Taking Note of Music Tech’s VC and Accelerator Market Trends in 2017

As a part of today’s modern music industry there exists a complementary and thriving support system of venture capital firms and music tech startup accelerators who are providing a multitude of innovative services.  A fascinating examination of the current state of this ecosystem appeared in an article entitled Music Pushes to Innovate Beyond Streaming, But Investors Play It Safe: Analysis, by Cherie Hu, posted on Billboard.com on 7/24/17. I highly recommend reading it in its entirety for its insights, assessments and accompanying graphics.

I will summarize this feature here, add some links and annotations and, well, venture a few of my own questions. Also, I believe this is a logical follow to three previous Subway Fold posts about the music biz including:

Tempo

In mid-2017, the music tech market is generating signals as to its direction and viability. For example, Jawbone, the once thriving manufacturer of wearable audio devices is currently being liquidated; Soundcloud  the audio distribution platform let go of 40 percent of its staff recently only days before the firm’s tenth anniversary; and Pandora has experienced high turnover among its executives while seeking a sale.

Nonetheless, the leaders in music streaming are maintaining “the music industry’s growth”. Music tech showcases and music accelerators including SXSW Music Startup Spotlight, the Midemlab Accelerator, and Techstars Music are likewise driving market transformation.   During 2017 thus far, 54 music startups from more than 25 cities across the globe have taken part in these three entities. They have presented a range of submissions including “live music activations and automated messaging to analytics tools for labels and artists”.

While companies such as Live Nation, Balderton Capital and Evolution Media have previously invested in music startups, most investors at this mid-year point have never previously funded a company in this space. This is despite the fact that investments in this market sector have rarely returned the 30% that VCs generally seek. As well, a number of established music industry stars are participating as first-time or veteran investors this year.

Of the almost $900 million funding in music tech for the first half of this year, 75% was allocated for streaming services – – 82% of which went only to the leading four companies. However, there remains a “stark disconnect” involving the types of situations where music accelerators principally “lend their mentorship” in “hardware, virtual reality1, chatbots, label tools”, and the issues that VC concentrate the funding such as “streaming, social media, brands”.  Moreover, this situation has the potential of “stifling innovation” across the industry.

To date, music accelerators have “successfully given a platform and resources” to some sectors of the industry that VCs don’t often consider. For example, automated messaging and AI-generated music2 are both categories that music accelerators avoided until recently, now equal 15% of membership. This expansion into new categories reflects a much deeper “tech investment and hiring trends”. Leading music companies are now optimistic about virtual digital assistants (VDA) including chatbots and voice-activated systems such as Amazon Alexa3. As well, Spotify recently hired away a leading AI expert from Sony.

Rhythm

However, this “egalitarian focus” on significant problems has failed to “translate into the wider investing landscape” insofar as the streaming services have attracted 75% of music tech funding. The data further shows that licensing/rights/catalog management, social music media, and music, brands and advertising finished, in that order, in second at 11.1%, third at 7.1% and fourth at 3.9%.

These percentages closely match those for 2016. Currently, many VCs in this sector view streaming “as the safest model available”. It is also one upon which today’s music industry depends for its survival.

Turning to the number of rounds of music tech funding rather than the dollar amounts raised, by segments within the industry, a “slightly more egalitarian landscape” emerges:

  • Music hardware, AI-generated music, and VR and Immersive media each at 5.0%
  • Live music; music brands and advertising; streaming; and social music media each at 15.0%
  • Licensing, rights, and catalog management at 25% (for such companies as Kobalt Music, Stem and Dubset)

Categories that did relatively well in both their number of rounds of funding and accelerator membership were “catalog management, social music platforms, and live music”.

Those music tech startups that are more “futuristic” like hardware and VR are seen favorably by “accelerators and conference audiences”, but less so among VCs.  Likewise, while corporate giants including Live Nation, Universal Music Group, Citi and Microsoft have announced movement into music VR in the past six months, VC funding for this tech remained “relatively soft”.

Even more pronounced is the situation where musical artists and label services such as Instrumental (a influencer discovery platform) and chart monitors like Soundcharts have not raised any rounds of funding. This is so “despite unmatched attention from accelerators. This might be due to these services not being large enough to draw too “many traditional investors”.

An even more persistent problem here is that not many VCs “are run by people with experience in the music industry” and are familiar with its particular concerns. Once exception is Plus Eight Equity Partners, who are trying to address “this ideological and motivational gap”.

Then there are startups such as 8tracks and Chew who are “experimenting with crowdfunding” in this arena but who were not figured into this analysis.

In conclusion, the tension between a “gap in industry knowledge” and the VCs’ preference for “safety and convenience”, is blurring the line leading from accelerator to investment for many of these imaginative startups.

My Questions

  • Of those music startups who have successfully raised funding, what factors distinguished their winning pitches and presentations that others can learn from and apply?
  • Do VCs and accelerators really need the insights and advice of music industry professionals or are the numbers, projects and ROIs only what really matters in deciding whether or not to provide support?
  • Would the application of Moneyball principles be useful to VCs and accelerators in their decision-making processes?

 


1.  See the category Virtual and Augmented Reality for other Subway Fold posts on a range of applications of these technologies.

2.  For a report on a recent developments, see A New AI Can Write Music as Well as a Human Composer, by Bartu Kaleagasi, posted on Futurism.com on 3/9/17.

3.  Other examples of VDAs include Apple’s Siri, Google’s Assistant and Microsoft’s Cortana.

I Can See for Miles: Using Augmented Reality to Analyze Business Data Sets

matrix-1013612__340, Image from Pixabay

While one of The Who’s first hit singles, I Can See for Miles, was most certainly not about data visualization, it still might – – on a bit of a stretch – – find a fitting a new context in describing one of the latest dazzling new technologies in the opening stanza’s declaration “there’s magic in my eye”.  In determining Who’s who and what’s what about all this, let’s have a look at report on a new tool enabling data scientists to indeed “see for miles and miles” in an exciting new manner.

This innovative approach was recently the subject of a fascinating article by an augmented reality (AR) designer named Benjamin Resnick about his team’s work at IBM on a project called Immersive Insights, entitled Visualizing High Dimensional Data In Augmented Reality, posted on July 3, 2017 on Medium.com. (Also embedded is a very cool video of a demo of this system.) They are applying AR’s rapidly advancing technology1 to display, interpret and leverage insights gained from business data. I highly recommend reading this in its entirety. I will summarize and annotate it here and then pose a few real-world questions of my own.

Immersive Insights into Where the Data-Points Point

As Resnick foresees such a system in several years, a user will start his or her workday by donning their AR glasses and viewing a “sea of gently glowing, colored orbs”, each of which visually displays their business’s big data sets2. The user will be able to “reach out select that data” which, in turn, will generate additional details on a nearby monitor. Thus, the user can efficiently track their data in an “aesthetically pleasing” and practical display.

The project team’s key objective is to provide a means to visualize and sum up the key “relationships in the data”. In the short-term, the team is aiming Immersive Insights towards data scientists who are facile coders, enabling them to visualize, using AR’s capabilities upon time series, geographical and networked data. For their long-term goals, they are planning to expand the range of Immersive Insight’s applicability to the work of business analysts.

For example, Instacart, a same-day food delivery service, maintains an open source data set on food purchases (accessible here). Every consumer represents a data-point wherein they can be expressed as a “list of purchased products” from among 50,000 possible items.

How can this sizable pool of data be better understood and the deeper relationships within it be extracted and understood? Traditionally, data scientists create a “matrix of 2D scatter plots” in their efforts to intuit connections in the information’s attributes. However, for those sets with many attributes, this methodology does not scale well.

Consequently, Resnick’s team has been using their own new approach to:

  • Lower complex data to just three dimensions in order to sum up key relationships
  • Visualize the data by applying their Immersive Insights application, and
  • Iteratively label and color-code the data” in conjunction with an “evolving understanding” of its inner workings

Their results have enable them to “validate hypotheses more quickly” and establish a sense about the relationships within the data sets. As well, their system was built to permit users to employ a number of versatile data analysis programming languages.

The types of data sets being used here are likewise deployed in training machine learning systems3. As a result, the potential exists for these three technologies to become complementary and mutually supportive in identifying and understanding relationships within the data as well as deriving any “black box predictive models”.

Analyzing the Instacart Data Set: Food for Thought

Passing over the more technical details provided on the creation of team’s demo in the video (linked above), and next turning to the results of the visualizations, their findings included:

  • A great deal of the variance in Instacart’s customers’ “purchasing patterns” was between those who bought “premium items” and those who chose less expensive “versions of similar items”. In turn, this difference has “meaningful implications” in the company’s “marketing, promotion and recommendation strategies”.
  • Among all food categories, produce was clearly the leader. Nearly all customers buy it.
  • When the users were categorized by the “most common department” they patronized, they were “not linearly separable”. This is, in terms of purchasing patterns, this “categorization” missed most of the variance in the system’s three main components (described above).

Resnick concludes that the three cornerstone technologies of Immersive Insights – – big data, augmented reality and machine learning – – are individually and in complementary combinations “disruptive” and, as such, will affect the “future of business and society”.

Questions

  • Can this system be used on a real-time basis? Can it be configured to handle changing data sets in volatile business markets where there are significant changes within short time periods that may affect time-sensitive decisions?
  • Would web metrics be a worthwhile application, perhaps as an add-on module to a service such as Google Analytics?
  • Is Immersive Insights limited only to business data or can it be adapted to less commercial or non-profit ventures to gain insights into processes that might affect high-level decision-making?
  • Is this system extensible enough so that it will likely end up finding unintended and productive uses that its designers and engineers never could have anticipated? For example, might it be helpful to juries in cases involving technically or financially complex matters such as intellectual property or antitrust?

 


1.  See the Subway Fold category Virtual and Augmented Reality for other posts on emerging AR and VR applications.

2.  See the Subway Fold category of Big Data and Analytics for other posts covering a range of applications in this field.

3.  See the Subway Fold category of Smart Systems for other posts on developments in artificial intelligence, machine learning and expert systems.

4.  For a highly informative and insightful examination of this phenomenon where data scientists on occasion are not exactly sure about how AI and machine learning systems produce their results, I suggest a click-through and reading of The Dark Secret at the Heart of AI,  by Will Knight, which was published in the May/June 2017 issue of MIT Technology Review.

Hacking Matter Really Matters: A New Programmable Material Has Been Developed

Image from Pixabay

Image from Pixabay

The sales receipt from The Strand Bookstore in New York is dated April 5, 2003. It still remains tucked into one of the most brain-bendingly different books I have ever bought and read called Hacking Matter: Levitating Chairs, Quantum Mirages, and the Infinite Weirdness of Programmable Atoms (Basic Books, 2003), by Wil McCarthy. It was a fascinating deep dive into what was then the nascent nanotechnology research on creating a form of “programmable atoms” called quantum dots. This technology has since found applications in the production of semiconductors.

Fast forward thirteen years to a recent article entitled Exoskin: A Programmable Hybrid Shape-Changing Material, by Evan Ackerman, posted on IEEE Spectrum on June 3, 2016. This is about an all-new and entirely different development, quite separate from quantum dots, but nonetheless a current variation on the concept that matter can be programmed for new applications. While we always think of programming as involving systems and software, this new story takes and literally stretches this long-established process into some entirely new directions.

I highly recommend reading this most interesting report in its entirety and viewing the two short video demos embedded within it. I will summarize and annotate it, and then pose several questions of my own on this, well, matter. I also think it fits in well with these 10 Subway Fold posts on other recent developments in material science including, among others, such way cool stuff as Q-Carbon, self-healing concrete and metamaterials.

Matter of Fact

The science of programmable matter is still in its formative stages. The Tangible Media Group at MIT Media Lab is currently working on this challenge included in its scores of imaginative projects. A student pursuing his Master’s Degree in this group is Basheer Tome. Among his current research projects, he is working on a type of programmable material he calls “Exoskin” which he describes as “membrane-backed rigid material”. It is composed of “tessellated triangles of firm silicone mounted on top of a stack of flexible silicone bladders”. By inflating these bladders in specific ways, Exoskin can change its shape in reaction to the user’s touch. This activity can, in turn, be used to relay information and “change functionality”.

Although this might sound a bit abstract, the two accompanying videos make the Exoskin’s operations quite clear. For example, it can be applied to a steering wheel which, through “tactile feedback”, can inform the driver about direction-finding using GPS navigation and other relevant driving data. This is intended to lower driver distractions and “simplify previously complex multitasking” behind the wheel.

The Exoskin, in part, by its very nature makes use of haptics (using touch as a form of interface). One of the advantages of this approach is that it enables “fast reflexive motor responses to stimuli”. Moreover, the Exoskin actually involves inputs that “are both highly tactily perceptible and visually interpretable”.

Fabrication Issues

A gap still exists between the current prototype and a commercially viable product in the future in terms of the user’s degree of “granular control” over the Exoskin. The number of “bladders” underneath the rigid top materials will play a key role in this. Under existing fabrication methods, multiple bladders in certain configurations are “not practical” at this time.

However, this restriction might be changing. Soon it may be possible to produce bladders for each “individual Exoskin element” rather than a single bladder for all of them. (Again, the videos present this.) This would involve a system of “reversible electrolysis” that alternatively separates water into hydrogen and oxygen and then back again into water. Other options to solve this fabrication issue are also under consideration.

Mt. Tome hopes this line of research disrupts the distinction between what is “rigid and soft” as well as “animate and inanimate” to inspire Human-Computer Interaction researchers at MIT to create “more interfaces using physical materials”.

My Questions

  • In what other fields might this technology find viable applications? What about medicine, architecture, education and online gaming just to begin?
  • Might Exoskin present new opportunities to enhance users’ experience with the current and future releases virtual reality and augmented reality systems? (These 15 Subway Fold posts cover a sampling of trends and developments in VR and AR.)
  • How might such an Exoskin-embedded steering wheel possibly improve drivers’ and riders’ experiences with Uber and other ride-sharing services?
  • What entrepreneurial opportunities in design, engineering, programming and manufacturing might present themselves if Exoskin becomes commercialized?

Pushing the Envelopes: New US Postal Service Report Assesses Possible Blockchain Applications

"Vibrant US Air Mail Stamp", Image by Nicolas Raymond

“Vibrant US Air Mail Stamp”, Image by Nicolas Raymond

Way before the advent of email, when people exclusively wrote letters on paper and mailed them to each other (yes, this really did happen once upon a time), there was a long-running scam known as the “chain letter“. Recipients who received such a letter were asked, often through manipulative language, to copy it and send it on to as many other people as possible. In effect, these were structured as fraudulent pyramid schemes that ultimately would collapse in on themselves.

Sometimes chain letters involved illegal financial dealings and other hoaxes, also producing unwanted emotional effects on who mistakenly fell for them. Variations of the chain letter still survive today online and operate using email, texting and social media.

However, an emerging new form of virtual chain, in conjunction with the mail service, might soon appear – – namely using the blockchain – – within the U.S. Postal Service (USPS). However, this combination could potentially produce four very positive improvements in services. These exciting prospects were the subject of a most interesting new post on Quartz.com on May 24, 2016 entitled Even the US Postal Service Wants to Start Using Blockchain Tech, by Ian Kar. I recommend reading this article in its entirety. I will summarize and annotate it, and pose some questions of my own (but without any additional postage due).

While blockchain technology has been getting a great deal of press coverage recently involving innovative new development initiatives in, among other fields, finance, law, government and the arts, this story illustrates how it also might affect something as routine and mundane as mail service with possibly dramatic results. Such changes could produce significant economic and logistical advances that would affect just about anyone who checks their real world mailbox every day.

(These six Subway Fold posts cover just a small sampling of blochchain projects.)

Better Letters

Image from Pixabay

Image from Pixabay

Traditionally, the USPS has never really distinguished itself as a leader in innovation. Rather, it has a long reputation for its inefficient operations. This could possibly be significantly changed by this series of a series of blockchain proposals. Because this technology is decentralized, widely accessible, and secured by encryption, it is highly resistant to tampering.

On May 23, 2016, the USPS Office of the Inspector General and a consulting firm called Swiss Economics, published a new report entitled Blockchain Technology: Possibilities for the U.S. Postal Service. It analyzed the following four possible future implementations:

1.  Financial Services:  US post offices currently offers a limited number of financial services such as international money transfers. The IOG report speculated that the USPS “could benefit from developing its own bitcoin-like digital currency”.  Perhaps it could be called “Postcoin”. This would permit the expansion into other financial services such as a “global payment service” for people without traditional bank accounts.

2.  Identity:  An individual’s identity could be verified for the USPS using a blockchain. Essentially, they already do this when they deliver your mail to you each day. By using a blockchain for this, the USPS could provide you with assistance to help you manage both your online and offline identities “by storing it on an immutable ledger”.

3.  Logistics Support:  Applying the blochchain to support the Internet of Things (IoT) could enhance the USPS logistics management operations. The IGO report imagine a system where “vehicles and sorting equipment could manage their own tracking, monitoring, and maintenance”. This could include items such as autonomously, efficiently and economically monitoring brake pad performance including:

  • Assessing when one will need to be replaced
  • Determining whether its warranty is still in effect
  • Creating a smart contract with a vendor to replace it
  • Paying for the part and its installation

4.  Mail Tracking:  On a daily basis, the USPS delivers 509 million pieces of mail. As stated in the OIG report, the blockchain can be deployed to uniquely identify each piece of it. This could be done with “a small sensor” on each piece in order to use the blockchain to “manage the chain of custody between different USPS partners, like UPS and Fedex”. As well, the blockchain could be put to the additional uses of:

  • Expediting customs clearance
  • Integrating payments
  • Shipping upon one unified platform

[All of these components form the very convenient anagram FILM, thus making it easier to, well, picture.]

For now, the USPS intends to keep studying blockchain technology. The OIG report states that the agency “could benefit from experimenting” with it on new financial products and then eventually progress on toward “more complex uses”.

"Stamped Mail to be Posted", Image by Steven Depolo

“Stamped Mail to be Posted”, Image by Steven Depolo

My Questions

  • Would these blochchain apps have a negative impact on USPS revenues as this massive government agency has been running at a budget deficit for many years? If so, would this have unintended negative consequences for consumers and/or the USPS?
  • Conversely, can the USPS use blockchain innovations to create new sources of revenue and employment? What new sorts of job descriptions and titles might emerge?
  • Would the blockchain do away with the traditional services of certified, registered, priority and insured mail? If so, what forms of proof of delivery or non-delivery could be provided to consumers?
  • Would any of these proposed new apps possibly create new privacy issues for consumers and policy concerns for the US government?
  • What type of opportunities might arise for entrepreneurs to create new mail apps built on the blockchain?

Ethical Issues and Considerations Arising in Big Data Research

Image from Pixabay

Image from Pixabay

In 48 of 50 states in the US, new attorneys are required to pass a 60 multiple-choice question exam on legal ethics in addition to passing their state’s bar exam. This is known as the Multistate Professional Responsibility Examination (MPRE). I well recall taking this test myself.

The subject matter of this test is the professional ethical roles and responsibilities a lawyer must abide by as an advocate and counselor to clients, courts and the legal profession. It is founded upon a series of ethical considerations and disciplinary rules that are strictly enforced by the bars of each state. Violations can potentially lead to a series of professional sanctions and, in severe cases depending upon the facts, disbarment from practice for a term of years or even permanently.

In other professions including, among others, medicine and accounting, similar codes of ethics exist and are expected to be scrupulously followed. They are defined efforts to ensure honesty, quality, transparency and integrity in their industries’ dealings with the public, and to address certain defined breaches. Many professional trade organizations also have formal codes of ethics but often do not have much, if any, sanction authority.

Should some comparable forms of guidelines and boards likewise be put into place to oversee the work of big data researchers? This was the subject of a very compelling article posted on Wired.com on May 20, 2016, entitled Scientists Are Just as Confused About the Ethics of Big-Data Research as You by Sharon Zhang. I highly recommend reading it in its entirety. I will summarize, annotate and add some further context to this, as well as pose a few questions of my own.

Two Recent Data Research Incidents

Last month. an independent researcher released, without permission, the profiles with very personal information of 70,000 users of the online dating site OKCupid. These users were quite angered by this. OKCupid is pursuing a legal claim to remove this data.

Earlier in 2014, researchers at Facebook manipulated items in users’ News Feeds for a study on “mood contagion“.¹ Many users were likewise upset when they found out. The journal that published this study released an “expression of concern”.

Users’ reactions over such incidents can have an effect upon subsequent “ethical boundaries”.

Nonetheless, the researchers involved in both of these cases had “never anticipated” the significant negative responses to their work. The OKCupid study was not scrutinized by any “ethical review process”, while a review board at Cornell had concluded that the Facebook study did not require a full review because the Cornell researchers only had a limited role in it.

Both of these incidents illustrate how “untested the ethics” are of these big data research. Only now are the review boards that oversee the work of these researchers starting to pay attention to emerging ethical concerns. This is in high contrast to the controls and guidelines upon medical research in clinical trials.

The Applicability of The Common Rule and Institutional Research Boards

In the US, under the The Common Rule, which governs ethics for federally funded biomedical and behavioral research where humans are involved, studies are required to undergo an ethical review.  However, such review does not apply a “unified system”, but rather, each university maintains its own institutional review board (IRB). These are composed of other (mostly medical) researchers at each university. Only a few of them “are professional ethicists“.

To a lesser extent, do they have experience in computer technology. This deficit may be affecting the protection of subjects who participate in data science research projects. In the US, there are hundreds of IRBs but they are each dealing with “research efforts in the digital age” in their own ways.

Both the Common Rule and the IRB system came into being following the revelation in the 1970s that the U.S. Public Health Service had, between 1932 and 1972, engaged in a terrible and shameful secret program that came to be known as the Tuskegee Syphilis Experiment. This involved leaving African Americans living in rural Alabama with untreated syphilis in order to study the disease. As a result of this outrage, the US Department of Health and Human Services created new regulations concerning any research on human subjects they conducted. All other federal agencies likewise adopted such regulations. Currently, “any institution that gets federal funding has to set up an IRB to oversee research involving humans”.

However, many social scientists today believe these regulations are not accurate or appropriate for their types of research involving areas where the risks involved “are usually more subtle than life or death”. For example, if you are seeking volunteers to take a survey on test-taking behaviors, the IRB language requirements on physical risks does not fit the needs of the participants in such a study.

Social scientist organizations have expressed their concern about this situation. As a result, the American Association of University Professors (AAUP) has recommended:

  • Adding more social scientists to IRBs, or
  • Creating new and separate review boards to assess social science research

In 2013, AAUP issued a report entitled Regulation of Research on Human Subjects: Academic Freedom and the Institutional Review Board, recommending that the researchers themselves should decide if “their minimal risk work needs IRB approval or not”. In turn, this would make more time available to IRBs for “biomedical research with life-or-death stakes”.

This does not, however, imply that all social science research, including big data studies, are entirely risk-free.

Ethical Issues and Risk Analyses When Data Sources Are Comingled

Dr. Elizabeth A. Buchanan who works as an ethicist at the University of Wisconsin-Stout, believes that the Internet is now entering its “third phase” where researchers can, for example, purchase several years’ worth of Twitter data and then integrate it “with other publicly available data”.² This mixture results in issues involving “ethics and privacy”.

Recently, while serving on an IRB, she took part in evaluated a project proposal involving merging mentions of a drug by its street name appearing on social media with public crime data. As a result, people involved in crimes could potentially become identified. The IRB still gave its approval. According to Dr. Buchanan, the social value of this undertaking must be weighed against its risk. As well, the risk should be minimized by removing any possible “idenifiers” in any public release of this information.

As technology continues to advance, such risk evaluation can become more challenging. For instance, in 2013, MIT researchers found out that they were able to match up “publicly available DNA sequences” by using data about the participants that the “original researchers” had uploaded online.³ Consequently, in such cases, Dr. Buchanan believes it is crucial for IRBs “to have either a data scientist, computer scientist or IT security individual” involved.

Likewise, other types of research organizations such as, among others, open science repositories, could perhaps “pick up the slack” and handle more of these ethical questions. According to Michelle Meyer, a bioethicist at Mount Sinai, oversight must be assumed by someone but the best means is not likely to be an IRB because they do not have the necessary “expertise in de-identification and re-identification techniques”.

Different Perspectives on Big Data Research

A technology researcher at the University of Maryland 4 named Dr. Katie Shilton recently conducted interviews of “20 online data researchers”. She discovered “significant disagreement” among them on matters such as the “ethics of ignoring Terms of Service and obtaining informed consent“. The group also reported that the ethical review boards they dealt with never questioned the ethics of the researchers, while peer reviewers and their professional colleagues had done so.

Professional groups such as the Association of Internet Researchers (AOIR) and the Center for Applied Internet Data Analysis (CAIDA) have created and posted their own guidelines:

However, IRBs who “actually have power” are only now “catching up”.

Beyond universities, tech companies such as Microsoft have begun to establish in-house “ethical review processes”. As well, in December 2015, the Future of Privacy Forum held a gathering called Beyond IRBs to evaluate “processes for ethical review outside of federally funded research”.

In conclusion., companies continually “experiment on us” with data studies. Just to name to name two, among numerous others, they focus on A/B testing 5 of news headings and supermarket checkout lines. As they hire increasing numbers of data scientists from universities’ Ph.D. programs, these schools are sensing an opportunity to close the gap in terms of using “data to contribute to public knowledge”.

My Questions

  • Would the companies, universities and professional organizations who issue and administer ethical guidelines for big data studies be taken more seriously if they had the power to assess and issue public notices for violations? How could this be made binding and what sort of appeals processes might be necessary?
  • At what point should the legal system become involved? When do these matters begin to involve civil and/or criminal investigations and allegations? How would big data research experts be certified for hearings and trials?
  • Should teaching ethics become a mandatory part of curriculum in data science programs at universities? If so, should the instructors only be selected from the technology industry or would it be helpful to invite them from other industries?
  • How should researchers and their employers ideally handle unintended security and privacy breaches as a result of their work? Should they make timely disclosures and treat all inquiries with a high level of transparency?
  • Should researchers experiment with open source methods online to conduct certain IRB functions for more immediate feedback?

 


1.  For a detailed report on this story, see Facebook Tinkers With Users’ Emotions in News Feed Experiment, Stirring Outcry, by Vindu Goel, in the June 29, 2014 edition of The New York Times.

2These ten Subway Fold posts cover a variety of applications in analyzing Twitter usage data.

3.  For coverage on this story see an article published in The New York Times on January 17, 2013, entitled Web Hunt for DNA Sequences Leaves Privacy Compromised, by Gina Kolata.

4.  For another highly interesting but unrelated research initiative at the University of Maryland, see the December 27, 2015 Subway Fold post entitled Virtual Reality Universe-ity: The Immersive “Augmentarium” Lab at the U. of Maryland.

5.  For a detailed report on this methodology, see the September 30, 2015 Subway Fold post entitled Google’s A/B Testing Method is Being Applied to Improve Government Operations.

Mary Meeker’s 2016 Internet Trends Presentation

"Blue Marble - 2002", Image by NASA Goddard Space Flight Center

“Blue Marble – 2002”, Image by NASA Goddard Space Flight Center

On June 1, 2016, at the 2016 Code Conference held this week in California, Mary Meeker, a world-renowned Internet expert and partner in the venture capital firm Kleiner Perkins, presented her fifteenth annual in-depth and highly analytical presentation on current Internet trends. It is an absolutely remarkable accomplishment that is highly respected throughout the global technology industry and economy. The video of her speech is available here on Recode.com

Her 2016 Internet Trends presentation file is divided into a series of eight main sections covering, among many other things: Internet user and financial growth rates, online advertising, generational market segments and technological preferences, new products and vendors, mobile screens for nearly everything, e-commerce, big data, privacy issues, video growth on social media platforms, messaging systems , smartphone growth,  voice interfaces, consumer spending, online security, connectivity, Facebook’s v. Google’s growth rates, and massive consumer markets in China and India. That is just the tip of the tip of the iceberg in this 213-slide file.

Ms. Meeker’s assessments and predictions here form an extraordinarily comprehensive and insightful piece of work. There is much here for anyone and everyone to learn and consider in the current and trending states nearly anything and everything online. Moreover, there are likely many potential opportunities for new and established businesses, as well as other institutions, within this file.

I very highly recommend that you set aside some time to thoroughly read through Ms. Meeker’s full presentation. You will be richly rewarded with knowledge and insight that can potentially yield a world of informative and practical dividends.

Digital Smarts Everywhere: The Emergence of Ambient Intelligence

Image from Pixabay

Image from Pixabay

The Troggs were a legendary rock and roll band who were part of the British Invasion in the late 1960’s. They have always been best known for their iconic rocker Wild Thing. This was also the only Top 10 hit that ever had an ocarina solo. How cool is that! The band went on to have two other major hits, With a Girl Like You and Love is All Around.¹

The third of the band’s classic singles can be stretched a bit to be used as a helpful metaphor to describe an emerging form pervasive “all around”-edness, this time in a more technological context. Upon reading a fascinating recent article on TechCrunch.com entitled The Next Stop on the Road to Revolution is Ambient Intelligence, by Gary Grossman, on May 7, 2016, you will find a compelling (but not too rocking) analysis about how the rapidly expanding universe of digital intelligent systems wired into our daily routines is becoming more ubiquitous, unavoidable and ambient each day.

All around indeed. Just as romance can dramatically affect our actions and perspectives, studies now likewise indicate that the relentless global spread of smarter – – and soon thereafter still smarter – – technologies is comparably affecting people’s lives at many different levels.² 

We have followed just a sampling of developments and trends in the related technologies of artificial intelligence, machine learning, expert systems and swarm intelligence in these 15 Subway Fold posts. I believe this new article, adding “ambient intelligence” to the mix, provides a timely opportunity to bring these related domains closer together in terms of their common goals, implementations and benefits. I highly recommend reading Mr. Grossman’s piece it in its entirety.

I will summarize and annotate it, add some additional context, and then pose some of my own Trogg-inspired questions.

Internet of Experiences

Digital this, that and everything is everywhere in today’s world. There is a surging confluence of connected personal and business devices, the Internet, and the Internet of Things (I0T) ³. Woven closely together on a global scale, we have essentially built “a digital intelligence network that transcends all that has gone before”. In some cases, this quantum of advanced technologies gains the “ability to sense, predict and respond to our needs”, and is becoming part of everyone’s “natural behaviors”.

A forth industrial revolution might even manifest itself in the form of machine intelligence whereby we will interact with the “always-on, interconnected world of things”. As a result, the Internet may become characterized more by experiences where users will converse with ambient intelligent systems everywhere. The supporting planks of this new paradigm include:

A prediction of what more fully realized ambient intelligence might look like using travel as an example appeared in an article entitled Gearing Up for Ambient Intelligence, by Lisa Morgan, on InformationWeek.com on March 14, 2016. Upon leaving his or her plane, the traveler will receive a welcoming message and a request to proceed to the curb to retrieve their luggage. Upon reaching curbside, a self-driving car6 will be waiting with information about the hotel booked for the stay.

Listening

Another article about ambient intelligence entitled Towards a World of Ambient Computing, by Simon Bisson, posted on ZDNet.com on February 14, 2014, is briefly quoted for the line “We will talk, and the world will answer”, to illustrate the point that current technology will be morphing into something in the future that would be nearly unrecognizable today. Grossman’s article proceeds to survey a series of commercial technologies recently brought to market as components of a fuller ambient intelligence that will “understand what we are asking” and provide responsive information.

Starting with Amazon’s Echo, this new device can, among other things:

  • Answer certain types of questions
  • Track shopping lists
  • Place orders on Amazon.com
  • Schedule a ride with Uber
  • Operate a thermostat
  • Provide transit schedules
  • Commence short workouts
  • Review recipes
  • Perform math
  • Request a plumber
  • Provide medical advice

Will it be long before we begin to see similar smart devices everywhere in homes and businesses?

Kevin Kelly, the founding Executive Editor of WIRED and a renowned futurist7, believes that in the near future, digital intelligence will become available in the form of a utility8 and, as he puts it “IQ as a service”. This is already being done by Google, Amazon, IBM and Microsoft who are providing open access to sections of their AI coding.9 He believes that success for the next round of startups will go to those who enhance and transforms something already in existence with the addition of AI. The best example of this is once again self-driving cars.

As well, in a chapter on Ambient Computing from a report by Deloitte UK entitled Tech Trends 2015, it was noted that some products were engineering ambient intelligence into their products as a means to remain competitive.

Recommending

A great deal of AI is founded upon the collection of big data from online searching, the use of apps and the IoT. This universe of information supports neural networks learn from repeated behaviors including people’s responses and interests. In turn, it provides a basis for “deep learning-derived personalized information and services” that can, in turn, derive “increasingly educated guesses with any given content”.

An alternative perspective, that “AI is simply the outsourcing of cognition by machines”, has been expressed by Jason Silva, a technologist, philosopher and video blogger on Shots of Awe. He believes that this process is the “most powerful force in the universe”, that is, of intelligence. Nonetheless, he sees this as an evolutionary process which should not be feared. (See also the December 27, 2014 Subway Fold post entitled  Three New Perspectives on Whether Artificial Intelligence Threatens or Benefits the World.)

Bots are another contemporary manifestation of ambient intelligence. These are a form of software agent, driven by algorithms, that can independently perform a range of sophisticated tasks. Two examples include:

Speaking

Optimally, bots should also be able to listen and “speak” back in return much like a 2-way phone conversation. This would also add much-needed context, more natural interactions and “help to refine understanding” to these human/machine exchanges. Such conversations would “become an intelligent and ambient part” of daily life.

An example of this development path is evident in Google Now. This service combines voice search with predictive analytics to present users with information prior to searching. It is an attempt to create an “omniscient assistant” that can reply to any request for information “including those you haven’t thought of yet”.

Recently, the company created a Bluetooth-enable prototype of lapel pin based on this technology that operates just by tapping it much like the communicators on Star Trek. (For more details, see Google Made a Secret Prototype That Works Like the Star Trek Communicator, by Victor Luckerson, on Time.com, posted on November 22, 2015.)

The configurations and specs of AI-powered devices, be it lapel pins, some form of augmented reality10 headsets or something else altogether, supporting such pervasive and ambient intelligence are not exactly clear yet. Their development and introduction will take time but remain inevitable.

Will ambient intelligence make our lives any better? It remains to be seen, but it is probably a viable means to handle some of more our ordinary daily tasks. It will likely “fade into the fabric of daily life” and be readily accessible everywhere.

Quite possibly then, the world will truly become a better place to live upon the arrival of ambient intelligence-enabled ocarina solos.

My Questions

  • Does the emergence of ambient intelligence, in fact, signal the arrival of a genuine fourth industrial revolution or is this all just a semantic tool to characterize a broader spectrum of smarter technologies?
  • How might this trend affect overall employment in terms of increasing or decreasing jobs on an industry by industry basis and/or the entire workforce? (See also this June 4, 2015 Subway Fold post entitled How Robots and Computer Algorithms Are Challenging Jobs and the Economy.)
  • How might this trend also effect non-commercial spheres such as public interest causes and political movements?
  • As ambient intelligence insinuates itself deeper into our online worlds, will this become a principal driver of new entrepreneurial opportunities for startups? Will ambient intelligence itself provide new tools for startups to launch and thrive?

 


1.   Thanks to Little Steven (@StevieVanZandt) for keeping the band’s music in occasional rotation on The Underground Garage  (#UndergroundGarage.) Also, for an appreciation of this radio show see this August 14, 2014 Subway Fold post entitled The Spirit of Rock and Roll Lives on Little Steven’s Underground Garage.

2.  For a remarkably comprehensive report on the pervasiveness of this phenomenon, see the Pew Research Center report entitled U.S. Smartphone Use in 2015, by Aaron Smith, posted on April 1, 2015.

3These 10 Subway Fold posts touch upon the IoT.

4.  The Subway Fold category Big Data and Analytics contains 50 posts cover this topic in whole or in part.

5.  The Subway Fold category Telecommunications contains 12 posts cover this topic in whole or in part.

6These 5 Subway Fold posts contain references to self-driving cars.

7.   Mr. Kelly is also the author of a forthcoming book entitled The Inevitable: Understanding the 12 Technological Forces That Will Shape Our Future, to be published on June 7, 2016 by Viking.

8.  This September 1, 2014 Subway Fold post entitled Possible Futures for Artificial Intelligence in Law Practice, in part summarized an article by Steven Levy in the September 2014 issue of WIRED entitled Siri’s Inventors Are Building a Radical New AI That Does Anything You Ask. This covered a startup called Viv Labs whose objective was to transform AI into a form of utility. Fast forward to the Disrupt NY 2016 conference going on in New York last week. On May 9, 2016, the founder of Viv, Dag Kittlaus, gave his presentation about the Viv platform. This was reported in an article posted on TechCrunch.com entitled Siri-creator Shows Off First Public Demo of Viv, ‘the Intelligent Interface for Everything’, by Romain Dillet, on May 9, 2016. The video of this 28-minute presentation is embedded in this story.

9.  For the full details on this story see a recent article entitled The Race Is On to Control Artificial Intelligence, and Tech’s Future by John Markoff and Steve Lohr, published in the March 25, 2016 edition of The New York Times.

10These 10 Subway Fold posts cover some recent trends and development in augmented reality.