Metalab_review_WEB_p_a_p.pdf

METALAB REVIEW
AI & CULTURE, BUSINESS AND SOCIETY
SPECIAL EDITION: STUDENT IDEAS THINK TANK
No 1, SEPTEMBER 2023

METALAB REVIEW ¦ 3
We are delighted to present this first edition of the Metalab Review, as a special issue
assembled by the talented members of Metalab IDEAS, a student think tank.
At ESSEC Business School, our mission is to prepare future leaders – our students
of today – to comprehend and responsibly unleash the power of artificial intelligence
and data science to benefit both industry and society. We believe that realizing AI's
potential requires a wide ranging and concerted effort. The responsible adoption of
these fast-deploying technologies requires cultivating a new generation of professionals
who combine scientific acumen and organization savviness with ethical and societal
mindfulness. Our conviction is that our business school students must be equipped with
the multifaceted expertise needed to invent new AI solutions to the problems societies
and companies face today.
The insightful articles authored for this magazine by the student editors and analysts
of Metalab IDEAS embody the spirit of responsible AI leadership we seek to instill.
Analyzing topics ranging from enhancing human creativity through AI to the policy
implications of digital currencies, their contributions highlight the immense yet
unevenly distributed potential of data driven technologies. Weighing opportunities with
responsibilities, their work delves into the nuanced elements that shape an equitable
and sustainable AI future.
We believe this first edition will enrich debates on campuses and beyond by grounding
AI discourse in the contextual complexity of the real world. We hope it inspires readers,
especially those poised to assume responsibilities, to keep advocating for a human-
centric AI that ethically addresses social needs.
Congratulations to the talented 2023 IDEAS students cohort on their commendable work
to advance conscientious AI leadership!
THE METALAB CODIRECTORS
BENOIT BERGERET
PROF. GUILLAUME CHEVILLON
PROF. JULIEN MALAURENT
FOREWORD BY
METALAB DIRECTORS
METALAB REVIEW ¦ 3

METALAB REVIEW ¦ 5
In an era reshaped by technological breakthroughs and environmental upheavals, agility and
adaptability have never been more critical in crafting solutions for tomorrow's challenges and
in reassessing how our society envisions its future to better prepare for it. Overcoming the
obstacles ahead hinges on substantial investments in research and innovation.
Fueled by this steadfast belief, the onepoint Institute, our cross-disciplinary initiative,
orchestrates applied research initiatives that transform knowledge into practical and tangible
advancements.
The emergence of generative AI technologies paints a vast landscape of opportunities.
Together with its academic partners, the onepoint Institute aims to convert these possibilities
into meaningful value, underpinned by a sustainable and sovereign approach.
It was this vision and ambition that naturally led onepoint to establish a strategic partnership
with Metalab, a leading authority in AI and data from ESSEC, in 2021. This alliance offers a
unique platform for enriching collective insights on the rapidly growing adoption of these
technologies. Ongoing dialogues between our consultants and experts, and ESSEC researchers
and students enhance our service and consultancy offerings to onepoint’s clients. They also
fuel the creation of content that informs society at large on these transformational topics,
such as the student contributions from ESSEC’s think tank IDEAS, which form the core of this
inaugural Metalab Review, to which we are honored to contribute.
This symbiotic partnership also advances our mutual understanding of the present and
future impacts of AI and data. A collaborative approach serves as a catalyst for deepening
domain-specific knowledge. The enhanced public and civic visibility of both partners is further
amplified through joint events and communications. More than 600 students have engaged
in these events and hackathons, and the synergy between one of the world's leading business
schools and one point, the « the Architect of Transformations » also fosters a harmonious
balance between the academic and corporate realms. Our operational teams provide essential
on-the-ground perspectives to conduct research that aligns with the real-world corporate
challenges in responsible AI.
Without a doubt, this high-impact, structurally significant partnership aims to drive positive
change in the world. It focuses on understanding and applying new technologies wisely and
ensures that preserving our humanity remains a top priority.
MURIEL TOUATY
PARTNER EDUCATION AND INNOVATION, ONEPOINT
METALAB REVIEW ¦ 5
FOREWORD BY
ONEPOINT

METALAB REVIEW ¦ 7
In 2020, ESSEC Business School pioneered the Metalab for data, technology and society,
a center aimed at creating dynamics around AI and disruptive technologies within ESSEC
programs - and beyond. As part of its activities, Metalab established the student-led IDEAS
think tank, a school-wide project to address the repercussions of technology on business
and management; from the increasing relevance of data analytics to the inescapable
reality of artificial intelligence. Now closing on our second year of existence, the think tank
has published numerous articles, developed privileged contacts with business partners,
conducted events, and produced a Podcast series—and we are only getting started!
With this first edition of the Metalab Review, we proudly present the editorial team’s work
produced over the 2022-23 academic year. We showcase a wide range of articles written
by the editors and analysts spanning multiple disciplines from the business school.
The articles correspond to each of the four key interest groups we have been leading: AI
Adoption, the Future of Sustainability & Society, Blockchain & Decentralization, and the
Future of Work & Business; and intermingled with these articles are snapshots of the
motivations behind some of the board’s participation in the Metalab.
This issue also features a series of the successful events organized by the team,
roundtables and poster sessions, as well as participation of Metalab IDEAS to other
relevant ESSEC initiatives. Indeed, in our second year, our team has endeavored to expand
beyond editorial publications. Such is the case for the release of Tech Tide: A Wave of
Ideas, a podcast series produced in conjunction with Tech ESSEC. It aims to shed light on
the impact of technology and AI developments on companies, society and the economy.
The publication of the magazine is a manifestation of the Metalab IDEAS team’s ambition,
hard work, and commitment to assuring the leaders of tomorrow are informed on the
technological advancements that will affect theirs and the lives of those they will lead. It
has not been easy, any member of the board will attest to that, but worthwhile? No doubt. It
is therefore the team’s greatest wish that not only will you be entertained by this issue, but
that you will learn from it.
IDEAS THINK TANK EDITORIAL BOARD
METALAB REVIEW ¦ 7
STUDENT
EDITORIAL

8 ¦ METALAB REVIEW
NELBERTO NICHOLAS
“SAM” QUINTO
PHD STUDENT IN THE
MANAGEMENT DEPARTMENT
AT ESSEC BUSINESS SCHOOL
I’m Nelberto Nicholas “Sam” Quinto and I am a
doctoral student who does research on human-AI
collaboration. I am particularly interested in how
“collaborating” with AI alters problem-solving,
creative thinking, and group dynamics in innovation
contexts. Aside from studying AI, I also use it
to analyze large amounts of data from creative
industries to uncover approaches to innovation that
yield replicable outcomes when used by different
individuals. My predilection for AI can be traced
to my work as a data science consultant at BNP
Paribas’ Analytics Consulting team, my analytics
internship in Amazon, and my coursework on big
data, machine learning, and AI strategy during my
Master’s in Management at ESSEC. Hence, within
my work in the Metalab, I strive to distill insights and
thought-processes from these many experiences
to both co-create and curate content that drives the
frontiers of ongoing AI discourse.
MARINA PELLET
MASTER IN DATA SCIENCES
& BUSINESS ANALYTICS AT
ESSEC BUSINESS SCHOOL &
CENTRALESUPÉLEC
I’m Marina Pellet, I’m French and Hungarian, and
I am a student in the DSBA Master's program
created by Essec and CentraleSupelec. Before that, I
studied in London at UCL and I obtained a bachelor
of Management Science with a specialization in
Cybercrime. I speak four languages and I have
lived in six different countries. I love photography,
cinema and reading. Also, I am very keen on sailing
and kitesurfing. I am simultaneously excited and
concerned about the increasing use of technology
by society, so I can’t wait to discover all aspects
together!
MICHELLE DIAZ
MASTER IN MANAGEMENT
STUDENT AT ESSEC BUSINESS
SCHOOL
I’m Michelle Diaz! I grew up
between Ireland and the Philippines, and graduated
with a B.A. International Joint Honors in English
Literature & Information and Social Computing
from University College Dublin, with a year-long
academic exchange at Waseda University in
Tokyo, Japan. I’m currently a fourth-year Master in
Management student. My work experiences are in
AI, startups, & entrepreneurship. And I’m currently
doing a double degree in Global Management at the
University of Queensland, Australia. My interests
are in sustainability, ethical issues in business and
technology, AI, and impact ventures. Moreover,
in my downtime, I love watching films, tv shows,
documentaries & I spend a significant amount of
time reading and writing. In another life, I would
actually be in graduate school for creative writing.
VANSHIKA SHARMA
CENTRALESUPÉLEC
I'm Vanshika Sharma. I grew up in New Delhi,
India and did Bachelor's in Commerce (Honours)
from University of Delhi. Prior to joining the
masters program at ESSEC Business School
and CentraleSupélec, I worked for two years as
an Associate in Quantitative Analytics and Data
Science at Gartner, Inc. I recently completed a
Master in Data Sciences and Business Analytics and
started my end-of-studies internship at Amazon.
I have always been intrigued by how transforming
data into meaningful insights can lead to better
decision-making and innovation. My interests are
in exploring upcoming technology, its influence
on various industries, and how it can be used
to promote sustainability. In my free time, I love
binge-watching thriller series, exploring different
cities, and discovering their gastronomy (especially
various vegan/vegetarian food options).
THE EDITORIAL
BOARD MEMBERS

METALAB REVIEW ¦ 9
KUNAL PUROHIT
MASTER IN MANAGEMENT AT
ESSEC BUSINESS SCHOOL
I am Kunal Purohit, originally from
Udaipur, India. After engineering, I
worked in product in two different Tech companies
for two years and while pursuing my first year of
MIM at ESSEC, I am currently working as Data
Analyst Apprentice at a startup in Paris and also
participating in Accenture SBA Chair. Reading about
new technologies, writing blogs, playing Table-
Tennis, listening to podcasts and watching movies
are my interests. Fluent in 3 different Indian regional
languages and English, I am currently learning
French.
PAUL BÉDIER
CENTRALESUPÉLEC
My name is Paul Bédier, I am 26 years old and
French. I completed a bachelor in Economics &
English, before obtaining a MSc in Finance from
EDHEC Business School. I then worked in different
financial firms and investment funds as an analyst.
After that I got very interested in AI and Data
Sciences so I joined the DSBA Master from which
I recently graduated. My interests include various
things like movies, food, and mountain trekking. I am
also curious about other cultures and I like learning
new languages (Japanese, Chinese), which is why I
went to Singapore to cap off my studies. Excited to
keep contributing to Metalab Ideas!
NEIL JR. ROMUALDEZ
MASTER IN STRATEGY &
MANAGEMENT OF
INTERNATIONAL BUSINESS
Hi! I’m Neil Romualdez Jr, 23 years
old. I’m currently taking the Master in Strategy &
Management of International Business (SMIB) under
the Managing Digital Transformation & Innovation
Track. Prior to this, I graduated with a bachelor’s
degree in Mathematics. I had a short stint in trade
reconciliations for hedge funds before I worked on
public policy as an economist for the Philippine
Ministry of Finance. I am deeply interested in how
emerging technologies and our dependence on
them can change the way the world interacts and
manages its resources. In my downtime, I read
books, watch movies, and play musical instruments.
PIETER JAN MOTMANS
CENTRALESUPÉLEC
I’m Pieter Jan Motmans, a beginning researcher
in the exciting field of Reinforcement Learning
currently doing an internship at ESSEC Business
School in Paris. I have been part of the Metalab
for two years now, first during my Master’s in Data
Sciences and Business Analytics and now during my
internship. Throughout these years, I was constantly
driven by my interest in studying the societal impact
of different technologies. It has been enriching to
be a part of the think tank to progress the debate on
these topics, and I greatly enjoyed writing my own
articles, and helping analysts and fellow editors in
writing theirs.
RINALYN PAGAO
MSC IN SUSTAINABILITY
TRANSFORMATION AT ESSEC
BUSINESS SCHOOL
My name is Rina. I completed
my Global BBA at ESSEC through the Singapore-
Paris track and graduated in 2020. After that, I
spent 2.5 years as a financial analyst at large
digital and marketing agencies. This allowed me to
have multicultural and international experiences,
from my upbringing in the Philippines to living
abroad, especially in Singapore, Paris, and
Barcelona over the past 6.5 years. I am currently a
pioneering master student in MSc in Sustainability
Transformation 2022–2023 program at ESSEC,
Cergy Campus.
In the face of the global climate crisis and other
challenges, my main interests are at the core of
sustainability, social innovation, and making a
positive influence in our society. I am especially
curious about how technology interacts with green
and sustainable growth within the confines of our
planetary boundaries. I am thrilled to be part of the
editorial team and to learn more!
With contributions from IDEAS think tank analysts:
SEETHAL REDDY
KAULURI - MASTER
IN MANAGEMENT
AMIR HUMZA
KHAN - MASTER
IN FINANCE.

10 ¦ METALAB REVIEW
TABLE OF
CONTENTS
ARTIFICIAL
INTELLIGENCE:
A BOOST
TO HUMAN
CREATIVITY
14
WILL AI END
CREATIVITY?
UNPACKING THE
HUMANITY BEHIND
GENERATIVE AI
CO-CREATIONS
20
THE AI CREATIVE
RENAISSANCE:
THE IMPACT OF
CO-CREATING WITH AI
ON CREATIVITY AND
THE FUTURE OF
WORK
30
AI & CREATIVITY
SUSTAINABILITY & SOCIETY
ATTENTION
ECONOMY:
YOU’RE NOT
PAYING ENOUGH
ATTENTION
48
THE PROGRESS
PARADOX:
CAN TECHNOLOGICAL
ADVANCEMENTS
COEXIST WITH
A DEGROWTH
ECONOMY?
40
CITIES OF THE
FUTURE
EVALUATING AI’S
POTENTIAL IN
CLIMATE-RESILIENCY
58
FROM VIRTUAL
MODELS TO
REAL-LIFE
IMPACT:
HOW DIGITAL TWIN
AND AI ARE DRIVING
SUSTAINABILITY
EFFORTS
66

METALAB REVIEW ¦ 11
EXPLAINABLE AI:
PART 2 - CAN WE
HAVE A STATUS
QUO WHERE AI IS
EXPLAINABLE?
138
PATHWAY TO A
FAIR METAVERSE
96
DIGITALIZATION
OF TALENT
ACQUISITION:
MOVE FORWARD
WITH CAGED
MACHINE
102
SOCIAL SCIENTISTS
IN THE QUEST FOR
AI ALIGNMENT
THE POTENTIAL OF
INTERDISCIPLINARY
COLLABORATION IN AI
SAFETY
126
HIGHLIGHTS
OF THE YEAR
144
DIGITAL
CURRENCY: THE
SUBSTITUTION
OF MONEY
76
EXPLAINABLE AI:
PART 1 - WHAT’S
AT STAKE AND
WHEN DOES IT
MATTER?
132
DIGITAL CURRENCY:
THE OVERHAUL OF
PUBLIC MONEY
WHY DO WE NEED
A CENTRAL BANK
DIGITAL CURRENCY
WHEN MONEY IS
ALREADY DIGITAL?
86
SAFETY & TRANSPARENCY
BLOCKCHAIN & DIGITALIZATION
112
BLOCKCHAIN:
THE ANSWER
TO INVESTORS’
GREENWASHING
WOES?

AI
&
CREATIVITY

ARTIFICIAL
INTELLIGENCE: A
BOOST TO HUMAN
CREATIVITY
WHAT IS CREATIVITY?
N
othing seems more human than
creativity—the trait that underpins
human innovation, from the arts to
the sciences, and pretty much everything
in between. According to the Cambridge
dictionary, creativity is defined as “the ability
to produce original and unusual ideas, or
to make something new or imaginative.”
However, physicists regard equations not only
for their originality, merit, or consequence, but
also for their elegance. On the way in which
an equation can embody a truth. Ingenuity is
defined not only by the solution-like quality
it may have, but by the subjective emotion it
can elicit.
One of the greatest love stories in medicine
is that between William Steward Halsted,
considered to be the father of American
surgery, and Caroline Hampton Halsted, his
scrub nurse. The story goes that around the
winter of the 1890s, Caroline complained
of dermatitis on her hands and arms due to
the solutions used in the operating room.
Given William’s regard for Caroline, he made
a request to the Goodyear Rubber Company
to make thin gloves as an experiment. And
these became the rubber operating gloves
used today, thin and reliable. Coupled
with hand hygiene, it significantly reduced
infections and deaths in the operating room.
A simple innovation borne out of necessity
and concern – a creative and consequential
solution sparked by an understanding of
context and the human need to alleviate
emotional turmoil.
As it stands, artificial intelligence remains
incapable of the emotion that makes
creativity human. It can neither comment on
the elegance of Einstein’s theory of special
relativity nor attribute any solution it proffers
as stemming from pain, devotion, or the
desire to simply evoke emotion. But ask any
AI specialist today, and they will heartily tell
you that AI already has a relationship with
creativity, one that is beneficial to both parties
By MICHELLE DIAZ
Master in Management Student at ESSEC Business School

and largely in service of human creativity. Not
quite out to compete with human creativity.
Not yet anyway.
DEFINING CREATIVITY
Over the years, creativity has been defined
in multiple ways. All with the explicit aim of
capturing and accounting for every facet
of the concept. From breaking it down into
different types, to analysing its consequences,
and clearly defining the common thread of
what makes a certain idea, behaviour, or
endeavour creative.
One of the most known and cited definitions
was given by Simonton in 2012. It follows the
criterion used by the United States Patent
Office to determine whether an invention
can come under patent protection. An idea
or invention must be original, useful, and
surprising to achieve either full, or partial
patent protection. Another famous definition
was used by Boden in 1998, in her article on
creativity and its connection with artificial
intelligence. According to her, there are three
types of creativity, all involving the generation
of novel ideas, and each type is capable of
bringing about the emotion of surprise:
©
Bench
Accounting
on
Unsplash

TYPES OF CREATIVE
ENDEAVOUR:
1. PSYCHOLOGICAL
>
Definition: New to creators
themselves.

Example: When an author writes a
story they’ve never written before.
2. HISTORICAL
Definition: New to society.

Example: Einstein’s theory of
Relativity.
In this way, computer models could be
built to mimic the process by which
creative ideas could be generated.
Three Types of Creativity
1. COMBINATIONAL CREATIVITY

Definition: When two new ideas share a
common inherent structure.
Example: Poetic imagery and analogy.
2. EXPLORATORY CREATIVITY

Definition: Characterised by the creation
of new ideas through the exploration of
structured conceptual spaces.

Example: Can include scientists, artists,
and musicians who all learn the rules
and styles of thinking involved in their
respective fields – superficially tweak
these established norms to achieve
something new.
3. TRANSFORMATIONAL CREATIVITY

Definition: Involves the transformation of
the space itself, so that new structures
can be generated that were before
considered impossible – has the
capacity to bring about a shock, that is,
ideas that, depending on the degree of
transformation, may be more difficult to
accept.

Example: Something like humanity’s
once upon a time dream of landing a
man on the moon. An idea seemingly
so out there that it is shocking, but a
vision easy enough to conjure that one
might deem it improbable instead of
impossible.
By categorising creativity in these three ways,
Boden was able to evaluate computer models
in accordance with the categories. She
additionally differentiated creative endeavours
as either being:
DISTINCTIVELY HUMAN
CREATIVITY
However, the key component of whether an
idea can be considered creatively successful
is the context in which it is made. Great poetry
does not simply follow a good rhyming scheme
but comments on the human condition in
a way that resonates with people—which is
to say, artificial intelligence when applied to
creativity must be directed. For instance, in
the fields of visual art or music composition,
AI can be programmed to produce something
that is transformational, in that it can create
something new and unexpected and be
deemed creative. But whether it can be
considered a work of art that is largely admired
by society is another question. It is imperative
for AI to understand, evaluate, and adjust
accordingly to contextual cues to compete with
this innately human aspect of creativity.

HOW AI ATTEMPTS
HUMAN CREATIVITY
Artificial neural networks (ANN), a set of
networks that are inspired by the human
brain, try to address this question of
recognition. ANN emulates and uses a
reduced set of frameworks from biological
neural systems. More specifically, these
models imitate the electrical activity of the
human brain and nervous system. The
ANN models are neurons in a complex and
nonlinear form. The neurons are connected
to each other by weighted links. There is a
supervised procedure that comprises three
layers: input, hidden, and output. Now, instead
of simply asking the algorithm to create
something novel and unexpected, it uses an
algorithm designed in accordance with the
human brain, with narrowed-down data sets
chosen by human beings.
For example, in music, as in several creative
fields, there exist melodies and patterns
that can influence human emotions in
certain ways. A study done in China using
AI capitalizes on this fact. Fundamentally,
music has three distinct parts: time, pitch,
and texture. Using machine learning and
deep learning paired with facial recognition
and music, they created a model that could
assess the effects of certain types of music
on a customer’s behaviour. Essentially, they
tracked if the music played would affect
how long a customer would stay in a certain
store. And it did. It confirmed that digital
transformation brought about by AI could be
used as an environmental stimulus to affect
customer behaviour.
All this to say that one can train a model using
a data set of the most known and beloved
musical pieces across the centuries and it will
manage to render melodies that will resonate
with human beings. In this way, the creativity
involved is combinational, exploratory, and
historical.
It is almost akin to Doctor Halsted bringing
about the invention of thin medical gloves,
wherein the data provided to the algorithm
is the context of the good doctor’s concern
for his eventual wife, thus emphasising the
human component in the creative endeavour.
Essentially, AI can create works of art or
demonstrate creativity by having access
to data that provides human preferences.
This type of work effectively improves
upon human creativity, actively resulting in
something useful like knowing the type of
music to play to encourage customers to stay
longer at a certain shop.
EXAMPLE: ARTIFICIAL
INTELLIGENCE CREATIVE
ADVERSARIAL NETWORK
(AICAN)
Another aspect of creativity is the
combination of transformational and
psychological, a creation that manages to
balance surprise with societal acceptance
and be new to the algorithm itself. In this
regard, there have also been advances. An
astounding example would be the work
of computer scientist Ahmed Elgammal
at Rutgers University in 2017. He used
generative adversarial networks (GAN) that
can do more than recognize existing images
of objects, but also generate novel images,
simply by inverting the image coding/
recognition procedure. He developed a new
GAN known as the Artificial Intelligence
Creative Adversarial Network (AICAN) which
was able to not only judge its own work, but
also look for styles that have yet to exist. In
essence, it could create.
The key part of this endeavour was that
he trained the algorithm on a database of
over 80,000 images from Western art in
the periods between 1400 and 2000. The
machine produced its own style by knowing

about the styles that already existed in that
period. Now for the judgement: the AICAN
images were shown at the 2016 Basel fair
in competition with works by human artists,
and the judges preferred the AICAN images.
The judges collectively regarded the images
as creative. The case to be made, however,
is that the newly produced AICAN images
followed the style of heavy abstraction, which
follows in line with the history of art.
As such, an argument could be made that in
this instance, the artwork fell just in line with
the creative categories of transformational
and psychological, given the domain of
western art paintings. Regardless, the results
were impressive and indicate a positive for AI
in creativity. But while it is brilliant that AI can
create something entirely new and manage
to adhere to human preferences, it remains
that there was a human touch to the data:
the algorithm was created by humans, and
trained on a data set curated by humans.
Hence, it misses the purpose born of an
artist’s context that is usually involved in
the production of art. Moreover, western
art is a domain with a wider tolerance
for astonishment and abstraction far
removed from human experience. A domain
wherein the purpose of art is allowed to be
less important than its ability to elicit an
imaginative response from humans.
WHERE AI FAILS TO ACHIEVE
HUMAN CREATIVITY
The opposite is required for great stories,
the narratives and writing that eventually
become a part of the literary and cinematic
canon need to be attached to the human
experience. Indeed, for stories to work, they
must go beyond the technical elegance of
the writing, they must speak to some sort of
human truth. Even the most fantastical of
stories, like the Harry Potter series or the Lord
of the Rings, revolve around certain universal
truths: the experience of adolescence and the
ethical conundrum of what is good or bad. In
essence, great stories must have a narrative
that humans can identify with.
In this realm, there are two use cases of AI
that have garnered a lot of attention.
TWO USE CASES:
1. COLLABORATIVE APPROACH:
FACILITATION OF HUMAN CREATIVITY
Most commonly used across different
storytelling mediums. For instance, the
incorporation of digital storytelling in
television, film, gaming, and the entertainment
industry fall under this category. In essence,
these AI interventions are to be incorporated
into the genre of Choose Your Own Adventure
(CYOA), a type of story that gives its audience
a hand in the direction of the narrative.
A familiar example would be Netflix’s
Bandersnatch, a standalone episode of the
popular Black Mirror series, wherein the
audience is presented with different choices
at different points throughout the narrative
that affect the ending.
The use of AI in this genre is through
narrative generation systems, wherein the
system responds to user input and allows
for interactivity. The difference between
©
Amauri
Mejia
on
Unsplash

KEY TAKEAWAY
Distilled, the relationship between AI and
creativity can be categorised in two ways:
the empowerment of human creativity
and the pursuit of a creativity that can
pass as human. Currently, AI has made
more strides in the first category, working
more so in partnership and with the
guidance of human creativity to achieve
new heights.
The latter category which proffers AI as
having the ability to compete with human
creativity by correctly accounting for
emotion, nuance, and societal context,
remains in progress. The question is
how long. But for now, creatives all over
can capitalize on the ways in which AI is
another means for them to exercise their
creative juices and dazzle their target
audiences—to lean in, and treat AI as what
it currently is: a powerful boost to human
creativity.
the traditional application of CYOA is that,
previously, the author had to create the
different predetermined storylines upon
writing the story. But the use of AI, will allow
computational algorithms to process and
produce audiovisual media more seamlessly
in service of the author’s vision.
This will allow for a wider variety of endings
with different nuances in place—making the
arc of the storyline more diverse and less
predictable for the viewers.
2. AI AUTHORS WORK THAT
RESONATES WITH SOCIETY:
CREATIVITY THAT PASSES AS HUMAN
This second approach is in line with the
combination of transformational and
psychological creativity; these forms of AI
try to be content creators themselves. Such
works have largely been experimental and
academic, but some projects have made it
into the public domain.
Some examples include projects like Ross
Goodwin and Oscar Sharpe’s AI screenwriter,
along with Botnik Studios AI. The stories
these projects have developed are far from
the coherent, emotional, and storytelling
standards of the commercial entertainment
industry.
But like AICAN images, they have managed
to intrigue enough to garner an audience.
Perhaps, with time, these stories will
eventually evolve from curious, abstract,
and compelling in their strangeness, to
emotionally moving narratives that account
for human context and emotion.
©
Rawpixel
from
Burst

R
ecent advancements in artificial
intelligence (AI) have prompted us to
ponder the fate of human creativity
and its relationship with technology. Present-
day AI platforms have demonstrated their
prowess in generating a diverse array of
creative outputs. From fabricating tailor-
made digital imagery, crafting compelling
advertising phrases, drafting cogent essays,
or even composing infectious tunes, the allure
of generative AI technologies is unmistakable.
In 2022 alone, they have drawn a staggering
$2.654 billion in investments, marking a
tenfold increase since 2020. As AI encroaches
upon what was once considered a uniquely
human domain, the ontological, economic,
and legal systems that underlie creative
production are consequently being redefined
1. Teresa M. Amabile et al., “Affect and Creativity at Work,” Administrative Science Quarterly 50, no. 3 (September 1, 2005):
367–403, https://doi.org/10.2189/asqu.2005.50.3.367.
Teresa M. Amabile, “The Social Psychology of Creativity: A Componential Conceptualization.,” Journal of Personality and
Social Psychology 45, no. 2 (August 1983): 357–76, https://doi.org/10.1037/0022-3514.45.2.357.
in profound, uncharted ways. Amidst this
upheaval, a question emerges: Is creativity
dying, and is AI the culprit?
WHAT EXACTLY IS
CREATIVITY AND WHY IS
IT IMPORTANT?
To untangle this provocative question,
it is essential to probe into the essence
of creativity—its core attributes and its
significance to society and organizations.
Creativity is defined as the generation
of ideas, solutions, or products that are
both novel and useful1
. It is a multifaceted
phenomenon, encapsulating not just the
outcome or process of idea development,
WILL AI END
CREATIVITY?
UNPACKING THE HUMANITY BEHIND
GENERATIVE AI CO-CREATIONS
By NELBERTO NICHOLAS QUINTO
PhD student in the Management department at ESSEC Business School

artistic creation, or problem-solving2
, but also
the inherent ability of individuals to produce
the new and valuable. As the cornerstone
of innovation, creativity transforms unique
ideas into tangible actions or products, which
in turn fuel technological advancements.
Within organizations, creative employees
are a catalyst for competitive advantage3
.
They contribute unique solutions to pressing
challenges, resulting in strategies, business
processes, and design concepts that drive
success. Creativity also bolsters adaptability
2. Spencer Harrison et al., “The Turn toward Creative Work,” Academy of Management Collections 1, no. 1 (August 4,
2022), https://doi.org/10.5465/amc.2021.0003.
3. Richard Florida and Jim Goodnight, “Managing for Creativity,” Harvard Business Review, July 1, 2005, https://hbr.
org/2005/07/managing-for-creativity.
4. Martin Reeves and Mike Deimler, “Adaptability: The New Competitive Advantage,” Harvard Business Review, July 1,
2011, https://hbr.org/2011/07/adaptability-the-new-competitive-advantage.
in the face of external changes and disruptive
technologies, enhancing the likelihood of
success for individuals and organizations4
.
To grasp the essence of creativity’s central
components – novelty (newness, originality)
and usefulness (value, quality) – think of
the last time you or someone around you
has deemed something to be ‘creative.’ Was
the value found in the end result or in the
process that led to it? As will be revealed, this
distinction is central to the debate of whether
©
Evgeniy
Alyoshin
on
Unsplash

the growing impact of AI will usher in a
creative renaissance or its antithesis.
HOW AI AFFECTS
CREATIVITY:
PERSPECTIVES,
BENEFITS, AND
LIMITATIONS
THE PRODUCT PERSPECTIVE
The traditional perspective of creativity places
emphasis on the final product. Think about
an evocative novel or an influential film.
Their creativity is gauged by the audience's
experience with the completed work. The
unpredictability of the plot, the introduction
of nonconforming characters, and the
use of groundbreaking narrative styles all
serve as sources of novelty. Meanwhile, the
exhilaration experienced from narratives
that defy convention, the emotions they
stir within us, the curiosity they spark, and
the respite they offer from everyday life—all
are markers of usefulness attributed to the
end product. AI-generated designs, leading
to a revolutionary product, align with this
perspective. From a managerial standpoint,
the value is not in the AI's process of creation
but in the resultant artifact—its appeal in the
market, and its innovative design that caters
to and anticipates consumer needs.
From this product-centered perspective,
AI emerges as a potent tool for enhancing
our creativity. It produces innovative ideas
and forms that inspire human artists and
democratize access to creative production
by making aesthetic prowess and innovative
combinations more accessible. Generative AI
can be conceptualized as a new 'paintbrush'
for artists and creatives. Anyone can pick up
this 'brush' and create—be it poems, design
prototypes, or unique product concepts—
©
Yannick
Pulver
on
Unsplash

without necessarily needing the traditional,
extensive training or experience. For many,
this accessibility may very well foster
inclusivity, thereby encouraging a larger
population to engage in creative pursuits.
It brings people who might never consider
performing artistic or innovative work into the
sphere of creative endeavors, exploring their
human ingenuity as they co-create with AI.
AI LIMITATIONS IN CREATIVE
PRODUCTION
However, such democratization comes
with its own challenges and limitations.
The novelty of the output generated heavily
relies on the creativity infused in prompts.
The usefulness of the final output also
remains somewhat limited, especially when
considering the current state of AI wherein
the quality of the generated paragraphs,
images, or media may still fall short of those
produced by traditional professionals. There's
often a substantial amount of trial and error
involved in crafting the right prompts, as
well as significant post-processing once
a satisfactory output is achieved. While
these are technical limitations that may be
resolved as AI advances, there's another
side to consider. As AI improves, so will the
benchmarks for what is considered quality,
useful, and new. Therefore, it's rare for a
few string of prompts to suffice in creating
something truly considered creative—that is,
novel and valuable—for its time. Even with
significant advancements in AI capabilities
over time, leading to minimal post-processing
or prompt engineering needs, there's always
an inherent risk tied to tools that simplify
processes.
THE PROCESS PERSPECTIVE
Another facet of creativity lies not in the final
product, but in the process itself. Envision
a Master Chef contestant, orchestrating a
culinary symphony with a keen eye for novelty
and a daring spirit to match the time and
ingredient constraints set by Gordon Ramsay
and his colleagues. Their masterpiece
unfolds as an intricate dance of unexpected
ingredient pairings, artistic presentations,
and innovative use of techniques, equipment,
and resources. Here, creativity is not solely
defined by the outcome but by the culinary
journey that unfurls, tantalizing taste buds
and challenging preconceived notions of what
can be done with limited resources. Similarly,
improvisational theater values the performers'
on-the-spot thinking, synchronized action,
and narrative creation, as much as the final
performance. The process is integral to
determining creativity. Even in organizational
settings, the sequential motions inherent
in problem-solving —brainstorming,
experimentation, and collaboration—
are regarded as creative, alongside the
effectiveness of their end solution.
HUMAN EXPERIENCE IS WHERE THE
REAL ISSUE LIES
Despite known limitations, numerous
instances exist where works co-created with
AI have been recognized for their creativity.
Last year, a digital image generated by AI
won a statewide art competition in Colorado.
The judges affirmed that their decision to
honor the contestant would have remained
the same, regardless of prior knowledge of
AI involvement in the artwork. In April of this
year, a song that employed AI to generate
melodies in the voices and styles of popular
artists Drake and The Weeknd, went viral on
social media. Titled 'Heart On My Sleeve', this
track mimicked the stars' distinctive styles
in verses ostensibly about pop sensation
Selena Gomez, who has romantic ties with
The Weeknd. The song was widely lauded for
its innovative stylistic fusion and its infectious
rhythm. Similarly, in corporate environments,
generative AI has been employed to aid
the development of innovative marketing
campaigns as well as fundamentally novel

and useful business strategies that managers
can build upon and implement. As such, AI
capabilities continue to improve over time, it's
becoming increasingly apparent that there's
little pushback against the technology’s
ability to generate works that are novel and
valuable, provided that creativity is interpreted
from a product oriented perspective. Hence,
the primary criticisms against AI's capability
to produce or enhance creativity stem from
adopting the process-centric one.
Valuing process over product often comes
with an emphasis on the emotional
and sensory journey inherent in human
imagination and innovation. This viewpoint
suggests that the true value of creative
work is deeply entwined with the feelings
and shared experiences manifested in its
creation. As AI produces creative works
based on learned patterns– without true
5. https://bit.ly/3LKyHY8
comprehension of our intentions, history,
or emotions– creations that leverage it are
seen to lack the depth and meaning that
gives value to the creative process. Thus,
for the many patrons of the human touch,
any process void of these elements loses
their usefulness automatically. Singer and
songwriter Nick Cave eloquently expressed
this very sentiment when reacting to a song
written by AI chatbot GPT in 'his style':
ARE AI CO-CREATIONS
REALLY DEVOID OF
HUMAN EXPERIENCE: A
CASE STUDY
In December of 2022, an intriguing event
unfolded in the creative world. One, that
invites reflection into the humanity behind AI-
co creations. Aamar Reshi, then a tech worker
in Silicon Valley, who had no prior experience
in graphic illustration or creative writing,
produced a children’s book in the span of 72
hours and sold 841 copies in Amazon over
a week. His secret sauce? OpenAI's Chat
GPT for the story narrative, and the AI art
generator, Midjourney, for the illustrations.
This well-documented accomplishment
represents an interesting shift in the creative
landscape, as tasks that traditionally
demanded years of learning and skill honing
were executed by Aamar in a mere three
days—and at virtually no financial cost.
A crucial aspect of this narrative is that
Aamar circumvented the laborious grind
of mastering digital design and storytelling
intricacies. His main inputs, as documented
on his Twitter feed5
were two-fold: textual
prompts that generated the narratives and
illustrations found in his book, and his clever
use of these digital tools to construct a
coherent piece in a limited amount of time.
“Songs arise out of suffering, by which
I mean they are predicated upon the
complex, internal human struggle of
creation and, well, as far as I know,
algorithms don’t feel. Data doesn’t
algorithms don’t feel. Data doesn’t
suffer. ChatGPT has no inner being,
suffer. ChatGPT has no inner being,
it has been nowhere, it has endured
it has been nowhere, it has endured
nothing,
nothing, it has not had the audacity
to reach beyond its limitations, and
hence it doesn’t have the capacity for
a shared transcendent experience,
as it has no limitations from which to
transcend. ChatGPT’s melancholy
role is that it is destined to imitate and
can never have an authentic human
never have an authentic human
experience, no matter how devalued
experience, no matter how devalued
and inconsequential the human
and inconsequential the human
experience may in time become.”
experience may in time become.”

Trial and error was central to his creative
process, as he experimented with different
prompts to craft his desired manuscript
and illustrations. What used up most of his
time was learning to maintain a consistent
depiction of his protagonists, Alice and
Sparkle on Midjourney. Yet, the conversion
of his imagined images and plot ideas into
tangible illustrations, descriptions, and
written stories required merely a few seconds
of waiting time for each iteration. While
Aamar's journey showcases the power of AI
to democratize the creative process, it also
highlights the pitfalls of such an approach.
His illustrations lacked consistency and
detail, likely a result of his over-reliance on AI
tools and his lack of domain expertise in the
digital arts. In the end, Sparkle, Alice's robot
companion, was rendered differently across
each page due to Midjourney's inability to
produce consistent illustrations from the
same descriptions. Alice, too, was not spared
from inconsistencies, depicted with missing
fingers on occasion.
THE CREATIVITY AND HUMANITY
BEHIND AAMAR’S CO-CREATION WITH
AI
Aamar was innovative in his clever use
of limited resources to solve a pressing
challenge: creating a children's book.
Although he did not utilize traditional
artistic techniques or software, his co-
creation with AI served as a conduit for
transmuting his imagination into tangible
prototypes that allowed him to develop
a novel plotline through experimentation
with various prompts. Confronted with the
issue of inconsistent images, Aamar applied
his human ingenuity to devise a clever
solution: describing Sparkle to be a robot
that metamorphosed into various forms- a
creative fix that cohesively blended with his
narrative.
As noted, his case also illustrates the
democratization and streamlining of creative
work. Even if he lacked formal training in
graphic design and had no prior experience
as an illustrator or storyteller, he was still
able to conceive an original, interesting
story that had (somewhat) coherent and
meaningful illustrations. In essence, he came
up with creative solutions to turning his fresh
ideas into a tangible product which found
significant demand, and hence– value, upon
its release. And although the usefulness of
his work is limited by the inconsistent and, at
times un-detailed, illustrations –a limitation
which might diminish as AI technology
continues to evolve and improve– the
evidence suggests that Aamar’s final product
is in fact, creative - i.e. novel and useful.
Despite the innovative manner in which he
developed his storybook however, the value
in his process remains questionable to
those who value the human elements which
underlie creativity production. Therefore,
the query looms: was his work void of the
humanity that– arguably– gives meaning,
depth, and usefulness to the creative
process?
Not only did he “borrow” the feelings and
emotions nested in the collective intelligence
within Chat GPT's memory to produce his
plot, dialogue, and illustrations, but upon
further contemplation, much of his process
actually involves a variety of inherently
human attributes. The excitement he felt
with his work, the love he felt for his niece
that sparked this project, the oscillations
between euphoria and melancholy during
each imaginative iteration, and the victorious
sensation he savored as he reveled in
his accomplished masterpiece were all
profoundly human experiences and emotions.
In the parlance of Nick Cave’s critique: his
blood, sweat, and guts coalesced into a
tangible expression of creativity– there at
his desk– a realization of a nebulous idea

that made its way to him. That is- within
the vast expanse of algorithmic and artistic
unpredictability, his creative idea found him.
In all his humanity. And he made it come
to fruition in three relentless days. Thus,
Aamar’s case illustrates that the process of
co-creation with generative AI can, and often
does, involve quintessential human aspects
where innovation emerges from processes
and ideas that are new and valuable.
REFLECTIONS ON THE
GENERALIZABILITY OF THESE CASE
TAKE-AWAYS
For those of you who have used AI to
generate works that were considered
novel and highly valuable by your peers,
organization, or audience-evaluators, perhaps
it is time to reflect and appreciate the inherent
humanity in your creative work. For those of
you who haven’t, you are invited to envision
what such a process should involve as you go
through the next sentences.
Think of instances where you brainstormed
ideas or developed potential solutions
through a conversation with Chat GPT.
Maybe there were times when you involved
generative AI in creating a business proposal,
an artistic illustration, a musical piece; or
perhaps a scientific publication, an innovative
product, or even a clever recommendation
that was, in fact, considered original and
beneficial. Did your creative journey involve
the emotional roller coaster of highs and
lows? The frustration felt when ideas fail? The
iterative cycles where you leveraged multiple
tools and information sources in inventive
ways to achieve a part of your desired
outcome?
Did you harness feelings and intuitions
from your gut? Did you rely on tacit
heuristics and knowledge formed from
years of accumulated experience and social
interactions deeply embedded in your human
psyche? If the answer to some of these
questions are a yes, then it only shows that
Aamar’s experience was not an isolated case-
but is, in truth, a generalizable one.
These aspects are integral to our humanity–
our shared experience– and they would very
likely have been present in the generative AI
co-creation instances that you experienced
or envisioned. Even the journey to developing
your accumulated expertise in whatever
it is you do involves painstakingly human
ways in which you labored to sharpen them.
More people need to be reminded that the
knowledge and skill that you and I have
developed is critical to both evaluating and
building upon the intermediate outputs
produced by AI to produce works that are
actually novel and useful.
Indeed, the route to producing work that
is genuinely innovative, with or without
AI's assistance, invariably involves a
unique recombination of our lived human
experiences and abilities. As can be drawn
from your personal cases, and that of Aamar
Reshi’s, creators often employ a range of
tools, techniques, and information sources
to generate value and endure iterative
procedures that are seldom smooth and free
of emotional dynamics. As such, so long as
humans remain in the production loop, any
creative process that leverages generative AI
still retains significant traces of our shared
experience and human nature.
WHEN DOES CO-
CREATING WITH AI HARM
CREATIVITY THEN?
As with all tools that streamline processes,
there is always a danger that individuals
might over-rely on them, progressively
depending less on their abilities and unique
value contributions. In this case, such a
trend could lead to a reduced cultivation of

both individual creativity and the essential
skills relevant to creative production—be it
mastering the use of a paintbrush, crafting
a riveting narrative for a target audience,
evaluating the aesthetics of a presentation
deck, or steering a company brainstorming
session. As AI takes up an increasing part of
the creative process, our aptitude for ideation,
improvisation, and critical thinking may begin
to fade.
Similarly, when individuals overestimate
AI’s ability to generate value, there is also a
tendency to bypass activities that cultivate
our ability to generate the novel and useful.
Examples include discussing our ideas with
our colleagues (as opposed to just chatting
with an LLM about them), engaging in
exploratory learning, or improving the depth
of our specific professional expertise. The
ease of producing AI-generated outputs that,
at first glance, might seem highly innovative
and valuable, might also cause a drop in
motivation to engage in creative work - i.e.
the question: 'If AI can generate creative
works with relative ease, why should I expend
the effort?' People need to understand that
the path is often an arduous, emotionally
tumultuous one, and cases where new and
useful products are developed with relative
ease are very much the exception rather
than the norm. Moreover, projecting into the
future, if AI does advance to the extent that
it eliminates the need for substantial post-
processing work, several prompt iterations,
inventive ways to combine different tools
and knowledge inputs to produce a novel
and useful work– and well, all the emotions
that come with these– would that signal
the demise of creativity? It definitely is a
possibility. If co-creating with generative AI
results in fewer problems that demand new
and impactful solutions, then creativity may
diminish simply because we would need less
of it. But that is, by all means, a good problem
to have.
CONCLUSION
It is imperative that individuals learn to
co-create with generative AI tools both
responsibly and proficiently. The outlined risks
to our creativity demands an understanding
that these technologies are not replacements
for our own cognitive ability and domain
expertise. Neither are they supposed to be
used as quick-fix mechanisms for producing
content (e.g. essays, images, or sounds) with
scant surprise or quality appeal. Instead,
individuals should engage with these tools
in ways that stimulate their critical thinking,
challenge them to push the boundaries of
convention, and inspire them to conceive
ideas, products, artworks, or business
processes that are not only distinct from
predecessors but also more efficient, value-
enhancing, and superior in quality. And all of
this begins with understanding that the path
to truly creative co-creation with generative
AI is a painstaking, iterative, and exploratory
process that requires novel ways to combine
our cumulative human experiences,
imaginative capacity, and knowledge with the
current capabilities of these technologies.
Such a paradigm shift necessitates
substantial investment from organizations,
educational institutions, and even
governments in programs designed to enable
and encourage these exploratory practices.
Experimentation, after all, benefits from
guidance and often comes at the cost of not
getting traditional work or schooling done. But
this should not be a cause of worry. We have
already witnessed select groups of individuals
and organizations leveraging generative AI
in new and useful ways that showcase their
unlocked creative potential. Business news
feeds and popular technology sites such as
TechCrunch, Product Hunt, and VentureBeat
are filled with a rich variety of new use
cases each week. Hence, it is conceivable
that support for such endeavors are likely
to come. And, as history has demonstrated,

©
Rod
Long
on
Unsplash

when the innovative use of AI enables select
groups of people or organizations to excel in
their niche, gain a competitive advantage, or
simply overcome their peers, then others will
emulate their strategies– fueling creativity
and perpetuating the cycle of innovation.
Will AI spell creativity’s demise, or could it
instead ignite a renaissance of sorts? If the
concern lies in losing the humanity behind
the creative process, then, so long as humans
are involved in the creation process, and that
problems and needs that require novel and
useful solutions, approaches, or products
continue to exist, then the more optimistic
of the two scenarios is likely to materialize.
In other words, AI may well just revolutionize
creativity for the better.
There are, however, a few other concerns
that need to be accounted for, such as the
lack of acceptance or understanding behind
the value that these generative technologies
bring. Particularly relevant as well is how
increasing AI adoption inevitably creates
higher standards for what is valuable, truly
unique, and feasible to accomplish within
a given period of time. The sequel to this
article attempts to summarize all of these
other concerns, building on the evidence
and logical arguments presented in this first
part to more robustly answer the tantalizing
question behind AI’s impact on creativity.
Importantly, this second installment will
underscore the necessity to shift our focus.
The imminent issue may not be a potential
dwindling of our ingenuity, but rather a
constellation of critical factors surrounding
the perception and common understanding
regarding what it takes to co-create ideas,
processes, or products with AI that are truly
novel and useful. There's also a pressing
need to consider the protective measures
extended to workers who are at the interface
of AI's influence. For instance, while AI may
not necessarily stifle overall creativity, it
holds the potential to extinguish the arts if
considerations around the valuation of artistic
capabilities and the protection of artists'
intellectual property are not meticulously
examined. These will all be touched upon in
the sequel of this two-part article series.

THE AI CREATIVE
RENAISSANCE:
THE IMPACT OF CO-CREATING WITH AI
ON CREATIVITY AND THE FUTURE OF
WORK
A
I's march into the realm of creativity
has been teeming with trepidation,
stemming from fears that increasingly
sophisticated machines might eclipse our
ingenuity and devalue the human experience.
Dissecting the intricacies of co-creating
works that are deemed creative– i.e. deemed
both novel and useful – with generative AI in
the first installment of this two-piece article
series however reveals an inherently human
process. A dance that involves iterative
bouts of innovative experimentation, unique
amalgamations of tools and ideas, and a
critically overlooked component – emotion.
The realization of these intensely human
aspects offer a distinctly more hopeful
perspective, contingent upon us remaining
actively involved in the process.
Transitioning from the debate concerning
the retention of humanistic elements in AI
co-creation – elements that imbue depth,
meaning, and value to the creative process,
as discussed in this article’s predecessor,
this installment aims to elaborate more
on the benefits, limitations, and long-term
challenges to creativity that arise from
this generative process. The question of
whether AI could potentially spell the demise
of creativity in the long-term is ultimately
addressed, followed by a conclusion that
steers the discourse towards identifying more
pressing concerns about AI that will require
much of our ability to provide novel and useful
solutions.
By NELBERTO NICHOLAS QUINTO
PhD student in the Management department at ESSEC Business School

RECAPPING THE
CREATIVE BENEFITS TO
LEVERAGING AI
Creativity is understood as the generation
of ideas, processes, or products that are
both novel and useful1
. When understood
as an ability to produce works that meet
this two-fold criteria of novelty (uniqueness,
originality) and usefulness (value, quality),
both the outcomes and processes inherent
in generating them become relevant. One
of the most widely observed benefits of
co-creating with generative AI is that it
1. Teresa M. Amabile et al., “Affect and Creativity at Work,” Administrative Science Quarterly 50, no. 3 (September 1, 2005):
367–403, https://doi.org/10.2189/asqu.2005.50.3.367.
Teresa M. Amabile, “The Social Psychology of Creativity: A Componential Conceptualization.,” Journal of Personality and
Social Psychology 45, no. 2 (August 1983): 357–76, https://doi.org/10.1037/0022-3514.45.2.357.
streamlines and democratizes the process
of creative production. By curtailing the
costs related to skill, talent, and equipment
(or software), AI facilitates the genesis of
valuable, new creations – be they illustrations,
poems, marketing slogans, or strategic
proposals. This empowerment invites a
wider demographic to unlock their inherent
creative potential and engage in the human-
AI symphony of creation. Take, for instance,
the case of Aamar Reshi discussed in detail
in the first part of this article series. His
imaginative journey to crafting a children's
storybook in 3 days without any prior
experience in illustration or creative writing
©
Matthew
Henry
from
Burst

was made possible by AI's ability to translate
his motivation into captivating illustrations
and engaging storylines.
AI also significantly lightens the cognitive
load associated with conceiving original
solutions to intricate, pressing problems. For
instance, imagine a marketing team trying
to brainstorm a new advertising campaign.
Instead of spending hours coming up with
basic ideas, a large language model (LLM)
such as Chat GPT could generate a list of
them within minutes. The team could then
immediately start discussing which of these
listed ideas are worth developing further. They
could also combine different AI-suggested
concepts to create something unique and
impactful. In this way, AI allows for more
effective use of the team's expertise and
creative thinking. And while much of the
content produced by LLMs tends towards
the mundane and predictable, this in fact
offers a crucial advantage. The immediate
availability of a broad spectrum of highly
conventional ideas allows individuals and
teams to swiftly dispatch with the obvious,
learn from these iterations, and refocus
their cognitive prowess. In the context of
prototyping, generative AI tools have emerged
as a catalyst for quickly transforming abstract
concepts in our heads into tangible, useful
drafts. They shoulder the cognitive and labor-
intensive burden of the initial groundwork,
generating the first iterations swiftly. As a
result, just as in brainstorming, teams can re-
allocate their mental energy and time towards
more creative tasks, including those where
human expertise still surpasses AI.
©
Charles
Deluvio
on
Unsplash

AI’S IMPACT ON
QUALITY STANDARDS
PERPETUATES
CREATIVITY
As we hurtle into a future fraught with
increasingly complex challenges requiring
novel solutions, it's clear that both creativity
and generative AI’s role in the creative
process is here to stay. While individuals
will continue to extract value from AI, the
benchmark for what constitutes quality
and usefulness will concurrently increase.
When productive expectations rise, fostering
creativity and innovation to meet these
heightened standards will always be a need,
and often, a priority. While the influx of novel
combinations of information and ideas might
make the task of generating something truly
different and unique with AI progressively
challenging as well, it will undeniably
necessitate increasingly creative methods
to continuously derive value from current
tools and systems. Thus, regardless of how
sophisticated AI systems become, creativity
will always have a place within organizations
and society.
For instance, in producing digital art, some
graphic designers are already leveraging AI
image generators such as Midjourney and
Stable Diffusion to simulate prototypes of
their ideas, draw inspiration from different
styles, or ultimately create distinct artworks
that require minimal post-processing. At first,
such use of AI was deemed innovative, and
there have been many cases where fresh
and valuable works have been produced
through such a process. But as leveraging AI
capabilities have become more widespread,
the novelty of such techniques have declined,
and the average uniqueness of generated
works have suffered as well. Consequently,
the standards for what is considered useful
have risen as more people have realized the
value of current AI tools. Artists must then
deepen their creative explorations, finding
fresh ways to collaborate with AI to generate
art that remains innovative and valuable
amidst the evolving landscape. This may
involve countless experimentations with
prompt patterns or combining different
tools, systems, or methods to process works
generated by AI.
Meanwhile, in organizational settings,
particularly when teams make use of
Large Language Models (LLM), such as
OpenAI’s ChatGPT or Google’s Bard, to
streamline brainstorming sessions, catalyze
idea generation, and decode complex
problems– the interplay between creativity
and AI unfolds in the same manner as in
the arts. Consider a tech start-up using
GPT technology to augment their product
design brainstorming. The AI solutions
might generate new perspectives on user
interface design, providing inspirations that
the team hadn't previously considered.
Companies that successfully integrate such
technologies into their workflow stand to
gain a competitive edge, as they can alleviate
the cognitive burden inherent in creative
tasks and propel their innovation teams
into uncharted territories. However, as AI-
assisted approaches become commonplace,
the novelty of these processes diminishes.
As more and more employees, teams, and
organizations become accustomed to
harvesting the creative benefits of AI across a
spectrum of tasks, the standard for what can
be achieved within a certain timeframe and
resource set escalates exponentially.
In response, organizations would need to
persistently cultivate creativity to extract
further value from AI. They might deploy
additional algorithmic tools to discern
patterns from past AI-laden brainstorming
sessions and predict potential hurdles.
For example, a company could use AI to
analyze both previous meeting notes and
past AI suggestions given various employee-

generated GPT prompt patterns. This would
allow individuals and teams to leverage
insights derived from such data analyses to
consequently modify their use of generative
technologies for idea development and
prototype-building. Such a solution could also
lead to routinized processes and systems
that facilitate extracting more value from
novel AI suggestions in order to suit their
unique problem contexts. For example, a
marketing team could develop protocols for
how to synthesize campaign ideas developed
through multiple rounds of brainstorming
with generative AI, across several meeting
groups. They could also devise a structured
process that involves integrating these
insights with those uncovered by social
media trends, competitor campaigns, and
customer behavior data that predictive AI
models concurrently deliver.
In such instances, creative production
necessitates innovation in processes where
different individuals and AI systems come
together to meet the new, heightened
standards for novelty and value that
innovation and competition propel. However,
when novel processes or new best practices
are found to be creative at a given point in
time, more and more companies are likely to
find value in them. This implies that standards
will rise again and organizations would need
to search for more ingenious processes that
leverage existing human and technological
capital, fostering creativity and perpetuating
its need.
THREATS TO
CREATIVITY: UNDER-
APPRECIATION AND
OVER-RELIANCE ON AI
Instead of pondering the supposed demise
of creativity, perhaps the real issue at hand
is the skepticism and under-appreciation of
the immense value generative AI brings to
the table. It is unsettling to see how quickly
some individuals abandon the use of these
©
Vonecia
Carswell
on
Unsplash

technologies, swayed by a few erroneous
outputs, unsuccessful prompts, or the
cynicism of others. On the flip side, there
exists an equally troubling group – those
over-reliant on AI to the extent that they
forsake nurturing their own critical thinking,
domain expertise, and breadth of knowledge.
This excessive dependency threatens to
hollow out human innovation and intuition,
reducing our contributions to mere button-
pressing reactions to whimsical needs. The
remedy to both of these conundrums lies in
fostering a comprehensive understanding of
AI's capabilities and limitations among the
broader population, as discussed in more
detail in the first piece of this two-part series.
There is simply so much value-creation lost
when people do not simply understand the
usefulness of generative tools that can rapidly
produce creative drafts and prototypes ; all
while harnessing centuries of accumulated
human knowledge to yield accurate, factual
results in at least 9 out of 10 instances. As
such, there is a pressing need to educate
individuals about applying even basic
generative AI capabilities to the multitude of
use cases in their personal and professional
lives. This requires promoting practices that
encourage persistent experimentation with AI,
while fully acknowledging its current bounds
and how it can complement our unique
strengths.
THE SOLUTION:
CONTINUOUS
EXPLORATION OF AI-
HUMAN BOUNDARY
CAPABILITIES
AI will continue to improve, and so too
will our abilities, skills, and talents. In this
constant cycle of progression, the necessity
of understanding the evolving capacities
of AI and human creativity cannot be
overstated. Identifying the complementary
intersections between AI and our innovative
capacity enables us to effectively harness
their combined potential. And this begins
by ensuring that we remain determined to
cultivate the requisite knowledge, expertise,
and capabilities to credibly evaluate the
usefulness, appropriateness, and credibility of
AI generated outputs.
In this dynamic panorama of evolving AI
systems and expanding human capabilities,
the value of experimentation in demarcating
the ever-changing boundaries of both AI and
our personal abilities becomes paramount.
In particular, this knowledge helps illuminate
our understanding of what AI can and cannot
do for us, and what we can achieve more
efficiently with or without these technologies,
for any given moment in time. It also enables
us to identify which domain-specific skills
and new capabilities we should invest our
time in developing and refining. And as
we navigate this blurred frontier, the role
of continuous learning, engagement, and
development of our unique creative abilities
vis-a-vis AI becomes ever more critical.
While the “death of creativity” is far from
imminent, the reshaping business and
societal terrain calls for both prudence
and immediate action. As AI emboldens
individuals and organizations to leverage
technology to augment their unique
capabilities and cumulative expertise,
navigating this evolving landscape thus calls
us to reconsider our part in the redefined
creative epoch. Are we disrupting, merely
keeping up, or falling behind? Survival
in competitive environments, after all,
necessitates exploiting the opportunities
emerging technologies offer, and we should
therefore set aside time in our schedules
to explore ways we can achieve this at a
personal level. Again, this begins by carefully
discerning what both we and AI uniquely
excel in, and identifying potent synergies that

allow us to balance each other's strengths
and weaknesses for our specific trade and
tasks. Whether you are a marketer, musician,
illustrator, business owner, or a corporate
planner, understanding how emerging
technologies affect the value and novelty
you produce at any given point in time is
paramount to continued success. Stop. Think.
Reflect. What critical inputs, processes, and
skills does AI need from you to deliver in
order for you to generate ideas, products, and
systems that are new and valuable? What
are you doing to know or develop this? Your
answers to these questions may well define
your survival amidst AI’s creative renaissance.
BEYOND THE ISSUE OF
CREATIVITY: WHERE
MORE PRESSING
CHALLENGES LIE
While this thought exploration attempts
to address whether AI would extinguish
the flame of human creativity, it inevitably
leaves a myriad of related issues unexplored.
Indeed, while AI, with its prodigious generative
capacities, promises to herald a creative
renaissance—exploring uncharted territories
of ideas and unveiling transformative
solutions to pressing issues—we must also
recognize the potential detrimental impact
it could have on our artistic workforce. As
discussed, the process of co-creating with
generative AI still necessitates an intricate,
often emotionally charged, and iterative
human endeavor. It involves the careful
orchestration of past human experiences to
weave into the fabric of our creations.
Yet a recurrent threat that we are treading is
the dangerous line of devaluing the authentic
human touch; that is– the artisanal signature
underlying much of the creative work we
know. Companies may start to undervalue
the finesse of artistic capability, leading to
reduced remuneration for graphic designers,
composers, and other artists. This, even
before a novice utilizing generative AI can
genuinely outperform seasoned creators.
Such devaluation can cause both current
and aspiring artists to neglect nurturing
their unique aesthetic skills and specialized
capabilities, which could be detrimental to the
future of creativity. After all, truly harnessing
the power of AI for creative endeavors
requires not just knowing its technological
boundaries, but also having a robust
foundation of one’s specialized domain
and the aesthetic sensibility needed to both
recognize and conjure quality art.
Furthermore, we need to tread carefully on
the path of intellectual property (IP) rights.
Artists may feel aggrieved as their creative
genius– their unique output– is utilized to
train AI systems without due recompense or
consent. This could make it facile for others
to mimic their distinctive style, enabling
these individuals to build on years of the
artists’ painstaking dedication without due
permission or acknowledgement. If we fail
to establish robust mechanisms for suitable
compensation, recognition, and consent
for creative IP, we risk discouraging artists
from trusting and reaping the benefits of AI.
Worse, we risk a decline in traditional artistic
pursuits, which form the bedrock of cultural
heritage and individual expression. On a less
immediate yet significant impact, we risk
losing valuable creative contributions that
future generations could build upon. If we
deter a whole generation from pursuing arts
due to lack of passion or adequate incentive,
we lose more than just individual livelihoods.
The vibrancy of our cultural tapestry and
our collective ability to innovate are at stake.
It is therefore vital that we safeguard the
livelihoods and IP of artists to prevent cultural
impoverishment.
Moreover, while AI undoubtedly creates
new job opportunities and uncovers novel

synergies between human and machine to
drive value and discover novel solutions to
critical problems, the rapid pace at which
AI is reshaping the job market is cause for
concern. The velocity of job displacement
could potentially outpace that of job creation
and skill development across a wide-array of
fields. Its reach already extends to every facet
of work, life, and the economy, sometimes
unpredictably. Such an imbalance could
endanger a substantial segment of the
workforce, along with their dependents.
While AI is not poised to extinguish the flame
of creativity, it could expedite the ebb of
certain industries and livelihoods faster than
it rebuilds or expands them. This necessitates
an inventive approach to temper potential
fallout. Hence, the real merit of AI lies not
only in catalyzing and amplifying human
creativity to forge new solutions to high-value
issues, but also in innovating answers to
the challenges it itself surfaces– from that
of artistic preservation, intellectual property
rights, overly rapid job displacement, and
beyond.

SUSTAINABILITY

SOCIETY

D
o you ever feel like the pursuit of
economic growth has taken us down
a dangerous path, where the health of
the planet and its inhabitants are sacrificed for
the sake of financial gain? If you are nodding
your head in agreement, then continue reading
because we are about to dive into a fascinating
topic: degrowth.
In our current global society, the growth-based
economic model has dominated for too long,
leading to environmental degradation and social
inequality1
. Fortunately, an alternative concept of
degrowth has emerged, promoting a supposedly
sustainable and more equitable way of life.
However it does not surprise us that regardless,
technological advancement and digitalization
continue to shape and transform our world in
profound ways that could seem inevitable.
1. Hickel, J. (2020). Less is More: How Degrowth Will Save the World. Penguin Random House.
2. Degrowth Movement. (2023). Degrowth. Retrieved from https://degrowth.info/degrowth
In this article, we will explore the intersection
of degrowth and technological advancement,
and critically analyze their intertwined potential
implications in a global context.
DEFINING DEGROWTH
Degrowth is a concept that challenges the
idea that economic growth is necessary
for human development and wellbeing. It
is based on the principles of sufficiency,
resilience, and equity, and calls for a reduction
in production and consumption levels to
achieve a sustainable and equitable society.
2
While the concept of degrowth has its roots
in the 1970s, it has gained more attention
in recent years as a response to the current
ecological and social crises, however it also
raises some criticisms as such that degrowth
is too radical and impractical, while others
THE PROGRESS
PARADOX:
CAN TECHNOLOGICAL ADVANCEMENTS
COEXIST WITH A DEGROWTH
ECONOMY?
By RINALYN PAGAO
MSc in Sustainability Transformation at ESSEC Business School

claim that it overlooks the needs of those in
poverty3
.
TECHNOLOGICAL
ADVANCEMENT AND ITS
IMPACTS
Technological advancement has undoubtedly
brought about many positive changes to
our world, from medical advancements
to increased connectivity and access to
information. However, it has also been
associated with negative impacts such as
3. Victor, P.A. (2019). Growth, degrowth, and climate change: A scenario analysis. Ecological Economics. Retrieved from
https://www.ledevoir.com/documents/pdf/victor_growth.pdf
4. Jonas Hallstrom (2020). Embodying the past, designing the future: technological determinism reconsidered in
technology education. International Journal of Technology and Design Education, Retrieved from
environmental degradation, social inequality,
and job displacement. The debate around
technological determinism, the idea that
technology shapes society, versus social
constructivism, the idea that society shapes
technology, is still ongoing4
. Both views
have their merits, and the truth likely lies
somewhere in between as per what the
scholars suggest. While this debate is not the
focus of this article it is still important for us
to consider both perspectives when thinking
about the relationship between technology and
society, as this will help us to develop a more
nuanced understanding of this complex issue.
©
Anastasiya
Badun
on
Unsplash

EXPLORING THE
INTERSECTION: IS
TECHNOLOGICAL
INNOVATION AND
DEGROWTH POSSIBLE?
Technological advancements per se in the
sustainability sector are the renewable energy,
clean transportation, energy efficiencies, and
carbon capture and utilisation storage (CCUS)
- can these potentially be a powerful tool to
degrowth our economy?
The latest report done by the International
Energy Agency (IEA) on its Clean Innovation
Report: Global status of clean energy
innovation in 2020 5
acknowledged that
technological innovation is crucial for
addressing climate change and achieving the
goals of energy policy, such as expanding
access to energy and lowering air pollution.
5. IEA (2020), Clean Energy Innovation, IEA, Paris https://www.iea.org/reports/clean-energy-innovation, License: CC BY
4.0
However, it might be hard to monitor
innovation progress, specifically the major
challenge to be able to quantify or allocate
inputs to policy goals like more affordable
technology, industrial change, and economic
growth. Nevertheless, a number of measures,
including (1) funding and (2) patenting, might
provide insight into clean energy innovation
on a worldwide scale. More comprehensive
sets of measurements are being created by
some governments in order to find and share
best practices.
• FUNDING
This trend (see: IEA public energy technology
RD and demonstration spending by
technology, 1977-2019) tells us that the
government funding on energy research
and development increased by 3% in 2019
to USD 30 billion globally, with over 80% of
that money going toward low-carbon energy
technology. Specifically in China, the low-
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Harper-Sunday
on
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carbon component of energy research and
development increased by 10% in 2019,
with significant increases in research and
development for energy efficiency and
hydrogen in particular. Spending on public
energy RD increased by 7% in both Europe
and the United States, exceeding the previous
year's trend.
• PATENTING
On the other hand, in terms of patenting
since 2011 (see: Issuance of patents for
low-carbon energy technologies in selected
countries and regions, 2000-2016), the
quantity of patents submitted for low-
carbon energy technologies has sharply
decreased after a decade of rapid increase.
Patents capture part of the intermediate
RD outputs, a percentage of which will be
converted into commercial products, and so
offer a window into the research operations
that are producing new information with a
view toward its perceived commercial value.
However, general patenting trends offer
us some insightful data on the scope and
direction of clean energy innovation.
The drop in renewable energy patenting
activity from roughly 2011 may be due to
the maturity of some technologies. The
dominance of existing solar PV, bioethanol,
and wind technologies may discourage
researchers from striving to improve them
and enter the markets in Europe, Japan,
and the United States. Moreover, renewable
energy patenting continues to be more active
than it was before approximately 2007, and
Li-ion battery patenting, in particular, is
expanding (EPO and IEA, 2020).
Now that we have built a solid foundation
on what constitutes a green technological
innovation, what begs a question here is
6. Hickel, J. and Kallis, G., 2019, ‘Is Green Growth Possible?,’ New Political Economy, DOI:
10.1080/13563467.2019.1598964
that how could it intersect with the degrowth
principle? In the publication done by Hickel
and Kallis (2019) they investigated and
tried to answer: is green growth possible?6
According to the green growth theory,
sustained economic expansion is consistent
with our planet’s ecology because technology
change and substitution will allow us to
completely disconnect GDP growth from
resource use and carbon emissions. This
claim is increasingly assumed in national and
international policy, including the Sustainable
Development Goals. Green growth has
developed as a major policy response to
climate change and ecological disintegration.
However, empirical evidence on resource
utilization and carbon emissions does not
support green growth theory. After reviewing
relevant papers on historical trends and
model-based projections, this research study
conducted reveals that:
“(1) there is no empirical evidence that
absolute decoupling from resource use
can be achieved on a global scale against a
background of continued economic growth,
and (2) absolute decoupling from carbon
emissions is highly unlikely to be achieved at
a rate rapid enough to prevent global warming
over 1.5°C or 2°C, even under optimistic policy
conditions. We conclude that green growth
is likely to be a misguided objective, and that
policymakers need to look toward alternative
strategies.”
Hence, even looking at the intersection
between the myriad of technological
innovations we have reached today, especially
the energy transition needed to net zero
emissions by 2050 commitment, the promise
of a sustainable future for our current and for
the next generation is still not guaranteed.

PARADOXES OF
TECHNOLOGICAL
ADVANCEMENT AND THE
DEGROWTH
In this section, let’s dig deeper on the four
main paradoxes that hinders technological
advancement toward sustainability and
degrowth: (1) decoupling growth from
resource consumption, (2) e-waste
generation, (3) conflicting power and politics,
and (4) cultural and social implications.
1. DECOUPLING GROWTH FROM
RESOURCE CONSUMPTION
Degrowth advocates for a reduction in
production and consumption levels to achieve
a sustainable and equitable society7
. However,
this poses a challenge in a world where
economic growth is closely tied to resource
consumption. This means that if we want to
reduce production and consumption levels,
we will also need to reduce economic growth.
This is a challenge because economic
growth is seen as essential for prosperity
by many people. There are a number of
ways to address this challenge. One way is
to change the way we measure economic
growth. We could focus on measures of well-
being, such as life expectancy, happiness,
and environmental quality, instead of GDP.
Another way is to decouple economic growth
from resource consumption. This means
finding ways to grow the economy without
increasing resource consumption.
While technological advancements can
7. Kallis, G. (2011). Degrowth: A vocabulary for a new era. London: Routledge.
8. Global Footprint Network. (2019). Ecological Footprint and biocapacity of 209 countries and territories, 1961-2016.
Retrieved from https://www.footprintnetwork.org/content/documents/2019_Country_Fact_Sheets.pdf
9. International Telecommunication Union. (2020). The Global E-waste Monitor 2020. Retrieved from https://www.itu.int/
en/ITU-D/Environment/Documents/Reports/GEM_2020_report.pdf
10. World Health Organization. (2018). E-waste and children’s health. Retrieved from https://www.who.int/ceh/
publications/e-waste-childrens-health/en/
facilitate the transition towards renewable
energy and more efficient production
processes, it is unclear whether they can
enable a complete decoupling of growth
from resource consumption. According to
the Global Footprint Network, achieving
sustainable resource use would require a
reduction in resource consumption by roughly
75% in high-income countries and 90% in
middle-income countries8
. This would be
challenging to achieve through technological
advancements alone. In addition, the findings
in the recent study stated that while energy
and material efficiency improvements have
reduced the amount of resources required
for each unit of GDP, the overall consumption
of resources has increased due to economic
growth.
2. E-WASTE GENERATION
According to the United Nations The Global
E-waste Monitor 2020, in 2019 there was
a record high of 53.6 million metric tonnes
(Mt) of electronic waste generated globally,
which is an increase of 21% in just five years9
.
E-waste is a term used to describe discarded
electronic devices and equipment such as
discarded electronic devices and equipment,
such as computers, mobile phones,
televisions, refrigerators, and air conditioners.
It may contain harmful substances, and can
pose significant risks to the environment and
human health if not managed appropriately.
The production of e-waste is increasing
quickly due to advances in technology and
the popularity of electronic devices among
consumers10
. As a consequence, it imposes

potential conflicts between degrowth and
technological advancement. The increasing
levels of e-waste, low collection rates,
and non-environmentally sound disposal
and treatment of this waste stream pose
significant risks to the environment and
human health. Also, as technology advances,
older devices become obsolete and are
often discarded, leading to a significant
environmental impact11
. Hence, degrowth
principles call for a reduction in consumption
levels, while the technology industry relies on
continuous consumption and disposal of new
products.
3. CONFLICTING POWER AND
POLITICS
The implementation of both degrowth
and technological advancement requires
significant changes to the current global
economic and political systems, which
is a very challenging task. The dominant
economic and political actors may not be
willing to relinquish their power and privilege
to facilitate such changes. It can be seen in
the reluctance of many governments to adopt
policies that would limit economic growth or
reduce resource consumption.
Furthermore, this is exemplified by the failure
of the COP26 climate summit where we
all witnessed countries failing to agree on
crucial measures to limit global warming12
.
The International Energy Agency has also
warned the public that current climate
policies fall short of what is required to limit
11. United Nations Environment Programme. (2019). Global E-waste Monitor 2019.
12. United Nations. (2023). COP26: Together for our planet. Available at: https://www.un.org/en/climatechange/cop26
13. Oxfam International. (2022, November 8). Billionaire emits a million times more greenhouse gases than average
person. Retrieved from https://www.oxfam.org/en/press-releases/billionaire-emits-million-times-more-greenhouse-
gases-average-person
14. World Economic Forum. (2020). The Global Risks Report 2020. World Economic Forum. Retrieved from https://www.
weforum.org/reports/the-global-risks-report-2020
15. UNICEF. (2018). Is social media bad for teens’ mental health?, Retrieved from https://www.unicef.org/stories/social-
media-bad-teens-mental-health
global warming to 1.5°C above pre-industrial
levels, and rapid action is needed to avert
a climate catastrophe. In addition, there
are questions around who benefits from
technological advancements and whether
the benefits are distributed equitably. Finally,
a study by Oxfam International found that
the world’s wealthiest 1 percent emit more
than double the carbon emissions of the
poorest 50 percent13
. This highlights the need
for degrowth principles to reconsider and
move away from the mentality that growth
is good for the economy, instead prioritizing
sustainability, equity, and well-being of the
public over endless growth and consumption.
4. CULTURAL AND SOCIAL
IMPLICATIONS
Finally, a report by the World Economic
Forum found that the gender gap in the
technology sector is widening, with women
underrepresented in artificial intelligence and
other emerging technologies14
. Additionally,
the reliance on technology can also lead
to social isolation and a disconnection
from the world behind the screens of
one’s smartphones. This illustrates that
the development of new technologies can
reinforce existing power structures and
exacerbate social inequalities. In the article
published by UNICEF, it is found that social
media use was associated with higher
levels of anxiety and depression among
teens’ mental health15
. The findings reveal
that social media use may contribute
to anxiety and depression by increasing

social comparison, leading to feelings of
inadequacy, and providing a platform for
cyberbullying. However, it is important to note
that correlation does not equal causation, and
more research is needed for us to understand
the complex relationship between social
media use and mental health.
CONCLUSION
Throughout this article we have seen that the
intersection of degrowth and technological
advancement presents us with a complex and
nuanced picture for our future. Technological
advancement is the development of new
technologies that can improve our lives
in a variety of ways. On the other hand,
degrowth is a socio-economic paradigm that
advocates for a reduction in production and
consumption levels to achieve a sustainable
and equitable society. While both concepts
offer potential solutions to the ecological and
social challenges we face, we must recognize
their limitations and critically evaluate their
implications. Degrowth, for example, could
lead to a loss of jobs and economic growth.
Technological advancement hence could
have negative environmental impacts, such
as increased pollution and resource depletion.
The cultural and social dimensions of
technological advancements must also be
considered. For example, some technologies,
such as social media, can have negative
impacts on mental health. We must work
towards a more equitable and sustainable
global society, where everyone has access to
the benefits of technological advancement,
and where the negative impacts are
minimized. Ultimately, our goal is to find a
balance between sustainability and progress,
and to ensure everyone can enjoy the benefits
of technology without harming the planet or
ourselves.
KEY TAKEAWAY
1. Technology is a tool, not a solution.
It can help us address environmental
challenges, but it cannot solve them on
its own. We need to use technology in
combination with other approaches, such
as degrowth and social change.
2. Achieving both degrowth and
technological advancement would
require significant global changes. These
changes would be difficult to achieve due
to political and economic complexities.
3. In our current economic system, which
is driven by growth, it can be challenging
to reduce production and consumption
levels. This would require a fundamental
shift in the way society and the economy
operate.
4. Technology has both benefits and
limitations. It can improve our lives, but
it can also create new problems and
exacerbate existing ones.
5. To achieve just sustainable economic
transition, we need to recognize the
complex and interconnected nature of
our environmental, social, and economic
challenges. Developing solutions that
address all of these challenges is needed
simultaneously.

ATTENTION
ECONOMY:
YOU’RE NOT
PAYING ENOUGH
ATTENTION
WHAT IS THE
ATTENTION ECONOMY?
E
conomics is the study of scarcity 1
;
from wealth, food, energy, or even
time. Otherwise known as human
attention. The latter example might seem
odd. Nevertheless, human attention is in fact
a scarce resource. One that is intangible, but
is nevertheless invaluable. After all, of the 24
hours we have access to a day, one third we
spend sleeping.
Every time we decide to focus our attention
on a particular task, our entire cognitive
resources are directed to that one task at
the expense of others. In economic terms,
spending time focusing our attention on a
1. https://www.merriam-webster.com/dictionary/economics
specific aspect of our environment carries
an opportunity cost, or the foregone benefit
that would have been derived from another,
unchosen task. Just like money, one can also
exchange attention, as we usually allocate
our attention to tasks in order to gain a
benefit, whether it is learning a new topic,
getting remunerated at work, taking care
of our health and body through exercise, or
releasing serotonin, endorphin or oxytocin by
engaging in a pleasurable activity. This small
analysis gives the idiom ‘paying attention’ all
its economical depth.
In this context, the attention economy, a
term first coined by psychologist, economist,
and Nobel Laureate Herbert A. Simon in
1971, can be defined as the mechanisms
By MICHELLE DIAZ MARINA PELLET -
Master in Management at ESSEC Business School
Master in Data Sciences Business Analytics at ESSEC
Business School CentraleSupélec

and strategies put in place to captivate the
scarce resource that is human brain time
to generate revenue2
. Everytime you pass
by an advertising board in the street that
successfully catches your attention, every
time your eyes deviate from the news article
you’re reading to that newest trendy shoes
ad on the side of the webpage, or every time
Instagram shows you a ‘suggested’ video that
you actually watch, you are participating in
the attention economy.
WHO ARE THE BIG
PLAYERS AFTER YOUR
ATTENTION?
2. BER staff. (March 31, 2020). Paying Attention: The Attention Economy. Berkeley Economic Review
As most people can guess, the stakeholders
after your attention are predominantly
technology, entertainment, social media
companies, in historical accordance with
the traditional media players: the press,
newspapers, TV channels, radio. All, to
some extent, are on the conquest of retaining
human attention. But in our modern times,
social media platforms have brought a new
dimension to capturing human attention.
Indeed, as most of them do not produce any
content themselves, their sole purpose and
main revenue stream is to sell available brain
time to advertisers.
In essence, there are two types of companies
after your attention, the subscription-
©
Andrew
Moca
on
Unsplash

based model and the advertising-based
model. In the first category, we have the
media and entertainment industry, like the
streaming companies: Netflix, Disney+, Hulu,
for example. In the second category, are
the social media platforms like Facebook,
Instagram, and Tiktok. Both rely on
consumers to actively and consistently use
the services provided, which results in tactics
to achieve said result, a feat these companies
have increasingly managed to do3
.
WHAT EMERGING
TECHNOLOGY IS DRIVING
THE ATTENTION
ECONOMY?
To sustain the audience or the consumer’s
attention, companies need to serve them
exactly the content they want. In the past,
companies did this by conducting market
research, adhering to what the market
3. Kemp, S. (July 20, 2023). Social Media Use Reaches New Milestone: User identities now equal to more than
sixty percent of the world’s population. Meltwater
deemed popular. Today, this market research
is bolstered by technology’s improved
capacity to collect more fine-grained,
instantaneous, and relevant data on human
behaviour through the various digital
platforms people use. Given the emergence
of artificial intelligence (AI), all this data can
now be fed into machine learning powered
algorithms that use relevant computational
techniques to better understand and predict
human preferences.
Nowadays companies are able to curate
content in unprecedented ways. And over the
years, platforms have successfully leveraged
big data and AI to maximise the time people
spend online. By collecting data every time we
like, comment, share, rewatch, scroll and post,
social media platforms are able to construct
extremely detailed profiles of their users
and their preferences. Such profiles are built
through sentiment analysis which is backed
by Natural Language Processing (NLP), the
branch of computer science—and more
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Winkler
on
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