On the material level, human biochemistry-based learning is fundamentally different from machine learning taking place on silicon-based transistors.
On
the
material
level
''
human
biochemistry
-
based
learning
is
fundamentally
different
from
machine
learning
taking
place
on
silicon
-
based
transistors
.
![]()
A human-machine peer learning curriculum (i.e., a HMPL-C) is a planned sequence of educational instructions–i.e., a curriculum–which involves:
1. At least one human learner G, H, I, ... which gradually develops her/his/their skill Γ.
2. At least one artificial learner a, b, c, ... which gradually develops its/her/his/their skill σ.
3. Activities by means of which G (resp. H, I, etc.) develops her/his/their skill Γ, which directly involve knowledge and competence exhibited by a (resp. b, c, etc.).
4. Activities by means of which a (resp. b, c, etc.) develops her/his/their skill σ, which directly involve knowledge and competence exhibited by G (resp. H, I, etc.).
1162
A
human
-
machine
peer
learning
curriculum
(
i
.
e
.''
a
HMPL
-
C
)
is
a
planned
sequence
of
educational
instructions
–
i
.
e
.''
a
curriculum
–
which
involves
:<
br
>
1
.
At
least
one
human
learner
G
''
H
''
I
''
...
which
gradually
develops
her
/
his
/
their
skill
Γ
.<
br
>
2
.
At
least
one
artificial
learner
a
''
b
''
c
''
...
which
gradually
develops
its
/
her
/
his
/
their
skill
σ
.<
br
>
3
.
Activities
by
means
of
which
G
(
resp
.
H
''
I
''
etc
.)
develops
her
/
his
/
their
skill
Γ
''
which
directly
involve
knowledge
and
competence
exhibited
by
a
(
resp
.
b
''
c
''
etc
.).<
br
>
4
.
Activities
by
means
of
which
a
(
resp
.
b
''
c
''
etc
.)
develops
her
/
his
/
their
skill
σ
''
which
directly
involve
knowledge
and
competence
exhibited
by
G
(
resp
.
H
''
I
''
etc
.).<
br
>
![]()
In this Boardroom Dialogue we will discuss the possibility of humans and AIs becoming "peers" in helping each other to acquire skills and competences.
The dialogue will start with introducing the concept of Human-Machine Peer Learning (HMPL) and exploring its potential to provide a paradigm for constructing human-machine learning curricula from which both humans as well as machines benefit.
Participants will acquire both the theoretical concept of human-machine peer learning and concrete insights into how HMPL is implemented through the illustration of two prototypical learning scenarios where HMPL is already deployed.
1155
<
div
>
In
this
Boardroom
Dialogue
we
will
discuss
the
possibility
of
humans
and
AIs
becoming
„
peers
“
in
helping
each
other
to
acquire
skills
and
competences
.
div
><
div
><
br
>
div
><
div
>
The
dialogue
will
start
with
introducing
the
concept
of
Human
-
Machine
Peer
Learning
(
HMPL
)
and
exploring
its
potential
to
provide
a
paradigm
for
constructing
human
-
machine
learning
curricula
from
which
both
humans
as
well
as
machines
benefit
.
div
><
div
><
br
>
div
><
div
>
Participants
will
acquire
both
the
theoretical
concept
of
human
-
machine
peer
learning
and
concrete
insights
into
how
HMPL
is
implemented
through
the
illustration
of
two
prototypical
learning
scenarios
where
HMPL
is
already
deployed
![]()
"obsessed" by human-robot relations from early childhood onwards (hello Johny 5!)
Čapek, Asimov, Turing, Cyberpunk ...
since beginning of my academic life I try to transpose main elements of ontogeny of human intelligence into computational domain (Master: Facial expression recognition; PhD: Computational models of language acquisition)
2011 Paper "Central Problem of Roboethics: from defintion towards solution" provides a potential solution to what AI folks label these days as "Alignment problem"
the solution is: To raise machines as we raise our (own) children.
one of the last pieces of puzzles is "peer learning"
1168
<
p
class
=
„
fragment
“
>
„
obsessed
“
by
human
-
robot
relations
from
early
childhood
onwards
(
hello
Johny
5
!)
p
><
p
class
=
„
fragment
“
>
Čapek
''
Asimov
''
Turing
''
Cyberpunk
...
p
><
p
class
=
„
fragment
“
>
since
beginning
of
my
academic
life
I
try
to
transpose
main
elements
of
ontogeny
of
human
intelligence
into
computational
domain
(
Master
:
Facial
expression
recognition
;
PhD
:
Computational
models
of
language
acquisition
)
p
><
p
class
=
„
fragment
“
>
2011
Paper
„
Central
Problem
of
Roboethics
:
from
defintion
towards
solution
“
provides
a
potential
solution
to
what
AI
folks
label
these
days
as
„
Alignment
problem
“
p
><
p
class
=
„
fragment
“
>
the
solution
is
:
To
raise
machines
as
we
raise
our
(
own
)
children
.
p
><
p
class
=
„
fragment
“
>
one
of
the
last
pieces
of
puzzles
is
„
peer
learning
“
![]()
To prepare for the discussion which will ensue, please think about the role which machines, AIs - and associated concepts, myths and archetypes - played (until this day) in Your own personal narrative.
1169
To
prepare
for
the
discussion
which
will
ensue
''
please
think
about
the
role
which
machines
''
AIs
-
and
associated
concepts
''
myths
and
archetypes
-
played
(
until
this
day
)
in
Your
own
personal
narrative
.
![]()
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