261. Is Power Seeking AI an Existential Threat

hello and welcome to session 261 in the
AI safety.com reading group tonight we
will be discussing is power seeking AI
an existential Risk by Joseph Carl Smith
Joseph Carl Smith is a senior research
analyst at open philanthropy and this is
was posted this report in April of 2021
but had a somewhat substantial update in
May 2022 or at least to the conclusion
now today we are only going to discuss
the optimistic Parts meaning that when
uh when Joseph describes his
probabilities we're gonna see uh look
into the arguments of why he doesn't put
a higher probability of an existential
threat and not the arguments for why it
is at least non-natural
this means in practice we'll be just
focusing on Section 6.4 and section 8.
now the paper is as I read it mostly
structured as to argue with someone who
does not believe in AI risk and argue
towards these while there is a not
insubstantial risk of an existential
catastrophe from
um from Advanced AI that means that I
have uh reformulated quite a bit of the
claims uh to to pull out the optimistic
Parts
um and of course when when I do that
there's a stronger risk that I have made
more errors also a substantial part of
the paper is uh like focusing on whether
power seeking is a good abstraction for
these and that's also not something
we're going to quite much into today
um one of the funny reasons why I
thought this was
um an interesting paper was that the fgx
future fund claimed that this paper was
Central to their relative optimism about
Ai and they offered in fact millions of
dollars if someone could convince them
that
um the the state the state of the world
was worse than what was described in
this paper
um I for the record I don't think anyone
would have won that price because in
general convincing people is really
really hard and I don't think that would
have been possible in any meaningful way
let's talk about Advanced power seeking
system uh which is Joseph cosmith's uh
uh abstraction and uh concept Advanced
capabilities are defined as a scientific
research engineering strategy hacking
and social manipulation so capabilities
uh above the human level and this this
is extremely close to uh what Nick
Bostrom uses uh talks about the
cognitive superpowers in the book super
intelligence from 2014
it is also close to my definition of AGI
in that uh I believe that AGI is
basically an AI That's capable of doing
these tasks and one more the one that is
missing is intelligence amplification
The crucial effect of
um if an AI is capable of improving ai's
uh in particular AI is similar to itself
so that it can perform an uh
intelligence explosion recursive
Improvement that kind of thing this is
missing from Joseph Carl Smith's
definition you could perhaps put it
under like either engineering or
scientific research but I think this is
a really really crucial fact and one
that should be
um be at the Forefront
Advanced power steering system has two
more requirements first is might be must
be able to do identity planning and it
must have some kind of strategic
awareness
and Joseph talks about why this uh is a
good strategy and a good concept I won't
go too much into this
I will add some comments to his
definitions on takeoff
he distinguishes between several kinds
first is a fast takeoff the ones that
where the transition from a relatively
high level of AI capability to a much
higher and much more dangerous uh level
takes relatively little time
he doesn't specify it as much as
busstrom so in particular for
operationalization purposes the thing I
think about is is it possible in
practice for us to react to a fast
takeoff
in this this continuous takeoff which is
defined as a transition that is faster
than some historical extrapolation
I dislike using the word this continues
for that
um this continues it functions is a
mathematical concept and a jump
discontinuity is if a in a particular
point there is a different limit from
the left and uh from the right and
that's very different from being like
faster than some historical
extrapolation
um I think what they are talking about
more seem to be differentiable uh
takeoff like if the curve suddenly has a
a kink or something upwards a sharp left
turn or something like that
uh also another reason why I dislike
this definition is some historical
extrapolation that is extremely vague
like you can take just about any uh any
uh event and uh you if you look uh uh
through enough history books and
statistics then you can say this is
totally in line with
um with X with uh historical uh Trends
even if you were totally unable to
predict anything
there's a concentrated takeoff and
intelligence explosion and recursive
self-improvement as three other kinds
and features of
um
of takeoffs I won't go much into this
detail uh but
um as an example to show where I think
Joseph cosmith is confused is in his
claim that we could see fast but not
discontinuous takeoff
um so that's a really interesting claim
if you imagine that you have a takeoff
that takes like an hour or so what kind
of historical Trend could you
extrapolate for that would that be
possible uh well I think you could in
fact
um extrapolate like you could say like
LJ bloom or something uh I don't know uh
fishing in nuclear weapons or something
like that you can probably always find
some kind of extra historical
extrapolation I'm sure AI impact would
be able to find something
um but the point is that it does not
really constrain what our expectations
for the future are
Joseph Carl Smith uh does not assume we
will get any uh takeoff and I think the
reason he does that is as a defensive
argument because he's mostly arguing
with someone who is more optimistic
um but he also doesn't present any
arguments against these as for at least
as fast I could find
Joseph Carl Smith uh produces a number
of mechanisms for takeover uh there are
these 12
and he goes through them all with
um and mostly argues that this is a real
thing that could happen but he also for
each of them gives reasons why they may
not be as powerful as you might expect
so and any given AI may not have all
these 12 mechanisms available
unfortunately the way I see it he
doesn't have any strong arguments uh on
the order of being able to argue that
any of them are impossible or even even
are likely just that there are
constraints such as like all
infrastructure may not be automated in
2017 which is true but there might still
be quite a lot that is in fact also
maintenance
um
so the the way I interpret his uh text
is that
for any given AI there are likely to be
some kind of uh constraints on on all of
these
um and from that he concludes that AI
takeover is likely going to be hard I
don't think that is
um uh first I should that this is a
place where I'm going I'm straying
somewhat from the text
um so this is my interpretation and the
way I see the limitations that Joe
cosmiths place on this all these are
really uh
um uh
weak and if an AI have all these 12
opportunities then that if they're like
mostly disjunctive
um then it seems like an AI takeover
cannot be uh ruled out based on the uh
the rather weak arguments your cosmith
is providing
um
power seeking is not something that
happens in a vacuum but it's something
that we expect there to be some kind of
competition
um there's a description about whether
this will be a unipolar scenario or a
multipolar scenario it's kind of written
as if it's an answer to Bostrom but I
think this is something that is well
covered in postrooms book
superintelligence
so if we assume one that AIS Drive most
of the scientific technological and
economic growth and also that the AIS
are misaligned and power seeking given
these two things Joseph cosmith
concludes that our Precision is genius I
think that is way too optimistic I think
our position if AIS are doing most of
the real things in the world and they
are misaligned and power seeking then
humanity is almost certainly doomed we
have a really poor situation because the
AIS just need to coordinate and that
doesn't seem very hard once you get past
a certain power level
this competition uh could still
um be in our favor uh we have we have
defenses against AI power seeking uh
some of them are like non-ai like
standard computer security and what have
we
um these seem unfortunately to be
improving much less rapidly than AI is
improving right now
um
we may also have better AIS at our
defense
um
depending on to what extent we can solve
the alignment problem uh we this may be
a solution but we're not pursuing it
strongly
um the current trends in my view is
rather bad
another argument Joseph Carl Smith
presents is that we shouldn't assume
that the AI is arbitrarily capable and I
don't think that the arguments for AI
Doom really require that they just
require that the AI is substantially
more powerful more intelligent more
capable than humans
a substantial part of the reason for
optimism is the concept of warning shots
which are defined as small unintended
power seeking by an AI
um
and of course Joseph cosmet believes
they are more likely than I do
um and I think the key thing is that if
you have enough strategic awareness to
try to seek power seek I know external
funding or something like that
um then you are almost certainly also
aware that if this is caught then the AI
will get shut down with prejudice and
will never be uh turned on again so
there is no point in trying to make
small kinds of Power seeking either you
go for
um go for a full Coupe or you don't go
there's some discussion about what kind
of power seeking weaker system would
like to do and again they are more
likely to get get
um uh caught and I agree of course
weaker systems are more likely to get
caught but I don't really think that is
something that needs to be discussed
very much the big thing to be uh that we
need to talk about is what is the
probability that these AIS will try to
do power seeking and try to take over
that is the thing that I think the
report should focus on rather than the
probability that this will fail
there's another sentence here we may
well devote a lot of the energy to try
to trigger misaligned power seeking I'm
not entirely sure what the energy really
uh refers to I think uh I think Joseph
cosmith may be saying that we may be
using uh like a lot of the world's GDP
or something like that uh for uh for
trying to figure out if AIS are
deceptively aligned
um but right now we are really really
not using a lot of the world's GDP for
this and I think we're missing some kind
of argument why this would change
uh and then yeah Joseph cosmith of
course talks about this in why this is
not going to be a fire alarm uh and I
appreciate his uh discussion the the key
thing that is missing is some kind of
explicit argument for why this uh
unintended policy king would be uh
common
once we have this unintended policying
the thing uh just customer expects is
Corrections uh so we assume here that a
lot of I think in Joseph cosmith's view
there are a lot of AIS that are deployed
all over the world and some of them
attempt to seize power and humans notice
that it's trying to do that and so we
pretend them from doing so and that is a
correction
um I think the key thing that is missing
from this definition of Correction is
that humans react in some way
you could imagine that uh an AI tries to
uh you know obtain a resource on the
internet that is not supposed to be able
to and a firewall
um blocks it
um that is a correction according to
this but even if humans don't actually
realize that something has changed so in
my view for something to be a correction
then humans need to do something that
prevents this in the future either by
unplugging a network cable or something
like that all at a higher level like
reconsidering whether the design of this
AI is good
uh and I think Corrections without uh an
explicit A corrective step by the humans
is some other misleading name
um and uh Joseph cosmith is optimistic
that we will be able to do these kind of
Corrections uh it's not guaranteed but I
think he's very optimistic
um I would be a lot less optimistic in
the uh with the assumption that this
strategically aware AI is
um believes it is capable of taking over
because if it believes that it is
capable of taking over then uh there's a
probability that it's right in
particular if it has more strategic
awareness than us
Joseph cosmith hopes we can get into
some kind of corrective feedback loop
where we get a an escalating series of
alignment failures
um that will trigger more and more
powerful corrective actions
um
that is uh uh or in particular updating
researcher beliefs incentives and
constraints
um I'm unfortunately less optimistic I
think morning shots are unlikely and
even if we get a one uh warning shot
then having a sufficient higher level
correction is going to be really really
hard I don't think that you can actually
expect the research incentives to change
very much based on this
um but I would be happy to be surprised
in particular Joseph Cosman suggests
that if we get sufficiently higher
impact accidents than we may globally
just ban AI
I the the word sufficient is uh of
course makes this a tautology so this is
true by definition
um but I think in order to for us to
globally ban AI then it needs to be
really really obvious that it was very
very close that we were disempowered and
in that case of course the the we won't
see that unless there is a like a real
risk
um and even if we do see a real risk
then Global bands just seems from a
political point of view to be really
really hard I don't expect that we'll be
able to globally coordinate to ban
something like AI especially if it's
well incentivized
um Joseph cosmith uh does uh agree with
uh many of the these points he is uh it
doesn't he
he is not that optimistic about
corrective feedback loops uh and that's
of course a big part of the paper
um but I think centrally the reason why
we won't be able to do these corrective
feedback loops is that the corrective
action is solving the alignment problem
and we don't know how to solve the
alignment problem so that is why we will
be unable to solve the alignment problem
when when the time comes
now for chapter 8 probabilities
so before we start uh Joseph cosmith has
a number of caveats
um one is that like hold the number
slightly and don't over update too much
of them and of course I can't do that
it's just impossible for humans to not
uh Focus too much on when whether he
says 35 or 30
um
and conjunctions uh have a known problem
uh like it's sometimes called the
multi-stage fallacy
um like if you have a a chain of
conjunctions then like first a and then
given a then B happens and given a and b
then C happens
um in that case updating hard enough on
the previous uh uh evidence is really
really hard because you're often
updating on things that like your models
are totally wrong for instance that kind
of statement can be really hard to
update on
um
also if there are many stages then uh
people often find it really hard in to
assign any particular claim a very high
probability and so if you add enough
stages then you can drive the
probability arbitrarily far down
and of course this uh
it's very possible that that you could
have a
um a claim that ends up being true even
if all the premises are are false uh so
there may be other ways to have an
existential catastrophe than the one
sketched out in
um Joseph cosmith's argument here
and
um Joseph cosmith describes this in
substantial details how he tries to get
around his biases and what they are and
I think it's this is a really good
section and I strongly encourage you to
read that because I think it's uh
original and admirable that it does work
hard on this
so the first claim it won't be both
possible and financially uh feasible to
build a advanced planning system
so uh this is uh
there would be a I think that would
avert an AI catastrophe if it turns out
that it's not possible to have like
either one of advanced capability
against
planning or strategic awareness
there is a limit a time limit on 2017
here and his probability are based on
his own forecast and Open Fields work
against a cultures centrally and puts a
35 probability that we will not be able
to have AGI by 2017.
um I think this is pretty long timelines
a lot of people have much shorter
timelines
um and um
for these three
um Advanced capabilities how close are
we to have any of these five uh it's of
course an interesting question and no
one knows but it seems like economic
productivity and like writing computer
code or things like that are not that
far away eccentric planning also seems
hard but not like 50 years away and
strategic awareness depending on what
questions you put into gbt3
um you may easily get something that
shows quite a bit of strategic awareness
um
so and also I don't really like the the
year 2017 very much because if we get an
existential catastrophe in 2071 then
that is also bad
um the thing that to me would
um put a lower uh bound on this is
whether it will never be possible to
build AGI uh I I think that is an
interesting article I have like to seen
what your cars with what probability he
puts on that
um because a number of people believe
that it is impossible and I don't know
to what extent uh Joseph cosmith also
does
the next is even if uh we uh
built a know how to build Ai and it's
possible then there won't be any strong
incentives to build them
and this is a rather broad claim uh it's
I think uh we should specify in more
details that this means that there are
no tasks where we have strong incentives
to build abs systems for
um given of course that it's both
possible and feasible to build a
advanced planning power seeking system
and the claim why this why there won't
be these strong incentives is that many
tasks don't benefit from identities or
strategic awareness
um enough and this was what I was aiming
for before that
um uh
if there are no strong incentives that
it doesn't matter for this claim that
there are many tasks that don't benefit
the question is are there any important
tasks where there are strong incentives
to build and one's passing system
um Joseph cosmith puts a 20 on this and
I think that's way too high
one of the uh like uh if he says that
there are no tasks then I only need to
point out one and the one task that I
could uh easily see is running a
business because running a business is
something that is clearly important and
if you're running a business then having
high level of capability is really
helpful having strategic uh awareness is
really helpful and some kind of agentic
planning is also clearly clearly helpful
so I think
by construction there is one example
where there is in fact a strong
incentive to build these systems
another example would be to like just
read job adverts in so many job AdWords
uh they write something like it is uh
the um uh the person applying for this
job must be a self-starter and must be
able to keep the big picture in mind and
things like that there are so many
positions in the real world where this
really really matters so I think at 20
probability that there is no place in
the world where strategic awareness
matters and no place in the world where
being authentic matters I think that is
clearly dramatically overconfident
yeah I think
here is a part where you know when we
are I feel we're not updating enough on
uh the previous uh stage in uh where we
assumed that this was feasible because
if we assume that it's feasible to build
an engineer but that is
just more capable than an a standard
human engineer then
um how can you say that there is only a
20
probability that no one that there is
training probability that no one will
find this useful like uh people really
really obviously want something that can
do engineering or that can do scientific
research that seems uh the incentives to
me seem extremely strong
next claim it won't be much harder to
develop a line uh
um systems compared to just a
superficially attractive misaligned uh
Power seeking system
so this is basically
um the claim we will solve the alignment
problem
yeah and this is assumed that uh it is
in possible feasible and incentivized to
build these systems and uh Joseph
cosmith says that we have 50 years
that's a long time to make progress
um but 50 years remember that's an off
of a bound we may have uh much less time
and it seems unfortunately that we are
progressing slowly in alignment and
rapidly towards AGI
another reason for optimism is that um
we only need the systems to be
uh
sorry uh aligned in Practical situations
and not all situations
I don't unfortunately think that's going
to give us a lot of Hope because
describing the actual situations in a
compact way seems obviously impossible
and that means that we don't get a lot
more it's not a lot harder to make a
system that is aligned in all situations
compared to one that's aligned in all
practical situations
there are some suggestions for how we
could solve the alignment problem
including by limiting capabilities or
objectives or making it myopic and
having AI supervision and all these kind
of things
um I'm
very I'm not that pessimistic but more
pessimistic certainly than
um just cost me about this because a lot
of these are directly trading off like
if you limit the capabilities then then
almost certainly it will be harder to uh
to the to do this aligned compared to uh
to do something that's just
superficially uh aligned
so we want some kind of AI where the a
where the alignment text is lower
uh so the the final number uh for will
we be able to solve the alignment
problem is 60 I think that is Hope
hopelessly optimistic and this would be
a place where I have one of my greatest
disagreement with Joseph cosmith I don't
think at all it looks like we're on
track with 60 probability to solve the
alignment problem
so even if we assume that these passes
passing systems are possible feasible
incentivized and we can't align them
then will they able to uh be able to
seek power
um
the way uh
high impact is operationalized is by
saying that the AIS collectively cost
more than one trillion dollars of damage
I think this is a really bad
operationalization and that is because
we are looking at something like one
trillion dollars of damage uh as
something that is very unlikely to
happen
let me try to explain why
if you are trying to make a coupe in the
United States
then you can ask the question will a
coupe in the United States control
county level resources
um and that's a
um like obviously when a coupe is
starting they have like zero power and
then they go to complete power so at
some point in between they must have
like the same amount of power as a city
council somewhere in the United States
but that is really
um
the way you obtain power is not by
becoming major in Los Angeles or
something like that you if you want to
be to do a coupe in the United States
you need to go to the White House and
the senate in Washington DC and things
like that so
um because coops are very much all or
nothing and so this something that
damages more than one trillion but
doesn't take over entirely is very
unlikely in my view
um the way I would rather uh
operationalize this is by looking at the
probability of success like will a coup
at some point be considered five percent
likely to succeed that is something that
um
Cuts reality much more uh uh
shows more uh what a coup is likely
going to be
um
the the warning shots that we talked
about previously is something that
Joseph cosmith has a lot of Hope in he
believes that before we get to one
trillion we're going to see a lot of
warning shots
um and we may have built in some kind of
limitations to the AI that makes it
impossible for them to uh seek power in
these high impact ways and again here I
feel that Joseph cosmith is not updating
sufficiently on the previous
um on the previous stage because we have
just assumed that alignment is
practically infeasible and then we can't
use as an argument at this stage that
given that alignment is infeasible we
may still put in some limitations on the
air that means they can't hurt us in
this way because we've just assumed that
uh limiting the AI and still having it
competitive was not going to be possible
also relevant actors have strong
incentives to prevent uh a large amount
of Damages
um I I think this incentives like we can
see right now that the incentives are uh
insufficient and I expect that most
actors will remain oblivious in
particular in in shorter timelines
so
um Joseph cosmet puts 35 probability
here and I think that is a very uh
optimistic as well
so going from one trillion to
disempowering humanity how hard is that
well it's possible that the world gets
its act together at that point and that
that's the claim um uh and 60
probability is given for the fact that
if even if a coup is able to uh take
over one trillion dollars of resources
or destroying or something like that
then
um uh it seems here like uh the
assumption is that there is a uh an
event that causes one trillion dollars
in damage and then after that we stop it
somehow
um but that's not the uh this is why I
feel we're not cutting reality at the
joints because this makes us think of an
event that
um uh destroys one trillion dollars but
doesn't uh take over the world and I
think that is vanishingly unlikely and I
think in this particular way of
splitting up these stages uh gives a
very uh a very wrong intuition
and finally uh if humans are
disempowered will that be an existential
catastrophe
um five percent probability uh so almost
certainly it will be an existential
catastrophe uh and I think here we have
an example of where people are just
unwilling to put on very very high
probabilities because if there is a
treacherous turn and the treacherous
turn is successful will Humanity lose
our potential well by definition right
the AI has the goal to stop humans and
then it succeeds in its goals will
humans be stuffed well almost by
definition almost 100 sure like uh that
is um if it has disempowered humans then
almost certainly that is an existential
catastrophe we are looking at some
really really strange in edge cases
where this won't happen certainly not
anything like five percent
um and
um Joseph cosmith does not provide any
such examples so there are no arguments
that actually fit into this part and
that's why I believe that it's wrong to
separate it out into several stages if
there are no
um specific arguments
um for this stage
so in total Joseph cosmet is 95 Pro puts
95 per percent probability of a good
outcome in total
um but in May 2022 he updated that to
less than 90 probability of a good
outcome
I'm not really happy about having this
kind of halfway bounded estimates I
don't actually know what less than 90
means like 10 is also less than 90 but
presumably that's not what it means
um I it's also not clear what evidence
has caused him to uh change his mind I
would expect this is mostly timelines uh
it's possible of course that in a
alignment or something like that became
a bigger deal for him but I guess it's
mostly timelines again he doesn't say so
it's uh quite unclear unfortunately
that is all for today thank you and see
you next time


OUT OF CONTROL  - The design of AI in everyday life  (Elisa Giaccardi) - 1st AiTech Symposium

cute yes good afternoon what happens
when AI begins to operate in response to
everyday interactions with people
how can a AI systems remain trustworthy
once they begin to learn from us and
from each other these are really big
questions and they're the ones that
actually troubled me as a designer one
of the dominant narratives today about
AI is that it will help us be more
accurate in our decision-making
processes it will help us make better
diagnoses and keep us safe on the road
these narrative come with the assumption
that somehow we the humans are the real
black boxes and if we just design a time
where enough and we exert enough control
then AI will compensate for our human
flows and the mess we have created now
dystopian scenarios of black mirror
aside this that I call a smart utopia
and the design ideals of control and
optimization that come with it are
actually a bit at odds with the messy
reality of everyday life in a study on
the future of Taiwanese mobility that we
conducted in Taipei in collaboration
with Taiwan tech design ideas of fuel
efficiency and energy savings proved to
be at odds with how Taiwanese use
scooters in everyday life in this
picture for example you can see how the
scooter used at a low speed at the
street market is no longer a vehicle for
transportation really but a cart for
grocery shopping and at a different
speed and within a different
configuration of everyday life it
becomes a means for establishing and
maintaining social relationships now ok
that doesn't seem very critical does it
and it's easy to relegate this case to
matters of culturally sensitive design
the potential friction suggested by this
case between the intended
use of smart autonomous technology and
how it might actually end up being used
by people in the context of their lights
seems quite irrelevant when we think of
the design of an AI that can save us
from a drunk driver or the wrong medical
diagnosis so why not let AI in even more
spheres of our lives and use it to
optimize also our wealth all we need is
to buy a SmartWatch make sure that we
stay active and reduce our insurance
premium while maybe even gaining
additional benefits that's the value
proposition of a start-up company called
vitality in the UK now it gets to be it
gets to be a bit more serious because
what if I get sick or for whatever
reason I just can't exercise anymore not
as much will I still be able to afford
medical coverage and what to do this was
an example presented by Jani this
morning what do we do what if a badly
designed and yet already implemented AI
system fires an talented motivated
teacher just because the mathis cause of
her students are not good enough how do
we fix it when we consider their
complexity of these real-life scenarios
it is quite apparent that the need for
control is morally justified so I really
hope not to be misunderstood when I say
that control mechanisms and regulations
are necessary but not enough frameworks
promoting principles of control explain
ability and transparency are necessary
to ensure accountability after the fact
after something has been designed but
design has to regain its agency in the
crafting of desirable relationships with
technology between people and technology
it has to become anticipatory gain both
to address the legal issues but also not
to stifle innovation so but for the
field of design to move forward I'd like
to make a step back and I'd like to ask
what are the design ideas that are
actually as designed
were locked into an I argue that as
designers we are locked into the fallacy
that all we need to do is to get it
right the right functionality the right
feature the right interface right
algorithm the right user experience you
name it
but these comes from times when working
iteratively and getting it right
accurate precise was the best way to
minimizing the risk of mass replicating
faults and shortcomings it is very much
anchored in design ideas of mass
production contemporary natural
technologies artificial intelligence as
well as the platform capitalism that
have made pasta have made possible not
only differed from the logic of
industrial production they fundamentally
challenged the conceptual space that as
designers we have created to cope with
complexity with runtime assembly of
natural services constant atomic updates
and agile development processes the
design process is no longer something
that happens before production and then
it's done it continues in use in this
characteristic constant becoming is
going to be further accelerated by
technologies that operate in everyday
life and actively learn while e-news
changing and adapting over time at an
even more fundamental level than is
currently the case so the point that I'm
trying to make is that while we jumped
with both feet in the digital society
our way of thinking our design
frameworks and methodologies are still
locked into an industrial past and this
table shows some of the shifts needed to
move towards a truly post-industrial
design for example if we consider core
performance that is the core dependency
of people and I more than they're
supposed autonomy and the degrees of
autonomy is between the two then we
begin to ask very different types of
questions
the type of questions that hopefully
will hear also in the next presentations
when we talk about narratives and
counter narratives and the very
important idea of design trade-offs and
one question that we might begin to ask
is for example how can we empower humans
running them controlling machines in the
resourceful aging project which is a
project we conducted and concluded last
year and that received by the European
Commission I an internet ng a next
generation internet a word for better
digital life we address this question by
looking at how machine learning can be
used to support older people's natural
strategies of improvisation and
resourcefulness right in the monitoring
predicting and prescribing behavior the
motors are networked so that our
colleagues from computer science
oriented often be looked into for this
project were implemented to answer a
different set of questions and accuracy
of prediction they were concerned with
the core usage and variety of
appropriation that latitude at which
older people who could use technology as
a resource to improvise in everyday life
learn from each other develop shared
norms and values and remain independent
not just from the care of their loved
ones but also from care technology and
we try to capture all the lessons in the
booklets available online so I'd like to
conclude by provoking the audience and
saying that design should not be about
accountability about fixing the things
that are wrong design is imagination of
how things might be it's about taking
agency and responsibility for our
designers for desirable relations
between people and technology it's about
our future isn't a lot in the motor of
our faculty but for that we need to
understand and fully engage conceptually
methodologically and ethically with the
true challenges of past industrial
design which are codependency not
autonomy
Mart intentionality not so much accuracy
and perhaps empowerment are not so much
controlled and with that I like to
invite get her the new in other going to
introduce him