Book Review of “How We Got to Now”

"Hubble's New Eyes: Butterfly Emerges from Stellar Demise in Planetary Nebula NGC 6302", Image by NASA Goddard Space Flight Center

“Hubble’s New Eyes: Butterfly Emerges from Stellar Demise in Planetary Nebula NGC 6302”, Image by NASA Goddard Space Flight Center

Remember back in high school when some teacher insisted that “science is fun” followed up by the inevitable directive to “pay attention and learn something”, all of which was about as well received by most of the class as a tooth ache?

Well, at least for some of us, the fun never left. Moreover, it has recently been revitalized by virtue of PBS’s recent TV series and the simultaneous publication of an accompanying book entitled How We Got to Now (Riverhead Books, 2014) , both hosted and written by the renowned and bestselling science author Steven Johnson. In each of the episodes and corresponding chapters, Johnson masterfully examines how innovations in glass, cold, sound, clean, time and light have evolved over the centuries to bring us into modern times. His onscreen and in-print enthusiasm, insight and eloquence make for an enlightening experience from start to finish.

Focusing particularly on merits of the book, the entire package of the author’s accessible and evocative  prose plus the generous helpings of photos and graphics have produced a work of science literature to behold. It is one of those uncommon instances where vivid narrations of science history combined with original analyses and supporting visuals take immediate hold of the reader’s imagination during every one of the six spheres of discovery. Clearly, he worked very hard to get all of this just right.

The most impressive accomplishment is how Johnson positions and threads several consistent themes throughout his text. First, is a phenomenon that lies at the very heart of this book: Innovations made to solve problem X often have completely unforeseen results upon issue Y. Just one of many extraordinary examples cited in every chapter involves the creation of a “flash light” by the famous muckraking writer and photographer Jacob Riis that enabled his to dramatically document the interiors of the squalid slums in New York with photographs in the late 19th century that later led to social reforms.

Second, inventors and their innovations benefit from networks of ideas and among like-minded entrepreneurs and scientists. This allows for new ideas to more readily be pollinated among innovators. Along similar lines, new breakthroughs often result in improvements and/or combinations built upon earlier and, at times, unappreciated advances. The author points to, among others, Thomas Edison and Steve Jobs in this regard.

Third, innovators can be through of as “time travelers” who are so ahead of their time that the world is just not ready to appreciate and implement their work until years later when new and wholly unanticipated needs arise. Johnson concludes his book with the compelling story of how Lady Ada Lovelace developed the world’s first computer code while working with Charles Babbage on what historians consider to be the world’s first mechanical computing device, during the 1840’s and 1850’s. Who knew that their work would not be fully comprehended let alone implemented until more than a century later? No need to look any further than at the nearest desktop/tablet/smartphone to see what they ultimately have wrought across the entire world.

While this book is so thoroughly grand in its scope across six sectors of innovation including items ranging from the finely carved oil lamps in King Tut’s tomb to posting selfies on Instagram and many other world-changing leaps in between,  it nonetheless steadily maintains a personally boundless and infectious sense of wonder about the world. In so doing this, Johnson’s text effortlessly moves back and forth between a close-up examinations of specific new developments and then focusing on the cumulative perspective of how all of these advances continue to coalesce and evolve on a global scale. Indeed, for regular fans of quality science literature as well as for those readers who would otherwise prefer reading a grocery list to anything scientific, this book fully and expertly asks and answers just exactly how we got to now.

~~ ~~~~~~~~~~~~~~~~~~~~~~~~~

I also recommend another review of this book in the December 28, 2014 Book Review section of The New York Times, written by Jon Gertner. In turn, for any interested in reading further about the nurturing  of modern innovation, I further and highly recommend his own recent book entitled The Idea Factory: Bell Labs and the Great Age of American Innovation (Penguin Press, 2012).

Mapping All the Stars in the Milky Way and All the Devices in the Web Way

This week, BusinessInsider.com has posted two articles that present extraordinary visualizations of all the known stars in our own celestial home – – no, not of Hollywood – – but rather, The Milky Way, while the other is of our own virtual world representing by all devices connected to the Web. I think that viewing them together makes for a very thought-provoking juxtaposition of the celestial and terrestrial/virtual worlds, and side-by-side comparison of their individual density. Moreover, they each display their striking vastness and beauty.

First, in an article entitled Incredible New Milky Way Map Is The Most Detailed Survey Of Our Stellar Home Ever Created, by Jessica Orwig, posted on September 16, 2014, we are presented with a “fish-eye mosaic” of the 219 million stars! in The Milky Way that have been cataloged to date. The report provides the technical on how a groups of scientists at University of Hertfordshire in the UK. The report characterizes this project as being an application of big data technology by the school’s astronomers. IMHO, the team members who worked on this are stars in their own right.

Second, is a report entitled This World Map Shows Every Device Connected To The Internet by Pamela Engel, posted on September 14, 2014. John Matherly at Shodan (which desscribes itself on its home page as ” Shodan is the World’s First Search Engine for Internet-Connected Devices”). The article provides the steps taken to generate this incredible visualization. What it very limns is the geographical inequality of available online access. For example, the US and Europe have far more dense levels of connectivity than some other countries and even entire continents. As well, there is an inconsistent relationship between certain areas’ population density and the cumulative numbers of web-connected devices.

I very highly recommend either opening these features and their accompanying graphics in two separate browser tabs and then toggling between them or alternatively opening two browsers and re-sizing them so both images can be seen simultaneously on the same screen. I believe both of these visualizations are testaments to the ever-increasing imagination of scientists who can construct plan and construct them.

I wonder though what, if any, are the possible commonalities of the structures, densities, patterns of change, and mapping processes of the Milky Way and the Net? Do the astronomers and the Net’s cartographers have anything procedurally and/or scientifically to learn from each other’s efforts?

Conflating the messages and information of both of these graphics further made me think that they might present an updated interpretation of the classic line spoken by the visiting alien to Gort, his servant robot, of “Klaatu barada nikto” in the original 1951 version of the sci-fi classic The Day the Earth Stood Still. According to this article on Wikipedia, the author of the screenplay, Edmund North, is quoted as saying this meant “There’s hope for earth, if the scientists can be reached”. As I see it, by providing this more grand perspective, the alien visitor was trying to teach the people of Earth that their planet is part of a much larger universe and they must be responsible for their actions and consequences affecting the larger spheres. Here too, by virtue of the, well, astronomical effort and originality that went into these new maps, perhaps the scientists responsible for them, at least to some degree, appreciate that message.

New Study About Taxi Ride Sharing and Its Implications for the Emergence of the “Sharing Economy”

Adding one of the more compelling scientific studies to the ongoing and rapidly developing saga of urban car ride-sharing services, the September 2, 2014 edition of The New York Times published a summary and analysis of a study of what would happen, as the titles states, If 2 New Yorkers Shared a Cab … , by Kenneth Chang and Joshua A. Kirsch. In the findings’ simplest terms, there would be a 40% reduction on the cab fleet and corresponding improvements in traffic flows, energy consumption and the environment.

The author of this fascinating study are Steven Strogatz*, a mathematics professor at Cornell, whose team included Carlo Ratti of MIT. This article contains links to their recently published paper, an accompanying graphic of the data points overlaid upon a street map of NYC, and a link to a site they have set established enabling anyone to peruse a massive database of taxi ride info.

This article also expertly explores:

  • The scientific methods used to obtain these results, balanced against the reality of the fact that New Yorkers are very reluctant to voluntarily share cab rides
  • How the recent introductions here of Uber and Lyft are impacting the economics and dynamics of the city’s taxi industry
  • Whether and how the possible introduction of self-driving cars might affect the study’s findings
  • The concerns of a scientist who is skeptical of the study’s conclusions

The day following day, on September 3rd, Strogatz and Ratti were interviewed about their report on the Brian Lehrer Show** on WNYC in New York. They covered more of the details concerning their methods, conclusions and predictions. But what really enlivened this show were the live calls from the listeners with remarkable stories of their cab rides in NYC as passengers and from an actual driver as they related to the prospect and realities of ride sharing. I highly recommend this 23 minute podcast entitled Should We Start Sharing Taxis? for these reports from the front lines of this story.

For additional original perspectives, commentary and insights into the emergence of the new sharing economy that I found to be quite relevant to this story, I further recommend the following three articles that were published during same week:

Will this sharing trend gain further traction in other sectors of the service economy? If so, what sectors and job types might be sucsceptible? If not, is this just a trend that will quickly run its course or perhaps morph into something more enduring?

___________________________

* Professor Strogatz has written a number of highly acclaimed books on science and math. Ten years ago I had the great pleasure of reading one of them entitled Sync: How Order Emerges From Chaos In the Universe, Nature, and Daily Life (Hyperion, 2004). This is a strikingly original work about how synchrony emerges from within a wide diversity of biological and environmental systems. I found his writing to be highly engaging and accessible about what otherwise would appear to be a highly complex topic for a general audience. He has done a masterful job here of explaining the concepts and examples with great clarity. I highly recommend it for any reader looking for something entirely new and different.

** X-ref to the August 1, 2014 post here entitled Discussion re: Faster Web Service, Media Mergers and Net Neutrality about another interesting segment of this show, including a link to its podcast.

2014 LinkedIn Usage Trends and Additional Data Questions

A very enlightening report was recently published on Forbes.com in May entitled New Research: 2014 LinkedIn User Trends (And 10 Top Surprises) that I highly recommend for its insights, detail and thoroughness. This professional social and networking sites continues to grow its global use base, services, influence and reputation on a daily basis. The particulars provided within this report about the size ranges of users’ personal networks, the percentages of free versus paid account, the average time users spend on the site, awareness of available feature sets, the utility of special interest groups, and other data points illuminate a truly thriving and extensible services.

What is particularly impressive about format and content of this report is the infographic it contains entitled Portrait of a LinkedIn User 2013 Edition. This expertly limns the who’s who and what’s what of the user base. Moreover, it sets into perspective just how unique LinkedIn is among the other leading social networks such as Facebook, Twitter, Google+ and others.

Having viewed many other infographics online, imho, this one receives an A+ from me for its simple and engaging design which belie such a wealth of useful information. I believe that you will learn much about LinkedIn here while simultaneously viewing a clinic on how to create a highly effective visual representation of data.

The data and graphics presenting a distribution of percentages of the relative sizes of users’ networks immediately grabbed my attention. The largest percentage, 25.2% of the entire user base, of first degree user connections falls between 500 to 999. Okay, I’m in there with my personal network, too. What I would further be interested in knowing is whether dividing the total number of second degree connections by the number of first degree connections, would produce an accurate average number of second degree connections among all of a user’s first degree connections. For example, if I have 100 first degree connections and, in turn, from them 2,000 second degree connections, does that mean that the average number of second degree connections among the first degree connections in my network is equal to 20? If this is a valid number, how can a user apply possibly this figure to advancing the size of his or her network, increase their presence and influence within their network, and assist in business and/or career development?

Another data point I am curious about is whether the degree to which one’s personal network on LinkedIn grows buy itself each day worth examining? That is, if you stop issuing or accepting new invitations to join other personal networks for a period of time, how much does a personal network continue to grow by virtue only of your own first degree connections continuing to send and accept invitations? If, for example, a network will increase its daily second degree connections in this manner by 0.005%, how can a user employ this factor in the same set of questions in the previous paragraph?

Finally, I would like to see some more granular data about networks involving particular professions and job titles. For instance, do attorneys as opposed to web designers have, on average, larger or smaller personal networks? As well, would this evidence direct causation or perhaps just correlation in the data?

Discussion re: Faster Web Service, Media Mergers and Net Neutrality

A far-ranging and highly informative discussion of some critical issues concerning the broadband industry in the US was presented on The Brian Lehrer Show on WNYC (the local NPR radio affiliate in New York City). The show’s host, Brian Lehrer, interviewed David Sirota, who is a columnist for The International Business Times. The topics they covered included:

  • The pending merger of Comcast and Time Warner
  • The service call to Comcast that went viral two weeks ago when someone tried to disconnect broadband service the company
  • The current developments and regulation affecting faster and cheaper web access in Tennessee and how this might affect potentially similar offerings in New York
  • Key issues concerning net neutrality

I highly recommend listening to this 23 minute podcast of this segment of the show entitled Will Fast, Cheap Internet Ever Come to New York? to help put these issues into a very timely and well-informed perspective.

On a multitude of many other topics, I also strongly recommend listening to The Brian Lehrer Show either on the air on WNYC in the New York metro area or online each weekday from 10 am to 12 noon EST. Each of the the show’s half dozen or so segments are quickly posted following the daily broadcasts and are available on the link to the show’s web page above. He is a truly remarkable interviewer with a deep and wide understanding of today’s issues, who has his guests and the audience members (live by phone and likewise participating via the show’s message board, Twitter and Facebook), discussing a range of local, national and global social and political issues, and topics concerning such areas as the media, work, health, the economy and so on.

Extensive Online Collection of Visualizations of Complex Networks

Following up on my earlier post about a tool to visualize your LinkedIn network, I recently came across VisualComplexity.com, a site devoted to being a resource for visualizing a wide range of complex networks. There are 777 viewable examples of networks in areas including, among others, social, biology, business, computers, music, knowledge and the web itself. Clicking through on any of the thumbnails across this site will take you to a dedicated page describing the visualization and its operation, the author, institute, year of its creation, and a direct link to its actual location. (Even in those instances where the links no longer work, there is still much to be learned on their descriptive page and screen captures.)

I found this resource to be remarkable resource and well worth the time spent here because it:

* Boldly displays the power of using visualization to understand the structure, dynamics and power of networks.
* Provides inspiration to explore these examples for their educational and analytical values.
* Displays the critical importance of carefully designing the structure of the manner in which data are being transformed into a display.
* Motivates visitors to consider the possibilities of applying visualization to their own professional projects.

As well, in a clear case of the merger of art and science, many of these of these visualizations are, imho, often quite aesthetically pleasing images that likewise stand on their own as works of art.

Another POV on the Power of the Network Effect

The propulsive power, structural operations and connective benefits of the Network Effect have been identified and studied in many fields of science, technology, the Web, telecom, transportation, biology, neuroscience and many others. Indeed, the Network Effect is writ large across nearly every aspect of the Web’s endless reach.

In an insightful post on Socialmediatoday.com on July 16, 2014, entitled Connection Brings Opportunity at Exponential Scale the author, Brian Vellmure, found his inspiration for this piece during a recent trip where he suddenly lost all connectivity. He then uses this to write about his perceptions of the multiplier effect the web has on creativity, science and industry by virtue of its potential for boundless numbers of connections to others out there in c-space. In effect, more connections equate to more value added with each additional user and node. He ends by posing the questions of how readers can use this to “evolve your organization to thrive in this new environment?”. I recommend a click-through and read of this worthwhile new take on this ubiquitous phenomenon.

Visualization Tool for LinkedIn Personal Networks

[UPDATE: LinkedIn Removed access to their networking tool on September 1, 2014. The notice indicating that they were working on new tools for users to map their personal networks on LinkedIn.]

Network mapping is a process of using graphics tools and algorithms to create visualizations of many varieties of, among many others, social, business, telecommunications, biological, and financial networks.

Given the wide availability of these capabilities, have you ever wondered what a visual map of your own network on LinkedIn might actually look like? If so, I highly recommend a click-through to LinkedIn Maps to quickly generate such a map. The site will ask your permission to access your LinkedIn account and then just take a few minutes to produce the map. After the image appears, you can use the “+” and “-” icons in the upper left to zoom in on the map. As you do this, you will see the names of your contacts begin to appear. When you click on a contact you will then see who that person is also connected to in your personal network and a brief summary of their work information in a sidebar on the right.

Besides giving form and shape to your network, this can be quite helpful in a job search or for business development as you start to see who is connected with whom in your network. What is really quite valuable and interesting in that you will likely find that there are members of you network who will be “hubs” connected to many others in your network, as well as those who are more like “spokes” with fewer connections.

Also, the color coding of different groupings of contacts is automatically done by some commonality of employment, education or other types of organizations. When you click on any specific contact within the graphic it will immediately highlight all of that person’s networking connections within your own network. There is a tool available in the interface to label these color concentrated sectors of your network.

Here is an example of what my LinkedIn network looks like (at a lower resolution so that the individual names do not appear):

linkedinmap

A Google search of social and business network mapping tools will produce a lengthy roster of other apps similar to LinkedIn Maps with a great diversity in their graphical and analytical capabilities.

 

Comprehensive Visualization of Future Paths of Technological Innovations

Data visualization tools and applications seem grow more intricate and original, and indeed more artistically bold and engaging, each day. Today, 4/8/14, is no exception as demonstrated in an new article posted on BusinessInsider.com entitled Science More: Health Future Science These Beautiful Charts Show The Coming Technologies That Will Change The World by Gus Lubin. He reports about a group of several private and Canadian governmental groups who have jointly produced a rather astonishing grahpics presentation predicting the development timelines on six major areas of technology. All of these are zoomable online for more detailed viewing. There is a single graphic that combines all six areas. Each of these six sectors are also individualls downloadable in PDF. They include:

  • Agricultural and Natural Manufacturing Technologies
  • Data and Communications Technologies
  • Energy Technologies
  • Health Technologies
  • Nantotechnology and Materials Science
  • Neurotechnology and Cognitive Technologies

Each of these sectors is broken down into subsections for specific developments and then each is expressed in a predictive timeline spanning the next 15 years.

While no one can accurately predict the future development paths of these sectors and the arrival dates of their presently percolating deliverables, these graphics are nonetheless a highly ambitious and original representations of what might occur. I highly recommend a click through and examination of these visualizations to appreciate the magnitude of this undertaking. Moreover, viewers might also see a challenge and find the inspiration to perhaps start or add something new that may one day appear in an update of this chart in, well, the future.

After spending some time exploring these graphics, I was reminded of the well known quote from the renowned computer scientist, Alan Kay, who once very famously said “The best way to predict the future is to invent it.”