Book Review of “Frenemies: The Epic Disruption of the Ad Business (and Everything Else)”

“Advertising in Times Square”, image by Dirk Knight

Every so often, an ad campaign comes along that is strikingly brilliant for its originality, execution, persuasiveness, longevity, humor and pathos. During the mid-1980’s, one of these bright shining examples was the television ads for Bartles & Jaymes Wine Coolers. They consisted of two fictional characters: Frank Bartles, who owned a winery and did all of the talking, and Ed Jaymes, a farmer who never spoke a word but whose deadpan looks were priceless. They traveled across the US to different locations in pursuit of sales, trying to somehow adapt their approaches to reflect the local surroundings. Bartles was very sincere but often a bit naive in his pitches along the way, best exemplified in this ad and another one when they visited New York.

These commercials succeeded beyond all expectations in simultaneously establishing brand awareness, boosting sales and being laugh-out-loud hilarious because Bartles’s and Jaymes’s were such charming, aw-shucks amateurs. In actuality, these ads were deftly conceived and staged by some smart and savvy creatives from the Hal Riney & Partners agency. For further lasting effect, they always had Bartles express his appreciation to the viewers at the end of each spot with his memorable trademark tagline of “Thanks for your support”. These 30-second video gems are as entertaining today as they were thirty years ago.

But those halcyon days of advertising are long gone. The industry’s primary media back then was limited to print, television and radio. Creativity was its  cornerstone and the words “data analytics” must have sounded like something actuaries did in a darkened room while contemplating the infinite. (Who knows, maybe it still does to some degree.)

Fast forwarding to 2018, advertising is an utterly different and hyper-competitive sector whose work product is largely splayed across countless mobile and stationary screens on Planet Earth. Expertly chronicling and precisely assaying the transformative changes happening to this sector is an informative and engaging new book entitled Frenemies: The Epic Disruption of the Ad Business (and Everything Else) [Penguin Press, 2018], by the renowned business author Ken Auletta. Just as a leading ad agency in its day cleverly and convincingly took TV viewers on an endearing cultural tour of the US as we followed the many ad-ventures of Bartles & Jaymes, so too, this book takes its readers on a far-ranging and immersive tour of the current participants, trends, challenges and technologies affecting the ad industry.

A Frenemy of My Frenemy is My Frenemy

Image from Pixabay

This highly specialized world is under assault from a confluence of competitive, online, economic, social and mathematical forces. Many people who work in it are deeply and rightfully concerned about its future and the tenure of their places in it. Auletta comprehensively reports on and assesses these profound changes from deep within the operations of several key constituencies (the “frenemies”, conflating “friend” and “enemy”). At first this might seem a bit too much of “inside baseball” (although the ad pitch remains alive and well), but he quickly and efficiently establishes who’s who and what’s what in today’s morphing ad markets, making this book valuable and accessible to readers both within and outside of this field.  It can also be viewed as a multi-dimensional case study of an industry right now being, in the truest sense of the word, disrupted.¹ There is likewise much to learned and considered here by other businesses being buffeted by similar winds.

Frenemies, as thoroughly explored throughout this book, are both  business competitors and partners at the same time. They are former and current allies in commerce who concurrently cooperate and compete. Today they are actively infiltrating each other’s markets. The full matrix of frenemies and their threats and relationships to each other includes the interests and perspectives of ad agencies and their clients, social media networks, fierce competition from streamers and original content producers like Netflix², traditional media in transition to digital platforms, consulting companies and, yes, consumers.

Auletta travels several parallel tracks in his reporting. First, he examines the past, present on onrushing future with respect to revenue streams, profits, client bases served, artificial intelligence (AI) driven automation, and the frenemies’ very fluid alliances. Second, he skillfully deploys the investigative journalistic strategy of “following the money” as it ebbs and flows in many directions among the key players. Third, he illuminates the industry’s evolution from Don Draper’s traditional “Mad Men” to 2018’s “math men” who are the data wranglers, analysts and strategists driven by ever more thin-sliced troves of consumer data the agencies and their corporate clients are using to achieve greater accuracy and efficiency in selling their goods and services.

A deep and wide roster of C-level executives from these various groups were interviewed for the book. Chief among them are two ad industry legends who serve as the x and y axes upon which Auletta has plotted a portion of his reporting. One is Martin Sorrell, who was the founder and CEO of WPP, the world’s largest advertising holding company.³ The other is Michael Kassan, the founder and CEO of MediaLink, a multifaceted firm that connects, negotiates and advises on behalf of a multitude of various parties, often competitors in critical matters affecting the ad business. Both of these individuals have significantly shaped modern advertising over many decades and are currently propagating some of the changes spotlighted in the book in trying to keep it vital, relevant and profitable.

Online Privacy v. Online Primacy

“Tug of War”, image by Pixabay

The established tradition of creativity being the primary driver of advertising creation and campaigns has given way to algorithm-driven data analytics. All of the frenemies and a myriad of other sites in many other parsecs of the websphere vacuum up vast amounts of data on users, their online usage patterns, and even go so far as to try to infer their behavioral attributes. This is often combined with additional personal information from third-party sources and data brokers. Armed with all of this data and ever more sophisticated means for sifting and intuiting it, including AI4, the frenemies are devising their campaigns to far more precisely target potential consumers and their cohorts with finely grained customized ads.

The high point of this book is Auletta’s nuanced coverage of the ongoing controversy involving the tension between frenemies using data analytics to increase click-through rates and, hopefully, sales versus respecting the data privacy of people as they traverse the Web. In response to this voracious data collection, millions of users have resisted this intrusiveness by adding free browser extensions such as AdBlock Plus to circumvent online tracking and ad distribution.5 This struggle has produced a slippery slope between the commercial interests of the frenemies and consumers’ natural distaste for advertising, as well as their resentment at having their data co-opted, appropriated and misused without their knowledge or consent. Recently, public and governmental concerns were dramatically displayed in the harsh light of the scandals involving Facebook and Cambridge Analytica.

Furthermore, Google and Facebook dominate the vast majority of online advertising traffic, revenues and, most importantly, the vast quantum of user information which ad agencies believe would be particularly helpful to them in profiling and reaching consumers. Nonetheless, they maintain it is highly proprietary to them alone and much of it has not been shared. Frenemies much?

Additional troubling trends for the ad industry are likewise given a thorough 3-D treatment. Auletta returns to the axiom several times that audiences do not want to be interrupted with ads (particularly on their mobile devices). Look no further than the likes of premium and the major streaming services who offer all of their content uninterrupted in its entirety. The growing ranks of content creators they engage know this and prefer it because they can concentrate on their presentations without commercial breaks slicing and dicing their narrative continuity. The still profitable revenue streams flowing from this are based upon the strengths of the subscription model.

Indeed, in certain cases advertising is being simultaneously disrupted and innovated. Some of the main pillars of the media like The New York Times are now expanding their in-house advertising staff and service offerings. They can offer a diversified array of ads and analyses directly to their advertisers. Likewise, engineering-driven operations like Google and Facebook can deploy their talent benches to better target consumers for their advertisers by extracting and applying insights from their massive databases. Why should their clients continue go to the agencies when their ads can be composed and tracked for them directly?

Adapt or Go Home

“Out with the Old, In with the New”, image by Mark

The author presents a balanced although not entirely sanguine view of the ad industry’s changes to maintain its composure and clients in the midst of this storm. The frenemy camps must be willing to make needed and often difficult adjustments to accommodate emerging technological and strategic survival methods. He examines the results of two contemporary approaches to avoiding adblocking apps and more fully engaging very specific audiences. One is called “native advertising“, which involves advertisers producing commercial content and paying for its placement online or in print to promote their own products. Generally, these are formatted and integrated to appear as though they are integrated with a site’s or publication’s regular editorial content but contain a notice that it is, in fact “Advertising”.

However, Auletta believes that the second adaptive mechanism, the online subscription model, will not be much more sustainable beyond its current successes. Consumers are already spending money on their favorite paywalled sites.  But it would seem logical that users might not be thus willing to pay for Facebook and others that have always been free. As well, cable’s cord-cutters are continuing to exhibit steady growing in their numbers and their migrations towards streaming services such as Amazon Prime.6

Among the media giants, CBS seems to be getting their adaptive strategies right from continuing to grow multiple revenue streams. They now have the legal rights and financial resources to produce and sell original programming. They have also recently launched original web programming such as Star Trek: Discovery on a commercial-free subscription basis on CBS All Access. This can readily be seen as a challenge to Netflix despite the fact that CBS also providing content to Netflix. Will other networks emulate this lucrative and eyeball attracting model?

As Auletta also concludes, for now at least, consumers as frenemies, appear to be the beneficiaries of all this tumult. They have many device agnostic platforms, pricing options and a surfeit of content from which to choose. They can also meaningfully reduce, although not entirely eliminate, ads following them all over the web and those pesky stealth tracking systems. Whether they collectively can maintain their advantage is subject to sudden change in this environment.

Because of the timing of the book’s completion and publication, the author and publisher should consider including in any subsequent edition the follow-up impacts of Sorrell’s departure from WPP and his new venture (S4 Capital), the effects of the May 2018 implementation of EU’s General Data Protection Regulation (GDPR), and the progress of any industry or government regulation following the raft of recent massive data breaches and misuses.

Notwithstanding that, however, “Frenemies” fully delivers on all of its book jacket’s promises and premises. It is a clear and convincing case of truth in, well, advertising.

So, how would Frank Bartles and Ed Jaymes 2.0 perceive their promotional travels throughout today’s world? Would their folksy personas play well enough on YouTube to support a dedicated channel for them? Would their stops along the way be Instagram-able events? What would be their reactions when asked to Google something or download a podcast?

Alternatively, could they possibly have been proto-social media influencers who just showed up decades too soon? Nah, not really. Even in today’s digital everything world, Frank and Ed 1.0 still abide. Frank may have also unknowingly planted a potential meme among today’s frenemies with his persistent proclamations of “Thanks for your support”: The 2018 upgrade might well be “Thanks for your support and all of your data”.

 


For a very enlightening interview with Ken Auletta, check out the June 26, 2018 podcast entitled Game Change: How the Ad Business Got Disrupted, from The Midday Show on WNYC (the local NPR affiliate in New York).


September 4, 2018 Update: Today’s edition of The New York Times contains an highly enlightening article directly on point with many of the key themes of Frenemies entitled Amazon Sets Its Sights on the $88 Billion Online Ad Market, by Julie Creswell. The report details Amazon’s significant move into online advertising supported by its massive economic, data analytics, scaling and strategic resources. It comprehensively analyzes the current status and future prospects of the company’s move into direct competition with Google and Facebook in this immense parsec of e-commerce. I highly recommend a click-through and full read of this if you have an opportunity.


1.   The classic work on the causes and effect of market disruptions, the disruptors and those left behind is The Innovator’s Dilemma, by Clayton Christensen (HarperBusiness, 2011). The first edition of the book was published in 1992.

2.    Netflix Topples HBO in Emmy Nominations, but ‘Game of Thrones’ Still Rules, July 13, 2018, New York Times, by The Associated Press. However, see also Netflix Drops Dud on Wall St. As Subscriber Growth Flops, July 16, 2018, New York Times, by Reuters.

3.   Sorrell is reported in the book as saying he would not leave anytime soon from running WPP. However, following the book’s publication, he was asked to step down in April 2018 following allegations of inappropriate conduct. See Martin Sorrell Resigns as Chief of WPP Advertising Agency, New York Times, by Matt Stevens and Liz Alderman, April 14, 2018. Nonetheless, Sorrell has quickly returned to the industry as reported in Martin Sorrell Beats WPP in Bidding War for Dutch Marketing Firm, New York Times, by Sapna Maheshwari, July 10, 2018.

4.  For a very timely example, see The Ad Agency Giant Omnicom Has Created a New AI Tool That is Poised to Completely Change How Ads Get Made, BusinessInsider.com, by Lauren Johnson,  July 12, 2018.

5.   Two other similar anti-tracking browser extensions in wide usage include, among others Ghostery and Privacy Badger.

6.   See also  Cord-Cutting Keeps Churning: U.S. Pay-TV Cancelers to Hit 33 Million in 2018 (Study), Variety.com, by Todd Spangler, July 24, 2018.

TechDay New York 2018: 500 Local Startups’ Displays, Demos and Delights for the Crowd

All photos on this page by Alan Rothman.

Sometimes in traditional advertising for creative works like movies, TV shows, books and plays, the quoted reviews and taglines include the exclamation “This one’s got it all!” Yet this is only rarely, if ever, true.

Well, wait a minute. Let’s check that.

Last Thursday, May 10th, I had the great pleasure of attending TechDay New York 2018, held at Pier 94, on the West Side of midtown Manhattan. This is a monumental annual exhibition of 500 startups located throughout NYC almost did have it all. In addition to all of these new companies, there were separate areas set up for brief products and services demos and talks by industry experts. Even the TV show Shark Tank was on site there.

First and foremost, massive amounts of thanks to everyone at Techday for putting on such a terrifically enjoyable, informative and memorable event. Their efforts clearly showed that they worked long and hard to get everything about it right.

On to the show …

One of New York City’s greatest economic and cultural strengths has always been its incredible global diversity of it population. So, too, is that dynamic comparably evident in the breadth of it startup ecosystem. From one end of Pier 94 to the other, there was artificial intelligence this, blockchain that, and data analytics everything infused everywhere.

Just a sampling of who and what were on display, among many others, were startups in legal services, architecture, editorial software, video search, incubators and accelerators, social media support services, event planning platforms, programmer aptitude testing, intellectual property protection, pharmacy order and delivery services, office design consultants, branding and digital experience designers, augmented and virtual reality hardware and software, venture capitalist, crowdfunding services, multi-platform public relations strategists, fashion designers, food services (some displaying much chocolate!), consumer data tracking analyst, competitive intelligence trackers and analysts, restaurant reservations, media consultants, phone apps, online security planning and systems, fully integrated electronic health records and billing systems, and dedicated tech recruiters as well as exhibitors themselves looking for new talent. Whew!

Notwithstanding the vastness of the exhibition space, hundreds of startups and thousands of attendees, the organization and presentations of the startups’ display areas was well planned and easy to navigate. The startups were grouped in helpful sectors for social media, e-commerce, fintech and others into more general categories.

The three among the twelve TechDay Talks I attended were quite compelling and evinced great enthusiasm by both the speakers and their audiences. These included:

Above all other considerations, I found every entrepreneur I stopped and spoke with, asking them to tell me about their company, to be highly enthusiastic, engaging and sincere. They were knowledgeable about their markets and competitors, sounded willing to adapt to changing market conditions and, most importantly, convinced that they would become successful. At no point did any of them move on to their next visitors until they sensed that I understood what they were saying and encouraging me to follow their progress online. They were not so much giving visitors hard sales pitches, but rather, much more of the who, what, where, how and when of their businesses. My gratitude to all of them for their patience with me and many of the other attendees I saw them talking to with the same level of professionalism.

Below are some of the photos I took while I was there. I was trying to capture some sense of infectious energy and engagement being generated across entire day’s events.

My very best wishes to all 500 startups to succeed and prosper.

 


 *   For some very worthwhile deep and wide analysis of the effects of AI upon current and future employment, I highly recommend the recently published book entitled Human + Machine: Reimagining Work in the Age of AI, by Paul Daugherty (Harvard Business Review Press, 2018).


 

 

 

 

 

Artificial Swarm Intelligence: There Will be An Answer, Let it Bee

Honey Bee on Willow Catkin", Image by Bob Peterson

“Honey Bee on Willow Catkin”, Image by Bob Peterson

In almost any field involving new trends and developments, anything attracting rapidly increasing media attention is often referred to in terms of “generating a lot of buzz”. Well, here’s a quite different sort of story that adds a whole new meaning to this notion.

A truly fascinating post appeared on TechRepublic.com this week on January 22, 2016 entitled How ‘Artificial Swarm Intelligence’ Uses People to Make Smarter Predictions Than Experts by Hope Reese. It is about a development where technology and humanity intersect in a highly specialized manner to produce a new means to improve predictions by groups of people. I highly recommend reading it in its entirety. I will summarize and annotate it, and then pose a few of my own bug-free questions.

A New Prediction Platform

In a recent switching of roles, while artificial intelligence (AI) concerns itself with machines executing human tasks¹, a newly developed and highly accurate algorithm “harnesses the power” of crowds to generate predictions of “real world events”. This approach is called “artificial swarm intelligence“.

A new software platform called UNU has being developed by a startup called Unanimous AI. The firm’s CEO is Dr. Louis Rosenberg. UNU facilitates the gathering of people online in order to “make collective decisions”. This is being done, according to Dr. Rosenberg “to amplify human intelligence”. Thus far, the platform has been “remarkably accurate” in its predictions of the Academy Awards, the Super Bowl² and elections.

UNU is predicated upon the concept of the wisdom of the crowds which states that larger groups of people make better decisions collectively than even the single smartest person within that group.³  Dr. Roman Yampolskiy, the Director of the Cybersecurity Lab at the University of Louisville, has also created a comparable algorithm known as “Wisdom of Artificial Crowds“. (The first time this phenomenon was covered on The Subway Fold, in the context of entertainment, was in the December 10, 2014 post entitled Is Big Data Calling and Calculating the Tune in Today’s Global Music Market?)

The Birds and the Bees

Swarm intelligence learns from events and systems occurring in nature such as the formation of swarms by bees and flocks by birds. These groups collectively make better choices than their single members. Dr. Rosenberg believes that, in his view there is “a vast amount of intelligence in groups” that, in turn generates “intelligence that amplifies their natural abilities”. He has transposed the rules of these natural systems onto the predictive abilities of humans in groups.

He cites honeybees as being “remarkable” decision-makers in their environment. On a yearly basis, the divide their colonies and “send out scout bees” by the hundreds for many miles around to check out locations for a new home. When these scouts return to the main hive they perform a “waggle dance” to “convey information to the group” and next decide about the intended location. For the entire colony, this is a “complex decision” composed of “conflicting variables”. On average, bee colonies choose the optimal location by more than 80%.

Facilitating Human Bee-hive-ior

However, humans display a much lesser accuracy rate when making their own predictions. Most commonly, polling and voting is used. Dr. Rosenberg finds such methods “primitive” and often incorrect as they tend to be “polarizing”. In effect, they make it difficult to assess the “best answer for the group”.

UNU is his firm’s attempt to facilitate humans with making the best decisions for an entire group. Users log onto it and respond to questions with a series of possible choices displayed. It was modeled upon such behavior occurring in nature among “bees, fish and birds”. This is distinguished from individuals just casting a single vote. Here are two videos of the system in action involving choosing the most competitive Republican presidential candidate and selecting the most beloved sidekick from Star Wars4. As groups of users make their selections on UNU and are influenced by the visible onscreen behavior of others, this movement is the online manifestation of the group’s swarming activity.

Another instance of UNU’s effectiveness and accuracy involved 50 users trying to predict the winners of the Academy Awards. On an individual basis, they each averaged six out of 15 correct. This test swarm was able to get a significantly better nine out of the 15.  Beyond movies, the implications may be further significant if applied in areas such as strategic business decision-making.

My Questions

  • Does UNU lend itself to being turned into a scalable mobile app for much larger groups of users on a multitude of predictions? If so, should users be able to develop their own questions and choices for the swarm to decide? Should all predictions posed be open to all users?
  • Might UNU find some sort of application in guiding the decision process of juries while they are resolving a series of factual issues?
  • Could UNU be used to supplement reviews for books, movies, music and other forms of entertainment? Perhaps some form of “UNU Score” or “UNU Rating”?

 


1.  One of the leading proponents and developers of AI for many decades was MIT Professor Marvin Minsky who passed away on Sunday, January 24, 2016. Here is his obituary from the January 25, 2015 edition of The New York Times entitled Marvin Minsky, Pioneer in Artificial Intelligence, Dies at 88, by Glenn Rifkin.

2.  For an alternative report on whether the wisdom of the crowds appears to have little or no effect on the Super Bowl, one not involving UNU in any way, see an article in the January 28, 2016 edition of The New York Times entitled Super Bowl Challenges Wisdom of Crowds and Oddsmakers, by Victor Mather.

3.  An outstanding and comprehensive treatment of this phenomenon I highly recommend reading The Wisdom of the Crowds, by James Surowiecki (Doubleday, 2004).

4.  I would really enjoy seeing a mash-up of these two demos to see how the group would swarm among the Star Wars sidekicks to select which one of these science fiction characters might have the best chance to win the 2016 election.

New IBM Watson and Medtronic App Anticipates Low Blood Glucose Levels for People with Diabetes

"Glucose: Ball-and-Stick Model", Image by Siyavula Education

“Glucose: Ball-and-Stick Model”, Image by Siyavula Education

Can a new app jointly developed by IBM with its Watson AI technology in partnership with the medical device maker Medtronic provide a new form of  support for people with diabetes by safely avoiding low blood glucose (BG) levels (called hypoglycemia), in advance? If so, and assuming regulatory approval, this technology could potentially be a very significant boon to the care of this disease.

Basics of Managing Blood Glucose Levels

The daily management of diabetes involves a diverse mix of factors including, but not limited to, regulating insulin dosages, checking BG readings, measuring carbohydrate intakes at meals, gauging activity and exercise levels, and controlling stress levels. There is no perfect algorithm to do this as everyone with this medical condition is different from one another and their bodies react in individual ways in trying to balance all of this while striving to maintain healthy short and long-term control of BG levels.

Diabetes care today operates in a very data-driven environment. BG levels, expressed numerically, can be checked on hand-held meter and test strips using a single drop of blood or a continuous glucose monitoring system (CGM). The latter consists of a thumb drive-size sensor attached with temporary adhesive to the skin and a needle attached to this unit inserted just below the skin. This system provides patients with frequent real-time readings of their BG levels, and whether they are trending up or down, so they can adjust their medication accordingly. That is, for A grams of carbs and B amounts of physical activity and other contributing factors, C amount of insulin can be calculated and dispensed.

Insulin itself can be administered either manually by injection or by an insulin pump (also with a subcutaneously inserted needle). The later of these consists of two devices: The pump itself, a small enclosed device (about the size of a pager), with an infusion needle placed under the patient’s skin and a Bluetooth-enabled handheld device (that looks just like a smartphone), used to adjust the pump’s dosage and timing of insulin released. Some pump manufacturers are also bringing to market their latest generation of CGMs that integrate their data and command functions with their users’ smartphones.

(The links in the previous two paragraphs are to Wikipedia pages with detailed pages and photos on CGMs and insulin pumps. See also, this June 27, 2015 Subway Fold post entitled Medical Researchers are Developing a “Smart Insulin Patch” for another glucose sensing and insulin dispensing system under development.)

The trickiest part of all of these systems is maintaining levels of BG throughout each day that are within an acceptable range of values. High levels can result in a host of difficult symptoms. Hypoglycemic low levels, can quickly become serious, manifesting as dizziness, confusion and other symptoms, and can ultimately lead to unconsciousness in extreme cases if not treated immediately.

New App for Predicting and Preventing Low Blood Glucose Levels

Taking this challenge to an entirely new level, at last week’s annual Consumer Electronics Show (CES) held in Las Vegas, IBM and Medtronic jointly announced their new app to predict hypoglycemic events in advance. The app is built upon Watson’s significant strengths in artificial intelligence (AI) and machine learning to sift through and intuit patterns in large volumes of data, in this case generated from Medtronic’s user base for their CGMs and insulin pumps. This story was covered in a most interesting article posted in The Washington Post on January 6, 2016 entitled IBM Extends Health Care Bet With Under Armour, Medtronic by Jing Cao and Michelle Fay Cortez. I will summarize and annotate this report and then pose some of my own questions.

The announcement and demo of this new app on January 6, 2016 at CES showed the process by which a patient’s data can be collected from their Medtronic devices and then combined with additional information from their wearable activity trackers and food intake. Next, all of this information is processed through Watson in order to “provide feedback” for the patient to “manage their diabetes”.

Present and Future Plans for The App and This Approach

Making the announcement were Virginia Rometty, Chairman, President and CEO of IBM, and Omar Ishrak, Chairman and CEO of Medtronic. The introduction of this technology is expected in the summer of 2016. It still needs to be submitted to the US government’s regulatory review process.

Ms. Rometty said that the capability to predict low BG events, in some cases up to three hours before they occur, is a “breakthrough”. She described Watson as “cognitive computing”, using algorithms to generate “prescriptive and predictive analysis”. The company is currently making a major strategic move into finding and facilitating applications and partners for Watson in the health care industry. (The eight Subway Fold posts cover other various systems and developments using Watson.)

Hooman Hakami, Executive VP and President, of the Diabetes Group at Medtronic, described how his company is working to “anticipate” how the behavior of each person with Diabetes affects their blood glucose levels. With this information they can then “make choices to improve their health”. Here is the page from the company’s website about their partnership with IBM to work together on treating diabetes.

In the future, both companies are aiming to “give patients real-time information” on how their individual data is influencing their BG levels and “provide coaching” to assist them in making adjustments to keep their readings in a “healthy range”. In one scenario, patients might receive a text message that “they have an 85% chance of developing low blood sugar within an hour”. This will also include a recommendation to watch their readings and eat something to raise their BG back up to a safer level.

My Questions

  • Will this make patients more or less diligent in their daily care? Is there potential for patients to possibly assume less responsibility for their care if they sense that the management of their diabetes is running on a form of remote control? Alternatively, might this result in too much information for patients to manage?
  • What would be the possible results if this app is ever engineered to work in conjunction with the artificial pancreas project being led in by Ed Damiano and his group of developers in Boston?
  • If this app receives regulatory approval and gains wide acceptance among people with diabetes, what does this medical ecosystem look like in the future for patients, doctors, medical insurance providers, regulatory agencies, and medical system entrepreneurs? How might it positively or negatively affect the market for insulin pumps and CGMs?
  • Should IBM and Medtronic consider making their app available on and open-source basis to enable other individuals and groups of developers to improve it as well as develop additional new apps?
  • Whether and how will insurance policies for both patients and manufacturers, deal with any potential liability that may arise if the app causes some unforeseen adverse effects? Will medical insurance even cover, encourage or discourage the use of such an app?
  • Will the data generated by the app ever be used in any unforeseen ways that could affect patients’ privacy? Would patients using the new app have to relinquish all rights and interests to their own BG data?
  • What other medical conditions might benefit from a similar type of real-time data, feedback and recommendation system?

NASA is Providing Support for Musical and Humanitarian Projects

"NASA - Endeavor 2", Image by NASA

“NASA – Endeavor 2”, Image by NASA

In two recent news stories, NASA has generated a world of good will and positive publicity about itself and its space exploration program. It would be an understatement to say their results have been both well-grounded and out of this world.

First, NASA astronaut Chris Hadfield created a vast following for himself online when he uploaded a video onto YouTube of him singing David Bowie’s classic Space Oddity while on a mission on the International Space Station (ISS).¹ As reported on the October 7, 2015 CBS Evening News broadcast, Hadfield will be releasing an album of 12 songs he wrote and performed in space, today on October 9. 2015. He also previously wrote a best-selling book entitled An Astronaut’s Guide to Life on Earth: What Going to Space Taught Me About Ingenuity, Determination, and Being Prepared for Anything (Little, Brown and Company, 2013). I highly recommend checking out his video, book and Twitter account @Cmdr_Hadfield.

What a remarkably accomplished career in addition to his becoming an unofficial good will ambassador for NASA.

The second story, further enhancing the agency’s reputation, concerns a very positive program affecting many lives that was reported in a most interesting article on Wired.com on September 28, 2015 entitled How NASA Data Can Save Lives From Space by Issie Lapowsky. I will summarize and annotate it, and then pose some my own terrestrial questions.

Agencies’ Partnership

According to a NASA administrator Charles Bolden, astronauts frequently look down at the Earth from space and realize that borders across the world are subjectively imposed by warfare or wealth. These dividing lines between nations seem to become less meaningful to them while they are in flight. Instead, the astronauts tend to look at the Earth and have a greater awareness everyone’s responsibilities to each other. Moreover, they wonder what they can possibly do when they return to make some sort of meaningful difference on the ground.

Bolden recently shared this experience with an audience at the United States Agency for International Development (USAID) in Washington, DC, to explain the reasoning behind a decade-long partnership between NASA and USAID. (This latter is the US government agency responsible for the administration of US foreign aid.) At first, this would seem to be an unlikely joint operation between two government agencies that do not seem to have that much in common.

In fact, this combination provides “a unique perspective on the grave need that exists in so many places around the world”, and a special case where one agency sees it from space and the other one sees it on the ground.

They are joined together into a partnership known as SERVIR where NASA supplies “imagery, data, and analysis” to assist developing nations.  They help these countries with forecasting and dealing “with natural disasters and the effects of climate change”.

Partnership’s Results

Among others, SERVIR’s tools have produced the following representative results:

  • Predicting floods in Bangladesh that gives citizens a total of eight days notice in order to make preparations that will save lives. This reduced the number to 17 during the last year’s monsoon season whereas previously it had been in the thousands.
  • Predicting forest fires in the Himalayas.
  • For central America, NASA created  a map of ocean chlorophyll concentration that assisted public officials in identifying and improving shellfish testing in order to deal with “micro-algae outbreaks” responsible for causing significant health issues.

SERVIR currently operates in 30 countries. As a part of their network, there are regional hubs working with “local partners to implement the tools”. Last week it opened such a hub in Asia’s Mekong region. Both NASA and USAID are hopeful that the number of such hubs will continue to grow.

Google is also assisting with “life saving information from satellite imagery”. They are doing this by applying artificial intelligence (AI)² capabilities to Google Earth. This project is still in its preliminary stages.

My Questions

  • Should SERVIR reach out to the space agencies and humanitarian organizations of other countries to explore similar types of humanitarian joint ventures?
  • Do the space agencies of other countries have similar partnerships with their own aid agencies?
  • Would SERVIR benefit from partnerships with other US government agencies? Similarly, would it benefit from partnering with other humanitarian non-governmental organizations (NGO)?
  • Would SERVIR be the correct organization to provide assistance in global environmental issues? Take for example the report on the October 8, 2015 CBS Evening News network broadcast of the story about the bleaching of coral reefs around the world.

 


1.  While Hatfield’s cover and Bowie’s original version of Space Oddity are most often associated in pop culture with space exploration, I would like to suggest another song that also captures this spirit and then truly electrifies it: Space Truckin’ by Deep Purple. This appeared on their Machine Head album which will be remembered for all eternity because it included the iconic Smoke on the Water. Nonetheless, Space Truckin‘ is, in my humble opinion, a far more propulsive tune than Space Oddity. Its infectious opening riff will instantly grab your attention while the rest of the song races away like a Saturn Rocket reaching for escape velocity. Furthermore, the musicianship on this recording is extraordinary. Pay close attention to Richie Blackmore’s scorching lead guitar and Ian Paice’s thundering drums. Come on, let’s go space truckin’!

2. These eight Subway Fold posts cover AI from a number of different perspectives involving a series of different applications and markets.

New Startup’s Legal Research App is Driven by Watson’s AI Technology

"Supreme Court, 60 Centre Street, Lower Manhattan", Image by Jeffrey Zeldman

[New York] “Supreme Court, 60 Centre Street, Lower Manhattan”, Image by Jeffrey Zeldman

May 9, 2016: An update on this post appears below.


Casey Stengel had a very long, productive and colorful career in professional baseball as a player for five teams and later as a manager for four teams. He was also consistently quotable (although not to the extraordinary extent of his Yankee teammate Yogi Berra). Among the many things Casey said was his frequent use of the imperative “You could look it up”¹.

Transposing this gem of wisdom from baseball to law practice², looking something up has recently taken on an entirely new meaning. According to a fascinating article posted on Wired.com on August 8, 2015 entitled Your Lawyer May Soon Ask for This AI-Powered App for Legal Help by Davey Alba, a startup called ROSS Intelligence has created a unique new system for legal research. I will summarize, annotate and pose a few questions of my own.

One of the founders of ROSS, Jimoh Ovbiagele (@findingjimoh), was influenced by his childhood and adolescent experiences to pursue studying either law or computer science. He chose the latter and eventually ended up working on an artificial intelligence (AI) project at the University of Toronto. It occurred to him then that machine learning (a branch of AI), would be a helpful means to assist lawyers with their daily research requirements.

Mr. Ovbiagele joined with a group of co-founders from diverse fields including “law to computers to neuroscience” in order to launch ROSS Intelligence. The legal research app they have created is built upon the AI capabilities of IBM’s Watson as well as voice recognition. Since June, it has been tested in “small-scale pilot programs inside law firms”.

AI, machine learning, and IBM’s Watson technology have been variously taken up in these nine Subway Fold posts. Among them, the September 1, 2014 post entitled Possible Futures for Artificial Intelligence in Law Practice covered the possible legal applications of IBM’s Watson (prior to the advent of ROSS), and the technology of a startup called Viv Labs.

Essentially, the new ROSS app enables users to ask legal research questions in natural language. (See also the July 31, 2015 Subway Fold post entitled Watson, is That You? Yes, and I’ve Just Demo-ed My Analytics Skills at IBM’s New York Office.) Similar in operation to Apple’s Siri, when a question is verbally posed to ROSS, it searches through its data base of legal documents to provide an answer along with the source documents used to derive it. The reply is also assessed and assigned a “confidence rating”. The app further prompts the user to evaluate the response’s accuracy with an onscreen “thumbs up” or “thumbs down”. The latter will prompt ROSS to produce another result.

Andrew Arruda (@AndrewArruda), another co-founder of ROSS, described the development process as beginning with a “blank slate” version of Watson into which they uploaded “thousands of pages of legal documents”, and trained their system to make use of Watson’s “question-and-answer APIs³. Next, they added machine learning capabilities they called “LegalRank” (a reference to Google’s PageRank algorithm), which, among others things, designates preferential results depending upon the supporting documents’ numbers of citations and the deciding courts’ jurisdiction.

ROSS is currently concentrating on bankruptcy and insolvency issues. Mr. Ovbiagele and Mr. Arruda are sanguine about the possibilities of adding other practice areas to its capabilities. Furthermore, they believe that this would meaningfully reduce the $9.6 billion annually spent on legal research, some of which is presently being outsourced to other countries.

In another recent and unprecedented development, the global law firm Dentons has formed its own incubator for legal technology startups called NextLaw Labs. According to this August 7, 2015 news release on Denton’s website, the first company they have signed up for their portfolio is ROSS Intelligence.

Although it might be too early to exclaim “You could look it up” at this point, my own questions are as follows:

  • What pricing model(s) will ROSS use to determine the cost structure of their service?
  • Will ROSS consider making its app available to public interest attorneys and public defenders who might otherwise not have the resources to pay for access fees?
  • Will ROSS consider making their service available to the local, state and federal courts?
  • Should ROSS make their service available to law schools or might this somehow impair their traditional teaching of the fundamentals of legal research?
  • Will ROSS consider making their service available to non-lawyers in order to assist them in represent themselves on a pro se basis?
  • In addition to ROSS, what other entrepreneurial opportunities exist for other legal startups to deploy Watson technology?

Finally, for an excellent roundup of five recent articles and blog posts about the prospects of Watson for law practice, I highly recommend a click-through to read Five Solid Links to Get Smart on What Watson Means for Legal, by Frank Strong, posted on The Business of Law Blog on August 11, 2015.


May 9, 2016 Update:  The global law firm of Baker & Hostetler, headquartered in Cleveland, Ohio, has become the first US AmLaw 100 firm to announce that it has licensed the ROSS Intelligence’s AI product for its bankruptcy practice. The full details on this were covered in an article posted on May 6, 2016 entitled AI Pioneer ROSS Intelligence Lands Its First Big Law Clients by Susan Beck, on Law.com.

Some follow up questions:

  • Will other large law firms, as well as medium and smaller firms, and in-house corporate departments soon be following this lead?
  • Will they instead wait and see whether this produces tangible results for attorneys and their clients?
  • If so, what would these results look like in terms of the quality of legal services rendered, legal business development, client satisfaction, and/or the incentives for other legal startups to move into the legal AI space?

1.  This was also the title of one of his many biographies,  written by Maury Allen, published Times Books in 1979.

2.  For the best of both worlds, see the legendary law review article entitled The Common Law Origins of the Infield Fly Rule, by William S. Stevens, 123 U. Penn. L. Rev. 1474 (1975).

3For more details about APIs see the July 2, 2015 Subway Fold post entitled The Need for Specialized Application Programming Interfaces for Human Genomics R&D Initiatives

Watson, is That You? Yes, and I’ve Just Demo-ed My Analytics Skills at IBM’s New York Office

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My photo of the entrance to IBM’s office at 590 Madison Avenue in New York, taken on July 29, 2015.

I don’t know if my heart can take this much excitement. Yesterday morning, on July 29, 2015, I attended a very compelling presentation and demo of IBM’s Watson technology. (This AI-driven platform has been previously covered in these five Subway Fold posts.) Just the night before, I saw I saw a demo of some ultra-cool new augmented reality systems.

These experiences combined to make me think of the evocative line from Supernaut by Black Sabbath with Ozzie belting out “I’ve seen the future and I’ve left it behind”. (Incidentally, this prehistoric metal classic also has, IMHO, one of the most infectious guitar riffs with near warp speed shredding ever recorded.)

Yesterday’s demo of Watson Analytics, one key component among several on the platform, was held at IBM’s office in the heart of midtown Manhattan at 590 Madison Avenue and 57th Street. The company very graciously put this on for free. All three IBM employees who spoke were outstanding in their mastery of the technology, enthusiasm for its capabilities, and informative Q&A interactions with the audience. Massive kudos to everyone involved at the company in making this happen. Thanks, too, for all of attendees who asked such excellent questions.

Here is my summary of the event:

Part 1: What is Watson Analytics?

The first two speakers began with a fundamental truth about all organizations today: They have significant quantities of data that are driving all operations. However, a bottleneck often occurs when business users understand this but do not have the technical skills to fully leverage it while, correspondingly, IT workers do not always understand the business context of the data. As a result, business users have avenues they can explore but not the best or most timely means to do so.

This is where Watson can be introduced because it can make these business users self-sufficient with an accessible, extensible and easier to use analytics platform. It is, as one the speakers said “self-service analytics in the cloud”. Thus, Watson’s constituents can be seen as follows:

  • “What” is how to discover and define business problems.
  • “Why” is to understand the existence and nature of these problems.
  • “How” is to share this process in order to affect change.

However, Watson is specifically not intended to be a replacement for IT in any way.

Also, one of Watson’s key capabilities is enabling users to pursue their questions by using a natural language dialog. This involves querying Watson with questions posed in ordinary spoken terms.

Part 2: A Real World Demo Using Airline Customer Data

Taken directly from the world of commerce, the IBM speakers presented a demo of Watson Analytics’ capabilities by using a hypothetical situation in the airline industry. This involved a business analyst in the marketing department for an airline who was given a compilation of market data prepared by a third-party vendor. The business analyst was then assigned by his manager with researching and planning how to reduce customer churn.

Next, by enlisting Watson Analytics for this project, the two central issues became how the data could be:

  • Better understand, leveraged and applied to increase customers’ positive opinions while simultaneously decreasing the defections to the airline’s competitors.
  • Comprehensively modeled in order to understand the elements of the customer base’s satisfaction, or lack thereof, with the airline’s services.

The speakers then put Watson Analytics through its paces up on large screens for the audience to observe and ask questions. The goal of this was to demonstrate how the business analyst could query Watson Analytics and, in turn, the system would provide alternative paths to explore the data in search of viable solutions.

Included among the variables that were dexterously tested and spun into enlightening interactive visualizations were:

  • Satisfaction levels by other peer airlines and the hypothetical Watson customer airline
  • Why customers are, and are not, satisfied with their travel experience
  • Airline “status” segments such as “platinum” level flyers who pay a premium for additional select services
  • Types of travel including for business and vacation
  • Other customer demographic points

This results of this exercise as they appeared onscreen showed how Watson could, with its unique architecture and tool set:

  • Generate “guided suggestions” using natural language dialogs
  • Identify and test all manner of connections among the population of data
  • Use predictive analytics to make business forecasts¹
  • Calculate a “data quality score” to assess the quality of the data upon which business decisions are based
  • Map out a wide variety of data dashboards and reports to view and continually test the data in an effort to “tell a story”
  • Integrate an extensible set of analytical and graphics tools to sift through large data sets from relevant Twitter streams²

Part 3: The Development Roadmap

The third and final IBM speaker outlined the following paths for Watson Analytics that are currently in beta stage development:

  • User engagement developers are working on an updated visual engine, increased connectivity and capabilities for mobile devices, and social media commentary.
  • Collaboration developers are working on accommodating work groups and administrators, and dashboards that can be filtered and distributed.
  • Data connector developers are working on new data linkages, improving the quality and shape of connections, and increasing the degrees of confidence in predictions. For example, a connection to weather data is underway that would be very helpful to the airline (among other industries), in the above hypothetical.
  • New analytics developers are working on new functionality for business forecasting, time series analyses, optimization, and social media analytics.

Everyone in the audience, judging by the numerous informal conversations that quickly formed in the follow-up networking session, left with much to consider about the potential applications of this technology.


1.  Please see these six Subway Fold posts covering predictive analytics in other markets.

2.  Please see these ten Subway Fold posts for a variety of other applications of Twitter analytics.