Australia's AI Ecosystem 2019 - Annual snapshot of the local AI ecosystem, and what it needs to develop into a globally competitive industry ...
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Australia's AI Ecosystem 2019 Annual snapshot of the local AI ecosystem, and what it needs to develop into a globally competitive industry
© 2019 Silverpond Ltd
All rights reserved
Exception: Data from Appendix A available under
a Creative Commons Attribution-NonCommercial-
ShareAlike license.
About us
Silverpond is a team of data scientists, machine
Acknowledgement of Country learning specialists and software engineers who
design solutions to hard problems. We love big
We would like to acknowledge the Wurundjeri data and turning blue-sky ideas into reality.
people, the traditional owners of the Kulin Nation
where this report was created. Over 14 years we have developed big data and
software solutions for clients in industries ranging
We would like to pay our respect to their Elders from utilities, media, retail, and technology, to
past, present and emerging, and extend that healthcare, education and research.
respect to all Indigenous Australians. We
acknowledge that sovereignty was never ceded. silverpond.com.au
Australia's AI Ecosystem - 02
Australia's AI
Ecosystem 2019
AI Ecosystem at a Glance 05
People in AI 06
Organisations in AI 09
Interviews 11
Agustinas Nalwan 12
Jonathan Chang 16
Katherine Bailey 20
Tim Miller 24
Toby Walsh 28
Appendix: Survey Results 32
Australia's AI Ecosystem - 03
AI isn't the future... it's here
AI shapes our lives, informing what we watch, purchase, and learn. AI
patrols our beaches to save lives, drives improvements in IVF, and helps
businesses reach their customers in new ways. It is no longer about when
AI will arrive; our lives are already impacted by this technology every day.
How will Australia respond?
Will we be reliant on importing AI from overseas, or will we foster our own
ecosystem to harness the benefits of creating, managing, and applying
AI solutions?
Acknowledgement of Country
We would like to acknowledge the Wurundjeri
people, the traditional owners of the Kulin Nation
where this report was created
We would like to pay respect to their Elders past,
present and emerging, and extend that respect to
all Indigenous Australians. We acknowledge that
sovereignty was never ceded.
Australia's AI Ecosystem - 04
AI Ecosystem
at a Glance
01
it will be able to develop into an important area of capability
a regional powerhouse. The within the State. We understand
results support this hypothesis: the new Victorian Department
there are talented and educated of Jobs, Precincts and Regions
individuals hungry to learn and is exploring the opportunity to
work in the field, but the industry establish an AI Hub in Melbourne
needs support to develop. and we hope this report can help
inform their decision making.
This report examines the current In 2018 we published the first
state of Australian AI and how Victorian AI Ecosystem report While this is a Victoria-centric
its growth can be supported. to provide a basis for better report (78% of respondents
It contains insights from the understanding of the size are Victorian residents), AI is a
Australian AI Ecosystem Survey and capability of Victoria’s national issue. All stakeholders
plus interviews with five leaders AI ecosystem. The Report from the federal government to
in the field. was welcomed by Victoria’s community groups will need to
Department of Department of be involved in supporting and
Our hypothesis when we started
Economic Development, Jobs, regulating its growth.
this survey was that there is a
Transport and Resources as it
small but talented ecosystem
established benchmark data on
in Australia, and with support
Australia's AI Ecosystem - 05
Snapshot
People in AI
In 2019, the typical member of Australia's AI
ecosystem is a white man in his 30s who is new
to the field, highly educated, and in search of
new opportunities. Diversity is a problem.
To grow Australia's AI capacity, we should focus on people:
• Educate the public, business, and government about AI
• Stem the brain drain to attract and retain diverse talent
Survey highlights about
the human side of AI
The ecosystem is highly
educated - more than half of
the people involved in AI in
Australia have post-graduate or
doctorate degrees.
Women are higher educated than
their male colleagues.
People are largely new to the
field with 65% of respondents
having worked in AI for four
years or less. Prefer not to say
Non-binary women
Men
Women
Australia's AI Ecosystem - 06
Snapshot
Educate the public, business, and government
Low understanding of Case Study: Education Australians turning to
AI in the community, campaign in Finland online education
boardroom, and
The Finnish Government recently Similar to our peers in Finland,
government
launched an initiative to educate Australians turn to online courses
The AI ecosystem perceives low 1% of its 5.5 million citizens to further their AI knowledge.
understanding of AI across the about AI. This program, titled
As traditional education providers
board, highlighting a need for Elements of AI, provides people
like universities have lagged
education. Respondents rated from all backgrounds with a
behind, online AI courses from
the general public understanding basic understanding of what
overseas providers such as Edx
at 3.7 out of 10, corporate AI is and how it is applied. It is
and Coursera have been filling
understanding at 4.4 out of 10, a free online university course
this gap. Universities locally and
and government understanding open to anyone. According to
overseas are now starting to
at 3.6 out of 10. Politico it has taught 142,000
create AI-specific degrees.
students around the world since
early 2018.
“It's not just
about the
skills shortage,
it’s about
having a more
informed
democracy.”
Katherine Bailey
Australia's AI Ecosystem - 07
Snapshot
Stem the brain drain to retain and attract
diverse talent
Talent loss to overseas Diversity Comments from survey
respondents:
In addition to looking overseas The lack of diversity is notable
for education, our highly in Australia's AI ecosystem. "We are already behind. I'm
educated workforce is looking Just 21% of respondents thinking of going overseas to
overseas for jobs as well. identified as women or non- pursue better opportunities
binary. 22% indicated they were and salaries."
This is spurred by the from under-represented groups
lack of funding and "When I finish my PhD I
including LGBTQI+, people of
opportunities in Australia. plan to leave Australia for
colour, and disabled people.
better opportunities."
5% identified intersectional
Hiring and training
underrepresentation. "Were it not for the fact I'm on
Most respondents reported a PR visa, I would have been
We acknowledge the
that their organisations build headhunted to either HK or
difficulties that people from
AI capabilities by hiring SF already."
underrepresented groups
(75%) or training existing
experience accessing the AI
employees (67%). "Without Australian companies
ecosystem, and the negative realising that they are competing
However, it appears that it is impact this has on their with the US for talent, and paying
difficult for these organisations wellbeing, the quality of AI corresponding compensation,
to hire skilled staff. One of created, and the ecosystem we will keep losing the best and
the biggest challenges for as a whole. brightest to the US where most
organisations was finding people of my peers have ended up."
with the right skills (56% of
respondents). "To prevent the brain drain we
need both government and
With 58% of respondents looking private investment in the sector
for new opportunities to work which encourages risk taking and
in Australia, it appears there’s exploratory work."
a market failure in connecting
labour supply and demand.
Australia's AI Ecosystem - 08
Snapshot
Organisations in AI
Applying AI in Australia's most successful
industries will help the ecosystem grow, but the
lack of opportunities is a barrier.
Organisational Top three challenges Top three opportunities
challenges facing AI in Australia for AI in Australia
Apart from hiring, other 1. Number of opportunities 1. Innovation mindset
challenges faced by Australian available in Australia 2. Local talent
organisations are access to 2. Talent leak to overseas roles 3. Australia-specific data
data of sufficient quality (57% of
3. AI market maturity sources
respondents) and volume (50%
of respondents). While getting
good data is difficult, 37.1% of
respondents also saw Australian
data sources as an opportunity.
Organisational
opportunities
Respondents believe that AI will
improve Australian powerhouse
industries such as Health and
Medical, Transport, Finance,
and Agriculture.
There are already great examples
of AI application in these
markets. For example, IVF
Australia and Virtus Health Group
developed an AI system called
Ivy to predict the likelihood of a
viable pregnancy from transfer of
an individual embryo in a woman
undergoing IVF.
Australia's AI Ecosystem - 09Interviews
Once there’s a proper
ecosystem in place, it
will help more traditional
businesses get to grips with
new technologies. Smaller,
more agile companies lead
the way and show what
can be done.
Katherine Bailey
Senior AI Principal, Accenture
Australia's AI Ecosystem - 010Interviews
02
Quantitative data can government support (both
funding and regulatory), the
only go so far. We asked
difficulty of attracting and
industry leaders about
retaining talent, the value of
some of the challenges
public education about AI, and
and opportunities
Australia's unique opportuniites.
facing the AI ecosystem
in Australia. Thankfully there are clear
steps that organisations and
They were selected to cover a
governments can take to
range of perspectives including
overcome these barriers and take
academic, corporate and startup.
advantage of these opportunities.
Despite their diverse It won't be quick or easy, but it's
backgrounds, strong themes certainly possible and important.
emerged: the importance of
Australia's AI Ecosystem - 011Interviews
Agustinus Nalwan
Head of Artificial Intelligence and Machine
Learning at Carsales shares how his team
implemented AI without expert knowledge
With more than 25 years of software development experience,
Agustinus (Gus) Nalwan is very passionate about making people’s
lives easier through technology innovation, and is well-known for
his unconventional approach to solving difficult problems.
Gus has worked across various industries, including 3D/Animation
to games development, desktop software, mobile apps, and most
recently computer vision, ML and AI.
For close to a decade Gus has worked at Carsales.com Ltd
(carsales) in Melbourne. He was the Lead iOS developer at carsales
until he was promoted in late 2017 to his current role as Head of AI
and ML.
Gus and his team provide AI technical direction across the carsales
business, and invent and build cool AI projects, such as their multi-
award winning AI-assisted image recognition tool called Cyclops.
✅What do you see as some of the big We all acquired our AI and ML skills and knowledge
challenges facing AI in Australia? on the on the job through trial, error and practice.
One of the biggest misconceptions people have However, it’s important to highlight we all had
is that developing AI is hard and expensive, and to quickly develop an understanding of the
requires the skills of experienced data scientists / fundamentals, like how to prepare our data to
PhD graduates. This is not true! ensure our AI tool wasn’t biased.
At carsales our AI and MI team is comprised of only The majority our AI and ML projects at carsales
five people, who prior to joining carsales had no didn’t require us to have a deep understanding of AI
previous data science experience. We came from techniques, framework or model architecture. A few
various software engineering backgrounds and years back when we built Cyclops, the solutions
leveraged our existing skills and tools available to available in the market were too expensive, so we
solve business problems.
Australia's AI Ecosystem - 012Agustinus Nalwan
built Cyclops from scratch. However recently my What do you see as the biggest
team employed third party AI and ML applications opportunities for AI in Australia?
to help us build a lot of our new AI.
The opportunities are massive because not many
Some examples of AI and ML services that require companies are adopting AI at present.
just a basic understanding of data science are
AWS Sagemaker, Microsoft ML Studio and Google At carsales we have recently launched our new AI
Auto ML. tool called Tessa to help our customer service team
approve vehicle listings at a faster rate, therefore
I strongly believe many business problems can be improving the customer experience.
solved by utilising AI third party tools. I feel there is
no need for a business to heavily invest into hiring Vehicle ads on carsales used to take up to 3 hours
expensive talent before trying these applications. to approve, now they’re approved in 7 seconds!
Another challenge facing AI is integration. The AI Previously our customer service team had to
journey doesn’t end once the AI is built – you’re manually look through each ad listing that was
only 40 per cent finished! Integration is the step that created on carsales to ensure they adhered to our
is often neglected, but it makes up the final 60 per terms and conditions before the ad was published.
cent, therefore it’s extremely important to get it right It was a manual and time consuming process,
to ensure the AI is supported by all stakeholders which has now been eliminated thanks to Tessa!
and consumers across the business.
Tessa was built partially using AWS SageMaker,
I feel every AI and MI team should align themselves which is a managed service designed to
with the KPIs of their business stakeholder, so it is make it simpler to build and train machine
in their best interest to adopt the technology. Plus learning algorithms.
bring their key stakeholders on the AI journey by
I feel more companies in Australia should adopt
actively engaging with them from the start to find
AI and ML engines, like Tessa, to help automate
out what business problems they need solved, and
some of their clunky and time consuming manual
then regularly check-in and seek their feedback at
processes. They will improve their customer
the different stages of the AI and ML development.
experience and free up their staff’s time to focus on
If implementing AI and ML is new to a business, I other important business tasks to help the business
strongly recommend identifying smaller projects remain competitive and grow.
first that can make a big impact, especially because
building AI and ML takes time. This is a great
What industries are best placed to
approach to gain trust from the business to invest
improve performance with AI?
more in this space. Most industries can benefit from AI, especially retail
where personalisation plays a big role in improving
The people aspect is the most important
the customer experience.
consideration when deploying AI and ML to ensure
a smooth integration. For example, a retail vendor could use AI to
provide their customers with recommendations
Australia's AI Ecosystem - 013Agustinus Nalwan
around what shoes or accessories they may like effectiveness, growth and most importantly the
to purchase to match the outfit they previously customer experience.
purchased online.
Unique to Australia: carsales is probably not the
What do you think would need to first to develop an AI image recognition tool for
happen in Australia to foster more vehicles, but we were first to market in Australia.
significant AI capabilities? Our offering is unique because our AI engine
recognises vehicles that are available in the
It would be terrific if there were more government Australian market. Therefore other businesses
incentives for research and development. While should follow suit and capitalise on products in
they do have grants, it’s hard to qualify and I feel their industry that are in demand and are unique to
there are few to go around. Australia, because it’s highly likely that international
AI engines are not trained to identify products that
Universities and businesses could also collaborate
are unique to Australia.
more to ensure postgraduate skills are relevant
to the industry, and to help businesses identify What's the coolest thing you've seen
talent so they can develop career pathways for come out of Australia in the last year?
these students.
Recently I met a Medtech company that totally
This could include businesses sponsoring students blew my mind. They’re working with an IVF
and offering them work experience opportunities company and have built an AI tool that predicts
to help them develop their skills and establish the most viable eggs out of a collection of 10
industry contacts. As a result, students may choose to 15. I was told that during their trial the AI tool
subjects and research projects that are aligned with helped produce around 200 more babies than the
the business sponsoring them. traditional methods.
What opportunities do you see Is there anything else you’d like to add?
Australia as uniquely positioned to
capitalise on? I would like to continue to raise awareness of AI
through sharing my knowledge and experiences
There are a couple of key opportunities that to help people learn from my mistakes and
businesses in Australia could capitalise on: high accomplishments. I would like everyone to flourish
quality data, and uniquely Australian opportunities. in this space, especially in Australia, because if
more businesses can successfully adopt AI, the
High quality data: AI performance is dependent
whole AI ecosystem will grow faster.
on the quality of the data provided. To become
leaders in the AI and ML space, businesses in
Australia should adopt strict practices to ensure the
quality of their data is maintained through proper
governance, because without healthy data the AI
performance suffers, which can affect business
Australia's AI Ecosystem - 014Agustinus Nalwan
Case Study: How Agustinus
spearheaded an AI project within
a large corporation
Four years ago we started an initiative at carsales After building our proof of concept (POC) for
to use AI, with all the hype we wanted to see Cyclops we required more resources, so we entered
whether AI it was just a gimmick or could help us Cyclops into an internal carsales Hackathon.
solve business problems.
The carsales Hackathon is an event where people
We decided to explore what machine learning could from across the business come together to
do for our business by gathering around 15-20 solve business issues or be innovative. Cyclops
people from across the business and to work on was developed by a team of tech and non-tech
four AI projects. professionals for diversity of thought and to ensure
the final product would be commercially viable.
I was a member and the leader of the Cyclops
team, and our business case was to identify After a successful carsales Hackathon, we were
how image recognition could automate our given the green light to work more regularly on
internal processes. We focused on how we could Cyclops. From the original Cyclops prototype
specifically reduce the manual load in classifying we conducted a pilot integration into our internal
photos by carsales staff for vehicle ad listings. photographic management solution. This process
took about three months and we had terrific
Initially we looked into solutions already available results. Cyclops is now integrated into all the photo
in the market, but they were going to be too publishing pipelines at carsales (including our
expensive, so we decided to spend the next two mobile apps) and processes more than 100,000
weeks building something ourselves. photos a day.
If implementing AI and ML tools is new to a
business, I strongly recommend identifying
smaller projects first that can make a big
impact, especially because building AI and ML
takes time. This is a great approach to gain trust
from the business to invest more in this space.
Australia's AI Ecosystem - 015Interviews
Jonathan Chang
Silverpond's CEO says Australia needs to
grapple with difficult questions about ethics
and responsibility
Jonathan Chang is the founder and CEO of Silverpond, a machine
learning and artificial intelligence company based in Melbourne,
Australia. Jonathan leads a team of 30 data scientists, machine
learning engineers, designers and project managers who help
Silverpond’s customers adopt machine learning and artificial
intelligence technology across industries such as media, energy,
asset management, retail, and healthcare.
He’s passionate about how AI will transform society; you can
find him speaking at events and conferences, or working with
local industry groups and government on responsibly applying
this technology.
Silverpond was an early adopter of AI the Deepmind Paper “Playing Atari with Deep
in Australia. What got you interested in Reinforcement Learning”. We set up the machine
AI in the first place? to play and learn on the Friday night, but it kept
dying after a few seconds. When we came back
Silverpond had an office in Portland, Oregon on Monday morning it successfully passed the
when we were working with customers on the first level on its own. That ability to learn made it
west coast of the USA. At that time in 2014, apparent to me what was possible with this kind
deep learning was becoming popular in both the of technology.
academic and startup scene on the west coast
after demonstrating amazing results on common How have you seen things develop in
academic benchmarks. Australia since then?
When I came back to Melbourne from Portland, a Machine Learning as a field has a long history,
few colleagues including Andy Kitchen reproduced being used in industries such as banking and
Australia's AI Ecosystem - 016Jonathan Chang
telecommunications, but deep learning is a regulate this since it will be developed with different
recent phenomenon. Five years ago few people biases and values from what Australians hold
in Australia were aware of deep learning as a dear. We need to be willing to grapple with these
technology so there wasn’t much of an industry. questions. If we do well we maybe able to export
our values.
It developed momentum when practitioners
started training models on GPUs, which lowered What do you see as some of the
the barriers to entry for individuals to start biggest opportunities for AI in
experimenting. I saw an increasing number of Australia?
practitioners go to meetups to share knowledge
Australia will have an edge in AI projects involving
and found startups to take advantage of
the physical world, like infrastructure, agriculture,
the technology.
mining and medicine. Australia has big industries in
It remained a small cottage industry until interest those areas that are competitive globally.
from the media in 2017-2018 helped spur broader
The other thing I think Australia is known for is
interest in AI. We expect this to continue to grow
quality and our distinct values, which shows up in
in 2019.
agriculture and food industries. We're highly trusted
How do you rate Australia's AI for the quality of clean and green agriculture and
capabilities at the moment? the food that we export.
There are great pockets of capability across What would be required for Australia
academia and the commercial industry, but we to develop more significant AI
don’t have the concentrated ecosystem that I’ve capabilities?
seen overseas. Government backing has made a
It would be great to see the community collaborate
difference in China and Singapore where they’re
to build an ecosystem that competes on the
making great strides in developing local talent and
global stage.
connecting stakeholders.
A lot of people would benefit from increased
What do you see as some of the
access to the knowledge required to operate this
biggest challenges facing AI in
technology, from increased collaboration between
Australia?
universities and corporates, to shared discussions
Anecdotally, I’ve seen and heard of talent going around the risks, governance, and ethical issues of
overseas for opportunities. Keeping people here how we apply deep learning and AI.
appears to be challenging for both research
institutions and corporations. What's the coolest thing you've seen
come out of Australia in the last year?
It will be challenging for local teams to compete
One of the cool startups I've come across is
globally in areas such as facial recognition and
a company called CCLabs, working at the
autonomous vehicles which are receiving enormous
intersection of AI and neuroscience. They're
funding overseas. Since it’s likely we’ll import
building a platform to allow you to train real
this technology, we will need to work out how to
live neurons and have them learn and solve
Australia's AI Ecosystem - 017Jonathan Chang
problems just like you would with a silicon-based
neural network.
That's a really interesting take on artificial
intelligence - physical neurons versus
silicon neurons.
By silicon neurons, do you mean
silicon chips?
Yes. The deep learning algorithms we use mimic
human neurons, but they're they're running on
computer chips built in silicon. CCLabs are going to
use biological neurons. It’s an interesting approach
where they are constructing a platform similar to
Amazon Web Services to allow researchers and
companies to experiment with neurons.
While neurons don’t have consciousness, a large
number of these chips networked together might.
At scale it will raise interesting ethical questions.
Australia's AI Ecosystem - 018Jonathan Chang
It would be great to see
the community collaborate
to build an ecosystem
that competes on the
global stage... from
increased collaboration
between universities and
corporates, to shared
discussions around the risks,
governance, and ethical
issues of how we apply
deep learning and AI.
Australia's AI Ecosystem - 019Interviews
Katherine Bailey
The Senior AI Principal at Accenture says Australian
policies and investments are restricting growth
Katherine Bailey is the Senior AI Principal within Accenture
Australia’s AI and Automation Engineering group. Originally from
Dublin, Ireland, her background is in software engineering and data
science, with over a decade in the technology industry, primarily in
Canada, the US and Australia.
Prior to joining Accenture she was Principal Data Scientist at
Acquia, a Boston-based Software-as-a-Service company, where
she spearheaded the company’s Machine Learning initiative.
Katherine speaks and writes regularly on the topic of AI and is
committed to dispelling the myths and removing the confusion
around it, teasing apart the real from the imaginary implications of
these technologies, both practical and ethical.
How did you get started in AI? We were already building products that were doing
stuff with data, but we didn't actually have a data
I was working as a software engineer for Acquia, science team in house at the time, which I saw
a Boston based SaaS (Software as a Service) as a serious gap. It is easy to do stupid things
company. We were working on a personalisation with data if you don't have people who know
product, which included an AB testing component, what they're doing, so I approached the Head of
so somebody had to figure out how the hell you Product and said that we needed a data science
run a hypothesis test. I took it upon myself to get team and I would like to start it. To my delight he
more involved in that side of the product, started agreed and the data science and machine learning
learning about statistical inference and ended initiative at Acquia was born. I went on to hire a
up building the reporting engine for it. Statistical team of data scientists and engineers focused on
inference took me to machine learning and once enhancing the product with ML, specifically Natural
I started down that path, I realized I was far more Language Processing as it was part of a content
interested in machine learning than in straight-up management system.
software engineering.
Australia's AI Ecosystem - 020Katherine Bailey
Australia recently introduced rules that make it very
How do you find Australian AI scene
difficult to attract senior talent because there isn't a
compared to Boston?
path to Permanent Residency. Senior professionals
Culture-wise I see similarities, but the big difference in the peak of their career are never going to come
is the scale of it. The scale of things in Boston if there’s no path to PR. Obviously that's going
is amazing - here in Melbourne there aren't the to be a problem. You also want to attract senior
numbers. In Boston you've got MIT, you've got academics, especially if you want excellent PhD
Harvard, you've got people who are leading programs - no program depends entirely on home-
research in areas like natural language processing. grown talent. If you're not able to attract senior
This feeds a vibrant startup scene and that academic researchers, that's going to be a problem
innovation eventually feeds into the corporates for education in Australia.
because startups are looking to go to market
and pitching their solutions. And there are a lot of And the biggest opportunities?
venture capital firms in Boston. First, education is the big focus to drive adoption of
AI. It's not just about training people to implement
I think we might be a little more risk averse as well.
machine learning solutions, but also having a
That’s obviously a major factor.
population that’s more educated about AI. You have
When you're talking about businesses, I would probably heard about Finland's initiative to educate
say definitely Australian businesses have some 1% of the population about AI. That's a fantastic
catching up to do in their thinking around what can idea. It's not just about the skills shortage, it’s
be done with ML. Especially in Boston, you have about having a more informed democracy.
all of these startups providing services already with
Second, I see the future of AI as being very
machine learning - they're right there, and they're
human-centric, serving human interests and
talking, they're doing, they're solving business
acknowledging the necessary role played by
problems. And because there aren't so many
humans in AI, for example to annotate utterances
startups here, the rest of Australian business isn't
that our smart speakers don’t understand so that
seeing those concrete use cases.
the AI can learn and improve. Companies providing
What do you see as the major AI-based products need to stop hiding that side of
challenges in Australia? how these things work because it’s not going to go
away – humans will always be needed to annotate
The start up culture really, really needs to grow. data. And those whose data is being annotated,
including those whose utterances are being listened
The other main thing is talent. There are great
to, need to be told about it.
universities here producing great talent. But
keeping talent and attracting talent to Australia CTO of Accenture Paul Daugherty wrote a book
depends not just on being able to show a vibrant called “Human + Machine” about how humans
scene where there's interesting work being done in and machines complement each other, which I
AI, but also in a pragmatic and mundane way relies totally agree with. We're building tools, right? It's
on future pathways. not about imitating humans, it's about building
tools to help humans do their jobs better or to
Australia's AI Ecosystem - 021Katherine Bailey
have a better customer experience. So there's an able to cobble together this facial recognition
opportunity to shift the focus away from designing system using tools that are widely available
algorithms to designing the human component, because of the democratisation of AI. One of
i.e. the user interface of the tools that incorporate his points is that anybody can do this, it's an
the algorithms. open data set. They annotated these faces with
judgements about whether people are attractive,
What do you think needs to happen for weird looking, et cetera, to train the system. Then
Australia to develop and foster more when you look at it or send your photo, it'll make an
significant AI capabilities? assessment on how attractive, ugly, weird looking,
or responsible a person you are.
Don't make it so difficult for senior level people to
have a path to PR, that's shooting yourselves in the A lot of people misunderstood what it was about.
foot. You want to be able to attract talent. Some people were outraged because they thought
the suggestion was that this should be deployed.
Also, foster a more vibrant scene that is attractive
Interestingly he was approached by some
to people as a place to come and work on AI.
companies who thought, "we want to be able to
There is a vibrant scene here but it's too small
judge whether somebody is responsible based on
scale. This is something that’s definitely not going
their facial features" which of course is horrific and
to happen overnight and represents a much bigger
clearly missing the point.
story - walking around Melbourne you really see
that the business culture here is very traditional Another interesting thing was about how people
and corporate. It's banks and natural resources reacted to what the machine said about them, and
companies. It's not so much cutting edge the tendency to believe the machine’s judgement
technology. That needs a bigger slice of the pie must be true. That's dismaying and speaks to
here in order to attract and keep people. how badly we need the general public to be more
educated about machine learning. Where there is
And of course it will also help the more traditional
machine learning involved there is data, and that
businesses get to grips with these new
data has been collected by humans. It's so easy
technologies once there’s a proper ecosystem in
to encapsulate the biases in society in the data
place with lots of smaller, more agile companies
that you use for your machine learning system. I
leading the way and showing what can be done.
thought the Biometric Mirror was such a great way
What's the coolest thing you've seen of packaging that up and showing it and exposing
come out of Australia in the last year? these problems with machine learning.
Definitely the Biometric Mirror project at the
University of Melbourne. It makes a really
interesting statement about people's attitudes
towards machine learning.
The creator Neils Wouters’ main field is
architecture. He is not an AI researcher, but was
Australia's AI Ecosystem - 022Katherine Bailey
It's not just about training
people to implement
machine learning
solutions, but also having
a population that’s more
educated about AI....
It's about having a more
informed democracy.
Australia's AI Ecosystem - 023Interviews
Tim Miller
University of Melbourne's explainable AI
expert discusses human rights in the age of
computer intelligence
Tim Miller is an associate professor in computer science at
the University of Melbourne. His area of expertise is in artificial
intelligence, with particular emphasis on human-AI interaction,
AI planning, and explainable AI. His work is at the intersection of
artificial intelligence, interaction design, and cognitive science/
psychology. His areas of education expertise are in artificial
intelligence, software engineering, and technology innovation.
Tim has extensive experience developing novel and innovative
solutions with industry and defence collaborators.
How did you get started in AI? Did your interest in explainable AI
come from that research project?
I got into AI almost by accident. I was formerly a
software engineer when I applied for a postdoctoral Explainable AI came from when I was looking for
position in the AI lab at the University of Liverpool, a new research area. I was looking for something
which was a very strong lab then. They wanted that was future-looking that nobody else might
someone with a background in AI but mostly be doing. I got onto the problems with ethics and
software engineering. I took the risk and got it. decision making, and hunted around University of
I do love software engineering, but the research Melbourne, but couldn't find anyone who was really
side came with AI stuff and that's how I drifted interested in that problem. I have found people
into that area. since who were interested back then, but I never
knew who they were.
Australia's AI Ecosystem - 024Tim Miller
I talked with people about problems they were to do real time experiments with real people on
having employing machine learning and autonomy. their algorithms, which we can't do in universities.
They were employing tools that were quite robust,
but weren't being adopted because the users didn't What do you see as some of the
trust them. A lot of them were using this phrase, biggest challenges facing AI here?
“you can give a decision and you can't explain The biggest challenge is the lack of any
why”. This was a recurring theme. It built on my acknowledgement from state and federal
background in human agent interaction better than governments that this is a really important area,
ethics did, and contributing to transparency would unlike other countries which are bursting forward
mitigate some ethical problems. and trying to do something around it. Ours seem
to be almost paralyzed or they don't care. It's a big
Can you tell us what explainable AI is?
problem that we don't have government backing
If we could define it, that would make things a lot and we're doing everything on our own.
easier. My definition is that it is any tool or method
In trying to compete with other countries, we're
that goes alongside artificial intelligence or is built
too small to have an impact. A small company here
in artificial intelligence that helps a person explain
providing something that's not niche to a particular
why that artificial intelligence has made that
client or Australian need is going to struggle to
decision or made a distinct decision.
compete for talent, funding, and resources.
It could be giving you an explanation, it could be
making decisions that are more intuitive to the What about Australia's biggest
person running the AI, or it could be giving some opportunities?
little bit of insight that helps the person construct The biggest opportunity - we are running behind, it
an explanation for themselves. would have been a better opportunity two or three
years ago - is looking at responsible employment of
There are fantastic academics
AI. Canada, Sweden, Finland, and a lot of Europe
conducting world class research at
are trying to do this in a more principled manner.
Australian universities. Is there a risk
Maybe regulated, maybe not, but it’s about using
of brain drain going overseas or to
AI in a more responsible way and considering the
industry?
impact it has on people rather than being focused
It's hard for us to compete with North America in on the accuracy or things like that.
this field right now, and we're competing with China
The other opportunities involve problems that are
and Europe for talent from Southeast Asia. It can be
unique to Australia. The way we do farming, mining,
difficult to get people to come all the way out here
government and law are different here and require
a long way from home. It's a real problem.
different solutions to those coming from overseas.
Another big problem is that industry is poaching The big superpower AI companies aren't focusing
strong researchers and paying them twice as much on this so there's an opportunity for us there.
as we can pay them, if not more, and giving them
access to massive data sets. They have the ability
Australia's AI Ecosystem - 025Tim Miller
being made in legal or medical situations when
What industries do you see as best
there shouldn't be yet.
placed to improve their performance
with AI? What's the coolest thing you've seen
The legal profession has always been ripe for come out of Australia in the last year?
technological disruption but that hasn't occurred AI to detect poachers in protected wildlife reserves
yet. The finance industry is happening now. across Africa was a really great application. It was
the right tool for the right problem, doing something
Organizations or hospitals where they're doing a lot
meaningful. It would have a nice outcome for
of hand over and transferring information are trying
everybody there except the poachers.
to automate, but there’s such a complicated scope
to make these types of tools useful. I don’t mean Is there anything else you’d like to add?
necessarily in medical diagnosis, where people are
crowing about a lot now, but supporting nurses, A lot of the problems around AI decision making
administrators, and doctors to do better case are being framed as a human rights issue. That's
handling and handover. a positive thing that brought about the human
rights commission white paper on AI. I think people
What do you think we need to develop should know that.
more capabilities?
Also, people in this ecosystem should be familiar
Across technology in general, the simplest thing with the EU General Data Protection Regulation
is a better relationship between industry and if they're not already. Presumably we'll have
academia. The countries that are forging ahead something similar. It would be framed quite
have that already. differently in the local context. The debate around
what that means has been ongoing since 2016
Then, educating people - not just pushing them
when it was first drafted.
through universities but educating people to
understand the limitations and capabilities I also like the idea of using checklists as an ethical
of technology and give them a more realistic code of conduct framework. Give people incentives
perception. That's not what the media give them to use them and have external auditors available to
right now, which is more based around movies. give star ratings similar to the Capability Model in
Software Engineering which is a self-assessment
What opportunities do you see
that you can get external auditors to review you
Australia uniquely positioned to
on. It's a six-level scale of how mature you are as
capitalize on?
a company around the way you develop software
The two things I talked about earlier. There's also and understand your process. People in safety
a better appreciation for getting things right, we're critical software use this, you make it clear what
not as gung-ho as other countries. The whole is being used to make decisions. That's a level of
'move fast and break things'... that happens here, transparency above what most people can give
but people are a little bit more conservative. This is right now.
a downside from an innovation perspective, but it’s
also good that we don’t have high stakes decisions
Australia's AI Ecosystem - 026Tim Miller
The way we do farming,
mining, government and
law are different here
and require different
solutions to those coming
from overseas. The big
superpower AI companies
aren't focusing on this, so
there's an opportunity for
us there.
Australia's AI Ecosystem - 027Interviews
Toby Walsh
The Scientia Professor of Artificial Intelligence
at UNSW questions the lack of a national plan
Toby Walsh is a leading researcher in Artificial Intelligence. He was
named by the Australian newspaper as a "rock star" of Australia's
digital revolution.
He is Scientia Professor of Artificial Intelligence at UNSW, leads the
Algorithmic Decision Theory group at Data61, Australia's Centre of
Excellence for ICT Research, and is Guest Professor at TU Berlin. He
has been elected a fellow of the Australian Academy of Science,
and has won the prestigious Humboldt research award as well as
the NSW Premier's Prize for Excellence in Engineering and ICT. He
has previously held research positions in England, Scotland, France,
Germany, Italy, Ireland and Sweden.
What do you think we should be What do you see as the major
doing to increase the general challenges in Australia?
public's understanding of AI and its
implications? Where's the government's AI policy - the
investment, the policy, the focus?
Education. From K-12 through to retired. Hollywood
has given people all the wrong ideas. The UK has a one billion pound plan. Germany
has three billion euros. Australia has a few tens of
We should emulate Finland which has a MOOC millions. That isn't going to be competitive.
and employers lining up to ensure 1% of the entire
population will have a basic understanding of AI. What would need to happen for
Australia to develop and foster more
Is there a risk of academic brain drain, significant AI capabilities?
either overseas or to industry?
A national AI plan with significant investment in the
Definitely. I struggle to get my students to stay in billions of dollars.
academia, especially in academia in Australia.
Australia's AI Ecosystem - 028Toby Walsh
What do you see as our biggest What is the coolest thing you have
opportunities? seen come from the local AI scene in
the last 12 months?
Problems that challenge Australia especially, or
where we have a natural advantage - so mining, AI for IVF. AI is making babies. Hard to be cooler
medicine, fin-tech, disaster management, than that!
climate change.
Which industries are best placed to
improve performance with AI?
Every industry. But the early wins will be in
knowledge-intensive areas like marketing
and finance.
Where's the government's
AI policy - the investment,
the policy, the focus?
The UK has a one billion
pound plan. Germany has
three billion euros. Australia
has a few tens of millions.
That isn't going to be
competitive.
Australia's AI Ecosystem - 029Further resources
Inspired? Dig a little deeper with these resources about the state of
Australia's AI and technology ecosystems:
• McKinsey Digital Australia Report
• ACS Federal Election Manifesto
• AI Now Diversity Report
• Gartner Predicts the Future of AI Technologies
• 2018 Victorian MLAI Survey
• Ivy - Artificial Intelligence in IVF
Acknowledgements
We'd like to acknowledge the AI Leader Interviews: Thanks to
support that Silverpond received in Agustinus Nalwan, Jonathan Chang,
the creation of this second annual Katherine Bailey, Tim Miller, and Toby
Australian AI Ecosystem Report. Walsh for the time and consideration
Our heartfelt thanks for your time they put into the interviews, as well as
and input. their work in Australia's AI ecosystem.
Thank you as well to everyone who Silverpond Team: Susie Sheldrick,
took the time to complete the survey, Adel Foda, Ed Zambruno, Jonathan
as well as those who passed it on Chang, Lizzie Silver, Katie Wallace,
through their networks and shared on and Yanni Florence
social media.
Community groups: Melbourne MLAI,
A final thank you to all those WiMLDS Melbourne
taking part in Australia's AI
Victorian Government: Kathy Coultas
ecosystem, particularly those from
underrepresented groups - we ANU: Kobi Leins
acknowledge there is an enormous
amount of work to be done to make
access equitable.
Australia's AI Ecosystem - 030Australia's AI
Ecosystem 2019
Contact
Silverpond Ltd
silverpond.com.au
Address:
Level 2, 382 Little Collins Street
Melbourne, VIC 3000 The information contained in this document does not
constitute advice and should not be relied on as such.
Australia Professional advice should be sought prior to any action
being taken in reliance on any of the information.
Silverpond disclaims all responsibility and liability arising
Contact: from anything done or omitted to be done by any party
P: +61 (0) 3 9008 5922 in reliance, whether wholly or partially, on any of the
information. Any party that relies on the information
E: community@silverpond.com.au does so at its own risk.Appendix:
Survey Results
Part 1: About you
Part 2: AI Employment
Part 3: AI in Australia
This data was collected through The survey was promoted
a Typeform survey that was through the Melbourne Meetup
publicly available from Monday community, Silverpond’s network,
18th February to Monday and other networks, particularly
25th March 2019. The survey those in other states.
contained multiple choice and
written responses.
Questions were adapted from
Silverpond's 2017/2018 Victorian
AI Ecosystem Survey. Further
questions were added to give
a deeper undertstanding of the
Australian AI ecosystem.
Australia's AI Ecosystem - 032Appendix: Survey Results
Part 1: About you
A. Age
Age
Format - Multiple choice
prefer to not say 3
207 responders
60 and over 7
50-59 14
40-49 59
30-39 89
20-29 34
under 20 1
0 20 40 60 80 100
B. Gender Identity
Gender
GenderIdentity
Identy
Format - written
203 responders
Note: Genders derived
from answers
Male 150 Female 42 Prefer to not say 10 Non-binary female 1
Australia's AI Ecosystem - 033Appendix: Survey Results
C. Where do you live?
Where do you live?
Format - Multiple choice
180 161
160
207 responders
140
120
100
80
60
40 20
20 11 5 4 2 2 1 1
0
T
ia
d
s
lia
lia
d
ed
NT
ale
AC
lan
or
an
ra
tra
ifi
ct
w
al
ns
st
ec
us
Vi
Ze
Au
h
ee
sp
hA
ut
w
Qu
un
rn
So
Ne
ut
te
w
So
es
Ne
W
D. What type of place
What type of place do you live? do you live?
Rural 2 Format - Multiple
choice, multiple answer
Other 3
207 responders
Regional center 7
Regional 8
Capital city 187
0 50 100 150 200
Australia's AI Ecosystem - 034Appendix: Survey Results
E. Do you identify
Do you identify yourself as belonging to an
yourself as belonging to
under-represented group in the tech industry? an under-represented
group in the tech
industry?
Format - Multiple choice
207 responders
Yes 46 No 149 Prefer not to say 12
F. If yes, please specify
Specification ofof
Specification under-represented group.
underresented group.
Format - Written
Female 30 response
Disability 4 43 responders
Mother 1
Note. Some responders
Older 2
identified with multiple
Immigrant 3 groups. These have
Person of colour 10 been split in the interest
of privacy
Poor 2
LGBQTI+
LQBQTI+ 4
0 5 10 15 20 25 30 35
Australia's AI Ecosystem - 035Appendix: Survey Results
G. What academic
What is your highest tertiary qualification? qualification/s do you
hold? Please list your
NA 20 degree, field of study,
and academic institute.
Advanced Diploma 1
Format - Written
Bachelor 74
response
Diploma 1
207 responders
Post graduate 53 Note. Answers derived
from written responses
PHD 58
0 10 20 30 40 50 60 70 80
H. How would
How would you describe your involvement you describe your
in AI in Australia? involvement in AI in
140 125 Australia?
120
Format - Multiple
100
choice, multiple
80
answers
60
40 29 33
202 responders
18 18
20
2
0 "Other": Job seekers
Technical Non-technical Non-technical Student Amature Other
employee manager employee enthusiast Note. More responders
working with looking to listed "other" however
AI utilise AI
the answers were
categorised into the
fields given
Australia's AI Ecosystem - 036Appendix: Survey Results
Part 2: AI Employment
A. Are you looking for
Are you looking for new opportunities to work new opportunities to
in AI in Australia? work in AI in Australia?
140
123 Format - Multiple
120
choice, Other includes a
100 prompt to write answer
79
80
Other- Maybe
60
207 responders
40
20 Note. Most "other"
5
answers converted to
0
yes or no
Yes No Other
B. Do you currently
Do you currently work in or have you previously work in or have you
been employed in the field of AI? previously been
1 40 132 employed in the field of
Artificial Intelligence?
1 20
1 00 Format - Yes or No
80 74
206 responders
60
Yes - continues to next
40 question
20
No - goes to part 3
0
Yes No
Australia's AI Ecosystem - 037Appendix: Survey Results
C. What type of work do
What type of work do you do in AI? you do in AI?
120
100 Format - Multiple
100 choice, multiple
answers, other includes
80
a prompt to write
61
60
answer
132 responders
40
24
"Other" answers
20
converted to the
0 categories on offer
Applied Research Support
D. How long have you
How long have you worked in AI? worked in AI?
30
Format - Multiple choice
25
25 23
132 responders
20
17
16 16
14
15
11
10
10
5
0
20 + Years 11-20 5-10 Years 4 years 3 years 2 years 1 year >1 year
Years
Australia's AI Ecosystem - 038Appendix: Survey Results
E. What sort of
What is your highest tertiary qualification? organisation(s) do you
currently work for?
NA 20
Format - Multiple
Advanced Diploma 1 choice, multiple
answers
Bachelor 74
132 responders
Diploma 1
Post graduate 53
PHD 58
0 10 20 30 40 50 60 70 80
F. Would you describe
Would you describe your organisation as a your organisation as a
"Tech" organisation? "Tech" organisation?
Format - Yes or No
132 responders
Yes 103 No 29
Australia's AI Ecosystem - 039Appendix: Survey Results
G. Is this job located in
Is this job located in Australia? Australia?
Format - Yes or No
132 responders
Yes - go to I
No - go to H
Yes 127 No 5
H. If not in Australia,
Is this job located in Australia? where is your job
located?
Answers:
Format - Written
• USA
responses
• Sweden
• Norway 4 responders
• New Zealand
Yes 127 No 5
Australia's AI Ecosystem - 040Appendix: Survey Results
I. To which industry
To which industry is this AI work is this AI work most
most closely aligned? closely aligned, if any?
Real Estate, Rental and Leasing 4 Format - Multiple
choice, multiple
Accomodation and Food Services 1
answers, other includes
Whol es ale trade 4 a prompt to write
Mini ng 5 answer
Agriculture, Fores try and Fis hi ng 4 128 out of 207
responders
Adminis trative and Support Serv ices 7
Public Adminis tration and Safety 7 "Other" answers
converted to the
Transport, postal and Warehousing 8
industries provided
Manufacturing 7
Cons truct ion 8
Arts and Recreation 9
Retail Trade 16
Electricity, Gas, Water, Waste services 17
Finance and Insurance 22
Education and Training 21
Health Care and Soci al As sis tance 26
Professional, Scientific or Technical Services 40
Information Media and Telecommunications 44
0 10 20 30 40 50
Australia's AI Ecosystem - 041Appendix: Survey Results
J. Do you outsource any
Do you outsource any AI capabilities? AI capabilities?
Yes, Everything 3 Format - Multiple
choice, multiple
Other 6 answers, other includes
a prompt to write
Data Collection and cleaning 8 answer
Model development 11 128 responders
Labelli ng 16 No - jumps to M
No 92 "Other" answers state
dependance on client or
0 20 40 60 80 100
project needs dictates
outsourcing
K. If your organisation
If your organisation outsources AI, where is the outsources AI, where
external team based? is the external team
16 based?
14
14
Format - Multiple
12
10 choice, multiple
10
8 answers, other includes
6 a prompt to write
4 4
4 3 answer
2
2 1 1 1
32 responders
0
"Other" refers to non-
il
es
r
ia
a
A
e
UK
ina
he
az
ali
p
US
d
in
ro
In
Br
Ot
Ch
str
pp
Eu
geographic workforces
Au
il i
Ph
such as Mechanical
Turk
Australia's AI Ecosystem - 042Appendix: Survey Results
L. How do you or your
How do you or your organisation adopt organisation adopt AI
AI technologies? technologies?
Format - Multiple
Crowdsourced development, e.g. Kaggle 8 choice, multiple
answers, other includes
a prompt to write
Other 10
answer
Enterprise software with AI, e.g. SAP 128 out of 207
15
Leonardo machine learning responders
Automated machi ne learning, e.g. Data "Other"
24
Robot
Co-development wi th partners 37
Cloud based AI ser vices, e.g. Googl e Vision
60
API
Open source development tools, e.g.
adopting models from GitHub 94
Data science modelling tools, e.g.
108
TensorFlow
0 20 40 60 80 100 120
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