Between Mindsharing and Mindfulness: Musings on the wisdom of the crowd

Many people extol the arrival of a new era of mindsharing where social networks enable us to consult with the wisdom of the crowd. Experiments such as the famous cow weighing experiments demonstrate that a crowd can sometimes arrive at conclusions better than any individual contributor. Referring to , one of the books who started discussing this topic we find that most crowds don’t really bother reading the basic requirements for effective wisdom generation as laid out in this book; In some cases, groups are remarkably intelligent and are often smarter than the smartest people in them. The three conditions for a group to be intelligent are diversity, independence, and decentralization. The best decisions are a product of disagreement and contest. Too much communication can make the group as a whole less intelligent. So it seems that by their very nature, social networks are not a good medium for mindsharing. Networks for mindsharing should actually separate the questions from the answers. People who are answering should not see other answers, and most probably should not see who is asking the question, but if this is the case, why would people participate ? This answer should probably be answered by startups trying to build networks for mindsharing. My interest is the relation of the motivation problem to open innovation. In many cases open innovation is a contest based, non information sharing platform, so it meets the basic requirements. However, as anyone who has dabbled in open innovation quickly finds out, the return on invested time is abysmally low. In fact many times you compete with hundreds of teams for an illusive target. The chances of winning are low, even if you are an expert at the particular field. The solution adopted in some platforms is publicity for winners. However this solution does not scale well, as there is always only one first place. People fare better by writing articles and publishing their work. Digging deeper into most platforms actually reveals an interesting fact; very few people actually participate in these platforms. After all platforms which aim to tap the knowledge of humanity, only attract a few thousand experts of which most don’t actually participate in the different competitions. So while crowds can be wise, its an open game to find ways to motivate the individuals to make this happen.


Patent Strategy

To chart a route leading from a great idea to a strong patent (portfolio) one needs a ‘Patent Strategy’.   Charting routes is a tricky business, especially when we consider that patents should relate to things which would come to pass  in the next 20 years.   A way I found useful for organizing the patent strategy for myself or for my clients is a patent strategy chart of which an example is shown below


The chart has two axis, one axis describes the different elements of the device, and the second axis describes the function.  The first aspect of the chart is that it helps drill down into the details of the invention.  The second aspect is that it helps to map out areas for which the current invention may not be protected, or alternatively areas where currently there is no inventive step and which may warrant a dedicated ideation session.  The concept is best explained with an example and we can take a car as a field in which we want to invent.   Breaking down the car into its elements can yield the following components (body, drive train, engine, power source (hydrogen, gas, battery), sensors, control, etc.).  When writing the components, we can break down into broader or tighter categories, depending on the anticipated scope. While it seems that function is many times a greater source of innovation, sometimes components can also be used in a creative way.  Examples in the car can include, heads up display, screens, radar, or even a swivel chair.  Adding a component by itself is not inventive, however integrating it into the car, and addressing its functionality might be inventive.  Examples of functions can include, getting from A to B, fuel efficiency, fun, playing media, comfort, sleeping, safety, etc.  Of course cars are examples of systems which are protected by thousands of patents, so the chart should focus on the areas of invention.  The invention can be broad, like flying cars, to narrow like a new method for wiping water off the windshield.  If we take the latter example, and our invention is composed of a transparent, windshield wiper .  The principle of operation is ultrasonic transducers combined with a special glass formation process.  An example of a chart can be




After we have a chart, we can place the idea or ideas we have on the chart, for example



In this example, we have three ideas, with some overlap between the ideas.  We have also highlighted white space areas where we currently do not have any ideas and where we are not protected by the current idea pool.  The chart is also useful in mapping out the current state of art, and identifying white space areas in the invention field.  Obviously a solid patent strategy portrayed in this manner provides a lucid picture of areas of  ‘freedom to operate’ while at the same time highlighting areas which should be the focus of ideation sessions or invention creation.

As always in strategy, as in other aspects of life, the devil is in the details.  Adopting the patent strategy chart is a good start to building strategic patent portfolios,  but they are no alternative to sound patent counselling from experienced patent attorneys.


A rational coprocessor

My previous discussion on input devices, brings to mind another topic. As we consider the role of connected devices and electronic helpers the prevailing concept is of an imaginary helper. Something that takes care of the boring chores and fills our life with fun and creativity. We tend to think of the helper much in terms that we have thought about calculators many eons ago. They can do the math but always fall short of being a human. Scifi has of course explored what happens when robots develop feelings and become humans. Yet, no one has yet suggested the unfathomable and perhaps most important electronic aide we need; a rational co processor.
In fact, people always would argue against it, after all Spock from Star Trek was above all rational but lacked feeling. But I am not advocating loss or relegation of feeling. The rational co processor would provide that missing element in any comparative shopping application- the option of not buying. After all, from soft drinks to politicians our world is filled with means to manipulate our irrational part and induce us to buy, vote, or act in certain ways. Its really amazing to consider how much of the GDP is actually stuff which we don’t need but are induced to buy. So if the rational co processor was to take hold, would that bring the economy to a grinding halt ?

Inventions and the metaphysics of obviousness

In US patent law, one of the key requirements to grant a patent is that the patented idea is non obvious.   The legal meaning and implications of non obviousness have attracted considerable discussion and research.  Obviousness puts a threshold for invention and differentiates normal problem solving skills from the qualities required of an invention.

This raises an important question regarding the use of structured thinking tools such as TRIZ to create patents.  If we take the extreme case and imagine a patent machine.  A machine which takes as input the current state of art and comes up with new ideas based on a set of manipulations and predefined criteria.    The question is whether the output of this machine is patent-able, or are the obtained patents obvious because anyone skilled in the art following the same instructions would have found them ?

It would seem that the invention requires something beyond the predefined instruction set, an expected stroke of genius, to convince the USPTO, the idea is worthy of a patent.  This also highlights one of the differences between problem solving and inventing; which is framing.

When you solve problems, the goal is to find a solution.  This solution can be tested and verified and the problem resolved.  However not every solution is patentable or an invention.  Putting aside issues of novelty, and focusing on the obviousness, the question is one of context.  TRIZ for example offers structure for solving problems, but not of wording or defining the problem.  Hence in the case of TRIZ, the obvious part may be the solution, but framing the problem is non obvious and yet since it leads to a solution, it is at the heart of the invention.  In cases where the creative process creates many options to choose from, the question is whether the choice is obvious or not.

The situation is somewhat analogous to photography.  After all, a photograph is a representation of the world. Something that everyone sees.  However,the photograph frames reality.  It focuses on some elements while relegating others to the background or outside the frame.  By doing so, we can now see things we had not seen previously. The frame has created a new context.  Similarly in inventing, the act of framing, putting boundaries, changing view point, focus, or even colors brings to light things that were not obvious.

On a practical note, to invent we need to go beyond problem solving.  A problem is a good starting point, as is a solution. But we then need to go beyond that, looking at it from different angles, uses, aspects.  In framing the problem or solution in several ways we have a unique view, which sometimes leads to inventions.

For example we can start with a problem of the phone of the future.  Some envision that Glasses would be the way we communicate.  They provide vision, hearing, situation awareness.  But they seem to lack user input methods.  So this is a good place to think about.  What kind of input do we need to provide and how do the glasses use this input.  we can imagine 3D image capture and the use of hands and gestures.  This by itself is obvious.  Yet what kind of gestures make sense and which do not.  Can or should we overlay the commands on the hands or surface, and how can we provide tactile feedback.  All these questions can find solutions.  Some obvious and some not.  But even a simple question like gesture recognition can be challenging in the context of eye glasses as they contend with challenging angles, weight and dimension limitations and user modalities.  We need to focus on one aspect and drill it down to enablement.  But at this stage its clear, that no route is obvious.  Hence the outcomes might be patentable.




Selling Ideas

A Level Playfield
Apps are a great example of reducing the required resources to take a software idea to revenue. The critical question is what is the Return On Investment for the App market. This question has two aspects. The first relates to any investment decision in apps. The second is more general and holds lessons for any idea market.
App Statistics
App stores publish general statistics on downloads, and overall income, but refrain from publishing detailed statistics. Running through the published numbers reveals that apps in general do not provide a return on investment. The simple calculation is dividing the announced income from apps by the number of apps in the App Store resulting in an income of less than $10,000 per app. Since the required development cost of an app is estimated at around $50,000, it’s clear the ROI is difficult to justify. This also explains the absence of detailed statistics and a focus on success stories. After all success stories, as the lottery industry well knows, are a strong sales driver for app developers.
So the problem with lowering the barrier to revenue is that it promotes a gambling approach, where the thrill of participation offsets the low potential of winning. Another advantage of apps is the fact revenue is often not the primary success driver and downloads often count as the critical parameter. This works well for app developers as it provides short term measures of success.
Between Apps and Ideas
While apps create a thrill, and provide short term measures for success, many other idea markets lack these characteristics. Patents for example, have an ROI of several years, and there is little measure of intermediate success. One way to resolve these problems is creating idea competitions. Most of the crowd sourcing and open innovation sites use competitions to create the required thrill and induce idea submission. The problem with this approach is the ROI for the inventor. If there are hundreds of participants and only one or two winning solutions it’s clear the ROI doesn’t justify investment of time or resources. This also highlights the scalability challenge of open innovation sites.
Inventor Networks
A possible solution is to create an inventor network. After all in inventing, like in anything else, it’s all about the people. The network through peer review and mentorship creates a community spirit which addresses the time to ROI. The network should include an active buyer community which helps direct the invention process, provides feedback and even some short term monetary motivation. Intellectual Ventures is a great example of an early innovator in this space. It is actively building a worldwide inventor network. Inventors in the network are exposed to request for inventions as well as other inventors and collaboration opportunities. The inventors can submit their ideas to IV, and IV partners with inventors on bringing the best of these ideas to market. Future inventor networks may be fashioned as a social network where ideas are developed between network members and directed by other members towards buyers. But this already is the start of the pitch of my next startup.
To sum, I am a strong believer in idea markets and open innovation and their potential to accelerate innovation and create a better world. Drawing on lessons from the current activities in this field, I think the key elements to enable a sustainable idea market are

  • return on investment
  • active engagement model
  • potential for large upside – success stories
  • How much is an idea worth ?

    Valuation Gap
    In a market place of ideas, the central question is how much is an idea worth ?
    When we consider the technical and market risks going from an idea to revenues as well as the time and required capital resources, we quickly realize that the $ value difference between a ‘good’ and ‘bad’ idea are small. There is an obvious gap between the idea originator who focuses on the business potential, and the buyer, who sees the risk and required time and capital.
    This is the reason many people pursue the entrepreneurship route. Entrepreneurship stresses the importance of execution and adaptability. Investors in new ventures invest primarily in the the team, realizing that ideas evolve over time.
    One approach to overcoming the valuation gap, is by assigning the value of the idea as a percentage of future income. This approach is best applied when the idea provides a wide enough basis for creating a revenue. It is more challenging in cases where the idea is a small ‘feature’. An alternative approach is to streamflow the path from idea to revenue. This is possible in industries with very well defined interfaces. A fascinating example is the evolution of the app market, which has lowered the barrier for software enabled ideas to reach revenue. Additional examples of industries which have streamlined the idea to revenue process are the toy industry, the Silicon IP business in the semiconductor industry, Amazon with its platform for publishing online books and even YouTube for the entertainment business. In all these cases, the execution barrier has been lowered and the requirements to enable an idea and create revenue have been lowered.
    Future Extensions
    An open challenge is extending this concept to additional industries. It’s clear that the key is to create a well defined interface which streamlines the ideation process. Of course such a process will also provide internal benefit helping better focus internal research goals and procedures.
    One may argue that this process creates ‘many of the same’ ideas and restricts innovation. I look at this in a different light. Today people have access to computing, graphic and image capabilities which in the past were restricted to top researchers in academic or industrial labs. In the near future the same will be true of chemistry, material science, biology, etc. this will happen either as universities open up their research labs or the cost of equipment will drop as a result of technology breakthroughs such as 3D printing. This process will democratize research and create new opportunities. Most will be incremental and will benefit from the streamlined process. A few will be groundbreaking, and these, as all great ideas, will expand the boundaries of our perception and capabilities.

    Brainstorm Companion

    A useful link summarizing the TRIZ process

    But TRIZ is a language. There are no hidden shortcuts to creativity and invention. Edison said “most people miss opportunity because it comes dressed in rags and looks like work”. While Edison is probably the wrong person to quote in regards to TRIZ, the bottom line still rings true. To master a language one must use it, there are no short cuts.