Topos 132

no 132
2025
to po s.

COVER
PHOTO: Milad Fakurian on Unsplash
TYPOGRAPHY: Alexander Weiß
Once you've spotted it, you can't unsee it: The
brain on the cover is not surrounded by artfully
shaped white streaks. Instead, the letters of this
issue's title – AI Pioneers – bend around its
shape. Would an AI have recognised this?
It speaks fluently now – this thing we still call
artificial intelligence, though the term has long
since outgrown its own definition. It drafts our
emails, draws our buildings, answers our questions
before we’ve finished asking them. Sometimes
it lies. Sometimes it hallucinates. Always,
it responds.
And that, of course, is the seduction.
This issue of topos does not celebrate AI. Nor
does it warn you off. It does something more
dangerous: it takes the machine seriously.
For the urbanist, the architect, the planner, the
administrator of increasingly digitalised complexity,
AI is no longer a speculative force. It is
embedded – silently and exponentially – in everything
from traffic modulation to zoning
simulation, from energy grids to civic chatbots.
The city, once a physical terrain of political decision
and social negotiation, is becoming
something else: a system increasingly shaped
by systems.
But who built those systems? What values were
trained into them? What assumptions lie dormant
in the code? And – perhaps most urgently
– what happens when the simulation becomes
more legible than the street itself?
AI, as deployed in today’s urban contexts, is neither
neutral nor magical. It is a mirror polished
by scale. It reproduces the visible past with stunning
precision – and with it, the invisible exclusions.
It recommends what is common, not
what is just. It optimises for what already exists,
not what ought to be. And in doing so, it threatens
to turn the practice of urbanism into an act
of retroactive confirmation.
Cities, we are told, will be more efficient, more
intelligent, more predictable. But one might also
say: more predictable is less democratic. More
optimised is less open. And more intelligent – if
that intelligence is detached from judgement – is
not wisdom, but automation.
In these pages, you will find no techno-utopian
platitudes. You will find hackers who know
what it means to switch off a city. You will find
ethicists who question the morality of training
machines on stolen text. You will read about
model bias, infrastructural fragility, and the
quiet geopolitical centralisation of cognitive
power. You will see cities rendered by code –
and cities distorted by it.
And if we are lucky, you will begin to ask better
questions. Not “what can AI do for urbanism?”,
but: “what does it mean when urbanism becomes
a function of AI?”
Because in the end, the great urban question is
not one of tools, but of control. Who gets to
plan? Who gets to decide? And who – when the
lights go out, when the voice stops answering,
when the model fails – is still able to think?
This is not an issue about intelligence. It is an issue
about responsibility.
I hope you read it with curiosity, with discomfort
– and above all, with your mind firmly
switched on. With this in mind, I look forward
to your feedback, suggestions and all the discussions
that will be sparked by this issue.
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TOBIAS HAGER
Chief-Content-Officer
t.hager@georg-media.de
topos 132 005

CONTENTS
OPINION
Page 8
CURATED PRODUCTS
Page 100
THE BIG PICTURE
Page 10
METROPOLIS EXPLAINED
Page 12
WHEN CITIES LEARN
A City Portrait of Hangzhou
Page 54
URBANISM.EXE
How AI is Influencing Urban Futures
Page 16
THE DEVELOPMENT OF ARTIFICIAL
INTELLIGENCE
An Overview
Page 24
THE AI AUGMENTERS
AI Augmenting Architects at Foster + Partners
Page 26
THE NAVIGATOR
Generative Design Through Patrik Schumacher
Page 30
LONDON AI
A City Portrait of London
Page 34
THE STRUCTURISERS
MVRDV NEXT Between Research and Practice
Page 44
THE CONDUCTOR
Tim Fu on AI's Creative Potential
Page 48
SHADOW AND LIGHT
The Risks of AI in Planning
Page 52
THE CHOREOGRAPHER OF URBAN
INTELLIGENCE
Carlo Ratti on Human-Centered, Data-Driven
Urbanism
Page 62
THE CATALYST
Oliver Thomas Bridges Computation and Design
Page 66
THE ARCHITECT OF EMPATHIC INTELLIGENCE
Shicong Cao Champions Human- Centered Data
Page 68
ARTIFICIAL ILLUSIONS
The Unseen Cost of Intelligent Machines
Page 72
HELSINKI'S QUIET AI REVOLUTION
A City Portrait of Helsinki
Page 76
THE PURPOSER
Siegfried Zhiqiang Wu links AI to Planning
Page 84
THE PARTICIPANT
Dr. Yan Wang Shapes Urban AI Ethics
Page 86
CONTRIBUTORS
Page 98
CITY GAMECHANGERS
Page 112
EDGE CITY
Page 114
IMPRINT
Page 113
LOST IN THE ECHO
Page 90
Photos: Seele An on Unsplash; Nick Fancher on Unsplash
006 topos 132

OPINION
THE ONLY THING
WE HAVE TO
FEAR IS …
REGULATION?
008 topos 132

Opinion
Let’s be honest: no civilisation in history has
been so pathologically afraid of its own progress
as 21 st -century Europe. A continent that once
launched the Renaissance, split the atom, and
gave the world Bauhaus now trembles at the
mere mention of a machine learning model.
Artificial Intelligence – arguably the most
promising technological breakthrough since
electricity – is met not with ambition or excitement,
but with bureaucratic dread, academic
foot-dragging, and the mother of all regulatory
frameworks: the “German Angst”, which is now
increasingly becoming “European Angst”.
Let’s be clear. The European AI Act, for example,
is not just cautious – it’s neurotic. Designed
under the pretext of human dignity and safety, it
betrays a deeper pathology: a collective Western
panic in the face of exponential technological
change. While American tech giants iterate,
scale, and deploy with a boldness bordering on
recklessness, Europe reaches for the one instrument
it trusts more than innovation: regulation.
We don’t build the future – we legislate against it.
But why are we so afraid of AI? Is it really because
it threatens our autonomy? Our privacy? Our
jobs? Or is it, perhaps, because it threatens our
institutional laziness? Because it dares to do better,
faster, and with fewer lunch breaks? The truth
is, AI doesn’t want anything. It’s not sentient. It
has no political ideology, no supposed, modernwoke,
moral compass, no sinister desire to
enslave humanity. What it does have is potential
– a massive, dazzling, disorienting potential to
automate the tedious, accelerate the necessary,
and rethink what’s possible. And we, in our infinite
caution, are running from it.
This is not a call for techno-utopianism. But let’s
get real: true innovation today rarely comes
from governmental institutions or the university
system. Those structures, noble as their ideals
may be, have largely been relegated to playing
catch-up. The groundbreaking tools shaping
our century – transformative AI models, largescale
language systems, generative design tools
– emerge from private labs, startups, and the
restless minds of developers who weren’t waiting
for a government grant or an ethics commission
to give them permission to think. That
may be uncomfortable for public-sector romantics,
but it is reality.
And yet, here comes the EU, armed with a thousand-page
legislative hammer, determined to
flatten every spark of entrepreneurial energy
into an acceptable format for committee review.
Risk-based classification, real-time compliance
reporting, mandated explainability – this is the
language not of invention, but of institutionalised
anxiety.
The irony, of course, is that AI might be the best
shot we’ve had in decades at addressing the very
bureaucratic inefficiencies that make Europe
groan under its own weight. AI could streamline
public services, declutter urban logistics,
and democratise access to everything from education
to city planning. Instead of embracing
that opportunity, we’re busy legislating its obituary
before it’s even out of the lab. AI can also be
a huge help to individuals. Interestingly, an
incredible number of people already use AIbased
solutions without much fear or concern.
Could it be that the supposed fear among the
population is simply being used as a pretext for
over-regulatory measures?
Meanwhile, the real world moves on. Cities are
becoming smarter – not through policy, but
through platforms. Businesses deploy AI not
because they’re reckless, but because they have
to. In a global economy defined by speed, complexity,
and competition, efficiency isn’t a luxury
– it’s survival. And AI, for all its flaws, is a
spectacular tool for efficiency. It doesn’t replace
human intelligence; it extends it, multiplies it,
scales it. It takes our best ideas and pressuretests
them in milliseconds. It takes our worst
habits and flags them in bright red. It forces us
to become better – not by replacing us, but by
outpacing us.
And what’s our response to this new industrial
revolution? A mixture of moral panic and
paperwork. We want “ethical AI” but can’t
define ethics. We want transparency from systems
we don’t understand. We want innovation,
but only after the next council meeting, two
stakeholder workshops, and a series of public
consultations moderated by people who still
think deep learning is a form of introspection.
Let’s be brutally honest: fear is easy. It costs nothing.
It flatters our sense of moral superiority
while demanding no action. Courage, on the
other hand – courage to innovate, to iterate, to
risk imperfection in pursuit of progress – that is
harder. And Europe, for all its intellect and history,
is suffering a courage deficit. The real risk isn’t
a rogue algorithm; it’s a paralysed system clinging
to a fantasy of control in a world it no longer
understands. The true dystopia isn’t one ruled by
machines, but one stifled by paperwork.
AI is not the enemy. Stagnation is. Mediocrity
is. The endless comfort of process over purpose
is. If we want to remain relevant – not just technologically,
but civically, socially, globally – we
must stop confusing regulation with vision, and
fear with wisdom.
In short: we must stop being afraid of the very
thing that might finally force us to grow up.
TOBIAS HAGER is a journalist and Chief Content Officer
and member of the management board at GEORG Media.
Responsible for all GEORG brands such as topos magazine,
BAUMEISTER and Garten + Landschaft, his focus is on the
areas of content, digital, marketing and entrepreneurship.
topos 132 009

TEXT: TOPOS MAGAZINE
THE AI AUGMENTERS
At Foster + Partners, the Applied Research + Development Group has become
a core driver of technological exploration within the architectural process.
Blending computational design, data science, and interdisciplinary
collaboration is shaping how one of the world’s most prominent architecture
firms approaches digital tools, sustainability, and emerging technologies
such as artificial intelligence.
026 topos 132

AI Pioneers
Since its inception, Applied Research + Design has operated as more than
a technical support team. Founded on a model of cross-disciplinary integration,
the group brings together architects, engineers, programmers,
and scientists to tackle complex, data-rich design challenges. Its members
are fluent in an array of computational platforms, and frequently develop
custom scripts, workflows, and simulation engines to extend the capabilities
of traditional design tools.
One defining contributions lies in embedding real-time feedback loops into
design processes – allowing performance metrics such as daylighting,
structure, and energy use to inform early-stage decisions. In large-scale
projects like the Mexico City Airport (cancelled in 2018), computational
input enabled designers to test structural and environmental scenarios iteratively,
streamlining the complexity of vast geometries.
Artificial Intelligence: experimental applications with practical goals
In recent years, they have begun experimenting with machine learning
to support tasks such as surrogate modelling – using trained algorithms
to approximate visual and spatial connectivity analyses that would otherwise
require extensive computation time. These models are still in a
research stage, but show promise in providing faster feedback loops.
While the group often explores AI’s potential to suggest design variations
(e.g., furniture layouts or spatial configurations), the emphasis remains
on augmenting rather than replacing human decision-making. As discussed
in internal publications, such AI tools are informed by Foster +
Partners’ project archives, allowing models to reflect learned preferences
from past designs. However, rather than autonomous design agents, these
systems currently function more as intelligent retrieval or suggestion
interfaces, requiring continuous input and supervision by architects.
Claims about the use of advanced models – such as Generative Adversarial
Networks (GANs) for developing responsive or self-deforming façades
– remain largely theoretical, as suggested by the specialists.
Tools in practice: digital twins, semantic search, and inclusive design
Research increasingly feeds back into live projects. The team has worked
on digital twin models for monitoring building performance, notably at
the firm’s Battersea campus. These models incorporate sensor data related
to energy consumption and occupancy patterns.
Another internal tool is “Ask F+P”, natural-language search to help architects
navigate Foster + Partners’ internal knowledge base. While details
about the underlying technology are limited, it appears to leverage semantic
search principles – most likely via adapted third-party models rather
than proprietary large language models. Applied R+D has developed
tools like the AI Portal, a platform delivering enterprise-grade generative
AI without compromising client confidentiality or creative control. The
AI Portal enables designers to generate and edit different media (like
images and videos), fine-tune results with custom training of key ML
models on historical design data and collaborate through branching
workflows. The platform seamlessly integrates local models for sensitive
projects with rigorously vetted cloud models, accessible through desktop,
mobile, and native design software plugins like in Mcneel's Rhino.
A further area of interest is inclusive design. They have collaborated with
academic partners on platforms such as VARID, which use virtual and
augmented reality to simulate spatial experiences from the perspective of
users with visual impairments. These tools aim to inform accessible
design strategies during the concept phase and align with the group’s
broader interest in user-centred, ethical design approaches.
topos 132 027

Standing on the Thames'
riverbank, the London
Eye is one of London's
world-famous
landmarks. Less visible
is the British capital's
leading role in the
AI sector.
Photo: Sam Quek on Unsplash
topos 132 035

One of London's world-famous landmarks, clearly visible on the Thames, is the
London Eye. Less visible is the position that the British capital has earned in the AI
industry. The British government has set itself the goal of further expanding the UK's
pioneering role and ensuring that the country is at the forefront of the new space
race – this time for AI. A look at the AI ecosystem and planning projects in London.
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Is there anything humans can do
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10:20
Since I am experiencing low growth, it
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notice any other issues, seeking advice
from a professional could be beneficial.
10:20
036 topos 132

TEXT: TOPOS MAGAZINE
THE CATALYST
As founder and CEO of the Archi-Tech Network (ATN), and an independent
architect based in London, Oliver Thomas operates at the intersection of
computation, design strategy, and architectural production. With a background
that spans façade consultancy, architectural practice, and educational
outreach, he represents a generation of architects committed to
bridging technical fluency with design intelligence. Rather than claiming to
reinvent architecture through technology, Thomas approaches digital transformation
as a process of continuous refinement – balancing innovation
with critical reflection.
066 topos 132

AI Pioneers
Educated in the UK, Thomas studied architecture at Oxford Brookes University
before earning a Master of Architecture from the University of
Liverpool. His early professional years included experience in Hong
Kong, where he became a registered architect (RIBA), and in London,
where he worked with firms like Aedas and Front Inc. At Front, a consultancy
known for complex geometry and digital fabrication, he contributed
to projects such as the Morpheus Hotel by Zaha Hadid Architects – a
role that sharpened his focus on the interface between design intent and
construction logic. Although details of his individual contributions are
not officially confirmed, his trajectory reflects a deep engagement with
computational tooling from early on.
Until early 2024, Thomas held the position of Design Technology Manager
at BIG's London office, where he played a significant role in advancing
digital processes across the firm’s operations. His work involved overseeing
the integration of design computation, scripting, and BIM workflows
into architectural production. While external sources confirm his strategic
involvement, assertions that these systems spanned every phase of
project delivery – from concept through construction – should be viewed
as internal aspiration rather than externally documented fact. What is
clear is his focus on workflow coordination, tool interoperability, and cultivating
a shared digital culture within multidisciplinary teams.
Between speculation and implementation
Thomas is vocal about the potential of artificial intelligence to streamline
repetitive design tasks and augment early-stage decision-making. He has
spoken publicly about the use of machine learning and generative models
for spatial analysis, massing studies, and daylight optimisation. However,
specific case studies or measurable impacts from AI deployment within
his past roles remain largely undocumented. Similarly, while the development
of internal data pipelines and project knowledge indexing tools is
plausible – and common in large firms – there is no public evidence of
such systems being fully institutionalised under his leadership.
Claims that Thomas formalised firm-wide digital standards or made AI a
“routine” part of BIG’s workflows overstate the extent of what can be independently
verified. BIG has long maintained a strong culture of design
technology and computational design across offices and teams. Thomas’s
contributions appear to align with this broader ethos, helping to shape
and extend existing capacities rather than initiating a digital transformation
from scratch.
More verifiable are his current roles beyond firm-based practice. As
founder and CEO of the Archi-Tech Network (ATN), Thomas leads an
international platform for professional exchange in architectural technology.
ATN focuses on sharing knowledge, fostering collaboration, and
supporting education around the intersection of architecture and emerging
technologies in the AEC industry. He also regularly teaches at institutions
like the Institute for Advanced Architecture of Catalonia (IAAC),
where he leads courses on AI in design practice. His public appearances,
including on podcasts and at events such as Computational Design:
NEXT, reflect a commitment to sharing knowledge beyond traditional
practice. In these forums, he articulates a clear position: that design technology
should remain grounded in ethical awareness, contextual understanding,
and disciplinary rigour.
A disciplined voice in a rapidly changing field
Oliver Thomas’s work captures the ambitions and contradictions of architecture’s
digital present. He embraces the exploratory dimension of computational
design, while cautioning against an over-reliance on automation
or surface-level aesthetics. His call for transparency in AI decisionmaking,
and for retaining a narrative sensibility in digital design, resonates
at a moment where generative tools risk overwhelming human judgement.
While he is sometimes credited with shaping firm-wide transformations
that are difficult to confirm externally, his impact is more credibly seen in
the culture of experimentation, coordination, and discourse he fosters –
both in his previous roles and through his teaching and outreach.
By focusing less on sweeping declarations and more on incremental
refinement, Thomas offers a realistic model for architectural innovation.
He situates digital tools not as ends in themselves, but as evolving frameworks
for practice – tools that must remain open to critique, collaboration,
and recalibration. As the profession continues to absorb new forms
of intelligence and automation, his approach suggests that the most
meaningful change may lie not in technology alone, but in how thoughtfully
we choose to integrate it.
topos 132 067

AI Pioneers
HELSINKI’S QUIET
AI REVOLUTION
VERONIKA MINKINA
076 topos 132

AI Pioneers
Helsinki has quietly but decisively developed into a European showcase city for artificial
intelligence. As well as applications in urban planning and architecture, the
Finnish capital is primarily using the technology to improve public services and
make innovation more accessible. Here, AI is not just being developed – it is being
put at the service of the people.
Images that accompany the global AI debate are often futuristic, depicting
robots, metropolises full of sensors and autonomous vehicles. Cities
such as San Francisco, Shanghai and Seoul are renowned for their digital
innovation. However, a closer look reveals a quieter, more profound
change on the edge of the Baltic Sea. Helsinki has become a pioneer of
urban artificial intelligence – not through spectacle, but through systems.
Rather than using AI to demonstrate technical dominance, the Finnish
capital is using it as an intelligent tool to improve the organisation of
administration, citizen participation, urban design and public welfare.
While other cities focus primarily on technological progress, Helsinki
takes a holistic, often social approach, asking: How can AI improve quality
of life, strengthen participation, and enable a sustainable, trust-based
approach to technology?
How Helsinki is bringing AI to the city
One of the key factors in Helsinki’s success lies in its ability to treat artificial
intelligence not as an isolated discipline, but as a cross-sectional technology
with a tangible impact on everyday life. Rather than leaving innovation
in laboratories, Helsinki is actively seeking applications in public
administration and society. This starts at a very practical level: the city
offers almost 800 municipal services, ranging from education and healthcare
to urban development and cultural offerings. In the past, many of
these services involved high administrative barriers: Citizens had to know
which service matched which request, find the right form, fill it out and
send it in – and then wait. Today, AI is transforming this process. The aim
is to transition from reactive to proactive services. One example of this is
the city’s kindergarten system. In the past, parents with children of kindergarten
age had to search for places and submit applications manually.
Now, an AI system automatically identifies families with children of the
right age, matches addresses with available daycare centres and proactively
sends a text message with the proposal and provisional placement. This
initiative was a complete success within a very short time: around 93 per
cent of parents contacted responded to the offer, and 89 per cent accepted
the suggested places. For many people, this meant not only less bureaucracy,
but also a new form of participation, free from applications, hurdles
and language barriers.
Data, trust and responsibility
Such upheaval presupposes the processing and evaluation of sensitive
data, such as place of residence, age, and family situation. Despite this
extensive use of data, Helsinki is not met with international criticism, but
with recognition, due to a deeply rooted principle: trust. The city pursues
a rigorous ethical strategy in all data-driven projects. Its declared aim is to
provide “the most usable and widely used municipal data in the world“
under conditions of maximum transparency.
To implement this, Helsinki presented its own code of ethics in the form
of nine guidelines. These define not only the right to access data, but also
the city’s obligation to make it usable for the benefit of the population.
This includes the world’s first AI Register. This openly documents the
areas in which AI is used, ranging from personnel planning and image
topos 132 079

TEXT: TOPOS MAGAZINE
THE PARTICIPANT
Dr. Yan Wang, Associate Professor at the University of Florida, stands at the
intersection of artificial intelligence, urban planning, and community resilience.
Her research combines computational precision with an insistence on
transparency, ethics, and inclusive decision-making – charting a credible
path forward for AI in urban governance.
086 topos 132

AI Pioneers
With a background in civil engineering and urban planning, Dr. Wang
brings a systems-thinking approach to the question of how cities can
become more adaptive, equitable, and responsive in the face of disruption.
As the founding director of the Urban Agility and Resilience Lab (UAR
Lab) and a core member of the Florida Institute for Built Environment
Resilience (FIBER), she has helped define a research agenda focused on
post-disaster recovery and digital infrastructure for urban resilience. Her
selection as a recipient of the National Science Foundation’s CAREER
Award recognises the significance of her current project, “Generative Deep
Learning for Post-Disaster Spatial Regeneration Planning.” This work
explores how generative AI techniques – referred to as “GenAI” – can be
used not to replace planners, but to support long-term recovery strategies
that promote spatial equity, housing access, and economic viability, while
ensuring that technology remains accountable to human needs.
Wang’s methods combine machine learning with participatory planning
frameworks, offering an approach that is as concerned with values as with
outputs. Rather than fixating on physical infrastructure alone, her research
prioritises the measurement of human movement, behaviour, and sentiment
in disrupted environments. Tools developed in her lab are designed
to support scenario-based modelling, risk communication, and real-time
planning assistance, helping governments and communities respond more
quickly and inclusively during crises. These contributions have positioned
her work within both academic discourse and applied planning contexts –
reaching scholars, practitioners, and policymakers alike.
Research, recognition, and responsible technology
As the head of a cross-disciplinary research team, Dr. Wang has attracted
over $3 million in competitive research funding, including multiple
awards from the NSF. Her more than 40 peer-reviewed publications span
topics from automated spatial analytics to crisis informatics, placing her
among the leading female voices in the field of AI-enhanced urbanism.
Importantly, her academic output is paired with a strong commitment to
mentorship and teaching. At the University of Florida’s College of Design,
Construction and Planning, she has played a key role in developing digital
planning curricula and cyberinfrastructure that prepares students to
think critically about the tools they use.
Central to Wang’s mission is the insistence that AI in public systems must
be built on principles of ethical governance and equity. In her recent
work, she has highlighted concerns around algorithmic bias, spatial disadvantage,
and the risk of deepening digital divides. Rather than treating
these as peripheral challenges, she embeds them at the core of system
design, insisting that the goal of urban AI must be to serve whole populations
– not just technically feasible zones or privileged demographics. Her
position is clear: digital augmentation must remain subordinate to public
interest and democratic accountability.
A measured, human-centered vision for AI in cities
Dr. Wang’s contributions do not rest on futuristic visions or rhetorical
ambition. Instead, her work offers a model for how technology can be
applied thoughtfully within the real-world constraints of urban policy,
community dynamics, and infrastructure recovery. Her concept of “digital
agility” – the ability of cities to reconfigure both physically and institutionally
in response to unexpected events – has gained traction among
urbanists seeking grounded, implementable tools. Though still evolving,
her frameworks already influence how scholars and practitioners across
sectors think about resilience, equity, and the responsible integration of
artificial intelligence.
By combining rigorous computation with careful ethical reflection, Dr.
Yan Wang has become an influential voice in shaping what AI can – and
should – mean for cities in the 21st century. In a rapidly digitising planning
landscape, her work stands as a reminder that smarter cities are not
necessarily better ones – unless they are also more just.
088 topos 132