A contribution to the discussion about Maurizio Ferraris' notion of "total mobilization"

1. Fondation Maison des sciences de l'homme - Luca De Biase
Who is writing
my autobiography
Dans la toile du Web

2. Am I the author of my life?

3. (the following is just a research idea
for a media ecology approach)

4. Digital is the new environment
❖ DIGITALLY RECORDED KNOWLEDGE:
❖ 2000: 25% ———> 2013: 98%
❖ In 2013, 98% of information recorded by humans was in
digital format; in the year 2000 it was 25% - Martin
Hilbert, quoted by Victor Mayer-Schönberger and
Kenneth Cukier in BIG DATA 2013

5. Shift happens
❖ Big data
❖ Robotics
❖ Nanotechnology
❖ Biotechnology
❖ Neuro-science
❖ Particle physics
❖ Additive production
❖ Artificial intelligence
❖ Collective intelligence
❖ Sharing economy
❖ Climate change
❖ Space exploration
❖ Startups
❖ Bitcoin

6. Am I the author of my life?

7. –Steve Jobs. June 12, 2005
“Your time is limited,
so don’t waste it living someone else’s life”.

9. Steve Jobs said: «the computer
is like a bicycle for our minds»
http://www.bikeboom.info/efficiency/

10. the phone is even more than a bike

11. the phone is more like a prosthesis…

12. the phone is part of
human anatomy,
and it is writing our
biography all the time

13. The phone has changed
both the human body and the human environment

14. ❖ DIGITALLY RECORDED KNOWLEDGE:
❖ 2000: 25% ———> 2013: 98%
❖ In 2013, 98% of information recorded by humans was in
digital format; in the year 2000 it was 25% - Martin
Hilbert, quoted by Victor Mayer-Schönberger and
Kenneth Cukier in BIG DATA 2013

15. The recording machine

16. The mobilizing machine

17. Our obligations towards other people enhanced by recording machines? or…
“Mobilisation totale” is…

18. … our obligations towards a human-machine-system that is too big to know?
“Mobilisation totale” is…

19. A robot suitcase which
follows you is made by the
Israeli startup NUA Robotics.
It is full of sensors, computer
vision and robotics

20. Teslasuit is a virtual reality
device for full immersion
experiences

21. Mercedes concept vehicle with drones on top

22. http://time.com/4398196/dallas-shooting-bomb-robot/
who is shooting?

23. http://blog.debiase.com/2016/07/01/fatal-error-il-primo-incidente-mortale-di-una-tesla-
mentre-era-senza-pilota/
who is driving?

24. who is writing?

25. Facebook’s experiment

26. We show, via a massive (N = 689,003) experiment on Facebook, that emotional states can
be transferred to others via emotional contagion, leading people to experience the same
emotions without their awareness. We provide experimental evidence that emotional
contagion occurs without direct interaction between people (exposure to a friend
expressing an emotion is sufficient), and in the complete absence of nonverbal cues.
http://www.pnas.org/content/111/24/8788.full
“Experimental evidence of massive-scale emotional
contagion through social networks”

27. so who is writing?

28. ❖ persuasive interfaces
❖ secret algorithms
❖ unequal control of data

29. B.J. Fogg’s model
Technologies
can be persuasive

30. Designer’s and users’ values
are embedded in the platform

31. Mind and mobilisation
❖ Computer is a bike for the mind: it supports human
rational abilities augmenting and speeding them
❖ Computer is a bike for the mind: it changes human
strategies for memorization
❖ Computer is a bike for the mind: it is a medium for
managing and enhancing human relational habits

32. Interface and mobilisation
❖ Human-Computer interface can be a very persuasive
technology
❖ All computer enhanced activities are fully recorded with
linear and complex consequences
❖ All complex activities generate big data and can only be
managed by algorithms and machine learning

33. Algorithm and mobilisation
❖ Algorithms which we hardly understand
❖ Algorithms which we are hardly aware of
❖ Algorithms which are often kept secret

34. Mind and mobilisation
❖ Mobilisation happens when recording becomes
documenting thus generating social obligations…
❖ In the meanwhile, recording is being linked to machine
learning and algorithms which are making choices that
most humans don’t understand or are not aware of…
❖ Thus, humans who don’t know and don’t understand
are letting something else write their autobiography?

35. Frank Pasquale
The Black Box
Society
The Secret Algorithms that Control
Money and Information
Catherine Taylor story. ChoicePoint
makes a mistake, Catherine doesn’t find
a job and a house anymore…
http://blog.debiase.com/2016/10/08/
lasimmetria-della-trasparenza-la-realta-
autoritaria-dellingiustizia-informativa/

36. Cathy O’Neil
Weapons of Math
Destruction
How Big Data increases inequality and threatens democracy
We live in the age of the algorithm. Increasingly, the decisions that affect
our lives—where we go to school, whether we get a car loan, how much
we pay for health insurance—are being made not by humans, but by
mathematical models. In theory, this should lead to greater fairness:
Everyone is judged according to the same rules, and bias is eliminated.
But as Cathy O’Neil reveals in this shocking book, the opposite is true.
The models being used today are opaque, unregulated, and
uncontestable, even when they’re wrong. Most troubling, they reinforce
discrimination: If a poor student can’t get a loan because a lending
model deems him too risky (by virtue of his race or neighborhood), he’s
then cut off from the kind of education that could pull him out of
poverty, and a vicious spiral ensues. Models are propping up the lucky
and punishing the downtrodden, creating a “toxic cocktail for
democracy.” Welcome to the dark side of Big Data.
http://www.goodreads.com/book/show/28186015-weapons-of-math-destruction

37. BREAKING THE BLACK BOX
What Facebook Knows
About Youby Julia Angwin, Terry Parris Jr. and Surya Mattu, ProPublica
September 28, 2016
https://www.propublica.org/article/breaking-the-black-box-what-facebook-knows-about-you

38. WE LIVE IN AN ERA of increasing automation. Machines help us not only with manual labor but also with intellectual
tasks, such as curating the news we read and calculating the best driving directions.
But as machines make more decisions for us, it is increasingly important to understand the algorithms that produce their judgments.We’ve
spent the year investigating algorithms, from how they’ve been used to predict future criminals to Amazon’s use of them to advantage itself
over competitors.
All too often, these algorithms are a black box: It’s impossible for outsiders to know what’s going inside them. Our first stop:
Facebook and your personal data.
https://www.propublica.org/article/breaking-the-black-box-what-facebook-knows-about-you

39. BREAKING THE BLACK BOX
When Algorithms Decide What
You Payby Julia Angwin, Terry Parris Jr. and Surya Mattu, ProPublica
October 5, 2016
https://www.propublica.org/article/breaking-the-black-box-when-algorithms-decide-what-
you-pay

40. Every website you visit is created, literally, the moment you arrive. Each element of the page — the pictures, the ads,
the text, the comments — live on computers in different places and are sent to your device when you request them.
That means that it’s easy for companies to create different web pages for different people. Sometimes that customization is helpful, such as
when you see search results for restaurants near you. Sometimes it can be creepy, such as when ads follow you around from website to
website. And sometimes customization can cost you money, research has shown. Orbitz showed higher-priced hotels to owners of Mac
computers, for instance. Staples offered the same products at higher prices to people living in certain ZIP codes.
Last year, we found that The Princeton Review was charging different prices for its online SAT tutoring course in different ZIP codes.
In some ZIP codes, the course cost $6,600; in others that same course was offered for as much as $8,400.
https://www.propublica.org/article/breaking-the-black-box-when-algorithms-decide-what-
you-pay

41. Frank Pasquale
The Black Box
Society
Designers values are embedded in
algorithms
- racial bias
- mistaken data
- fraudolent misinformation
We feed databases with data that are
secretly processed by unknown
algorithms to generate autobiographies
which we didn’t write

42. There is a problem
❖ Persuasive interfaces, secret algorithms, unequal control
of data shape the eco-cultural niches in which humans
and machines co-evolve
❖ The shaping happens accordingly with the values
embedded in the design and development of the
platforms

43. Mind and mobilisation
❖ In eco-cultural niches humans and machines co-evolve
❖ Mobilization happens according to that co-evolution
❖ Designer values, users’ knowledge, cultural context are
embedded in the emerging system, which then shapes
individual and collective stories

44. of course, we need to questions this
in order to write our own autobiography

45. ❖ Jacques Le Goff, Saint Louis: biography is written by
looking into documents which mirror the values of
those that have collected or recorded the data.
❖ The idea of individual person has a history. And its
biography is also the story of shared models about
humanity or human role in history.

46. ❖ An autobiography is about facts of a life, generated by a
body, in an environment
❖ Both context and content develop in the eco-cultural
niche in which the human-machine “system” evolves
❖ Default decisions happen in relation with the functioning of the body and the environment, and since both of
them are shaped by the change introduced by digital technology, the design of these generates action
❖ Present action has consequences over the next set of
technological decisions

47. Shift happens
❖ Big data
❖ Robotics
❖ Nanotechnology
❖ Biotechnology
❖ Neuro-science
❖ Particle physics
❖ Additive production
❖ Artificial intelligence
❖ Collective intelligence
❖ Sharing economy
❖ Climate change
❖ Space exploration
❖ Startups
❖ Bitcoin

48. –The Economist
“Economics is the science that studies why
its predictions didn’t work”.

49. –Institute for the Future
“There are no facts in the future, only narratives”

50. Narratives
❖ Finance
❖ Technology
❖ Ecology

51. Narratives
Finance
The only judge is profit. If humans cost
more than robots they will be replaced
by robots. If a starup is better financed
wins over a better startup. The rest is
secondary.

52. Narratives
Tecnology
What works wins. Every winning
technology beats everything else. Every
new version is better than the previous.
Exponential laws help understand that
technological progress is inevitable.
Resistance is futile.

53. Narratives
Ecology
Everything is linked to everything else.
Phenomena co-evolve. Regularities
emerge in a complex system. The more
biodiversity the better the ecosystem.
Sustainability is environmental, social
and cultural. Every growth has a limit.
Every mutation needs its eco-cultural
niche.

54. Media ecology, narratives, embedded values…

55. Knowledge sets us free
❖ If we know the power of interfaces, algorithms and
complex systems…
❖ … then we understand how we co-evolve in our eco-
cultural niches with our machines
❖ Consequence? Adaptation. Maybe acceptance of our
being plural. In a reality emerging in a system that
innovators are able to reveal. But while they do so, they
also embed their values in their revealing forms…

56. Civic media
❖ Social media help people meet other people they like
❖ People need to meet also people they don’t necessarily
like, when they have something to do together
❖ “Civic media” need to be designed in order to meet that
need
❖ “Civic media” can be the next big thing