How brand new science will manage the fourth industrial revolution – “Managing the Machines”
It’s
about artificial intelligence, data, and things like quantum computing
and nanotechnology. Australian National University’s 3A Institute is
creating a new discipline to manage this revolution and its impact on
humanity.
Image: Diagram by Christoph Roser at AllAboutLean.com (CC BY-SA 4.0))
Diagrams explaining the fourth industrial revolution,
like this one by Christoph Roser, are OK as far as they go. Apart from
the term “cyber physical systems”. Ugh. What they mean is that physical
systems are becoming digital. Think of the Internet of Things (IoT)
supercharged by artificial intelligence (AI).
But
according to Distinguished Professor Genevieve Bell, these diagrams are
missing something rather important: Humans and their social structures.
“Now
for those of us who’ve come out of the social sciences and humanities,
this is an excellent chart because of the work it does in tidying up
history,” Bell said in her lecture at the Trinity Long Room Hub at
Trinity College Dublin in July.
“It
doesn’t help if what you want to think about was what else was going
on. Each one of those technological transformations was also about
profound shifts in cultural practice, social structure, social
organisations, profoundly different ideas about citizenship, governance,
regulation, ideas of civil and civic society.”
Another problem with this simplistic view is the way the Industry 4.0 folks
attach dates to this chart. Steam power and mechanisation in 1760-1820
or so. Mass production from maybe 1870, but the most famous chapter
being Henry Ford’s work in 1913. Then computers and automation started
being used to manage manufacturing from 1950.
“That
time scheme works really well if you’re in the West. It doesn’t hold if
you’re in China or India or Latin America or Africa, where most of
those things happened in the 20th century, many of them since 1945,”
Bell said.
Bell wants to know what we can learn from those first three revolutions. She heads the 3A Institute at the Australian National University, which was launched in September 2017 and is working out how we should respond to, and perhaps even direct, the fourth revolution.
Take
the steam engines of the first industrial revolution. They were built
by blacksmiths and ironmongers, who knew what they needed to build the
engines. But they didn’t know how to shape the industries the engines
could power, or how to house them, or about the safety systems they’d
need. These and other problems generated the new applied science of
engineering. The first school of engineering, the École Polytechnique,
was established in Paris in 1794.
The
large-scale factories and railway systems of the second industrial
revolution needed massive amounts of money. Raising and managing that
money literally led to capitalism, and concepts like common stock
companies and futures trading. And the first business school with
funding from industry.
Early
in the computer revolution, the US government had a problem. Nearly all
of its computers relied on proprietary software from companies like IBM
and Honeywell. So it asked Stanford University mathematician George
Forsythe to create an abstract language for all computers. Two years
later, his team developed a thing called computer science, and issued a
standard 10-page curriculum. An updated version is still used globally
today.
“So,
engineering, business, and computer science: Three completely different
applied sciences, emerging from three completely different technical
regimes, with different impulses,” Bell said.
“Each
starts out incredibly broad in terms of the ideas it draws on, rapidly
narrows to a very clear set of theoretical tools and an idea about
practice, then is scaled very quickly.”
With
this in mind, Bell said that the fourth industrial revolution needs its
own applied science, so that’s exactly what the 3A Institute is going
to build — as the website puts it, “a new applied science around the
management of artificial intelligence, data, and technology and of their
impact on humanity”.
And the 3A Institute plans to do it by 2022.
Nine months into this grand project, it’s identified five sets of questions that this new science needs to answer.
First is Autonomy
If
autonomous systems are operating without prewritten rules, how do we
stop them turning evil, as so many fictional robots do? How do different
autonomous systems interact? How do we regulate those interactions? How
do you secure those systems and make them safe? How do the rules change
when the systems cross national boundaries?
Or,
as Bell asked, “What will it mean to live in a world where objects act
without reference to us? And how do we know what they’re doing? And do
we need to care?”
Second is Agency,
which is really about the limits to an object’s autonomy. With an
autonomous vehicle, for example, does it have to stop at the border? If
so, which border? Determined by whom? Under what circumstances?
“Does your car then have to be updated because of Brexit, and if so how would you do that?” Bell asked.
If
autonomous vehicles are following rules, how are those rules litigated?
Do the rules sit on the object, or somewhere else? If there’s some
network rule that gets vehicles off the road to let emergency vehicles
through, who decides that and how? If you have multiple objects with
different rule sets, how do they engage each other?
Third is Assurance,
and as Bell explained, “sitting under it [is] a whole series of other
words. Safety, security, risk, trust, liability, explicability,
manageability.”
Fourth is Metrics
“The
industrial revolution thus far has proceeded on the notion that the
appropriate metric was an increase in productivity or efficiency. So
machines did what humans couldn’t, faster, without lunch breaks,
relentlessly,” Bell said.
Doing
it over again, we might have done things differently, she said. We
might have included environmental sustainability as a metric.
“What
you measure is what you make, and so imagining that we put our metrics
up at the front would be a really interesting way of thinking about
this.”
Metrics for fourth revolution systems might include safety, quality of decision-making, and quality of data collection.
Some
AI techniques, including deep learning, are energy intensive. Around 10
percent of the world’s energy already goes into running server farms.
Maybe an energy efficiency metric would mean that some tasks would be
done more efficiently by a human.
Fifth and finally are Interfaces. Our current systems for human-computer interaction (HCI) might not work well with autonomous systems.
“These
are objects that you will live in, be moved around by, that may live in
you, that may live around you and not care about you at all … the way
we choose to engage with those objects feels profoundly different to the
way HCI has gotten us up until this moment in time,” Bell said.
“What
would it mean to [have] systems that were, I don’t know, nurturing?
Caring? The robots that didn’t want to kill us, but wanted to look after
us.”
As
with computer science before it, the 3A Institute is developing a
curriculum for this as-yet-unnamed new science. The first draft will be
tested on 10 graduate students in 2019.
Bell’s
speech in Dublin, titled “Managing the Machines”, included much more
detail than reported here. Versions are being presented around the
planet, and videos are starting to appear. This writer highly recommends
them.
