!  Learning inputs and outcomes will not be based on what we do on computers or game consoles (device orientation), it will be based on things we do inside a world where most things and places are networked and sensing (learner orientation).

Focusing on Grades vs The Journey’s Experience
In the following talk Jesse Schell explores the future of game based learning in a future world shaped by objects (products) and environments with embedded sensors, ubiquitous access to scalable cloud-based web services, and unified interfaces via voice/video/virtual agent-based experiences.

Schell explores how these emerging platforms mgiht build upon current day trends around games that integrate reality (not allow us to escape from it!) – fantasy football, hiking/geo-caching for treasures, and Weight Watcher ‘point systems’.   He imagines at the center of these games that engage us in the layers of our reality, will be a learner who can see all relevant data, understand system structure, and become more self reflective and accountable based on their actions!

He argues (or at least, my interpretation!!)  that we need to design games as life long learning systems centered on feedback loops of privately managed data sets that connect what we do with our outcomes (e.g. overweight because what I ate; ill-informed about a world issue because of what I have/haven’t read; I have bad teeth because I don’t brush long enough).   This notion builds upon the often cited work related to  ’Quant Self‘ or Quantified Self. [See resources below]

Schell’s vision (that I share!!) is that games and experience design supports the emergence of a culture of learning and a desire to genuinely improve ourselves!

How do we get there?  The learning system design shows you the path and tracks your progress – pointing out where you did well and where you need to improve your outcomes by changing your behavior!

One of my favorite paraphrased lines from Schell’s talk… ‘instead of giving out grades we should hand out experience points‘!

Absolutely!! Replacing snapshot static grades with pathway and apprenticeship style experience points?  Brilliant!

If we expect to teach people how to become life long learners, we must not give out snapshot grades and graduate them based on age, rather use apprenticeship style progress reports that show there is still much more to learn ahead!!!!

Moving forward?
First, we need to recognize the infancy stage of learning management systems and personal learning platforms that bridge informal and formal learning via games or social learner paradigms!  We are not there yet!  In fact, I’m not sure we even have an inspiring vision?!!

Second, we need to proactively address all the fear oriented assumptions related to the management of transparent lives in this ‘quantified self’ future scenario.

Leaders in the learning space might apply foresight and engage all stakeholders in discussions about emerging assumptions regarding identity management, transparency, and the value of personal data and feedback loops that connect our behavior with outcomes.  Otherwise, fear and confusion will shut down otherwise open minds.

Stepping off my soapbox… watch Schell’s video!!

(video via Kevin Fox‘s blog, thanks!)

Other people to follow in this ‘quant’ self space:

• Kevin Kelley’s Quant Self Resource List is a great place to start;
• Alvis Brigis (Blog; Twitter)
• I have written on a similar evolution of learning systems based on the principles of situational awareness based learning via perception, comprehensive and projection – and the role media might play in learning!

Cisco CEO John Chambers is selling a very powerful vision of future growth based on innovation timed to major market transitions occurring in business, government, education and infrastructure.  His current ‘network-based collaboration’ stump speech offers lessons on building an organizational culture based on foresight and innovation:

• Innovate across Market Transitions - The secret to company longevity is the appropriate application of strategic foresight that allows companies to innovate ‘across market transitions’ instead of fighting for market share during economic downturns or mature phases of industry growth.
• The Network is the Platform – The web is evolving as a platform for unified communication systems and business services.  Business model innovation and operational execution are the foundations for tapping the power of network-based delivery of high value services.
• Social Enterprise – The way to unleash productivity is to replace rigid org chart based communication channels with social enterprise structures that allow any individual to identify internal expertise, and directly share knowledge and experience across the organization.
• Video-based Collaboration – Forget about ‘virtual teams’ based on email exchanges!!!   The game-changer in web collaboration is visually connected workers, partners and customers. Video (real-time and recorded) is likely to emerge as the preferred mode of collaboration in the years ahead.

Here are five videos featuring John Chambers exploring the dynamics of the ‘next generation’ organization:
(My favorites include the MIT talk and India Holographic presentation):

2008 Keynote at World Business Forum

MIT Video: Building the Next Generation Company

Recorded: October 15, 2008   Running Time: 1:07:45

A sneak peak at future holographic versions of telepresence [India 2008]

Video
Harvard Business Review Interview [Recorded February 06, 2009]

Cisco Collaboration Products Demo – 2009

The 2010 World Economic Forum (“Davos”) has released a set of 5 minute video presentations from its IdeasLab program. Presentations are limited to 5 minutes (20 slides) so there is no ‘death by powerpoint‘, just good old fashioned ideas sharing from some of the world’s brightest minds.

Here are five presentations from a group of MIT Professors and Researchers on the nature of intelligence via social brain, reverse engineering the brain, collective wisdom, and web scale change:

MIT’s Rebecca Saxe: Social Brain

MIT’s Josh Tenenbaum: Reverse Engineering Brain

MIT’s  Sebastian Seung

“… your conectome is the totality of your brains connections”

Tim Berners-Lee – Intelligence at Web scale

MIT – Thomas Malone
How can computers and human groups be connected to be intelligent and wise?

Forecast: Our enterprise tools for searching, synthesizing, manipulating and transforming data into knowledge and skills will soon move beyond short keyword text searches into an era of more interactive, personalized and software-guided experiences.  The next wave of enterprise search, collaboration and learning tools will be built around: voice (natural language/conversation), video, location, social relationships, real-time activities and sentiments, agent-based applications, decision-making support, workflow support, and meaning applied to unstructured data.

A Disruptive Innovation Opportunity: ‘Searching/Sharing to Learning’
The web and web user experience seems ripe for disruptive innovation.  We have reached a point of diminishing returns of our search paradigm as we drown in too much information, and not enough context.  The tools for more effective searching, knowledge discovery and creation are absent from most consumer and enterprise web experiences.

Today, our expectations for building our search skills are shockingly low as most people just type in a keyword and click the first search result without any critical thought. Today’s web is an easy target for critics who believe easy searching has created a disincentive for building more challenging critical thinking skills. (I agree, but am optimistic that new tools and expectations are on the horizon!)

The mainstreaming of the social web has obvious upsides for ease of sharing ideas, but what about tools and platforms for more robust learning and evolution of our skill sets?

The disruptive opportunity of taking us from an Era of Searching to Learning is enormous, and it is exciting to see real movement among incumbents, startups and research institutions in evolving our tools and expectations for learning in a world where information is abundant, but the skills to build knowledge are lacking.

Terms like ‘semantic web’, ‘natural language processing’, and ‘mash up’ have become stale to geek web culture, but they are just now finding an audience in mainstream enterprise and consumer markets.  The following lists includes [Updated: January 12, 2010] companies and projects to monitor as we prepare for the disruption of web learning…

Learn more below with a list of Incumbents, Startups and Projects to Watch…

Start ups Companies to Watch
[Updated: January 12, 2010]

• Altus – enterprise video search and learning platform
• Alitora – search, navigation and collaboration solutions
• Brainware
• Clarabridge – text mining
• Cognition – semantic solutions
• Collibra – enterprise data and business integration solutions
• Coveo – enterprise search and knowledge
• Exalead – enterprise search-based application (SBA) developer
• eVri – search and context engine
• Feedmil – ‘long tail’ search engine
• hunch -
• iGlue – web search and context platform
• Linguistic Agents – agent based interface platforms
• OpenAmplify – search and knowledge
• Pingar
• Rippol – a personalized, social video discovery engine
• SnapLogic – ‘ a new kind of data integration company’
• Synaptica – standardizing business vocabulary and language
• Temis – text mining and knowledge discovery
• TenForce- project ‘knowledge from data’
• Triviox – personalized job search
• Viewdle – video search
• VizSearch – supply chain and manufacturing exchange platform *
• Location based search – Google Near Me Now, Aloqua,
• Financial / Markets data – SkyGrid,
• Real-time search – OneRiot,  - more coming
• Video search – Viewdle, VideoSurf

Enterprise Solution Incumbents to Watch:
[Updated: January 12, 2010]\

• Microsoft Live Labs is pushing Pivot a new way to interact with data
  [Also see 'EntityCube' project; Bing Map Integration] – more to come…
• Google has released its beta version of Fusion (Fusion Tables); Living Stories; … more to come
• Oracle -project list coming soon
• IBM - Blue Pages, Bee Hive, project list coming soon
• Cisco – Cisco Pulse (Thanks, Anurag) – full project list coming soon

Projects to Watch:

• AnalogySpace (MIT)
• Paraview – is an open source
• Common Sense – open sourced project gathering common sense knowledge
• Common Sense Computing Group (MIT)
• Divisi (MIT) – a library for reasoning and semantic web applications
• *InfoChimps – open source knowledge and data marketplace platform *
• FedThread – search and interact with data from Federal Registry
• MESH – future of news and learning project
• Quora – collecting questions and answers
• Software Agents Group (MIT)
• YAGO - Max Planc Institute semantic web knowledge base project
• 2Wit (MIT) -
• List of ‘deep web’ search tools

*I’m refining my semantic web list to the most current and active projects**

Just to have on your radar

• DataDesigner – build a data platform
• GiniPic – simultaneous visual search
• GizaPage – learn more about your social graph
• Rank Em – crowdsourcing music discovery engine
• PearlTrees – visualization knowledge organization platform
• Mikojo – ‘the intelligent search engine’
• Oamos – meta search engine
• Public Database – gov 2.0 project
• Principle Global Indicators – global data
• Similar Page – discovery with searching
• SensesBot
• Spezify – search platform

Leave comments with any notable companies, projects that I miss… and I will update with credits!!

[Follow lists via  my del.icio.us tags on search]

Forecast: Leveraging and supporting India’s ‘demographic dividend’ will soon become the focus of many nations (beyond India) as a driver of economic growth and geopolitical stability in the next fifty years.

Having spent nearly two years of my life living in South Asia (Nepal and India), I will admit a favorable (and optimistic) bias towards the subcontinent (India, Nepal, Bangladesh, Sri Lanka and Pakistan).

Despite the many obstacles, I think South Asia’s influence in the next century will be overwhelmingly positive across a wide spectrum of indicators for economic growth and quality of life for people around the globe.  South Asia has a lot to contribute in the next century, and there is little doubt that leveraging India’s demographic fortunes will be key to success.

In this TED Talk we hear from past CEO of Infosys turned visionary Nandan Nilekani about ’four brands of ideas that will determine whether India can continue its recent breakneck progress’:

Shifting their strategy from trying to attract ‘reader’ eyeballs in  world dominated by celebrity news, to engaging ‘learners’ around the life of news stories might be just what the world of mainstream media needs to thrive in the age of web-based media.  Could the holy grail of news in the age of web media be informal learning?

Google’s new Living Stories platform is a collection of many simple web services that aims to deliver a richer, more personalized media experience on the web.  The beta-version service pulls feeds from the NYTimes and Washington Post to deliver a full spectrum of web media elements including story timelines, graphics, key people, videos, et al.   The story feeds are then personalized based on the behavior of the reader.  The vision? Readers never see the same headline twice - and follow stories based on the most relevant story lines and media  formats.   The service is classic Google ‘beta’ strategy.  It was probably realized too early for general audiences to like  it, but enticing enough to stretch our thinking of what is possible in an era of personalized learning media.

What is the innovation waiting beyond this ‘beta’ version?  Social web feeds and learning stream management.  The audience target of professional journalism might be the ‘learner’, and stop trying to compete for eyeballs of the lowest common denominator of  celebrity news that can dominate traffic. It is still early days for the future of web-based media, but I’m cautiously optimistic that personalized learning media apps could help raise the bar and lead to brighter days for professional journalism.  Google’s Living Stories might be the right skeleton of a new form of media based on learning systems.

Google Living Stories