Artificial intelligence and Creativity

Artiﬁcial Intelligence and
Creativity
Luis Gustavo Martins - Catholic University of Portugal
lmartins@porto.ucp.pt
Symposium on Creative Industries
The Lisbon Consortium – Cultural Spaces / Creative Trends
Macau
17 April 2015

ATTRIBUTION-NONCOMMERCIAL-SHAREALIKE 3.0 UNPORTED (CC BY-NC-SA 3.0)
http://creativecommons.org/licenses/by-nc-sa/3.0/
This presentation was highly inspired by:
The AI Revolution: The Road to Superintelligence (http://waitbutwhy.com/2015/01/artiﬁcial-intelligence-revolution-1.html)
The AI Revolution: Our Immortality or Extinction (http://waitbutwhy.com/2015/01/artiﬁcial-intelligence-revolution-2.html)
Several images throughout this presentation are used without prior permission - authors can contact in case of misuse or copyright violations.

Artiﬁcial Intelligence…
The What…
The How…
The If…
The When…

What is Intelligence?
5
http://skyview.vansd.org/lschmidt/Projects/The%20Nine%20Types%20of%20Intelligence.htm

What is Intelligence?
“Intelligence is the computational part of the ability to
achieve goals in the world. Varying kinds and degrees of
intelligence occur in people, many animals and some
machines.”
(John McCarthy, Stanford University)
http://www-formal.stanford.edu/jmc/whatisai/node1.html

Measuring Human Intelligence
For centuries, philosophers have tried to pinpoint the true measure of
intelligence.
More recently, scientists have tried to formulate objective
measurements for different types of intelligence.

It has been proposed that intelligence increased as a
response to an increased necessity for solving social
problems as human society became more complex.
Human Intelligence Progress

We have the illusion that human intelligence has
evolved linearly, over time…

… but in fact, it is growing exponentially!
“We are on the edge of change comparable to the rise of human life on Earth” (Vernor Vinge)

Law of Accelerating Returns - Ray Kurzweil
Exponential human intelligence evolution happens because
more advanced societies have the ability to progress at a
faster rate than less advanced societies—because they’re
more advanced.

Law of Accelerating Returns - Ray Kurzweil
The average rate of advancement between 1985 and 2015
was higher than the rate between 1955 and 1985—because
the former was a more advanced world—so much more
change happened in the most recent 30 years than in the
prior 30.

Law of Accelerating Returns
Kurzweil suggests that:
the progress of the entire 20th century would have been achieved in only 20 years
at the rate of advancement in the year 2000 - i.e. by 2000, the rate of progress
was ﬁve times faster than the average rate of progress during the 20th century.
another 20th century’s worth of progress happened between 2000 and 2014
and that another 20th century’s worth of progress will happen by 2021, in only
seven years.
a couple decades later, a 20th century’s worth of progress will happen multiple
times in the same year, and even later, in less than one month.
the 21st century will achieve 1,000 times the progress of the 20th century.

Why do we tend to be
skeptical about such
outlandish forecasts of the
future?

Why do we tend to be skeptical about such
outlandish forecasts of the future?
1. When it comes to history, we think in straight
lines…

Why do we tend to be skeptical about such
outlandish forecasts of the future?
2. The trajectory of very recent history often tells a
distorted story

Why do we tend to be skeptical about such outlandish forecasts of the
future?
2. The trajectory of very recent history often tells a distorted story
1995~2007: explosion of the internet, the introduction of Microsoft, Google, and Facebook into the public
consciousness, the birth of social networking, and the introduction of cell phones and then smart phones.
But 2008~2015 has been less groundbreaking, at least on the technological front…
Someone thinking about the future today might examine the last few years to gauge the current rate of
advancement, but that’s missing the bigger picture. In fact, a new growth spurt might be brewing right now.

Why do we tend to be skeptical about such outlandish
forecasts of the future?
3. Our own experience makes us stubborn old men
about the future.
When we hear a prediction about the future that contradicts our experience-based notion of how
things work, our instinct is that the prediction must be naive.
Velho do Restelo (1904),
Columbano Bordalo Pinheiro
Museu Militar de Lisboa.

The Road to Superintelligence
Is Artiﬁcial Intelligence (AI)
a path to Superintelligence?

What is Artificial Intelligence (AI)
We associate AI with the movies…
http://www.theguardian.com/culture/gallery/2015/jan/08/the-top-20-artificial-intelligence-films-in-pictures

We use AI all the time in our daily lives, but we often don’t realize it’s AI…
…stop thinking of anthropomorphic robots!

“The science and engineering of making intelligent machines, especially
intelligent computer programs. It is related to the similar task of using
computers to understand human intelligence, but AI does not have to
conﬁne itself to methods that are biologically observable.”
AI is a broad topic.

Types of AI
Artificial Narrow Intelligence (ANI)
Sometimes referred to as Weak AI, Artificial Narrow Intelligence is AI that
specializes in one area.
Artificial General Intelligence (AGI):
Sometimes referred to as Strong AI, or Human-Level AI, Artificial General
Intelligence refers to a computer that is as smart as a human across the board
—a machine that can perform any intellectual task that a human being can.
Artificial Superintelligence (ASI):
Oxford philosopher and leading AI thinker Nick Bostrom defines superintelligence as
“an intellect that is much smarter than the best human brains in practically every
field, including scientific creativity, general wisdom and social skills.” Artificial
Superintelligence ranges from a computer that’s just a little smarter than a
human to one that’s trillions of times smarter—across the board.

A World running on ANI is not particularly scary…
… at most we would have to leave with some non-catastrophic
“annoyances”
bad GPS routing when driving
lost luggage in airports
false positive medical diagnosis
power grid outages
nuclear power plant malfunctions
ﬁnancial markets disaster
e.g. the 2010 Flash Crash when an ANI program reacted the wrong way to an unexpected
situation and caused the stock market to brieﬂy plummet, taking $1 trillion of market value with it,
only part of which was recovered when the mistake was corrected
…
Where We Are Currently…

Where We Are Currently…
A world running on evolving ANIs
ANIs are the building blocks to increasingly large and complex ecosystems
of relatively-harmless ANI
Each new ANI innovation quietly adds another brick onto the road to AGI
and ASI.
ANIs “are like the amino acids in the early Earth’s primordial ooze” (Aaron
Saenz)

The Road From ANI to AGI
AGI: a computer as smart
as humans in general
not just at one narrow
specialty
can tackle more generic and
broad tasks and challenges,
similarly to the way humans
do…

AGI: a computer as smart as humans in general
Challenging…
Nothing will make you appreciate human intelligence like
learning about how unbelievably challenging it is to try to
create a computer as smart as we are.
As of now, the human brain is the most complex object in the known universe

Why It’s So Hard…
Build a computer that can multiply two
ten-digit numbers in a split second—
incredibly easy.
Make AI that can beat any human in
chess? Done.
OK
OK

Build AI that can look at a dog and
answer whether it’s a dog or a cat
—spectacularly diﬃcult.
Make AI that can read a paragraph
from a six-year-old’s picture book
and not just recognize the words
but understand the meaning of
them? - Google is currently
spending billions of dollars
trying to do it.
X
X

Hard things—like calculus,
ﬁnancial market strategy, and
language translation—are mind-
numbingly easy for AI…
Easy things—like vision,
hearing, motion, movement,
and perception—are insanely
hard for AI…
OK
X

“AI has by now succeeded in doing essentially everything that requires
‘thinking’…
…but has failed to do most of what people and animals do ‘without thinking’.”
(Donald Knuth)
Things that seem easy to humans are actually unbelievably complicated, and they only
seem easy because those skills have been optimized in humans (and most animals)
by hundreds of million years of animal evolution.

First Key to Creating AGI:
Increasing Computational Power
If an AI system is going to be as intelligent as the brain, it’ll
need to equal the brain’s raw computing capacity.

Human brain:
Computation Power: around10 quadrillion (10
16
) calculations per second
(cps) = 10 petaﬂops
Small: around 1200 cubic centimetres
Low power: ~20 Watts
Cost: comes built-in with each human being
Highly usable for countless tasks and wide challenges

World’s fastest supercomputer, China’s Tianhe-2:
Computation Power: 34 quadrillion cps (34 petaﬂops)
—> 3,4 times faster than Human Brain!!
(Very) large: 720 square meters of space
(Very) high power: 24 megaWatts
High Cost: 390 million US$ to build
Not especially applicable to wide usage, or even most commercial or industrial
usage yet.

Increasing Computational Power -
Moore’s Law
“Processor speeds, or overall
processing power for computers will
double every two years.”
—> computer hardware
advancement, like general human
advancement through history, grows
exponentially.
world’s $1,000 computers are now
beating the mouse brain and
they’re at about a thousandth of
human level.
Being at a thousandth in 2015
puts us right on pace to get to an
aﬀordable computer by 2025 that
rivals the power of the brain.

What about NP-complete problem domains?
the progress needed to make advancements in intelligence also grows
exponentially harder with each subsequent step, which will cancel out the
typical exponential nature of technological progress…
Problems in these domains are solvable, but seem to take time exponential in the
size of the problem.
Humans often solve problems in NP-complete domains in times much shorter than
is guaranteed by the general algorithms, but can't solve them quickly in general.
Some experts and thinkers believe this is by itself the major
roadblock to superintelligence in the short/mid-term…

Furthermore, raw
computational power alone
doesn’t make a computer
generally intelligent…

Increasing Computational Power: SPEED VS QUALITY
SPEED:
super-smart computer = intelligent as a human but can think
much, much faster
machine that thinks like a human, except a million times quicker
=> it could ﬁgure out in ﬁve minutes what would take
a human a decade.

Increasing Computational Power: SPEED VS QUALITY
QUALITY:
What makes humans so much more intellectually capable than chimps isn’t a
difference in thinking speed
it’s that human brains contain a number of sophisticated cognitive modules that
enable things like complex linguistic representations or longterm planning or abstract
reasoning, that chimps’ brains do not.
Speeding up a chimp’s brain by thousands of times wouldn’t bring him to our
level—even with a decade’s time
he wouldn’t be able to ﬁgure out how to use a set of custom tools to assemble an
intricate model, something a human could knock out in a few hours.
There are worlds of human cognitive function a chimp will simply never be
capable of, no matter how much time he spends trying.
But it’s not just that a chimp can’t do what we do, it’s that his brain is unable to grasp
that those worlds even exist

May not be sufﬁcient by itself…
So, how do we bring human-level and
quality intelligence to all that
computing power?

Second Key to Creating AGI:
Making it Smart
Hard, really hard!!
no one really knows how to make it smart…
But there are a bunch of far-fetched strategies
out there and at some point, maybe one of them
will work…

Making it Smart - common approaches:
Plagiarize the brain
The science world is working hard on
reverse engineering the brain to ﬁgure out
how evolution made such a rad thing
so far, we’ve not yet just recently been
able to emulate a 1mm-long ﬂatworm
brain, which consists of just 302 total
neurons. The human brain contains 100
billion…
but remember the power of
exponential progress!
optimistic estimates say we can
do this by 2030.

Try to emulate evolution instead
“Genetic Algorithms”
“The survival of the ﬁttest”
performance-and-evaluation process,
repeated again and again…
Over many, many iterations, this natural
selection process would produce better
and better computers.
The challenge would be creating an
automated evaluation and breeding
cycle so this evolution process could
run on its own.

Self-Learning computers and AI
we’d build a computer whose two major skills would be doing
research on AI and coding changes into itself
allowing it to not only learn but to improve its own architecture

Self-Learning computers and AI
Google’s X lab built a neural network of 16,000 computer processors with
one billion connections and let it browse YouTube
The “brain” simulation was exposed to 10 million randomly selected YouTube
video thumbnails over the course of three days
after being presented with a list of 20,000 diﬀerent items, it began to
recognize pictures of cats and human faces using a “deep learning” algorithm
no information on distinguishing features that might help identify cats or
any other entity or object was provided to the system (i.e. unsupervised
system)
he system achieved 81.7% accuracy in detecting human faces, 76.7% accuracy
when identifying human body parts and 74.8% accuracy when identifying cats

All of This Could Happen Soon…
These predictions are based on highly speculative statistics, and they’re only representative of the center opinion of the AI expert community,
but it tells us that a large portion of the people who know the most about this topic would agree that 2060 is a very reasonable estimate for the arrival
of potentially world-altering ASI. Only 45 years from now. - http://waitbutwhy.com/2015/01/artiﬁcial-intelligence-revolution-2.html

“The Singularity” (or “technological singularity.”)
The moment in the future when our technology’s intelligence
exceeds our own (Vernor Vinge, 1993)
a moment when life as we know it will be forever changed and normal rules will no
longer apply.
Ray Kurzweil states that singularity is brought about by three
simultaneous revolutions in biotechnology, nanotechnology, and,
most powerfully, AI.
Towards Artiﬁcial SuperIntelligence (ASI)

AGI would have some signiﬁcant advantages over humans…
Hardware:
Speed.
Size and storage.
Reliability and durability.
Nanotechnology
Biotechnology
Software:
Editability, upgradability, and a wider breadth of possibility.
Collective capability / BigData / Internet of Things
AI, which will likely get to AGI by being programmed to self-improve, wouldn’t see
“human-level intelligence” as some important milestone—it’s only a relevant marker from
our point of view—and wouldn’t have any reason to “stop” at our level.

Cause of concerns (from human perspective)…
while the intelligence of different kinds of animals varies, the main
characteristic we’re aware of about any animal’s intelligence is
that it’s far lower than ours
we view the smartest humans as WAY smarter than the dumbest
humans (though in theory there is ALMOST NO DIFFERENCE!)

Cause of concerns (from
human perspective)…
Contextual Gap
hopeless trying to understand the
power of a ASI machine, even if
its intelligence is only slightly
above human intelligence…
there is no way to know what ASI
will do or what the consequences
will be for us…

Increasing Intelligence => Increased (and concentrated) Power.
ASI, when (if?) created, will have tremendous power, and all living things, including humans, could end
up entirely at its whim…
Singleton theory implies that once the ﬁrst ASI is created, it will immediately see a
strategic beneﬁt to being the world’s only ASI system => POWER CONCENTRATION RISK
Who or what will be in control of that power, and what will their motivation be?
Will it be GOOD or BAD?

ASI maliciously used
A malicious human, group of humans, or government develops
the ﬁrst ASI and uses it to carry out their evil plans
Possible, and dangerous… though ASI is still far from being
easily and widely accessible… for now…

ASI Consciousness (or lack of it)?
A malicious ASI is created and decides to destroy us all?
Machines are not intrinsically evil…
They are amoral
They are obsessed with fulfilling its original programmed goal…
Nick Bostrom believes that intelligence-level and final goals are orthogonal,
meaning any level of intelligence can be combined with any final goal.
Any assumption that once superintelligent, a system would be over it with
their original goal and onto more interesting or meaningful things is
anthropomorphizing.
Humans get “over” things, not computers.

A rational agent will pursue its goal through the most eﬃcient means, unless it has an
objective reason not to.
if it doesn’t have a reason not to hurt something in the name of achieving an instrumental
goal, it will.
ASI Goal: “Assure happiness for all Humanity”

And because ASI lacks consciousness, ASI may (naively) become
a danger to humans
…just like a wild animal would do.

So given the combination of obsessing over a goal, amorality, and the ability to easily
outsmart humans, it seems that almost any AI will default to Unfriendly AI
Unless carefully coded in the ﬁrst place with this in mind.
building a Friendly ANI is easy…
… building one that stays friendly when it becomes an ASI is hugely
challenging.
To be Friendly, an ASI needs to be neither hostile nor indiﬀerent
toward humans.
We’d need to design an AI’s core coding in a way that leaves it with a
deep understanding of human values.
…this is harder than it sounds (if not impossible).

ASI Consciousness and Morality
Would we be able to program it into ASI?
humans would never be able to agree on a single set of morals…
giving an AI a ﬁxed set of morals would lock humanity into our
modern moral understanding, for eternity.
In a thousand years, this would be as devastating to people as it
would be for us to be permanently forced to adhere to the ideals of
people in the Middle Ages.
we’d have to program in an ability for humanity to continue
evolving…
Hard problem, with no solution in the horizon…

How long until the ﬁrst machine reaches superintelligence?
opinions vary wildly and this is a heated debate among scientists and thinkers…
Many, like professor Vernor Vinge, scientist Ben Goertzel, Sun Microsystems co-
founder Bill Joy, or, most famously, inventor and futurist Ray Kurzweil, agree with
machine learning expert Jeremy Howard when he believes that this is happening
soon, within the next few decades…
Others, like Microsoft co-founder Paul Allen, research psychologist Gary Marcus,
NYU computer scientist Ernest Davis, and tech entrepreneur Mitch Kapor, believe
that thinkers like Kurzweil are vastly underestimating the magnitude of the
challenge and believe that we’re not actually that close to such an
achievement (if considering it feasible at all)…

How long until the ﬁrst machine reaches superintelligence?
Nick Bostrom, believes neither group has any ground to feel certain about the timeline
Philosopher Hubert Dreyfus, believe all three of these groups are naive for believing in the Singularity theory, arguing that
it’s more likely that ASI won’t actually ever be achieved.
Nevertheless, the more consensual prediction for ASI is around 2060…
These predictions are based on highly speculative statistics, and they’re only representative of the center opinion of the AI expert community,
but it tells us that a large portion of the people who know the most about this topic would agree that 2060 is a very reasonable estimate for the arrival
of potentially world-altering ASI. Only 45 years from now. - http://waitbutwhy.com/2015/01/artiﬁcial-intelligence-revolution-2.html

Different views on if,
when and how ASI
will happen…
AI experts seem to
be taking this
seriously, though!

Different views on if, when and how ASI
will happen…
The conﬁdente Corner - “The Future Might Be
Our Greatest Dream”
Peter Diamandis and Ben Goertzel, Ray Kurzweil,
…
The Anxious Avenue - “The Future Might Be Our
Worst Nightmare”
Stephen Hawking, Bill Gates, Elon Musk, Nick
Bostrom …

ASI will be:
Extremely powerful
Goal obsessed
Naive
Unconscious
Amoral
Void of Values (?)
Void of Feelings (?)
Void of Emotions (?)
Void of Creativity (?)
Potentially unfriendly and lethal (?)
Will ASI be up to Human Intelligence, after all?

Can a machine “behave” like a human?
Touring Test - “The Imitation Game”

Can a machine “behave” like a human?
True Intelligence or simply Imitation?
The Chinese room is a thought experiment presented by John
Searle to challenge the claim that it is possible for a
computer running a program to have a "mind" and
“consciousness" in the same sense that people do,
simply by virtue of running the right program.
The experiment is intended to help refute a philosophical
position that Searle named "strong AI”:
"The appropriately programmed computer with the right
inputs and outputs would thereby have a mind in exactly
the same sense human beings have minds."
The philosopher John Searle says that the idea of a non-biological machine being
intelligent is incoherent.

Before the prospect of an intelligence explosion, we humans are like small
children playing with a bomb.
Such is the mismatch between the power of our plaything and the
immaturity of our conduct.
Superintelligence is a challenge for which we are not ready now and will
not be ready for a long time.
We have little idea when the detonation will occur, though if we hold the
device to our ear we can hear a faint ticking sound.

References
Nick Bostrom – Superintelligence: Paths, Dangers, Strategies
James Barrat – Our Final Invention
Ray Kurzweil – The Singularity is Near
J. Nils Nilsson – The Quest for Artificial Intelligence: A History of Ideas and Achievements 
Steven Pinker – How the Mind Works 
Vernor Vinge – The Coming Technological Singularity: How to Survive in the Post-Human Era
Ernest Davis – Ethical Guidelines for A Superintelligence 
Nick Bostrom – How Long Before Superintelligence?
Vincent C. Müller and Nick Bostrom – Future Progress in Artificial Intelligence: A Survey of Expert Opinion
Moshe Y. Vardi – Artificial Intelligence: Past and Future 
Russ Roberts, EconTalk – Bostrom Interview and Bostrom Follow-Up 
Stuart Armstrong and Kaj Sotala, MIRI – How We’re Predicting AI—or Failing To 
Susan Schneider – Alien Minds 
Stuart Russell and Peter Norvig – Artificial Intelligence: A Modern Approach 
Theodore Modis – The Singularity Myth
Gary Marcus – Hyping Artificial Intelligence, Yet Again
Steven Pinker – Could a Computer Ever Be Conscious?
Carl Shulman – Omohundro’s “Basic AI Drives” and Catastrophic Risks
World Economic Forum – Global Risks 2015
John R. Searle – What Your Computer Can’t Know
Jaron Lanier – One Half a Manifesto
Bill Joy – Why the Future Doesn’t Need Us
Kevin Kelly – Thinkism
Paul Allen – The Singularity Isn’t Near (and Kurzweil’s response)
Stephen Hawking – Transcending Complacency on Superintelligent Machines
Kurt Andersen – Enthusiasts and Skeptics Debate Artificial Intelligence
Terms of Ray Kurzweil and Mitch Kapor’s bet about the AI timeline
Ben Goertzel – Ten Years To The Singularity If We Really Really Try
Arthur C. Clarke – Sir Arthur C. Clarke’s Predictions
Hubert L. Dreyfus – What Computers Still Can’t Do: A Critique of Artificial Reason
Stuart Armstrong – Smarter Than Us: The Rise of Machine Intelligence
Ted Greenwald – X Prize Founder Peter Diamandis Has His Eyes on the Future
Kaj Sotala and Roman V. Yampolskiy – Responses to Catastrophic AGI Risk: A Survey
Jeremy Howard TED Talk – The wonderful and terrifying implications of computers that can learn

References
http://waitbutwhy.com/2015/01/artificial-intelligence-revolution-1.html
http://waitbutwhy.com/2015/01/artificial-intelligence-revolution-2.html
http://www.businessinsider.com/how-elon-musks-10-million-donation-will-help-keep-us-safe-from-artificial-intelligence-2015-7
https://arstechnica.co.uk/information-technology/2015/12/demystifying-artificial-intelligence-no-the-singularity-is-not-just-around-the-
corner/
https://www.wired.com/2015/02/ai-wont-end-world-might-take-job/
http://yudkowsky.net
https://en.wikipedia.org/wiki/Chinese_room
https://ai100.stanford.edu/sites/default/files/ai_100_report_0831fnl.pdf
http://www.pewinternet.org/2014/08/06/predictions-for-the-state-of-ai-and-robotics-in-2025/
https://qz.com/911968/bill-gates-the-robot-that-takes-your-job-should-pay-taxes/
https://www.youtube.com/watch?v=GHmkuv69PQE
https://www.linkedin.com/pulse/mind-blowing-ai-announcement-from-google-you-probably-gil-fewster
https://arstechnica.co.uk/business/2016/11/elon-musk-universal-income-survive-robot-workers/
http://www.ted.com/talks/zeynep_tufekci_machine_intelligence_makes_human_morals_more_important
https://www.linkedin.com/pulse/what-happens-when-millions-jobs-lost-because-jeff-selingo
http://www.ted.com/talks/anthony_goldbloom_the_jobs_we_ll_lose_to_machines_and_the_ones_we_won_t
http://moralmachine.mit.edu

Thank you.
Luis Gustavo Martins
lmartins@porto.ucp.pt

Artificial intelligence and Creativity

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