The group that I'm particularly
focused on, really, is the
convergence of
response to applications and transformation.
So how do we actually take this technology,
not just at a high level or as
a sort of, you know, an AI whitewashing
type
blur, but how do you actually practically apply
it around some
significant industrial problems?
Earlier this year, we talked to Darren Martin,
CDO of Atkins Realis,
about the relationship between AI and humanity.
We saw how Darren had used big data
in his early career as a clinical psychologist
to identify effective treatments for severe mental illness.
We saw that machine learning and big data
could be powerful tools,
but they were not a fix for every
problem.
But what does it mean to live in
a world where AIs control autonomous devices that
work alongside us?
As machine autonomy replaces or supplements human work,
what does that mean for how we design,
build, and live in cities?
These are some of the questions that Darren
has been examining along with fellow members of
the World Economic Forum's
AI Governance Alliance.
This really boils down to,
for example,
how my robots and people
relate to each other and work with each
other in a safe way
on a mega
project, like an, a project in the Middle
East where we're building huge
cities, and how might we
help achieve that construction
faster
with the AI
and the people working together.
Bringing that together in a safe, practical way
is really important.
But if you then flip out into
different
areas of opportunity
and discuss the pros and cons of this
technology with and the applications
The impact of these technologies will be felt
throughout our society
We will be leaning into conversations about health.
We'll be leaning into conversations about
defense and security.
It has the potential to do great harm,
but also has the potential to
do great good.
Welcome to Engineering Matters.
I'm Johnny Dowling.
And I'm Rian Owen. Earlier this year, we
heard from Darren Martin, chief digital officer of
our partner, Atkins Realis,
about the importance of considering human needs in
our deployment of AI.
In this episode, Darren returns to look at
what it means for humans to live and
work alongside autonomous devices
and what that implies for the relationship between
big tech and architecture,
engineering, and construction professionals.
One day, autonomous devices will be close at
hand wherever we go. But for now, we
are in some corners of the world most
likely to encounter them on the road.
In San Francisco, for example,
one can get in a car without a
driver
and pay a fare and go.
So the Uber concept has evolved to a
a Robot Taxi
concept.
Now taking the learnings from San Francisco, which
is is very healing, but it's a grid
city. So it's, you know, it's a traditional
American city with the grids, and taking that
to where I live, and I latest it
with our single lane country lanes and, you
know, the all of the complexity that comes
with having a deer in the middle of
the road, and and how does the robot
taxi deal with
that? The ability of AIs to operate potentially
dangerous equipment in public spaces
is being proven in the neat grids of
American
cities. Development now is focused on improving the
safety of these systems and verifying that safety
so that they can be deployed
around the world.
It's bringing these two things together, like like,
what does the consumer need? How might that
be enabled?
And also,
what are the benefits for doing that?
If these autonomous devices can be shown to
be safe enough for our roads,
then they'll be well on their way to
working alongside us everywhere.
We can already see autonomy
autonomy in the workplace at ports around the
world. Here, autonomous rubber tire gantry
cranes move containers around ports
without human intervention.
In applications like this, the autonomous equipment is
separated from human staff by a fence.
Part of the terminal will be exclusively autonomous.
And part of it will be operated by
people.
There are many
quite advanced examples now with
the safety case has been lowered
for the technology, because people are not allowed
in there. And so if the technology goes
wrong,
it's embarrassing, it's expensive, but no one was
hurt. So the profile of it is much
lower.
But to extract the real efficiency benefits of
AI autonomy,
we need to be able to work with
these devices in the same space.
So the question is,
under what conditions can one move away from
a a closed loop scenario?
So
it's about the interoperability
of of humans
and the robot systems.
That could then allow a new generation of
robot workers to work in environments far more
complex and unpredictable than a modern port.
If we then translate that back into
how do we operate
a really complex,
dangerous, multi level, multi layered, multi machine
construction
site. The advantages of using a robot to
do something that
is dangerous, like working at height, working with
heavy loads,
working with dangerous substances,
for example,
is really appealing.
But some workplaces are even more risk laden
than a construction site, like a nuclear power
plant.
We're currently,
talking to a number of research institutes
to really explore how that is gonna work
in the future and start to trial it
in our ways of working. And and as
an organization where
we know we own,
one of the 6
nuclear technologies,
that are licensed on this planet and that
there's a significant
need for
more nuclear
facilities to be built.
The interoperability
of of humans
and the use cases of robots to keep
people safe and to to,
make sure we can design, run, and maintain
those facilities in the safest way is really
attractive.
There's a whole community of people that have
spent their whole lives working in those environments
and they're extremely
proud of what they've done
and long may that continue.
Their ability to get suited up and and
operate in that environment
and then move away from that environment, it
might take a whole day to spend
around 40 minutes or
maybe an hour in that environment, but it
would take a whole day to kinda go
through that process.
So your time on tools and your ability
to
interact and perform accurate maintenance
could be significantly improved if the human safety
factor
could be lowered.
An engineering business like Atkins Realis is well
placed to develop systems that can work in
these hazardous environments.
On one level, engineering is all about the
assessment and control of risk.
But as engineers,
architects, and construction managers build new infrastructure,
they must also think about creating an environment
that is suitable for the use of autonomous
machines.
But the
disadvantages
that occur when you have these closed loop
systems, you and you don't have people and
machines together, There's still many things the machines
can't do very well,
not nearly as well as humans. So the
advantage of that interoperability
of these two entities is is appealing. It's
and for me, personally, it is really appealing.
Like like,
from an academic perspective it's appealing, but also
from a real value
in terms of
doing things faster
and safer,
which is right at the ethos of
the construction industry.
From a design perspective,
how do you how does one design a
construction site? How do you even design a
city?
Where, as I mentioned before, you know, the
the robot taxis can operate in? But also,
how do we actually design
buildings so that we can
design for manufacturing
with people,
with 3 d printing,
and with robotic devices that have high mobility
and interoperability with people.
And I think I think that whole piece
is
we're scratching the surface of that.
Construction sites and the building materials supply chains
that support them can be designed to support
the use of autonomous devices.
We can imagine robots able to manipulate and
install large modular components
alongside human workers,
And this may give us the pace needed
to build new cities to house a rapidly
growing, urbanizing
and aging population.
As we think about how much infrastructure's gotta
be built to replace the aging infrastructure we've
got,
how the population keeps on growing, and there
are many more sustainable
energy transition
initiatives that have to be built
to
make sure we
are able to all survive on this planet.
I think that the ability to think about
how would
how do we design it in a way
that allow for modular construction, design for manufacturing,
and how would we
design it so that
there were some closed loop
environments where it's really not safe for a
human being to be in, but we designed
also for the for those two things to
come together.
The urban planners of the near future
shouldn't just be considering how construction sites can
safely allow for humans and machines to work
together.
They need to think about how to make
the best use of space
within cities
where new forms of transportation
are possible.
When I bring this back to an AEC,
an architecture engineering construction
situation,
the master planners, the architects of the new
cities,
the retrofitters of our existing cities,
how are we thinking about
transportation,
how are we thinking about social value, so
how are we thinking about
walkways that allow people to walk and cycle
and scoot for example and be more active
and be safer
but also how might we be thinking about
the utilization of car parking space?
Is that now social housing opportunities?
We've seen older people returning back to cities.
Is that community space for communities to
experience
different social interactions than our cities have typically
seen and how might you
design
a roadway system for robot
cars
preferably robot taxis because if we all have
robot cars parked outside wherever we choose to
live and work, we're taking up unnecessary real
estate space that
just doesn't really add a lot of value
other than the prestige of owning the car.
We live today in cities that have for
decades
been closed loop systems,
designed to allow for the widespread use of
unsafe,
unreliably controlled machines.
We mark off huge swathes of our cities
for cars, segregating roads from pavements and dedicating
space for them to sit unused.
Now urban planners should be thinking beyond these
risk controls.
If truly safe autonomous vehicles
designed to be shared and used constantly were
available,
what other uses could we find for those
spaces?
If you are gonna be in a car,
let's make sure that car is a robot
vehicle that isn't just going to park and
take up precious real estate.
I can trust you in a study at
the moment between
Cranfield University, Open University
and Oxford and Cambridge
looking at the some of the connections between
those
cities, those educational institutes and how do we
create thriving
natural
corridors between waterways,
cycle path routes, and so on to make
the the connectivity
of those parts of the world better.
Autonomous devices will change the way that we
build and design cities.
They will increase the pace at which we
build and create new space for us to
build in.
AIs are pattern matching machines.
They can mimic human communication,
allowing for their control by anyone,
and they can select designs that are safe
and buildable.
Taken together, this will allow for a tailored
design process
previously only available to the very rich.
And so when I think about high end
luxury goods, there have been some organizations
that have really brought in
the consumer into the personalization
process.
So hyper personalization.
Consumers of trainers and sunglasses can adapt designs
to their own taste, but within the options
offered by a drop down menu.
What would it mean if this personalization
could be taken beyond a set of fixed
choices
and intersections of the economy more vital to
life than luxury consumer goods?
But all of these are within parameters, so
the manufacturers
are able to offer a premium
differentiated
product,
but something that they can still affordably
manufacture and make profit from in a sustainable
and safe way.
Around the world, cities are now being planned
from scratch.
Robot workers will deliver the pace needed to
house 1,000,000,
and AI systems will allow residents to have
a real say in what their new homes
will look like.
Where we need to go
is the ability to
draw in
enough parameters
so the consumer can have ownership
and identify with that modular experience,
but at the same time, the benefits
of,
the construction process, the efficiencies, the sustainability
of it, the ongoing
operational maintenance of it are much better than
we've achieved in the past.
AI and autonomy
will allow us to build cities in a
new way.
We'll be able to rapidly construct
personalized
homes
and to interact and travel in a more
human way, free from the risk and waste
of cars.
But the climate crisis makes clear that even
designing cities from scratch is not enough.
We must leverage these new technologies
to consider and analyze our whole planet.
Part of my job and other people's at
Atkins Real Estate's job is to constantly
look at
what do certain technology partners bring
to our customers,
and what value together do we bring
to drive a better societal outcome for our
customers.
And one of the examples that, you know,
we're really interested in
is the impact of climate change
and the impact it has on society
and thinking about resiliency.
The risks and uncertainties of climate change have
undermined the functioning of insurance markets.
Without understanding the impact of climate change and
the resilience of our buildings and infrastructure,
many regions are becoming increasingly
uninsurable.
And just, you know, at the moment there
are some questions being asked around the bond
market,
the insurance bond market and
with the
frequency and the the impact of
climate change and weather,
impact on on critical infrastructure across the globe,
how do we keep on paying for it,
who underwrites it and it's a bet that
in the past used to come off quite
nicely. It's quite a profitable industry,
but actually a lot of these bets are
starting to become
loss making.
And in some places now,
all over the world.
Our current tools don't allow for reliable assessment
of risk and resilience.
Getting more precision from AI
about the exact nature
or and likelihood
of resiliency
impacts and also putting in remedial action to
mitigate against them where possible
is
really important because if you own real estate
or you own a business or you run
a school, you wanna make sure that it
can be insured and protected.
Atkins Realis is already using AI systems to
analyze the impact of climate change across tens
of thousands of properties
at a time.
We've done work with the federal emergency
management agency, FEMA, in the US,
where we've
been able to do surveys on properties that
have been impacted by, severe
climate change and prioritise
the surveying of those properties
to measure the impact
and to help,
free up funds
to get people back
in those homes or in new homes.
That's a 150,000
potential surveys that needed to be done.
Relying on human assessment
would leave those impacted by climate change in
vulnerable situations for weeks or months.
AI can allow support to be delivered where
it's most needed, when it's most needed.
With, being able to use AI to 0
in on
around,
1 5th of them that really needed to
be done as a huge priority
to,
make sure people were
helped and looked after as a result of
that,
climate
impact on their lives. And so
zeroing in and removing waste and prioritizing and
getting help and resources to people is something
that that I think
AI is a really good example of where
it can do it, and I think we
need to get better at that.
AI based analysis can identify the impact of
climate events across cities and regions.
One vision of the interaction of machine learning
and city planners has already been tried in
Canada.
In this vision, tech led the way and
engineering followed.
Google Sidewalk Labs,
it's, it's this company as part of the
Alphabet group that was set up,
and
its first project was to look at the
Quayside project,
on the South Bank of Lake Ontario,
which was a port area
back in Toronto,
and then the idea there was that
big government had aligned with big tech, Google,
and that this
large,
real estate project was gonna be put put
in and that it would it had some
fantastic benefits. I was looking at some of
the stats and I'm not an expert on
on this area, but just looking
at the stats,
it said by 2040, it would generate around
44,000
jobs. So it's an industrial pool, and it
was being turned into a,
you know, as we have in the UK,
you know, some really good
waterside
retail
business
and
residential,
quadrants and and and locations.
And
it was reducing emissions of that industrial site
by 89%,
and it was reducing the cost for
social housing,
assets
that were being put into that alongside some
higher end housing assets.
But the typical cost for a social housing
asset was
40%
below the market rate.
Sidewalks Labs' plan had been to offer more
jobs and cheaper housing in an attractive environment,
managed and maintained using sophisticated
monitoring.
But by 2020,
the project had fallen apart.
Stymied by the impacts of COVID and by
a lack of trust in the monitoring systems
used to manage the district.
Darren believes that projects like this need to
draw on the established expertise
of architecture,
engineering, and construction businesses.
Big Tech came in
and did a deal with big government,
and local government, and local sentiment, and human
permitting
considerations,
objections,
community resistance
wasn't dealt with in the same way
that perhaps Atkins Realis would have
understood
the nuances
of engaging with local government, understanding the planning
rules,
understanding how to engage with communities
to help them understand what the changes and
what the benefits are for them, but also
to adapt the master planning concept
based on consultation with those communities.
But just as Alphabet is moving out of
city building,
other big tech players are moving into engineering.
Cognizant
have put forward
and acquired
7 companies
in the with engineering focus since 2021.
So Cognizant typically would have been, you know,
Indian HQed
IT and Business Process Outsourcing Organization
competing with the likes of, you know, IBM,
Japan's Fujitsu, and so on. Probably doing so
on a lower price point.
It made a 1,300,000,000
acquisition
of an engineering company
in June 24.
Tata,
for example, bought an automotive
engineering company recently.
Accenture
have bought
IoT
companies,
a whole range of industrial and engineering
expertise.
As the space between big tech and engineering
closes,
those leading and investing in these sectors
should really think critically about the skills each
sector brings.
You have to ask the question,
is
a company like Cognizant becoming an engineering company?
Professional services businesses in architecture, engineering, and construction
should not, Darren believes, try to themselves into
tech firms.
Big tech is not accustomed to dealing with
the human complexity of urban planning.
This is not a space in which you
can just move fast and break things.
So how do these 2 sectors work together
in a new age of AI driven autonomy?
What can they learn from a project like
Sidewalk Labs?
Perhaps there wasn't the,
awareness
and the,
sensitivity
and experience
that an architecture engineering and
construction company would apply
in getting that project to work.
You can work out, for example, when the
lifts are being used
and, you know, are people exiting the building,
and how many people are in the in
the lifts, and what's the weight of the
lifts.
There are there are a number of less
intrusive ways
of understanding
how the,
buildings and the
the environment are being used
that don't require, you know, quite personal sense
of information to be shared. So once you're
in a community,
people don't want to feel that they're being
observed. Their movements are you know, who are
they talking to? How long are they spending
in these spaces?
The experienced human planners of an AEC business
can work alongside local governments and citizens
to deliver projects that really consider
human
needs, desires, and privacy.
While emerging technologies will have a vital part
to play, it is this human expertise and
experience
that will be key to meeting human needs.
We form part of a partner ecosystem,
which in some cases might be tech enabled,
in many cases it will.
We're highly differentiated
from Big Tech in our ability
to
create environments that are both progressive from an
economic standpoint but sympathetic to to communities and
enhance the communities.
Engineering Matters is a production of Reebi Media.
This episode was written and produced by Will
North and hosted by me, Rianne Owen, and
by Johnny Dowling, editing and series supervision by
John Young, sound engineering by Ross Macpherson, and
the human intelligence that steers our use of
data is Rory Harris.
Special thanks to our partner for this episode,
Atkins Realis, and thank you for listening. You
can find us on all podcast apps and
on our website engineeringmatters.
Rebi.media
and on LinkedIn.