Enhancing our capacity to lift: A call to invest in a new future (Douglas Engelbart)

Compiled from: Douglas Engelbart's 2003 talk: Improving Our Ability to Improve: A Call for Investment in a New Future . Douglas Engelbart was an American inventor best known for inventing the mouse, and his group was a pioneer in human-computer interaction, developing hypertext systems, network computers, and the graphical user interface; and Committed to advocating the use of computers and networks to collaboratively solve the world's increasingly urgent and complex problems. Died at his home in Atherton, California on July 2, 2013 at the age of 88 due to kidney failure.

Summary

Over the past five decades, we've seen tremendous growth in computing power - computing is everywhere and affects almost everything. In this talk, Dr. Douglas Engelbart , who pioneered much of the interactive computing we now take for granted, explores the forces that shaped this growth. He argues that our criteria for investing in innovation are actually short-sighted, focusing on the wrong things. Instead, he suggests investing in improvement infrastructure, which can lead to sustained, radical innovation that can transform computing and expand the kinds of problems we can solve with computing.

In this talk, Dr. Engelbart describes the process we need to implement and the capabilities we must support to stimulate this higher rate of innovation. At the end of his presentation, he called on the audience of the Co-Evolution Symposium to take action, as this is a group both concerned with and capable of determining the direction of innovation.

good news and bad news

Over the past five decades, the development of new computing technologies—in both hardware and software—has brought about astonishingly important changes in the way we work and solve problems.

I need to bring this assertion out at the beginning of this talk, because most of the rest of what I'm about to say might make you think I've forgotten about this progress, or that I don't appreciate it. So, let me get this straight... We've come a long way since the early 1950s, when I first started thinking seriously about how computers could be used to solve important societal problems. It has been an extraordinary fifty years.

In my first job at NACA (predecessor of NASA), fresh out of engineering school, I had no idea of an electronic computer at all. In fact, the term "computers" refers to a roomful of women sitting at desks using desk calculators to process wind tunnel data. This was in the late 40's. Later in my research, when I thought of using computers to manipulate symbols and language, rather than doing calculations on numbers , most people thought I was really pretty far gone. The idea of interactive computing - to most sane people, it's downright ridiculous.

So we've made really huge progress. It's incredible to have been in this industry for 50 years. But that's not what I'm going to talk to you about. Not because of a lack of appreciation for what computer technologists have developed, but because I can see that we haven't made any real progress in achieving really substantial returns. This payoff will come when we make better use of computers to bring people together in our communities and enhance people's human skills to solve difficult problems.

In this talk, I want to talk to you about this great reward, think with you about what's holding us back from making more progress, and enlist you to redirect our focus. The rewards of focusing on the right course are enormous. I want to show you that they can be yours.

The Vision: The Payoff

I need to quickly outline what I see as the goal of empowering people through the use of computers for huge rewards. This vision of success hasn't changed much for me in fifty years -- it's become more precise and detailed -- but its potential is the same as what I saw in the early 1950s. It's based on the very simple idea that when problems are very difficult and complex—things like solving hunger, curbing terrorism, or helping economies grow faster—the solutions come from the insight and ability of people to work together. So, it's not the computer working alone that can produce a solution. It's the combination of people and people, augmented by computers.

The key word here is "augment" . The reason I'm interested in interactive computing, even before we knew what it might mean, was the belief that it is only through the use of computers that people's ability to gather information, create knowledge, manipulate, and share knowledge can be expanded, Then put that knowledge into practice, and we can solve really hard problems. Just as airplanes have expanded our ability to move, computers have expanded our ability to process and use knowledge. Knowledge production is a collective activity, not an individual activity. When computers expand our ability to collaborate to solve problems beyond the scope of any single human mind, it will effectively expand our capabilities at a fundamental level.

I find that this idea of "augmenting" abilities needs clarification for many people. It is useful to contrast "augmentation" with "automation" . Automation is what most people think of when they think of using a computer. Automation is what happens when we use computers to calculate and print phone bills or record bank charges. In my opinion, this is not how we use computers to solve difficult problems. We have an opportunity to harness the unique abilities of computers to give us new and more efficient ways to use our brains and senses - so that computers can truly be a way to expand our capabilities.

A shovel is a tool, and a bulldozer is a tool. Neither can work independently, "automating" the excavation task. But both tools enhance our mining capabilities. Unsurprisingly, the tool that provides the greatest enhancement requires the most training and experience to use it effectively.

To get a greater return from our investment in computing, focusing on empowering groups to solve problems is the right place to start.

Evidence of Trouble

Because we're used to thinking in terms of huge advances and changes in computing, when it comes to these broader, socially and group-centric dimensions of computing, things are quite different.

Difficulty doing important collaborative work

For example, my organization, the Bootstrap Alliance , works closely with many other organizations to help them develop better ways to improve their ability to learn and use knowledge - in short, we work with organizations to help them improve ) ability to improve .

One organization we work with is the Global Disaster Information Network - or " GDIN " - a coalition of regional and local disaster relief organizations. An organization responding to a disaster is an excellent example of an organization that must learn to quickly adapt and use new information.

Computers, and the Internet in particular, clearly play a key role in coordinating this disaster response and in improving the ability to increase capacity throughout the life cycle of disaster response efforts. But it's amazing how difficult it is to take advantage of all the awesome capabilities of the systems we have today as GDIN strives to improve its ability to lift disaster relief. Sharing information across systems has proven to be very difficult -- where "sharing" means the ability to find the right information when it's needed, and the ability to use it across systems.

Even more difficult is the ability to monitor and reflect conditions using a computer network. Anyone who uses email regularly can easily imagine the chaotic flow of messages between different people and organizations in the event of a disaster, far from establishing the information framework needed to effectively coordinate a response. framework). There is no doubt that GDIN and its member disaster relief organizations find computers to be very useful - but what is even more alarming is that today's personal productivity and publishing systems provide capabilities that are not in line with the needs of these organizations match as they strive to coordinate effective responses flexibly and quickly.

Structural Roots of the Problem

Perhaps the best study of the systemic fundamental conflict between markets and innovation is Clayton Christensen 's classic and very valuable book , The Innovator's Dilemma Dilemma, 1997) . Christensen's thesis is that "continuous" innovation occurs when companies are well connected to their customers, generally speaking, "listening to the market" . It's an innovation that produces a better version than what's already on the market. If we all ride tricycles, continuous innovation will lead to more efficient, more comfortable, and perhaps more affordable tricycles.

But this will never produce a bike. To do that, you need a different kind of innovation—one that often produces products that don't make sense in the existing market in the first place, and therefore cannot be valued. Christensen calls it "discontinuous" innovation .

Discontinuous innovation is much riskier than continuous innovation—because it is less predictable. This threatens the position of market leaders, because as leaders they need to "listen" to existing markets and existing customers, continuously improving old technologies rather than taking advantage of new innovations. It is this power to create dramatic change that makes discontinuous innovation so valuable in the long run. This is how we step out of the existing paradigm and create something truly new.

A truly compelling example of discontinuous innovation in the past 50 years of computing history - with near-zero "intelligence" in the market - was the early World Wide Web software - especially Mosaic web browser. In the early days of the web, there were a number of companies that sold powerful electronic page viewers—viewers that could jump through e-books, follow different types of hyperlinks, display vector graphics, and do a lot more Something that early web browsers couldn't do. Companies in the early electronic publishing business could actually sell these "electronic readers" for as much as $50, meaning that when selling electronic document viewing to a large company with a large number of users This is big business when it comes to electronic document viewers.

Then came the Web and Mosaic—a free web browser that was far less capable than these proprietary offerings. But it's free! More importantly, it can do what other viewers can't - it provides access to information anywhere on the web. As a result, over the next few years, everything changed. In fact, we are indeed closer to the goal of computer assisting with collaborative work.

Later, I'll explain how we can overcome this systematic bias and open the door to great rewards from sustained, productive, discontinuous innovation. But before I get to the solution, I need to tell you another aspect of systemic bias that is holding us back from making important progress in finding new ways to use computers.

The alluring, disruptive appeal of "Ease of Use"

A second powerful, systemic bias, believing that "ease of use" is somehow equated with better products, steers the development of computing away from addressing serious issues of collaboration ) , for example, this kind of thing will really have an impact on disaster relief organizations.

Going back to my tricycle/bike analogy, it's clear that a tricycle is easier to use for an unskilled user. But, as we know, the return on investing in learning to ride a bike is enormous.

When we evaluate computing systems, we seem to overlook the most basic distinction between "ease of use" and "performance ." For example, just a few weeks ago, in early March, I was invited to participate in a series of discussions held at IBM's Almaden Labs on new research and technologies related to knowledge management and retrieval. Most speakers wanted to build a better three-wheeler - following the market into the next phase of continuous innovation - rather than thinking outside the box and thinking about something truly new.

But there is another bias, even in more innovative work—one that has to do with deciding to shelve technologies and user interactions that are “too hard” for users to learn. For example, I was particularly disappointed to learn that a site that offered knowledge retrieval online concluded that some potentially more powerful search tools should not be offered because user testing found them not easy to use.

Why do we think that, in computing, ease of use - especially for those with little training - is desirable for anyone but beginners? Surprisingly, in serious discussions with serious computer/human factors experts who may be trying to solve difficult problems of knowledge use and collaboration, ease of use has always been by design a key consideration.

Doesn't anyone aspire to be a serious amateur or professional in knowledge work?

Restoring Balance

I need to remind everyone that I said at the beginning of this talk: We have made tremendous progress in computing. It's been an amazing fifty years.

But I would like to draw attention to two very important facts:

1. We still cannot solve extremely important problems—especially if those problems require the efficient ability to gather and share knowledge among people.
2. This inability is not accidental, but stems from the values and approaches in our “designed into” approach to computing innovation.

We need to find solutions to harder problems and stimulate more discontinuous innovation.

From the "Invisible Hand" to Strategy

The good news is that it is possible to build an infrastructure that supports discontinuous innovation. There is no need to rely on mysterious, invisible hands and oracles hidden in the marketplace. Another option is to consciously invest in improvement infrastructure to support new, discontinuous innovations.

This is something a single organization can do – and it can also be done by local governments, states and regional coalitions of countries. What is needed is an understanding of how to structure this conscious investment.

ABCs of improving infrastructure

The key to developing an effective promotion infrastructure is to recognize that, within any organization, there are parts of the organization that relate to the main activity of the organization (I call this the "A" Activity [A Activity]) , and that the organization's ability to perform A-level functions is relevant There is a division of attention between the relevant parts. I call these promotions "B" activities . Two different levels of activity are shown in Figure 1.

The investment in "B" activity, along with a positive internal rate of return, can be recouped through productivity gains in "A" activity. If investments in R&D, IT infrastructure, and other aspects of "B" activity are effective, a dollar invested in an "B" activity will have a higher return than a dollar invested in an "A" activity Rate.

Clearly, there are limits to how far companies can pursue investment and growth strategies based on "B" activity -- at some point, the marginal returns on new investments start to decline. This begs the question: How can we maximize the return on investment of the "B" campaign and maximize the lift it brings?

In other words, we're asking how to improve our ability to improve. This question shows that we really need to think about another level of activity -- I'll call it "C" activity -- which specifically focuses on accelerating the speed of ascension. Figure 2 shows what I mean.

Clearly, investing in "C" activities has a potentially high leverage. Here, the right investment multiplies in terms of returns in B-level productivity (i.e. increased capability), which in turn multiplies in terms of productivity returns for the organization's primary activity. It's a way to get compounded returns on innovation investments.

The high leverage of investment in "C" activities makes this type of innovative investment especially suitable for public service organizations such as government, libraries, and a broad consortium of different companies and institutions across the industry. The reason for this is not only that a small investment can have a huge impact - although this is of course an important consideration - but also because investments in "C" activities are often pre-competitive investment . Such an investment can even be shared among competitors in an industry because, in essence, it is an investment that creates a better competitive environment. Perhaps in the U.S., the poster child for this kind of recent investment is the relatively small investment by the Department of Defense in what would eventually become the Internet.

Another example, from the private sector, is the investment made by companies to improve the quality of their products and processes as part of their participation in the quality movement. This investment is particularly important when it comes to ISO 9000 compliance and other quality programs and measures, companies – even competing companies – have joined industry consortia to jointly develop Benchmarks and Standards. They even share knowledge about quality projects. This collaborative activity at the C-level has resulted in substantial benefits for individual companies at the B- and A-levels. When you work at C-level, collaboration can yield far greater rewards than competition.

Invest wisely in boosting

Let's keep our larger goal in mind: we want to correct the current bias that stems from an over-reliance on market forces and an obsession with ease of use that hinders the development of better computing tools. We want to do this so that we can use computers to empower the entire group, because knowledge can be shared to solve really hard problems together. What I propose is to correct this bias by making relatively small but highly leveraged investments in an effort to improve our ability to lift - in what I refer to as category C activities.

This proposal is attractive not only for quantitative reasons—because it can make a big difference with relatively little investment—but also for qualitative reasons: the kind of investment that best supports disruption disruptive innovation - the kind of innovation necessary to embrace a new knowledge-centred society. The accelerated shift from a manufacturing-based economy to a knowledge-based one needs to be reflected in accelerated changes in the way we work with each other. It's a change we can embrace by focusing on "C" activities, focusing on improving our ability to improve.

With that in mind, what do we need to do?

The answers to these questions have two distinct but complementary dimensions. The first dimension has to do with process: how do you operate and set expectations in a way that fits into a "C" type of activity? The second dimension has to do with actual tools and techniques.

Process Considerations

Investing in "C" activities is different from investing in research or ERP systems for new materials to better control inventory and accounting. These types of investments have very specific goals and tend to follow a straight line from specification to final delivery. Of course, we know there are usually surprises and unplanned situations - but that's not what was originally expected. Class B investments should be predictable. For example, no one would think to install two ERP systems—say, SAP and Peoplesoft—to discover which is better. In a B-level investment, you make design decisions up front and then implement the design.

That's not the case with C-level investing. Here, you would typically execute multiple paths at the same time . At C-level, we try to understand how improvement actually happens, thereby improving our ability to improve. This means having different groups explore different paths to the same goal. As they explore, they are constantly exchanging information they have learned. Our goal is to maximize overall progress by exchanging important information as the different groups progress. This means that, in practice, the conversation between people working towards a goal is often as important as the end result of the research. Often, what the team learns in the process of exploration leads to breakthrough results.

Another difference between C-level innovations and innovations that are more focused on concrete outcomes is that, in C-level innovations, context is very important. Rather than trying to solve a specific problem, we gain insight into a wide variety of activities and opportunities for improvement. This means paying attention to both external information and the specifics of the specific work at hand. In fact, in my own work, I often find that when I seem to hit a dead end when pursuing a problem, the key is usually to move up a level of abstraction and look at the more general case ).

Note that this is in stark contrast to the typical approach to problem-focused, B-level problems, where you typically keep narrowing the scope of the problem to make it more tractable. In our improving improvement work, breakthroughs come from the other direction—starting by solving a larger problem.

Therefore, teams working at the C level work in parallel , sharing information with each other and linking their findings to external factors and larger issues. To put it more simply, C-level work requires investment integration, a concerted effort to tie the pieces together.

By the way, that's why the team I lead at SRI developed the method of connecting information with hyperlinks , which were already on the web more than two decades ago, and hyperlinks do is a key part of keeping track of what we do.

Thinking back to our research at SRI, I think of another key characteristic of C-level development work: You have to apply what you discover. This is how you reach out and grab a little future and bring it back to the present: you grab it and use it.

So, at C level, the focus of this method is:

• Concurrent development
• Integration of different concurrent activities through continuous dialogue and continuous cross checking with external information
• Application of the knowledge that is gained, not only as a way to test knowledge, but also as a way to understand the nature of knowledge and support ability improvement.

As a mnemonic to bring together the key features of a C-level process, you can put together "Concurrent Development", "Integration" and "Application of the knowledge" , called "CODIAK". To me, this invented word has become my shorthand for the most important feature of the C-level discovery campaign. Figure 3 illustrates the way in which the CODIAK process is based on continuous, dynamic integration of information so that members of the improvement team can learn from each other and move forward.

Tools and Technology Investments

How can governments and institutions make highly leveraged investments in different types of innovations that will bring new opportunities and capabilities in computing? Part of what is needed is a new approach to innovation processes - that's what CODIAK is all about. But pursuing CODIAK itself requires some technical infrastructure to support concurrent development and continual integration of dialogue, external information, and new knowledge. If this sounds a bit recursive to you, like a snake renews itself by swallowing its tail, rest assured, this recursion is not accidental. As I just said, a key principle of CODIAK is the application and use of what is learned. This recursive, reflective application was right from the start.

So, where do we need to start?

One of the most important things we need is a place to keep and share the information we collect - conversations, external information, what we learn. I call it the "Dynamic Knowledge Repository," or DKR. It's not just a database, nor just a simple collection of internet sites. It doesn't have to be all in one place - it can of course be distributed among different people and organizations that are collaborating on improving improvements - but it does need to be accessible to everyone - with for reading, writing and making new connections.

DKR ("Dynamic Knowledge Base") is a good example where you can start investing at a C level with modest means and pay off as it moves up to B and A levels. This is exactly what I mean by "bootstrapping" . It's a very American term - the image of a person being able to pull himself up with his shoelaces and perform a fantastic, impossible trick - but the idea is that every time we "start" (boot up) the computer will be put into practice. A small piece of code in permanent read only memory that knows how to go to disk to fetch more instructions, which in turn knows how to do more things like fetch more instructions. Ultimately, this process of using successive steps leading to larger steps, built on top of each other, gets the whole machine up and running. You start small and keep using what you know at each stage to solve a bigger and bigger problem.

This is exactly what building a DKR ("Dynamic Knowledge Base") at a C-level investment can bring. What you learn there can be used to improve C-level jobs, which in turn improve B-level competencies, which then translate into new competencies at the organization's primary A-level.

Another key early investment is to develop tools that provide access to knowledge in the DKR ("dynamic knowledge base") for all user segments, from beginners to professional knowledge workers expecting high performance. This "hyperscope" - that's my term - allows everyone to contribute and use the information in the DKR ("dynamic knowledge base") according to their abilities. It avoids the problem of having everyone, even experts, use the same overstretched "tennis racquets" that are helpful for beginners.

Related to "hyperscope" is the ability to provide different views - I mean "views" - of DKR ("dynamic knowledge base") knowledge - with an emphasis on "vision" ( visual) meaning. Beyond words on paper, we need to be able to visually analyze an argument—or the outcome of a meeting. We need to move beyond understanding the computer as some kind of fancy printing press and start using it to analyze and process the symbolic content of our work, expanding our own capabilities. We've done this in specialized cases—one of the most recent recent examples is the use of high-performance computing in analyzing the sequences that make up the human genome. Now, we need to extend this to a more general class of problems that people encounter when they work together, try to understand each other, and make decisions collaboratively.

Another key area of focus for tool and technology development is the way humans interact with computers. As we all know, it was in trying to broaden the bandwidth of the connection between humans and computers, combining the two dimensions of visual and motor skills, that I developed my most famous Invention - the computer "mouse".

There's still a lot going on here - I feel like we've only scratched the surface. Figure 4 gives you an overview of this very fertile field and opportunities for breakthrough innovation.

The Capability Infrastructure - this is what's in the middle of the picture, and what we call improving when we work at the C-level of innovation - combines what comes from the tool system and the human system ( human system) input. Tool System - This is the contribution of computers, providing access to different media, giving us different ways of portraying information, etc. Human systems bring rich paradigms, information captured in customs, and more. The more static parts of this set can be added directly to the Capability Infrastructure through construction of ontologies and other artifacts.

The human system, the part of the framework that is best at learning, also brings opportunities to develop new skills, benefit from training, and absorb and create new knowledge. These dynamic elements are "magic dust" that enable the entire system to innovate and solve complex problems. These make an "augmentation system" different from a pure automation system.

These valuable, dynamic, human inputs must of course enter the system through human motor and perceptual abilities. It is the boundaries between these human capabilities and the rest of the infrastructure—represented in this diagram by the bold red dashed line and labeled "H-AS Interface"—in the very real In a sense, defines the scope of capabilities of this augmentation system. If the interface is low bandwidth, passing only a fraction of what humans know and can do—and what machines can describe—then the whole system tends to be more "automated" and Not "augmentation" because computers and humans are isolated by this low-fidelity, limited interface.

On the other hand, if the interface could operate at high speed and capture nuance—perhaps even extending to changes in facial expression, heart rate, or fine motor responses , then we greatly increase the potential for integrating human capabilities directly into the overall system—meaning we can feed back, amplify, and use them.

When you start to think of human-system interfaces in this way, the whole concept of "ease of use" - the question we are so obsessed with now - seems like it should just be A single concept, and, from a macro perspective, is not a very important dimension in a richer structure. The key to building a stronger capability infrastructure is to expand the channels and modes of communication, not simplify them.

This is very powerful, exciting stuff. If we start acting on this (THIS) concept, our relationship as humans, with these amazing machines we create, we really start to open up new opportunities for growth and problem solving.

The point here is that the commitment to the CODIAK process leads to very specific investments in technology development - investments that your companies, institutions, institutions and governments can make. The reason for making these investments is to open new doors for innovation, empowering you to solve harder, but potentially richer, problems.

Your participation is important

I want to tell you again why this is so important and hope for your commitment to help us out of the dangerous, disappointing and narrow path we seem to be stuck on.

The most human characteristic of humans—the one that most clearly distinguishes it from other life forms on Earth—is not our opposable thumb, or even our use of tools. It is our ability to create and use symbols. Our ability to look at the world, turn what we see into abstractions, and then operate on those abstractions, rather than on the physical world itself , is a completely astounding, beautiful thing. We demonstrate this ability to work with symbols in wonderful, beautiful ways through music, art, architecture, and language, but the basic act of symbol making and symbol using is beautiful in itself.

As a simple but very powerful example, we invent the "negative" - our ability to deal with something that is NOT as simple as we deal with what it IS. Outside of the human mind, there is no "NOT" in nature, no "negative". But we invented it, we use it every day, and we use it to divide the world. This is an amazing creation, and a typical human creation.

When I first encountered a digital computer more than fifty years ago, it surprised me, even humbled me, because in computers I saw that we had a tool that was not just about moving the earth or Instead of bending steel, we have a tool that manipulates symbols and, more importantly, depicts symbols in new ways so we can interact with and learn from them. We have a tool that radically expands our capabilities in this field, making us more human and more powerful.

There is a myth about the coyote in the United States, a kind of dog on the American prairie. The coyote rains fire from the sky for human use, incurring the wrath of the gods and making humans more than the gods imagined. more powerful. My feeling is that computer science has given us more power to amplify and extend our ability to manipulate symbols.

It seems to me that the existing sources of power and wealth are somehow clear that the new power brought about by computers is dangerous to the existing structure of ownership and wealth, Because it, like fire, has the power to change and create new things.

As a recipient of the National Medal of Technology, I am committed to raising these questions and concerns within my own country.

We need to be better at being humans. Learning to use symbols and knowledge in new ways, across groups and cultures, is a powerful, valuable, and very human goal. It is also an achievable goal, if only we begin to open our hearts to the full and complete use of computers to enhance our most human capabilities.

Bootstrap Alliance

I came to this conference on behalf of my own small organization, the Bootstrap Alliance. We don't sell products - or anything else. But we do give you an opportunity to actively engage with other people and other institutions who are interested in understanding how to use this "new flame" from above.

More specifically, the Bootstrap Alliance is an improvement community of other improvement communities - we focus on improving the ability to improve and helping other groups with the same interests to do better. We exist to help C-level organizations do their jobs better. Not surprisingly, our approach is based on concurrent development, integration, and application of knowledge in these diverse pioneering communities.