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Qualified
Self
Prof. Lee SCHLENKER
E-Stratégies
Nov 12th 2015
How can you use enterprise
technologies to improve
apprenticeship?
Agenda
I. CHAT
II. The New World of Work
III. Productivity today
IV. Digital Workspaces
V. The Building Blocks
VI. The Value Proposition
VII. Market metaphores
VIII. The value architect™
IX. Conclusion and Perspectives
Intro Technology CasesDomains
©2014 L. SCHLENKER
Intro Technology CasesDomains
©2014 L. SCHLENKER
©2013 L. SCHLENKER
http://intranet-
matters.de/resources/intranet-maturity-
models/
I. Inputs
II. States
III. Performance
IV. Self-knowledge
Intro Technology CasesDomains
©2014 L. SCHLENKER
• The mechanical clock
• Harder, better, faster…
• Mechanized productivity
• Knowledge productivity
• Continuous Productivity
Intro Technology CasesDomains
©2014 L. SCHLENKER
The author suggests that the "Quantified
Self" movement is about self knowledge.
What does he want to know about
himself?
Describe one of the applications
described in the article (audience, data
sources, interface, use scenarios,
observations).
The article points out the fallacy of
"magical thinking". What does this mean
and how does this this apply to the
Quantified Self?
The article concludes that the goal isn't to
do more work, but to do better work. What
does this mean to you? Richard J. Anderson
Intro Technology CasesDomains
©2014 L. SCHLENKER
©2013 L. SCHLENKER
•Your search history
•Your search trends
•Your contacts
•Your location
•Your interests and demographics
www.google.com/dashboard
©2014 L. SCHLENKER
Intro Technology CasesDomains
©2013 L. SCHLENKER
I. The Quantified Self
II. The Qualified Self
III. Managerial Perspective
Intro Technology CasesDomains
©2014 L. SCHLENKER
•Data mediates the experience of
reality.
•Quantimetric self-tracking and
wearable computers
•Quantimetric self-sensing
•Gary Wolf - the Quantified Self
Early prototype of "Quantimetric Self-Sensing"
apparatus, 1996
Intro Technology CasesDomains
©2014 L. SCHLENKER
• Pythagoras of Samos - number is the key to reality
• Immanuel Kant - reality is comprehensible through
categories of significance (schemata)
• Michel Foucault: - technologies of the Self
• Martin Heidegger - care of the self before care of others
• Timothy Leary – «turn on, tune in, drop out”
• Steve Mann: - Souveillance vs. Surveillanc
QS as way of sharing meaning
rather than quantifying the individual?
Intro Technology CasesDomains
©2014 L. SCHLENKER
©2013 L. SCHLENKER
I. Health and Well-being
II. Personal and Group
Productivity
III. Education
IV. Social Interaction
Intro Technology CasesDomains
©2014 L. SCHLENKER
• Mobile devices and embedded
sensors can track heart rate, blood
sugar, caloric intake, sleep
quality…. .
• Capters can beam data to cloud
databases, which send advice to
consumers
• There is a real need in health-
care to cut down the number of
unnecessary medical visits
• Google has funded 23andMe
Inc., Fitbit has drawn $43 million
from investment firms
Intro Technology CasesDomains
©2014 L. SCHLENKER
• People have been keeping checklists
and to do’s for decades
• Ask the right question and then find
the right mix between curiosity and
measurable data
• RescueTime led writer Gina Trapani
to switch to a standing desk and
WordPress creator Matt Mullenweg do
impose new email rules.
•Mint for tracking where every Euro
and cent goes.
•MoodPanda for noting on a simple 1-
10 scale how you’re feeling
•PlaceMe, for automated location
tracking system
Intro Technology CasesDomains
©2014 L. SCHLENKER
• Track what you read – when, what, where
you stop, what you highlight, what you
annotate
• Track what you write - how many words,
how many pages, what and when you
write….
• Track how you learn - who you listen to ,
what you say, how you search….
• Technology can enable real-time feedback
•Santa Monica College’s Glass Classroom,
Stanford’s Multimodal Learning Analytics
• Do something with what you discover
http://www.edudemic.com/learning-analytics-in-
education/
http://glassclassroom.blogspot.fr/2012/12/the-glass-
classroom-big-data.html
Intro Technology CasesDomains
©2014 L. SCHLENKER
©2013 L. SCHLENKER
• Using data for personal meaning
challenge our ideas about human
connection
• Social networks like Facebook and
Twitter transform our social
interactions into quantifiable data
streams
• Social Graph - interactions
between people in a social network
• Is it possible to track emotions,
passions and memories?
• Could QS help us live together in a
sustainable way?
Will our communities be looking after us,
taking care, encouraging us, as well as discipline us?
Joerg Blumtritt
Intro Technology CasesDomains
©2014 L. SCHLENKER
©2013 L. SCHLENKER
I. Big Data, Little Data
II. Cloud Computing
III. Open Data
IV. Sensors and Capters
V. Visualisation
Intro Technology CasesDomains
©2014 L. SCHLENKER
©2013 L. SCHLENKER
• Examples
•Walmart : 1 million transactions/hr
•BBC: 7 PB video served/month
• Big Data definition: data sets on social
interactions that are too complex for
traditional DBMS (volume, velocity, variety)
• Little Data : data sets on individual rather
collective behavior
• Structured and unstructured data
Source: Mary Meeker, Internet Trends,
Intro Technology CasesDomains
©2014 L. SCHLENKER
©2013 L. SCHLENKER
• Computing as service rather than a
product
• Focuses on maximizing shared resources
• Public, private or hybrid
• Infrastructure as a service (IaaS)
• Platform as a service (PaaS)
• Software as a service (SaaS)
Intro Technology CasesDomains
©2014 L. SCHLENKER
• The idea that certain data should
be freely available to everyone to
use
• Facts cannot legally be
copyrighted, but aggregated data
can be privately owned.
• Journal publication is an implicit
release of the data to the
Commons
• Midata, the UK government’s
initiative to give consumers
access to data about them that is
held by brands
Anja Jentzsch
©2014 L. SCHLENKER
Intro Technology CasesDomains
©2013 L. SCHLENKER
•The Internet of things: Physical
objects linked by the Internet
that interact through web
services
•Usual gadgetry (e.g.;
smartphones, tablets) and now
everyday objects: cars, food,
clothing, appliances, materials,
parts, buildings, roads
•Embedded microprocessors in
5% human-constructed objects
(2012)1
1Source: Vinge, V. Who’s Afraid of First Movers? The Singularity Summit 2012.
http://singularitysummit.com/schedule
Melanie Swan
Intro Technology CasesDomains
©2013 L. SCHLENKER
• Study of abstract data to
improve human cognition
• Lévi-Strauss – the world has
become so complex that we
must “simplify it” to understand
it
•Goal of data visualization is to
communicate information
clearly and efficiently
• Visualization is today a critical
component in scientific
research, data mining, finance,
and market studies
Intro Technology CasesDomains
©2014 L. SCHLENKER
©2013 L. SCHLENKER
I. Babolat
II. Sensory Fashion
III. Asthmapolis
IV. Sleep on It
Intro Technology CasesDomains
©2014 L. SCHLENKER
©2013 L. SCHLENKER
• Tennis is stats heavy : serve
percentages, forehand winners, aces,
unforced errors
• Give the amateur some way of
assessing his or her game
• Hitting the sweet spot 100 % of the
time doesn’t mean you’ll win
• Data is often misleading, but winning
is often about fractions.
• It does have the potential to change
the way we think about coaching
Intro Technology CasesDomains
©2014 L. SCHLENKER
©2013 L. SCHLENKER
• Uses fashion and IT to create
responsive clothes offering therapeutic
value
•Scents as tools to improve mental and
physical wellbeing
• A localized ‘scent cloud’ is released to
fit specific moods
• Goal is unlock emotional memories and
to complement mood monitoring tools for
the ‘Quantified Self’
Dr Jenny Tillotson
Intro Technology CasesDomains
©2014 L. SCHLENKER
©2013 L. SCHLENKER
• 8.4% of Americans, or over 25 million
people, suffer from asthma.
• Third-leading cause of death in the US
with $50 billion associated annual
healthcare costs
• Helps researchers pinpoint
environmental triggers and monitor the
population of asthma suffers
• Attaches to an asthma inhaler and logs
the time and geographic location each
time its used
• Uncontrolled asthma declines by 50
percent
http://youtu.be/6CH1IxzmwUs
Intro Technology CasesDomains
©2014 L. SCHLENKER
©2013 L. SCHLENKER
• Sleep is the third pillar of health (with
diet and exercise)
• Works on the basis of actigraphy, which
is the detection and analysis of muscular
movement
•Sleep data reveals how your sleep is
related to factors such as diet, stress,
and physical activity
• The physical and psychological
benefits have yet to be proven
©2014 L. SCHLENKER
Intro Technology CasesDomains

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The Quantified self

  • 1. Qualified Self Prof. Lee SCHLENKER E-Stratégies Nov 12th 2015 How can you use enterprise technologies to improve apprenticeship?
  • 2. Agenda I. CHAT II. The New World of Work III. Productivity today IV. Digital Workspaces V. The Building Blocks VI. The Value Proposition VII. Market metaphores VIII. The value architect™ IX. Conclusion and Perspectives Intro Technology CasesDomains ©2014 L. SCHLENKER
  • 4. ©2013 L. SCHLENKER http://intranet- matters.de/resources/intranet-maturity- models/ I. Inputs II. States III. Performance IV. Self-knowledge Intro Technology CasesDomains ©2014 L. SCHLENKER
  • 5. • The mechanical clock • Harder, better, faster… • Mechanized productivity • Knowledge productivity • Continuous Productivity Intro Technology CasesDomains ©2014 L. SCHLENKER
  • 6. The author suggests that the "Quantified Self" movement is about self knowledge. What does he want to know about himself? Describe one of the applications described in the article (audience, data sources, interface, use scenarios, observations). The article points out the fallacy of "magical thinking". What does this mean and how does this this apply to the Quantified Self? The article concludes that the goal isn't to do more work, but to do better work. What does this mean to you? Richard J. Anderson Intro Technology CasesDomains ©2014 L. SCHLENKER
  • 7. ©2013 L. SCHLENKER •Your search history •Your search trends •Your contacts •Your location •Your interests and demographics www.google.com/dashboard ©2014 L. SCHLENKER Intro Technology CasesDomains
  • 8. ©2013 L. SCHLENKER I. The Quantified Self II. The Qualified Self III. Managerial Perspective Intro Technology CasesDomains ©2014 L. SCHLENKER
  • 9. •Data mediates the experience of reality. •Quantimetric self-tracking and wearable computers •Quantimetric self-sensing •Gary Wolf - the Quantified Self Early prototype of "Quantimetric Self-Sensing" apparatus, 1996 Intro Technology CasesDomains ©2014 L. SCHLENKER
  • 10. • Pythagoras of Samos - number is the key to reality • Immanuel Kant - reality is comprehensible through categories of significance (schemata) • Michel Foucault: - technologies of the Self • Martin Heidegger - care of the self before care of others • Timothy Leary – «turn on, tune in, drop out” • Steve Mann: - Souveillance vs. Surveillanc QS as way of sharing meaning rather than quantifying the individual? Intro Technology CasesDomains ©2014 L. SCHLENKER
  • 11. ©2013 L. SCHLENKER I. Health and Well-being II. Personal and Group Productivity III. Education IV. Social Interaction Intro Technology CasesDomains ©2014 L. SCHLENKER
  • 12. • Mobile devices and embedded sensors can track heart rate, blood sugar, caloric intake, sleep quality…. . • Capters can beam data to cloud databases, which send advice to consumers • There is a real need in health- care to cut down the number of unnecessary medical visits • Google has funded 23andMe Inc., Fitbit has drawn $43 million from investment firms Intro Technology CasesDomains ©2014 L. SCHLENKER
  • 13. • People have been keeping checklists and to do’s for decades • Ask the right question and then find the right mix between curiosity and measurable data • RescueTime led writer Gina Trapani to switch to a standing desk and WordPress creator Matt Mullenweg do impose new email rules. •Mint for tracking where every Euro and cent goes. •MoodPanda for noting on a simple 1- 10 scale how you’re feeling •PlaceMe, for automated location tracking system Intro Technology CasesDomains ©2014 L. SCHLENKER
  • 14. • Track what you read – when, what, where you stop, what you highlight, what you annotate • Track what you write - how many words, how many pages, what and when you write…. • Track how you learn - who you listen to , what you say, how you search…. • Technology can enable real-time feedback •Santa Monica College’s Glass Classroom, Stanford’s Multimodal Learning Analytics • Do something with what you discover http://www.edudemic.com/learning-analytics-in- education/ http://glassclassroom.blogspot.fr/2012/12/the-glass- classroom-big-data.html Intro Technology CasesDomains ©2014 L. SCHLENKER
  • 15. ©2013 L. SCHLENKER • Using data for personal meaning challenge our ideas about human connection • Social networks like Facebook and Twitter transform our social interactions into quantifiable data streams • Social Graph - interactions between people in a social network • Is it possible to track emotions, passions and memories? • Could QS help us live together in a sustainable way? Will our communities be looking after us, taking care, encouraging us, as well as discipline us? Joerg Blumtritt Intro Technology CasesDomains ©2014 L. SCHLENKER
  • 16. ©2013 L. SCHLENKER I. Big Data, Little Data II. Cloud Computing III. Open Data IV. Sensors and Capters V. Visualisation Intro Technology CasesDomains ©2014 L. SCHLENKER
  • 17. ©2013 L. SCHLENKER • Examples •Walmart : 1 million transactions/hr •BBC: 7 PB video served/month • Big Data definition: data sets on social interactions that are too complex for traditional DBMS (volume, velocity, variety) • Little Data : data sets on individual rather collective behavior • Structured and unstructured data Source: Mary Meeker, Internet Trends, Intro Technology CasesDomains ©2014 L. SCHLENKER
  • 18. ©2013 L. SCHLENKER • Computing as service rather than a product • Focuses on maximizing shared resources • Public, private or hybrid • Infrastructure as a service (IaaS) • Platform as a service (PaaS) • Software as a service (SaaS) Intro Technology CasesDomains ©2014 L. SCHLENKER
  • 19. • The idea that certain data should be freely available to everyone to use • Facts cannot legally be copyrighted, but aggregated data can be privately owned. • Journal publication is an implicit release of the data to the Commons • Midata, the UK government’s initiative to give consumers access to data about them that is held by brands Anja Jentzsch ©2014 L. SCHLENKER Intro Technology CasesDomains
  • 20. ©2013 L. SCHLENKER •The Internet of things: Physical objects linked by the Internet that interact through web services •Usual gadgetry (e.g.; smartphones, tablets) and now everyday objects: cars, food, clothing, appliances, materials, parts, buildings, roads •Embedded microprocessors in 5% human-constructed objects (2012)1 1Source: Vinge, V. Who’s Afraid of First Movers? The Singularity Summit 2012. http://singularitysummit.com/schedule Melanie Swan Intro Technology CasesDomains
  • 21. ©2013 L. SCHLENKER • Study of abstract data to improve human cognition • Lévi-Strauss – the world has become so complex that we must “simplify it” to understand it •Goal of data visualization is to communicate information clearly and efficiently • Visualization is today a critical component in scientific research, data mining, finance, and market studies Intro Technology CasesDomains ©2014 L. SCHLENKER
  • 22. ©2013 L. SCHLENKER I. Babolat II. Sensory Fashion III. Asthmapolis IV. Sleep on It Intro Technology CasesDomains ©2014 L. SCHLENKER
  • 23. ©2013 L. SCHLENKER • Tennis is stats heavy : serve percentages, forehand winners, aces, unforced errors • Give the amateur some way of assessing his or her game • Hitting the sweet spot 100 % of the time doesn’t mean you’ll win • Data is often misleading, but winning is often about fractions. • It does have the potential to change the way we think about coaching Intro Technology CasesDomains ©2014 L. SCHLENKER
  • 24. ©2013 L. SCHLENKER • Uses fashion and IT to create responsive clothes offering therapeutic value •Scents as tools to improve mental and physical wellbeing • A localized ‘scent cloud’ is released to fit specific moods • Goal is unlock emotional memories and to complement mood monitoring tools for the ‘Quantified Self’ Dr Jenny Tillotson Intro Technology CasesDomains ©2014 L. SCHLENKER
  • 25. ©2013 L. SCHLENKER • 8.4% of Americans, or over 25 million people, suffer from asthma. • Third-leading cause of death in the US with $50 billion associated annual healthcare costs • Helps researchers pinpoint environmental triggers and monitor the population of asthma suffers • Attaches to an asthma inhaler and logs the time and geographic location each time its used • Uncontrolled asthma declines by 50 percent http://youtu.be/6CH1IxzmwUs Intro Technology CasesDomains ©2014 L. SCHLENKER
  • 26. ©2013 L. SCHLENKER • Sleep is the third pillar of health (with diet and exercise) • Works on the basis of actigraphy, which is the detection and analysis of muscular movement •Sleep data reveals how your sleep is related to factors such as diet, stress, and physical activity • The physical and psychological benefits have yet to be proven ©2014 L. SCHLENKER Intro Technology CasesDomains

Editor's Notes

  1. Technics and Civilization, the historian  Lewis Mumford