Digitalization (learning : powerpoints and articles)
FOLLOW THE PROGRAMME
Stef Aupers : Digitalization and the challenge of AI
Definition : Digitalization is a process. It is the spread of digital media
and effect on individuals and society.
Three waves of digitalization :
- Personal computer
- Internet and social media
- AI : in everyday life it is an issue. How should we understand AI???
1) Personal computer
The way computers looked like in the 1950s. We can do all our
calculations with ten of them.
1960 and 1970 : we have seen that things changed. Hackers knew how
technology work. GOAL : BRINGING COMPUTER POWER TO THE PEOPLE :
we can do everything what we want with a computer so people need
them.
1975 : the first personal computer (APPLE) made by Steve Jobs and Steve
Wozniack. These two and Bill Gates were all part of the movement who
wanted to bring computer to the people.
1975-1985 : the development, mass-production and commercialization of
the PC.
Only the pc made it possible to end up with the second wave
2) internet and social media
The internet is an ecological system that existed long before the 90s.
Everything we can do on internet is because of the pc. Technology brings
us the future.
Web 1.0 : 1990s : interconnected PC’s
Web 2.0 : 2000s : social media platforms and User Generated Content
(UGC)
2008 : the person of the year were you because you can connect on social
media platforms with everybody.
Mark Zuckerberg : Facebook „Making the world more open and
connected”.
3) Artificial intelligence
Recent phenomenon in everyday life.
1
,John McCarthy and Marvin Minsky organised a conference in 1955 with
30 people about computer technology. They wanted to make a machine
behave in ways that would be called intelligent if a human were so
behaving.
Basic forms of AI :
- Weak AI : AI that imitate our cognitive functions. The computer
imitate just one function in our brain. AI with one function !
- Strong AI : create sentences, make art, play music,… AI does what
we as human also do.
- Top down AI : it was a programme that was instructed : how to deal
in a situation. The computers does what it was instructed. “if you
see something moving, shoot!”. There is no interpretation.
- Bottom Up AI : self-learning computer, it is evolutionary computer.
Ai involved a lot of philosophical questions. When can we say that the
intelligence of the computer is real? When can we say the pc is just like
us.
Alan Turning : The Turing Test : how can AI be intelligent like humans.
The test Participants: The test involves three participants:
A human evaluator (or judge).
A human participant.
A machine (the system being tested for intelligence)
If after 8 minutes you don’t know you talking against a pc or a human, it
means that you are solved. Humans are also machines, we think we are
very special, but our brain is also a software.
John Searle : The Chinese room experiment he wants to explain that
machines can never be intelligent. It was a close room, outside the room
you can have somebody that giving us all the Chinese words and let us
write it. On the output there is a Chinese figure his conclusion : the guy
in the room has instructions but doesn’t know anything about the
meaning.
Scenario: Imagine a person who does not understand Chinese sitting in a
closed room. This person is provided with:
A set of instructions (a rulebook) written in their native language.
A collection of Chinese characters (symbols) that they cannot read
or understand.
An input/output mechanism to receive and send messages in
Chinese.
Process:
2
, Outside the room, a Chinese-speaking individual sends written
messages in Chinese into the room.
Using the rulebook, the person inside matches the Chinese symbols
from the input with specific instructions on how to form a valid
Chinese response.
The person outputs the response without understanding the content
of either the input or the response.
Outcome:
To the outside observer, it seems as though the person in the room
understands Chinese because the responses are accurate and
coherent.
However, the person inside the room is simply following rules and
manipulating symbols, with no actual understanding of Chinese.
So :
Turning : If a computer can talk like humans for 8 minutes it is
intelligence
Searle : A computer is not intelligent it can do intelligent things
A third person in this debate : Kevin Warwick
The previous two are both wrong because they think about intelligence
which is only reserved for humans. Why do we think that only humans can
be intelligent? He says : there is more than human intelligence, don’t
forget animals,… we should not think in intelligence of humans, there are
many other types of intelligence.
Beyond philosophy of AI…
We are outsourcing human cognitive to AI. AI is now very much with us, it
is no longer philosophy. Ai is also tracking to find out some things about
humans. The government can use this info by example tracking terrorist
on WhatsApp. We are communication with AI, chatbots, social robots.
AI challenges for the social sciences
- Traditional view : Humans communicate with humans through a
medium ( film, radio, internet, social media)
- Ai challenge : humans no longer communicate through the media
but also with the media.
Bruno Latour : his argument is that sociology is how humans form
networks with others, we are social animals. Actor-Network Theory :
objects are actants and have, just like human actors, influence on humans,
social relations, organisations and other things. The internet of things, the
smartphone ‘talks’ to television, vacuum cleaner,…
3
FOLLOW THE PROGRAMME
Stef Aupers : Digitalization and the challenge of AI
Definition : Digitalization is a process. It is the spread of digital media
and effect on individuals and society.
Three waves of digitalization :
- Personal computer
- Internet and social media
- AI : in everyday life it is an issue. How should we understand AI???
1) Personal computer
The way computers looked like in the 1950s. We can do all our
calculations with ten of them.
1960 and 1970 : we have seen that things changed. Hackers knew how
technology work. GOAL : BRINGING COMPUTER POWER TO THE PEOPLE :
we can do everything what we want with a computer so people need
them.
1975 : the first personal computer (APPLE) made by Steve Jobs and Steve
Wozniack. These two and Bill Gates were all part of the movement who
wanted to bring computer to the people.
1975-1985 : the development, mass-production and commercialization of
the PC.
Only the pc made it possible to end up with the second wave
2) internet and social media
The internet is an ecological system that existed long before the 90s.
Everything we can do on internet is because of the pc. Technology brings
us the future.
Web 1.0 : 1990s : interconnected PC’s
Web 2.0 : 2000s : social media platforms and User Generated Content
(UGC)
2008 : the person of the year were you because you can connect on social
media platforms with everybody.
Mark Zuckerberg : Facebook „Making the world more open and
connected”.
3) Artificial intelligence
Recent phenomenon in everyday life.
1
,John McCarthy and Marvin Minsky organised a conference in 1955 with
30 people about computer technology. They wanted to make a machine
behave in ways that would be called intelligent if a human were so
behaving.
Basic forms of AI :
- Weak AI : AI that imitate our cognitive functions. The computer
imitate just one function in our brain. AI with one function !
- Strong AI : create sentences, make art, play music,… AI does what
we as human also do.
- Top down AI : it was a programme that was instructed : how to deal
in a situation. The computers does what it was instructed. “if you
see something moving, shoot!”. There is no interpretation.
- Bottom Up AI : self-learning computer, it is evolutionary computer.
Ai involved a lot of philosophical questions. When can we say that the
intelligence of the computer is real? When can we say the pc is just like
us.
Alan Turning : The Turing Test : how can AI be intelligent like humans.
The test Participants: The test involves three participants:
A human evaluator (or judge).
A human participant.
A machine (the system being tested for intelligence)
If after 8 minutes you don’t know you talking against a pc or a human, it
means that you are solved. Humans are also machines, we think we are
very special, but our brain is also a software.
John Searle : The Chinese room experiment he wants to explain that
machines can never be intelligent. It was a close room, outside the room
you can have somebody that giving us all the Chinese words and let us
write it. On the output there is a Chinese figure his conclusion : the guy
in the room has instructions but doesn’t know anything about the
meaning.
Scenario: Imagine a person who does not understand Chinese sitting in a
closed room. This person is provided with:
A set of instructions (a rulebook) written in their native language.
A collection of Chinese characters (symbols) that they cannot read
or understand.
An input/output mechanism to receive and send messages in
Chinese.
Process:
2
, Outside the room, a Chinese-speaking individual sends written
messages in Chinese into the room.
Using the rulebook, the person inside matches the Chinese symbols
from the input with specific instructions on how to form a valid
Chinese response.
The person outputs the response without understanding the content
of either the input or the response.
Outcome:
To the outside observer, it seems as though the person in the room
understands Chinese because the responses are accurate and
coherent.
However, the person inside the room is simply following rules and
manipulating symbols, with no actual understanding of Chinese.
So :
Turning : If a computer can talk like humans for 8 minutes it is
intelligence
Searle : A computer is not intelligent it can do intelligent things
A third person in this debate : Kevin Warwick
The previous two are both wrong because they think about intelligence
which is only reserved for humans. Why do we think that only humans can
be intelligent? He says : there is more than human intelligence, don’t
forget animals,… we should not think in intelligence of humans, there are
many other types of intelligence.
Beyond philosophy of AI…
We are outsourcing human cognitive to AI. AI is now very much with us, it
is no longer philosophy. Ai is also tracking to find out some things about
humans. The government can use this info by example tracking terrorist
on WhatsApp. We are communication with AI, chatbots, social robots.
AI challenges for the social sciences
- Traditional view : Humans communicate with humans through a
medium ( film, radio, internet, social media)
- Ai challenge : humans no longer communicate through the media
but also with the media.
Bruno Latour : his argument is that sociology is how humans form
networks with others, we are social animals. Actor-Network Theory :
objects are actants and have, just like human actors, influence on humans,
social relations, organisations and other things. The internet of things, the
smartphone ‘talks’ to television, vacuum cleaner,…
3
