Partnership on AI

Partnership on AI
Uses Responsive Web Design (RWD) so it only “works” on a handset form factor is “mobile first” [scrape-scroll down, which is non-obvious in the officework environment]

Statement of Purpose

<quote>Established to study and formulate best practices on AI technologies, to advance the public’s understanding of AI, and to serve as an open platform for discussion and engagement about AI and its influences on people and society.</quote>

Promoters

Tier 1
  • Amazon
  • Apple
  • DeepMind, of Google
  • Google, of Alphabet (GOOG)
  • Facebook
  • IBM
  • Microsoft
Tier 2
Enumerated
Generalizing, they comprise NGOs, Centers, Centres and industry booster clubs.

Theory

As, tenets, creed, doctrine, belief, theses; enumerated as eight fourteen (Item Six has seven sub-parts)…

Classes
  • Goals to be attained. the <bizpeak>BHAG</bizspeak>.
    as indicated by a directional sense. of the effort-to-be-expended. (EtbE).
  • Values to be held, preferring privileging one value over another.
    as measured in effort-to-be-expended (EtbE).
  • Belief to be held.
Cases
  1. [Goal] The greatest good for the greatest number.
    [EtbE] ensure an outcome, like a guarantee.
  2. [Goal] Educate the seekers of the knowledge..
    [EtbE] a state of being; being bound over to, tasked unto, being committed to.
  3. [Goal] Outreach as dialog and participation.
    [EtbE] a state of being; being bound over to, tasked unto, being committed to.
  4. [Belief] Something about a broad range of stakeholders.
    [EtbE] a state of being, that such belief is so held.
  5. [Goal] Something about representation in the business community.
    [EtbE] something about “engage with” and a participation metric.
  6. [Concern] Privacy of individuals
    [EtbE] work towards.
  7. [Concern] Security of individuals
    [EtbE] work towards.
  8. [Concern] understanding and respect; a.k.a. “to serve and protect”
    [EtbE] strive.
  9. [Goal] Responsibility to [the data controllers].
    [EtbE] work towards.
  10. [Goal] Control these dangerous and powerful [and important and really really cool] technologies.
    [EtbE]: ensure an outcome, similar to a guarantee.
  11. [Goal] Violate no international laws (“conventions”); violate no human rights.
    [EtbE] oppose, wherein such an opinion is so held.
  12. [Goal[ Do no harm.
    [EtbE] promote, wherein such an opinion is so held.
  13. [Goal] Provenance tracing for system supervision.
    [EtbE] a state of being, that the belief is so held.
    <ahem>This is a system architecture requirement; it does not require a belief system or an attestation to any specific belief.</ahem>
  14. [Goal] Cooperation within the Professions so enumerated as: Scientist, Engineer.
    [EtbE]: Strive.

Concerns

Dimensions of concern are metaphorically themed as pillars, evoking an image of a Greek temple, whence knowledge came

  1. Safety
  2. Supervision
    enumerated as Fairness, Transparency, Accountability
  3. HCI (Human-Computer Interface))
  4. Labor (the anti-Luddism)
  5. Society (LE, Policy, Regulation, etc.)
  6. Charity
  7. Other

Mentions

  • Blog cadence as press releases is “about every four months.”
  • They don’t seem to have a position paper [yet].

Previously filled.

 

Wall Street Firms to Move Trillions to Blockchains in 2018 | IEEE Spectrum

Wall Street Firms to Move Trillions to Blockchains in 2018; Amy Nordrum; In IEEE Spectrum; 2017-09-29.
Teaser: The finance industry is eagerly adopting the blockchain, a technology that early fans hoped would obliterate the finance industry

tl;dr → Depository Trust and Clearing Corporation (DTCC) will trial something with a blockchain in the title.

Mentions

Institutions

The Old Money Managers

Startups

The New Money Managers

Promoters

Boosting

  • Consensus 2017, the booster conference
  • Hype Cycle, Gartner Group.
    The metaphor of the Trough of Disillusionment of underdamped an control system, comprehending the social process of the diffusion of innovation.

Organizations

The Boosterists

The Products

Open

  • The canon is recited
  • Depository Trust and Clearing Corporation (DTCC)
  • permissioned blockchain
  • Hyperledger
  • J.P. Morgan
  • Axoni
  • Axcore
  • Consensus, a conference
  • Bloomberg
  • Thompson Reuters
  • Chain
  • IBM
  • Microsoft
  • Goldman Sachs
  • DApps
  • Go, a programming language
  • Hyperledger Fabric
  • Ethereum
  • public chain
  • Citibank
  • Proof of Concept (PoC)
    Proof of Work (PoW)
    Proof of Stake (PoS)
  • Enterprise Ethereum Alliance
  • World Economic Forum, (WEF)
  • Guernsey
  • Unigestion
  • Goldman Sachs
  • Northern Trust
  • R3
  • Corda

Pantheon

“Satoshi Nakamoto,” The Prophet.
An archetype figure: a Santa Claus or Moses or even a Jesus-type figure. “He” came, gave us a gift (and behold! it was perfect in every way!); upon the Redemption, he was Assumed and thus disappeared. No one is sure who “he” was or if “he” really existed. Whether “he” existed at all is not important to those of The Faith. “He” has no childhood friends or contemporaries who knew “him.” All we have are “his” writings, enshrined in the Wayback Machine and conspiracy theory discussion forums. Maybe “he” really was from The Future; maybe “he” really was sent by our descendants to prevent a Greater Evil, as was foretold in multi-part Hollywood hit movie, The Terminator. Maybe The Blockchain is itself “The Skynet” as was prophesied. No one knows. But, HURRY, INVEST NOW!

Quoted

For color, background & verisimilitude…

Referenced

Previously

In IEEE Spectrum

Previously filled.

Payment Request API | W3C

Payment Request API; W3C; 2017-09-21.

  • Adrian Bateman, Microsoft Corporation
  • Zach Koch, Google
  • Roy McElmurry, Facebook
  • Domenic Denicola, Google
  • Marcos Cáceres, Mozilla

Promotions

As IBM Ramps Up Its AI-Powered Advertising, Can Watson Crack the Code of Digital Marketing? | Ad Week

As IBM Ramps Up Its AI-Powered Advertising, Can Watson Crack the Code of Digital Marketing?; ; In Ad Week (Advertising Week); 2017-09-24.
Teaser: Acquisition of The Weather Company fuels a new division

tl;dr → Watson (a service bureau, AI-as-a-Service) is open for business.

Mentions

The Weather Company

  • lines of business
    • location-based targeted audiences, delivered to the trade.
    • weather indica, delivered to consumers.
  • 2.2 billion locations/15 minutes
  • Dates
    • WHEN?, Acquisition by IBM
    • 2016-01, new business strategy,
      “AI” as a service (AIaaS)
  • Artificial Intelligence (AI)
  • Cloud Computing
  • Products
    • WeatherFx
    • JourneyFx
  • The Weather Company is a <quote>legacy business<quote> (deprecated).
  • AIaaS is a <quote>cutting-edge advertising powerhouse</quote> (house of power).

Watson Advertising

  • Cognitive Advertising
    • contra Computational Advertising, circa the ‘oughties (2005)
    • something about
      • <buzzzz>transform every aspect of marketing from </buzzz>
      • something about image and voice recognition to big data analysis and custom content.
  • What is it? (What is Watson-as-a-Service?)
    • Count: <quote>dozens</quote>
    • Interfaces
      • API
      • Projects <quote>studio-like</quote>
    • Pricing: <quote>millions of dollars</quote>
    • Structure: four (4) sub-units
  • “<snip/>It’s not been designed to target consumers the same way that Alexa or Siri have been,” attributed to Cameron Clayton.

Units

The 4 pillars of Watson Advertising.
  1. Targeting, Audience construction & activation
  2. Optimization, Bidding & buying
  3. Advertising, Synthesis of copy and creative
  4. Planning, media planning, the buy plan, the execution plan

Audience Targeting

  • the flagship service
  • neural networks
  • scoring users, propensity scoring <quote>based on how likely they are to take an action</quote>
  • towards CPA or CCPV or CPVisit or <more!>
  • Performable on the Weather Company O&O
    • <quote>but on TV, print, radio and other platforms. <quote>
    • Partnerships
      • Cognitiv
      • Equals 3

Optimization

Bidding Optimization
  • Is too boring for details early in the article.
  • Optimize against brand-specific KPIs.
  • Uses <buzzz>deep learning and neural networks</buzzz>
  • Optimize Cost Per Action (CPA).

Advertising

  • Badged as Watson Ads and Watson Advertising
  • Services
    • content creation
    • content copywriting
  • Launched: 2016-06.
  • Is merely: nterest-Based Advertising (IBA)
    which in turn is a but regulatory term of art, that covers a wide range of in-trade practices.
  • Sectors, aspirational
    • <fancy>aviation</fancy> (airline ticket booking?)
    • insurance
    • energy
    • finance
  • Cognitive Media Council,
    • a focus group.
    • a user group, “friends & family” of the business.
    • a group of important customers representatives
      <quote>senior-level executives from agencies and brands</quote>
Reference Customers
Toyota
  • Mirai
  • Prius Prime
  • Benefits
    Attributed to Eunice Kim, Toyota (TMNA), something about…

    • <buzzz>create a one-to-one conversational engagement</buzzz>
    • <buzzz>garner insights about the consumer thought process that could potentially inform our communication strategies elsewhere”</buzzz>
Campbell’s
  • the Soup people
  • Something about creative synthesis
    themed as: recipe generation with flu symptoms with location
H&R Block
  • Something about creative synthesis
    themed as: automated robot tax expert, suggest tax deductions.
UM [You and Em]
  • An agency. Off shore? They have a “U.S. CEO” Maybe one of those English Invasion thingies.
  • Refused to name their client.
  • Something about auto dealerships.
  • <quote>meshing Watson data with client stats to analyze metrics across a large number of car dealerships in a way that optimizes ad spend while also checking local inventory to see whether or not it should personalize an ad to someone in that market.<quote>
  • <quote>combination of weather data, Google searches and pollen counts to trigger when media should be bought in various markets.</quote>

Planning

  • <quote>AI-powered planning</quote>

Partners

Cognitiv
Something about a partnership for understanding marketing texts.
Jeremy Fain, CEO and co-founder
Equals 3
Lucy, a product-service-platform.
Something about <quote>to uncover extra insights and research.<quote>

Fairness & Balance

Promotions

Ogilvy & Mather
  • Honorific <quote>longtime agency<quote> [fof record for IBM].
Stunts
2011
Jeopardy
2015
[Television] campaign, with Bob Dylan.
2016
Synthesis of the trailier for Morgan (a move; genre: science fiction)
2017-02
Performance, an “analysis” of the stylings of Antoni Gaudi, <quote>inspire an art installation </quote> (what does that mean?)
The “art installation” was exhibited at the Mobile World Congress in Barcelona.
Statista

…is quoted
the future is boosted.

Sectors
  • “AI services”
  • “Big Data services”

Themes

Problem
  • The people are “afraid” of AI.
  • The people need to be groomed to accept AI.
Remediation

Ensmoothen & enpitchen the Artificial Intelligence (AI) as…

  • humble
  • friendly
  • ”I’m here to help’ type personality”

Attributed to Lou Aversano, Ogilvy.

Detractors

James Kisner, Jeffries

Via: James Kisner, A Report, Jeffries, 2017-07.
Jeffries is an opinion vendor in support of an M&A banking operation.
tl;dr → Watson is a failing product-service. <quote>IBM is being “outgunned” in the race…</quote> (yup, he mixed the metaphor).

  • as evidenced in measured job listings at Monster.com
    Apple had more listings booked thereon than IBM.
  • Customers were interviewed.
    Watson’s performance/price ratio was low (the rate card is very high).
    2016-10, IBM reduced the rate card for API access <quote>by 70 percent</quote>
  • Lots of press
  • Not a lot of monetary results, as evidenced in the quarterly & annual reports.
Joe Stanhope, Gartner

Via: an interview, perhaps;
Gartner Group is an opinion vendor.

  • Too much hype, can be forgiven
  • Gartner runs the Hype Cycle brand
  • Claims: <quote>IBM does seem to be all-in with Watson.<quote> (be nice to hear that from IBM, not as a “hot-take” from a newshour pundit
DemandBase, Wakefield Research

A Report; attributed to “staff”; DemandBase and Wakefield Research

  • A survey,
    • “how do you feel?”
    • Do you “have plans-to …” in the next N months.
  • There are a lot of uncertainties

Uncertainties

Training Data
  • Just isn’t there.
  • And … computers can only give answers, it can’t give [pose] questions.
Does it [even] Work?
  • No one knows.
  • Many are nervous.
  • No one wants to be first to fail
    (& be fired for outsourcing their job function to The AI).

Competitors

  • Einstein, of Salesforce(.com)
  • Sensei, of Adobe
In-House
  • Buying operations, Xaxis of WPP
    the “AI” is a “co-pilot” to the trading desk operator; optimization recommendations towards CPM and viewability; North American operations only.
  • others?
    Surely everyone nowadays has some initiative that does “co-pilot”-level decision support to adops.
Research Efforts
  • Amazon
  • Facebook
  • Google
Venture Capital
  • Albert
  • Amenity Analytics
  • LiftIgniter
  • Persado
Amenity Analytics

An exemplar of the smaller-nimbler-smarter clones of the Watson genre.

  • A Watson-type experience, but cheaper
  • Does text mining of press releases
  • Reference customers:
    Pepsi
  • A spin-out from some hedge fund, <quote>origins in the hedge fund world</quote>
  • Nathaniel Storch, CEO, Amenity Analytics.
  • <zing!>“Think of it as ‘moneyball’ for media companies,”<zing!>, attributed to Nathaniel Storch.

Consumer

  • Siri, of Apple
  • Cortana, of Microsoft
  • Now, of Google

Who

  • Lou Aversano, U.S. CEO, Ogilvy & Mather (Ogilvy, O&M).
  • Jordan Bitterman, CMO, Watson (Business Unit), IBM.
    attributed in quoted material aso “earlier this year” (2017?); c.f. Michael Mendenhall
  • Kasha Cacy, U.S. CEO, UM
    UM is an agency.
  • Cameron Clayton,
    • General Manager, Content and IoT Platform, Watson (Business Unit), IBM..
    • ex-CEO, The Weather Company
  • Jacob Colker, “entrepreneur in residence,” The Allen Institute
    …quoted for color, background & verisimilitude.The Allen Institute is a tank for thinkers.
  • Jeremy Fain, CEO and co-founder, Cognitiv.
  • Chris Jacob, director of product marketing, Marketing Cloud, Salesforce(.com).
  • Eunice Kim, media planner, Toyota Motor North America (TMNA).
    …quoted for color, background & verisimilitude.
  • James Kisner, staff, Jeffries.
    …quoted for color, background & verisimilitude.
    Jeffries is an advice shop, like Gartner, but different.
  • Francesco Marconi,
    …quoted for color, background & verisimilitude.

    • strategy manager and AI co-lead, Associated Press
    • visitor, MIT Media Lab
  • Michael Mendenhall, CMO, Watson (BU), IBM.
    announced as CMO in prior press [Ad Week, Marty Swant, 2017-07-07].
  • Sara Robertson, VP of Product Engineering, Xaxis of WPP.
  • Joe Stanhope, staff, Forrester
    …quoted for color, background & verisimilitude.
  • Nathaniel Storch, CEO, Amenity Analytics.
  • Marty Wetherall, director of innovation, FallonFallon is the agency that certain campaign booked on Watson for H&R Block

Pantheon

  • Antoni Gaudi, architect (per civil engineering), citizen of Spain.

Previously

In archaeological order, within Advertising Week

Previously filled.

Tech is Public Enemy #1. So Now What? | John Battelle

John Battelle; Tech Is Public Enemy #1. So Now What?; In His Blog, white-labeled as NewCo, centrally-hosted on Medium; 2017-09-10.
Teaser: If tech wants to reverse the crushing tide of negative public opinion, it must start creating public good commensurate with its extraction of private profit.

tl;dr → Agree, perhaps. But it’s not clear to what one is agreeing at all. Whereas the lede is buried; that being the promotion of Richard Florida’s book The New Urban Crisis.
and → Unto the hook of the title: For the sin, The Nostrum. To wit:

Nostrum
  • Enumerate.
  • Confess,
  • Repent,
  • Restitute, reparate.
  • Return.

Occasion

John Battelle interviewed Richard Florida towards a book promotion.

Book

Richard Florida The New Urban Crisis: How Our Cities Are Increasing Inequality, Deepening Segregation, and Failing the Middle Class—and What We Can Do About It 1st Edition ; Basic Books; 2017-04-11; 336 pages; ASIN:0465079741: Kindle: $18, paper: $12+SHT.

Mentions

  • Where “tech” is Apple, Amazon, Facebook, Google, and maybe Netflix (rly?).
  • And JB foresaw it in a vision of 2017-01; fair. he also “saw” it in 2011-12, had Microsoft in the cohort, and pitched “The Internet Big Five” as a gushing chronicle-of-the-times, only-time-will-tell honorific of boosterist veneration. indeed though, it’s okay to change one’s mind upon further reflection.
  • Richard Florida is granted 191 words at the end to speak as a threat.
    Whereas Richard Florida has a direct line to Congress.
    Unless his demands are met … something will happen
  • Google Apple Facebook Amazon (GAFA),
    Google Amazon Facebook Apple (GAFA)
  • Facebook Amazon Netflix Google (FANG),
    Facebook Apple Netflix Google (FANG)
  • No Wintel.  The PC Revolution is over O.V.E.R.
    • No Microsoft?
    • No Intel?
Definition: the “tech” is an enumeration
  • Apple → fabless. Purveyors of phones & some laptops.
  • Amazon → Retail reseller. Cloud (billed as a service).
  • Facebook → Entertainment. laid against advertising.
  • Google → Fabless, phone designs. Cloud (billed as a service), Advertising marketplaces.  And 25 other hobbies as “Alphabet.”
  • Netflix → Licensed video entertainment. An Amazon cloud customer.
    …can’t really seriously belong in the class of the first four can it?

Epithets

  • Uber — a company that proved a perfect exemplar of tech’s most sociopathic characteristics*.
  • <quote>The bro culture long parodied in popular culture proved to be virulently on display at the world’s most valuable startup — misogyny, tone deaf management, winning at all costs, ignorance of social and political consequence.</quote>
  • Everything Store
  • <quote>rapacious and robotic approach to platform capitalism</quote>
  • Amazon’s purchase of Whole Foods
  • Big Tech
  • fake news
  • Russian information ops
  • <quote>They’re extracting — but giving nothing back.</quote>

Rebuttal

New bogies for new panics, not the old bogies from old panics…

Missing

Anyone that actually makes things out of actual atoms. No one is afraid of companies that fabricate things out of atoms.

  • Industry (even so called “light industry”)
  • Big Defense (denizens of ‘I’ in Military-Industrial Complex)
  • Big Oil
  • Big Food
  • Big Finance, a.k.a. “Wall Street”
  • Big Auto
  • Big Semiconductor
  • Big Telecom
  • Big Blue, a.k.a. IBM
  • Big Mining
  • Big Ads, a.k.a. “Madison Avenue”
  • Big Media, a.k.a. major market television
  • Big Music, a.k.a. “the Record Labels”
  • Big Hollywood, a.k.a. “The Movie Studios”
  • Big Newspaper
  • Big Cable
  • The Diamond Cartel, e.g. de Beers
  • Railroad Trusts
  • Anyone on the Conference Board.
    Remember the “interlocking directorate” research of ‘ago?
  • The QSR, as a self-conscious class.
  • Disney
  • Microsoft
  • Walmart
  • McDonald’s

And

  • No Japanese conglomerates. Remember MITI-managed organized markets?
  • No European national champions. Remember the ’90s?

Referenced

In archaeological order, newer outbursts on top, older opinements below…

Previously

In His Blog

Related

The publishing pile-on exponentially increasing across 2015, 2016, 2017. There are many more than are presented here. Everyone is sayin’ it, doin’ it; walkin’ the walk, talkin’ the talk. Yet presented here in archaeological order, newer outbursts on top, older opinements below…

Previously filled.

WebRTC and STUN for intra-LAN exploration & end-user tracking

WebRTC

  • WebRTC, promotional site
  • Availabilities
    all the browsers that matter

    • Android
    • Chrome (Linux, Android, Windows)
    • Firefox
    • Opera
    • Safari (iOS)

STUN

Related

Standards

  • RFC 7350Datagram Transport Layer Security (DTLS) as Transport for Session Traversal Utilities for NAT (STUN); Petit-Huguenin, Salgueiro; IETF; 2014-08.
  • RFC 7064URI Scheme for the Session Traversal Utilities for NAT (STUN) Protocol; Nandakumar, Salgueiro, Jones, Petit-Huguenin; IETF; 2013-11.
  • RFC 5928Traversal Using Relays around NAT (TURN) Resolution Mechanism; Petit-Huguenin; IETF; 2010-08.
  • RFC 5389Session Traversal Utilities for NAT (STUN); Rosenberg, Mahy, Matthews, Wing; IETF; 2008-10.
    (obsoleted)

    • RFC 3489STUN – Simple Traversal of User Datagram Protocol (UDP) Through Network Address Translators (NATs); Rosenberg, Weinberger, Huitema, Mahy; 2003-03.

In Jimi Wales’ Wiki.

Implementation

Tracking

In archaeological order

Leaking


665909webrtc WebRCT Tracking; In Bugzilla of Mozilla; 2011-06-21 →2016-01-11; Closed as INVALID


Some droid using the self-asserted identity token cchen; How to Stop WebRTC Local IP Address Leaks on Google Chrome and Mozilla Firefox While Using Private IPs; In Privacy Online Forums; 2015-01→2015-03.

Mentions

  • Availability
    of the problem (not of WebRTC in general)

    • Chrome of Google
      • Windows
    • Firefox of Mozilla
      • Unclear, perhaps Windows only
    • Internet Explorer of Microsoft
      WebRTC is not available at all.
    • Opera of Mozilla
      • Unclear
    • Safari of Apple
      WebRTC is not available except through a plugin
    • Unavailable
      • Chrome of Google
        • OS/X
        • Android
      • Linux at all
        not clear; not mentioned at all.
  • Blocking
    • Chrome of Google
    • Firefox of Mozilla
      • Production
        • about:config
        • media.peerconnection.enabled set to true (default true)
      • Development
        same

        • Canary
        • Nightly
        • Bowser
    • Opera of Opera
  • API Directory
    • voice calls
    • video chats
    • p2p file sharing

Configuration

  • Chrome
    default is available and active
  • Firefox
    • about:config
    • media.peerconnection.enabled set to true (default true)
  • Opera
    only when configured, with a plugin, to run Google Chrome extensions

Demonstration

webrtc-ips, a STUN & WebRTC test rig

  • diafygi/webrtc-ips
  • via on-page JavaScript, makes latent requests to certain STUN servers.
  • Firefox 34 → Does. Not. Work.
  • Fails with
    Error: RTCPeerConnection constructor passed invalid RTCConfiguration - missing url webrtc-ips:58

Argot

  • Private Internet Access (PIA)
  • Real-Time-Communication (RTC)
  • Virtual Private Network (VPN)
  • WebRTC

Previously

In Privacy Online Forums:

Referenced

  • 2013
  •  Since WebRTC uses javascript requests to get your IP address, users of NoScript or similar services will not leak their IP addresses.

Via: backfill.


Firefox

  • about:config
  • media.peerconnection.enabled set to true (default true)

The App-ocalypse: Can Web standards make mobile apps obsolete? | Ars Technica

The App-ocalypse: Can Web standards make mobile apps obsolete?; Larry Seltzer; In Ars Technica; 2015-12-28.
Teaser: Many big tech companies—absent Apple—are throwing weight behind a browser-based world.

tl;dr → Betteridge’s Law; i.e. No.

  • WebApps are a Google-culture thing.
  • And good luck with Apple; they are intransigent in their non-interest.

Mentions

In (the arbitrary) order of appearance in the piece:

Projects

Standards

Via: backfill.

On the path to the deprecation, abandonment & refusal to honor SHA-1 signatures

Policy

  • Chrome will completely stop supporting SHA-1 certificates, soon
    • on or before 2017-01-01 (after 2016-12-31).
    • but maybe 2016-07-01 (after 2016-06-30).
  • Chrome will exhibit a warning if
    AND

    • a site presents a certificate
    • the site’s certificate
      OR

      • is signed with a SHA-1-based signature
      • is issued on or after 2016-01-01 (after 2015-12-31)
      • chains to a public CA.
  • Chrome 48
    due “early in 2016″.

Who

  • Lucas Garron, Chrome security team, Google.
  • David Benjamin, Chrome’s networking group, Google.

Statements

Apologia

  • Ryan Sleev; A History of Hard Choices; On His Blog, at Medium; 2015-12-28; separately noted.
    Ryan Sleev, cross-platform crypto & PKI core, Chromium, Google.

Promotions

The Changing Digital Landscape: Where Things are Heading | Pew Research Center


The Changing Digital Landscape: Where Things are Heading; (Pew Research Center); Presented at Tencent Media Summit, Beijing, China; 2015-11-12; 36 slides.

Contents

  • Three (3) digital revolutions have changed the news
  • State of the digital news media 2015
  • Six (6) impacts on news and the media
  • Five (5) trends for the future

Mentions

Three (3) digital revolutions have changed the news

  1. Internet
  2. Mobile Connectivity
  3. Social Networking / Social Media

State of the digital news media 2015

  • ABC & CBS improved in 2014
  • NBC declined in 2014
  • Mobile crossover occurred
  • Digital Advertising grows
  • Mobile (Digital) Advertising grows
  • Digital News uses display (banner) advertisements
  • Video Advertising grows
  • 61% of revenue, industry-level to five
    1. Google
    2. Facebook
    3. Microsoft
    4. Yahoo
    5. AOL
  • Facebook leads mobile revenue

Six (6) impacts on news and the media

  1. Mobile majority, factoids recited
  2. Mobile and Social Go Together, trendoids are recited
  3. Facebook Now Rivals Legacy News Sources (TV, national & local)
  4. There are Clear Generational Divides
    • Millennials (age 18-34) → Facebook over Local TV
    • Generation X → not shown
    • Baby Boomers (age 51-68) → Local TV over Facebook
  5. Digital Video and Radio News on the Rise.
  6. Consumers are a Part of the Process
    • User-Generated Content (UGC)
    • The Internet is defined as
      • one-to-one
      • many-to-many
      • [not one-to-many; broadcasts, portals, "the" home page]

Five (5) trends for the future

The Internet of Things (IoT) of 2025 is the 4th Revolution

  1. Screens and data will be almost everywhere
    • Lots of screens → All Ads, All The Time & on Every Available Surface
    • All Audiences are Measured
  2. Augmented reality will bring media nd data into real life
    • location awareness
    • Selling Opportunites, Always Be Selling.
    • Privacy will be gone
  3. Virtual reality will become immersive and compelling
    • Product Placement → All Ads, All The Time & on Every Available Surface
    • Personalized
    • Distractions
  4. Alerts will become pervasive and people will regulate their media streams more aggressively
    • Stress → Fear Of Missing Out (FOMO)
    • Expect aggressive management of alerts (mod way down; high bar to disturb the consumer)
  5. Smart agents and machines enabled by “artificial intelligence” will work alongside people as their assistants and “media concierges”
    • the robots will be self-aware
    • they will be actually useful & actionable, not an IT headache

Via: backfill.

Compendium on Ad Blocking in Advertising Age through 2015-09-05


IAB Explores Its Options to Fight Ad Blockers, Including Lawsuits; ; In Advertising Age; 2015-09-04.
Teaser: Trade Org Has Held Two Summits This Summer to Map a Course of Action

Mentioned

  • Interactive Advertising Bureau (IAB)
  • A Summit Meeting, New York City, 2015-07-09.
  • PageFair, Adobe
    tl;dr → that same report is endlessly recited unquestioningly
    The 2015 Ad Blocking Report: The Cost of Ad Blocking; PageFair with Adobe; 2015-08-09; 17 pages; landing, previously noted.
  • Causality
    • Flash is deprecated
    • HTML5 is promoted
    • Viewability metrics cause blocking be measured & managed.

Options

  • make better ads
  • publishers ask consumers to pull shields down
  • lockout [publishers refuse to serve consumers who wear adblock]
  • litigation [c.f. an application of the DMCA]
  • countermeasures [technical means, via suppliers]
  • paywalls
  • native advertising

Countermeasures

(vendors)

  • PageFair
  • Secret Media
  • Sourcepoint
  • Yavli

Quoted

for color, background & verisimilitude

  • Scott Cunningham
    • senior VP, IAB
    • general manager, [IAB] Technology Lab.
  • David Moore
    • President, WPP Digital
    • Chairman, Xaxis

Via: backfill.


How Digital-Native Publishers Are Dealing With Ad Blocking, , 2015-09-03.
Teaser: Mic, Quartz, Vox Media Turn to Branded Content, Tech Platforms’ Apps

Mentions

  • BuzzFeed
  • Mic
  • Quartz
  • Vox Media
  • Ad Block Plus
  • Countermeasures
    • advertorials
    • branded content
    • custom branded content
    • native advertising
    • promotional placements
    • sponsorships
  • Distribution [contra running The Portal]
    • Apple News
    • Facebook Instant Articles
    • Flipboard
  • Dean Murphy
  • Exemplar
    • a page at Mic with the story of the renaming of Mt McKinley to Denali
    • work performed by Ad Age staff
    • [very confusing, read carefully] <quote>When Ad Age checked out Mic’s aforementioned Denali article using an iPhone’s Safari browser, the ad-carrying page weighed in at 4.11 megabytes, which is 1.51 megabytes heavier than the ad-free desktop version but 14.59 megabytes lighter than the ad-full desktop page.</quote>.
    • Tabulation
      Safari iOS iPhone ad-carrying 4.11 MB
      Safari OS/X Mac (Laptop) ad-free 2.60 MB
      Safari OS/X Mac (Laptop) ad-full 18.70 MB

Quoted

for color, background & verisimilitude

  • Chris Altchek, CEO, Mic
  • Jim Bankoff, CEO, Vox Media
  • Joy Robins, seinor VP-global revenue and strategy, Quartz

TV Networks Confront Ad Blockers Erasing Their Commercials Online, , 2015-08-31.
Teaser: CBS Blocks the Blockers While Fox Explores Friendlier Ad Models

Mentions

  • ABC
    • ABC.com
  • Fox
    • Fox.com
  • Hulu
  • NBC
    • NBC.com
  • Universal
  • Ad Block
  • Chrome
  • streaming episodes of TV shows delivered off of web sites.
  • CBS Interactive
  • several “declined to comment”

Quoted

for color, background & verisimilitude

  • Eric Franchi, co-founder, Undertone
  • Joe Marchese, president-advanced ad products, Fox Networks Group; ex-founder TrueX (acquired by Fox 2014-12).
  • David Morris, chief revenue officer, CBS Interactive

Ad Blocking Is a Growing Problem. What’s the Fix?, , , 2015-06-19.
Teaser: Publishers Including CBS Interactive, Forbes, DailyMail Weigh Their Options

Mentions

  • Eyeo
  • factoids are recited
  • UC browser
    • built-in ad blocking
    • 500M consumers
    • Regional popularity
      • India
      • China,
  • Maxthon Browser
    • built-in ad blocking
    • partnership with Ad Block Plus
    • 120M consumers
  • “I love my audience, but fuck you, ad blockers — 20% of my revenue is gone.” attributed to Mike Germano, Vice
  • Interactive Advertising Bureau (IAB)
  • Interested in solutions
    • CBS Interactive
    • Daily Mail
    • Forbes
    • Vice
  • Have paid off Ad Block (Eyeo)
    • Amazon
    • Google
    • Microsoft
  • Native advertisers
    • BuzzFeed
    • Outbrain
  • Fremium, paywall, subscriptions
    and more so: behind the paywall they still have ads

    • The New York Times (NYT)
    • Pandora
    • Spotify
    • The Wall Street Journal (WSJ)
    • YouTube

Options

  1. Pay the Ad Blockers
  2. Go Native
  3. Ask Consumers for Sympathy
  4. Block Content From Consumers Who Use Ad Blockers [The Nuclear Option]
  5. Fremium Model

Quoted

for color, background & verisimilitude

  • Ben Barokas, founder, Sourcepoint
  • Sean Blanchfield, CEO, PageFair
  • Scott Cunningham, IAB
  • Mike Germano, Chief Digital Officer, Vice [Media]
  • Dax Hamman, senior VP-business development and product, Rubicon Project.
  • Jason Kint, CEO, Digital Content Next (a trade booster)
  • David Morris
    • chief revenue officer, CBS Interactive
    • chairman, Interactive Advertising Bureau (IAB)
  • Jon Steinberg, CEO, DailyMail
  • Ben Williams, director, communications & operations, Eyeo

Publishers Watch Closely as Adoption of Ad Blocking Tech Grows, , 2015-02-15.
Teaser: IAB Says It Is a Growing Problem

Mentions

  • Ad Block Plus
  • ClarityRay,
  • bought by Yahoo
  • IAB Annual Leadership Meeting
  • Claimed to have paid off Ad Block Plus (Eyeo)
    • Amazon
    • Google
    • Microsoft

Quoted

for color, background & verisimilitude

  • Mark Addison, press relations, Ad Block Plus
  • Eric Franchi
    • co-founder, Undertone
    • board member, IAB
  • Mark Howard, chief revenue officer, Forbes.
  • Serge Matta, CEO, comScore
  • David Morris, Chairman, IAB
  • Mike Zaneis, exec VP-public policy and general counsel, IAB

 

Big Data and Privacy: A Technological Perspective | PCAST

Big Data and Privacy: A Technological Perspective; Executive Office of the President, President’s Council of Advisors on Science and Technology (PCAST); 2014-05-01; 76 pages; landing.

Related

Workshops

  • White House / UC Berkeley School of Information / Berkeley Center for Law and Technology; John Podesta; 2014-04-01; transcript, video.
  • White House / Data & Society Research Institute / NYU Information Law Institute; John Podesta; 2014-03-17; video.
  • White House / MIT; John Podesta; 2014-03-04; transcript, video.

Who

PCAST Big Data and Privacy Working Group.
  • Susan L. Graham, co-chair.
  • William Press, co-chair.
  • S. James Gates, Jr.,
  • Mark Gorenberg,
  • John Holdren,
  • Eric S. Lander,
  • Craig Mundie,
  • Maxine Savitz,
  • Eric Schmidt.
  • Marjory S. Blumenthal, Executive Director of PCAST; coordination & framing..

PCAST

  • John P Holdren, co-chair, OSTP
  • Eric S. Lander, co-chair, Broad Institute (Harvard&MIT)
  • William Press, co- vice chair, U. Texas
  • Maxine Savitz, co- vice chair, National Academy of Engineering
  • Rosina Bierbaum, U. Michigan
  • Christine Cassel, National Quality Forum
  • Christopher Chyba, Princeton
  • S. James Gates, Jr., U. Maryland
  • Gorenberg, Zetta Venture Partners
  • Susan L. Graham, UCB
  • Shirley Ann Jackson, Rensselaer Polytechnic
  • Richard C. Levin, Yale
  • Chad Mirkin, Northwestern
  • Mario Molina, UCSD
  • Craig Mundie, Microsoft
  • Ed Penhoet, UCB
  • Barbara Schaal, Washington University
  • Eric Schmidt, Google
  • Daniel Schrag, Harvard

Staff

  • Marjory S. Blumenthal
  • Michael Johnson

Recommendations

From the Executive Summary [page xiii], and also from Section 5.2 [page 49]

  • Recommendation 1 [consider uses over collections activites]
    Policy attention should focus more on the actual uses of big data and less on its collection and analysis.
  • Recommendation 2 [no Microsoft lockin; no national champion]
    Policies and regulation, at all levels of government, should not embed particular technological solutions, but rather should be stated in terms of intended outcomes.
  • Recommendation 3 [fund]
    With coordination and encouragement from [The White House Office of Science and Technology Policy] OSTP, the [Networking and Information Technology Research and Development] NITRD agencies should strengthen U.S. research in privacy‐related technologies and in the relevant areas of social science that inform the successful application of those technologies.
  • Recommendation 4 [talk]
    OSTP, together with the appropriate educational institutions and professional societies, should encourage increased education and training opportunities concerning privacy protection, including career paths for professionals.
  • Recommendation 5 [talk & buy]
    The United States should take the lead both in the international arena and at home by adopting policies that stimulate the use of practical privacy‐protecting technologies that exist today. It can exhibit leadership both by its convening power (for instance, by promoting the creation and adoption of standards) and also by its own procurement practices (such as its own use of privacy‐preserving cloud services)

Table of Contents

  1. Executive Summary
  2. Introduction
    1. Context and outline of this report
    2. Technology has long driven the meaning of privacy
    3. What is different today?
    4. Values, harms, and rights
  3. Examples and Scenarios
    1. Things happening today or very soon
    2. Scenarios of the near future in healthcare and education
    3. Healthcare: personalized medicine,
    4. Healthcare: detection of symptoms by mobile devices
    5. Education
    6. Challenges to the home’s special status
    7. Tradeoffs among privacy, security, and convenience
  4. Collection, Analytics, and Supporting Infrastructure
    1. Electronic sources of personal data
      1. “Born digital” data
      2. Data from sensors
    1. Big data analytics
      1. Data mining
      2. Data fusion and information integration
      3. Image and speech recognition
      4. Social‐network analysis
    2. The infrastructure behind big data
      1. Data centers
      2. The cloud
  5. Technologies and Strategies for Privacy Protection
    1. The relationship between cybersecurity and privacy
    2. Cryptography and encryption
      1. Well Established encryption technology
      2. Encryption frontiers
    3. Notice and consent
      1. Other strategies and techniques
        1. Anonymization or de‐identification
        2. Deletion and non‐retention
    4. Robust technologies going forward
      1. A Successor to Notice and Consent
      2. Context and Use
      3. Enforcement and deterrence
      4. Operationalizing the Consumer Privacy Bill of Rights
  6. PCAST Perspectives and Conclusions
    1. Technical feasibility of policy interventions
    2. Recommendations
    3. Final Remarks
  7. Appendix A. Additional Experts Providing Input
  8. Special Acknowledgment

Mentions

  • The President’s Council of Advisors on Science and Technology (PCAST)
  • PCAST Big Data and Privacy Working Group
  • Enabling Event
    • President Barack Obama
    • Remarks, 2014-01-17
    • Counselor John Podesta
  • New Concerns
    • Born digital vs born analog
    • standardized components
    • particular limited purpose vs repurposed, reused.
    • data fusion
    • algorithms
    • inferences
  • Provenance of data, recording and tracing the provenance of data
  • Trusted Data Format (TDF)

Claims

  • Right to forget, right to be forgotten is unenforceable infeasible [page 48].
  • Prior redress of prospective harms is a reasonable framework [page 49]
    • Conceptualized as vulnerable groups who are stipulated as harmed a priori or are harmed sunt constitua.
  • Government may be forbidden from certain classes of uses, despite their being available in the private
    sector

    • Government is allowed some activities and powers
    • Private industry is allowed some activities and powers
    • It is feasible in practice to mix & match
      • government coercion => private privilege => result
      • private privilege => private coercion => result

Consumer Privacy Bill of Rights (CPBR)

Obligations [of service providers, as powerful organizations]

  • Respect for Context => use consistent with collection context.
  • Focused Collection => limited collection.
  • Security => handling techniques
  • Accountability => handling techniques.

Empowerments [of consumers, as individuals]

  • Individual Control => control of collection, control of use.
  • Transparency => of practices [by service providers]
  • Access and Accuracy => right to review & edit [something about proportionality]

Definition of Privacy

The definition is unclear and evolving. It is frequently defined in terms of the harms in curred when it is lost.

Privacy Framework of Via Harms

The Prosser Harms, <quote> page 6.

  1. Intrusion upon seclusion. A person who intentionally intrudes, physically or otherwise (now including electronically), upon the solitude or seclusion of another person or her private affairs or concerns, can be subject to liability for the invasion of her privacy, but only if the intrusion would be highly offensive to a reasonable person.
  2. Public disclosure of private facts. Similarly, a person can be sued for publishing private facts about another person, even if those facts are true. Private facts are those about someone’s personal life that have not previously been made public, that are not of legitimate public concern, and that would be offensive to a reasonable person.
  3. “False light” or publicity. Closely related to defamation, this harm results when false facts are widely published about an individual. In some states, false light includes untrue implications, not just untrue facts as such.
  4. Misappropriation of name or likeness. Individuals have a “right of publicity” to control the use of their name or likeness in commercial settings.

</quote>

Adjacencies

<quote>One perspective informed by new technologies and technology‐mediated communication suggests that privacy is about the “continual management of boundaries between different spheres of action and degrees of disclosure within those spheres,” with privacy and one’s public face being balanced in different ways at different times. See: Leysia Palen, Paul Dourish; Unpacking ‘Privacy’ for a Networked World; In Proceedings of CHI 2003, Association for Computing Machinery, 2003-04-05.</quote>, footnote, page 7.

Adjacency Theory

An oppositional framework wherein harms are “adjacent to” benefits:

  • Invasion of private communications
  • Invasion of privacy ihn a person’s virtual home.
  • Public disclosure of inferred private facts
  • Tracking, stalking and violations of locational privacy.
  • Harm arising from false conclusions about individuals, based on personal profiles from big‐data analytics.
  • Foreclosure of individual autonomy or self‐determination
  • Loss of anonymity and private association.
Mosaic Theory

Oblique referenced via quote from Sotomayor.
<quote>“I would ask whether people reasonably expect that their movements will be recorded and aggregated in a manner that enables the Government to ascertain, more or less at will, their political and religious beliefs, sexual habits, and so on.” United States v. Jones (10‐1259), Sotomayor concurrence.</quote>

Yet, not cited, but related (at least):

Definition of Roles [of data processors]

  • data collectors
  • data analyzers
  • data users

The data generators or producers in this roles framework are substantially only customers or consumers (sic).

Definitions

  • Definition of analysis versus use
    • <quote>Analysis, per se, does not directly touch the individual (it is neither collection nor, without additional action, use) and may have no external visibility.
    • & by contrast, it is the use of a product of analysis, whether in commerce, by government, by the press, or by individuals, that can cause adverse consequences to individuals.</quote>
  • Big Data => definitions
    • [comprises data with] high‐volume, high‐velocity and high‐variety
      information assets that demand cost‐effective, innovative forms of information processing for enhanced insight and decision making,” attributed to Gartner Inc.
    • a term describing the storage and analysis of large and/or complex data sets using a series of techniques including, but not limited to, NoSQL, MapReduce, and machine learning.” attributed to “computer scientists” on arXiv.

Quoted

The strong, direct, unequivocal, un-nuanced, provocative language…

<quote>For a variety of reasons, PCAST judges anonymization, data deletion, and distinguishing data from metadata (defined below) to be in this category. The framework of notice and consent is also becoming unworkable as a useful foundation for policy.</quote>

<quote>Anonymization is increasingly easily defeated by the very techniques that are being developed for many legitimate applications of big data. In general, as the size and diversity of available data grows, the likelihood of being able to re‐identify individuals (that is, re‐associate their records with their names) grows substantially. While anonymization may remain somewhat useful as an added safeguard in some situations, approaches that deem it, by itself, a sufficient safeguard need updating. </quote>

<quote>Notice and consent is the practice of requiring individuals to give positive consent to the personal data collection practices of each individual app, program, or web service. Only in some fantasy world do users actually read these notices and understand their implications before clicking to indicate their consent. <snip/>The conceptual problem with notice and consent is that it fundamentally places the burden of privacy protection on the individual. Notice and consent creates a non‐level playing field in the implicit privacy negotiation between provider and user. The provider offers a complex, take‐it‐or‐leave‐it set of terms, while the user, in practice, can allocate only a few seconds to evaluating the offer. This is a kind of market failure. </quote>

<quote>Also rapidly changing are the distinctions between government and the private sector as potential threats to individual privacy. Government is not just a “giant corporation.” It has a monopoly in the use of force; it has no direct competitors who seek market advantage over it and may thus motivate it to correct missteps. Governments have checks and balances, which can contribute to self‐imposed limits on what they may do with people’s information. Companies decide how they will use such information in the context of such factors as competitive advantages and risks, government regulation, and perceived threats and consequences of lawsuits. It is thus appropriate that there are different sets of constraints on the public and private sectors. But government has a set of authorities – particularly in the areas of law enforcement and national security – that place it in a uniquely powerful position, and therefore the restraints placed on its collection and use of data deserve special attention. Indeed, the need for such attention is heightened because of the increasingly blurry line between public and private data. While these differences are real, big data is to some extent a leveler of the differences between government and companies. Both governments and companies have potential access to the same sources of data and the same analytic tools. Current rules may allow government to purchase or otherwise obtain data from the private sector that, in some cases, it could not legally collect itself, or to outsource to the private sector analyses it could not itself legally perform. [emphasis here] The possibility of government exercising, without proper safeguards, its own monopoly powers and also having unfettered access to the private information marketplace is unsettling.</quote>

Referenced

Substantially in order of appearance in the footnotes, without repeats.

Via: backfill, backfill


Snide

And yet even with all the letters and professional editing and techwriting staff available to this national- and historical-level enterprise we still see [Footnote 101, page 31]

Qi, H. and A. Gani, “Research on mobile cloud computing: Review, trend and perspectives,” Digital Information and Communication Technology and it’s Applications (DICTAP), 2012 Second International Conference on, 2012.

The correct listing is at Springer

Digital Information and Communication Technology and Its Applications;International Conference, DICTAP 2011, Dijon, France, June 21-23, 2011. Proceedings, Part I, Series: Communications in Computer and Information Science, Vol. 166 Cherifi, Hocine, Zain, Jasni Mohamad, El-Qawasmeh, Eyas (Eds.) 2011, XIV, 806 p.

But:

  • it’s → is a contraction for it is
  • its → is a possessive

Ergo: s/it's/its/g;

DECAF: Detecting and Characterizing Ad Fraud in Mobile Apps | Liu, Nath, Govindan, Liu

Bin Liu, Suman Nath, Ramesh Govindan, Jie Liu; DECAF: Detecting and Characterizing Ad Fraud in Mobile Apps; In Proceedings of NSDI (NSDI); 2014; 15 pages.

Abstract

Ad networks for mobile apps require inspection of the visual layout of their ads to detect certain types of placement frauds. Doing this manually is error prone, and does not scale to the sizes of today’s app stores. In this paper, we design a system called DECAF to automatically discover various placement frauds scalably and effectively. DECAF uses automated app navigation, together with optimizations to scan through a large number of visual elements within a limited time. It also includes a framework for efficiently detecting whether ads within an app violate an extensible set of rules that govern ad placement and display. We have implemented DECAF for Windows-based mobile platforms, and applied it to 1,150 tablet apps and 50,000 phone apps in order to characterize the prevalence of ad frauds. DECAF has been used by the ad fraud team in Microsoft and has helped find many instances of ad frauds.

Also

Bin Liu, Suman Nath, Ramesh Govindan, Jie Liu; DECAF: Detecting and Characterizing Ad Fraud in Mobile Apps; Technical Report 13-938; Viterbi School of Engineering; University of Southern California; 2013; 15 pages.

Xbox One busted at only sixty days out with a grinding noise from the DVD/BlueRay

Xbox One busted at only sixty days out with a grinding noise from the DVD/BlueRay.  Won’t play anything.

Remediation

  • Maybe you can (still) get a replacement unit from M$.
  • Percussive maintenance; as shown here

Folklore

Symptoms

How Mobile Is Eating The World | Benedict Evans, Enders Analysis at Business Insider

Benedict Evans (Enders Analysis); How Mobile Is Eating The World; In Business Insider; 2013-11-17.

Mentions

  • Lots of up-and-to-the-right.
  • Irrelevance of Microsoft
  • Scale at Samsung
  • Scale at Apple
  • Tablets
  • Post-PC Vision
  • Four Horsemen
    • Google
    • Apple
    • Facebook
    • Amazon
  • Chinese Android is not Android
  • WebKit Everywhere
  • Smartphones are inherently social
    • address book
    • photo library
    • push notifications
    • home screen, task switcher
    • switching apps is easy
  • Unbundling Functions vs Unbundling Friends
  • Cards as Content Packets
  • Social as Discovery
  • Tablet Trends
  • Open Questions
    • What is the identity platform
    • Watch: protocols-and-services

Outline

  • The state of PCs
  • Smartphones are exploding
  • More mobile growth coming
  • The future is mobile
  • The world is 2017
  • Growth in emerging markets
  • Fundamental change
  • Fundamental change in scale
  • Fundamental change in use
  • What does mass mobile internet use really mean? From this…
  • … to this
  • Industry scale
  • Polarisation of manufacturers
  • The irrelevance of Microsoft
  • Scale at Samsung…
  • and scale at Apple
  • Very different products
  • Apple sticking to the high end?
  • Glass is eating the world
  • Tablets overtaking PCs
  • Tablet market splitting
  • iPad dominates use everywhere
  • Two distinct ‘tablet’ markets
  • Tablet [is] dynamic quite different to smartphones
  • Tablet [is] dynamic quite different to smartphones, continued
  • Blurring definitions
  • Tablets in 2013
  • Still lots of unknowns
  • ‘Four horsemen’ driving the agenda
  • Ecosystem sizes
  • Reach != value
  • (Chinese Android isn’t Google)
  • Geographic variation
  • Ecosystem is the key leverage point
  • People like apps
  • Mobile platform wars over?
  • Speed of innovation?
  • Different focus for innovation
  • App engagement
  • Self-selection
  • Ecosystem cohorts
  • Ecosystem cohorts?
  • Future of Android
  • Mobile social scale
  • Mobile social scale, continued
  • Children’s use of messaging
  • Smartphones are inherently social, unlike the desktop web
  • People happily abandon history, 3x slides
  • Facebook is one of many
  • Facebook is doing well on mobile
  • Half of DAUs are mobile-only
  • Is the mobile opportunity so big that it doesn’ matter to Facebook if it isn’t dominant?
  • Unbundling
  • The Aggregation Cycle
  • Unbundling Facebook
  • Unbundling functions or unbundling friends?
  • Mobile social is still in flux
  • There’s money in stickers
  • The next opportunity is creating the next platform
  • Cards as content packets – social as discovery
  • Two trends for mobile content
  • Again, all this is in flux
  • Broader uncertainty and opportunity
  • Blurring boundaries

Via: backfill

Dynamic Adaptive Streaming over HTTP (DASH)

MPEG DASh Scope

Concepts

  • MPEG-DASH Media Presentation Description (MPD)

Origin

  • Adaptive HTTP streaming (AHS) in 3GPP Release 9
  • HTTP Adaptive Streaming (HAS) in Open IPTV Forum Release 2.

Related

  • Adobe Systems, HTTP Dynamic Streaming,
  • Apple, HTTP Live Streaming (HLS)
  • Microsoft Smooth Streaming.

Standard

Highlights

  • Use Cases
    • On-Demand
    • Live
  • Ad insertion. Advertisements can be inserted as a period between periods or segment between segments in both on-demand and live cases.
  • CDN
    • Multiple URL
    • CCN (CCNx)
  • Codec
    • Agnostic
    • Common Encryption
    • Multiple DRM
  • Coding
    • Scalable Video Coding (SVC)
    • Multiview Video Coding (MVC)

Implementations

Via: backfill

Data Privacy Day 2013 Survey Results, Personal Data Dashboard, Privacy in Action | Microsoft

Occasion

Method

  • ask “regular folk” what they “feel.”
  • record the results.

Considerations

  • Framing
  • Self-reported
  • Feelings & rememberances

Claims

  • Control over information gathering
    • 45% feel they have little or no control over such.
    • Unstated: therefore 55% feel that they have some control.
    • Framed as: gathering occurs on
      • Web browsing (page reading)
      • photo sharing
      • travel
      • gaming.
  • Reputation, track record and policies and considered toward usage
    • 32% always consider such.
    • Unstated: therefore 68% don’t always consider such.
  • When consumers have questions about protecting their privacy, they
    • 39% consult friends & family.
    • 39% consult website’s privacy statement.
    • 29% consult a company’s privacy policy.
    • Unstated: this totals to 107%
  • For privacy information, consumers trust
    • 33% friends and family.
    • 25% industry privacy or consumer organizations.
    • 22% a website’s privacy statement.
    • Unstated: therefore 20% trust none of these.

Pages & Sites

Collateral

Trivialities & 2-pagers.

STEM Labor Shortages? | Economic Policy Institute | Daniel Costa

Promoted from backfill

Daniel Costa; STEM labor shortages?; Economic Policy Institute; 2012-11-19.
Teaser: Microsoft report distorts reality about computing occupations

Mentions

  • <quote>Conclusion: Now is not the time to increase the number of H-1B visas and STEM green cards</quote>
  • <quote>Microsoft is proposing that the government increase the supply of STEM workers with college degrees even though their unemployment rate is already double the rate at which full employment occurs for such workers. Microsoft’s proposal is unsurprising, since adding workers to the STEM labor supply during times of high unemployment and insufficient job creation would propel STEM unemployment rates even higher, thereby preventing wages in these occupations from rising. If this occurs, more STEM workers would have little choice but to accept whatever terms and conditions are offered by employers. This wage suppression is already occurring in computer and mathematical occupations. Figure D shows the average hourly wage for college-educated workers in computer and mathematical occupations over the last 11 years.</quote>
  • <quote>The first significant problem with Microsoft’s report is the assumption that job openings “in computing” not filled by college graduates with computer science (CS) degrees will go unfilled. It is a well-known fact that computer science graduates are not the only source of new hires in computing.</quote>
  • <quote>They add that there is also an adequate supply of experienced STEM workers, writing, “Purported labor market shortages for scientists and engineers are anecdotal and also not supported by the available evidence” (Lowell and Salzman 2007, 43).</quote>

Promotions

Original Event

Summary: need more H-1B to keep labor rates low and lowering (a.k.a. “be competitive”)