In Brief | Artificial Intelligence in the Public Sector

Artificial intelligence (AI) is a way of describing a range of cognitive technologies that simulate the natural intelligence displayed by humans, such as learning and problem solving. Machine learning and robotics come under the umbrella of AI.The following resources will introduce you to artificial intelligence in the public sector.

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The seeds of modern AI were planted by classical philosophers who attempted to describe the process of human thinking. As Pamela McCorduck put it in Machines Who Think:  “Artificial Intelligence began with an ancient wish to forge the Gods.”The development of the computer in the 1940s allowed scientists to realise their longstanding dream of a thinking machine. Since then, machines have been "smarter" than us in many ways but a central place for AI has only become apparent recently with the development of the second-generation World Wide Web, which depends deeply on AI techniques for finding, shaping, and inventing knowledge. YouTube has grouped together a recent series of videos on AI here.

AI is seen as key technology in economic development with The Conversation noting that the US and China are considered to be leaders. The European Commission is developing a coordinated, 'human-centric' AI plan. The 2018-19 Federal Budget provided $29.9 million over 4 years to "strengthen Australia's capability in Artifical Intelligence...and Machine learning."

AI now appears to be on the brink of revolutionising industries as diverse as health care, law, journalism, aerospace, car transport and manufacturing, with the potential to profoundly affect how people live, work, and play. McKinsey Global Institute research suggests that by 2030, AI could deliver additional global economic output of $13 trillion per year.

Digital businesses are already pairing AI and big data to learn customer browsing patterns, purchase history, and preferences. The Appian blog describes AI applications including: personalised recommendations as customers browse online or chat with merchants via messaging apps; identification of customer calling patterns in hours instead of weeks or months; using AI-powered “bots” to handle routine tasks—with natural language processing—to interpret customer requests, and instantly search back-end systems for answers, without the help of live agents. 

The Future of Humanity Institute at Oxford University predicts that in 50 years there is a 50% chance that AI will outperform humans. For what this means for the future of innovation go to Content Group's Medium newsletter. A June 2018 executive briefing from the McKinsey Global Institute examines the promise and the challenge of automation and AI in the workplace and outlines some of the critical issues that policy makers, companies, and individuals will need to solve for. 

Applications of AI to the public sector are broad and growing, with early experiments taking place around the world.  A January 2018 Harvard Business Review article notes that “in addition to education, public servants are using AI to help them, for example, make welfare payments and immigration decisions, teach and evaluate students, detect fraud, plan new infrastructure projects, answer citizen queries, adjudicate bail hearings, triage health care cases, and establish drone paths. Capgemini’s 2017 report Unleashing the Potential of AI in the Public Sector sees improved quality as a key outcome of public sector AI, for instance in service personalisation. This August 2017 Ash Centre for Governance at Harvard University report explores the various types of AI applications and current and future uses of AI in government delivery of citizen services. Lisa Cornish discusses the use of AI to support better government decision making in this 2018 article from the Mandarin.

One way of considering how to make the best use of AI technologies is to think of them as a member of the team that can help people be more productive. Deloitte calls these team members “AI Assistants” with different capabilities which can “augment your current team; relieving them from mundane repetitive tasks and empowering them with analytics drawn by accessing huge quantities of data in just seconds”. For instance, the introduction of Amazon's Alexa digital assistant into Australia has spurred new service offerings through its third party Alexa skills set, including a phone finding service, property updates and energy account management.

Unlike the (often loathed) office assistant Clippy (introduced by Microsoft in the late 1990s) today’s sophisticated virtual assistants now understand colloquial language, provide intelligent answers to questions, and assist users to navigate websites.End users of government online services increasingly appreciate AI assistance. Not only is interacting with government complex but having contextual assistance can dramatically speed up the process. End-users appreciate notifications from government, such as changes in superannuation payments and are starting to look at services in terms of life events (eg death of a family member, having a child).

In a 2019 article for The Mandarin, Pia Waugh writes that these end users are looking for both "a more conversational service when it came to transacting with government, and full visibility of the interactions that happen between agencies on their behalf to give them the ability to correct the record (where required) without delay."  For government this means the possibility to personalise interactions with citizens, and simplify complex and abundant information on agency websites, in line with the government’s Digital Service Standard.

The Australian Taxation Office (ATO) was the first agency to implement a virtual assistant – ‘Alex’ – on their website in August 2015. Alex responds to queries about personal tax, and importantly, understands conversational language and learns from questions to improve answers.  In November 2018, then Minister for Human Services and Digital Transformation Minister Michael Keenan announced  that the DHS Augmented Intelligence Centre for Excellence would lead development of virtual assistants and encourage their adoption by other arms of the federal bureaucracy. The Australian Digital Health Agency which runs the MyHealth record system has also reportedly started work on a proof-of-concept for its own advanced virtual assistant

As AI becomes more ubiquitous, people who work both inside and with government are coming up with an ever-expanding list of ways to use it. This infographic gives an inexhaustive list of specific use cases — some of which are already up and running and some of which are still just ideas. Go to Wikipedia's page on AI in government for more examples and the Centre for Public Impact's How to make AI work in government and for people for a guide on ways governments can reach decisions and reshape government services.

AI can help manage government data, analyse it and find patterns that humans might not have thought of. When it comes to data sets so big that they become difficult for humans to manually interact with, AI leverages the speedy nature of computing to find relationships that might otherwise be proverbial haystack needles. IP Australia has been an early adopter of AI. The Mandarin quotes a senior officer from the agency as saying in 2015 that “that these technologies will form the foundations of the service delivery of the future and we must start engaging with them”.  As well as trialing IBM’s Watson cognitive computing tool, IP Australia Trade Mark Search – launched in February 2017- contains several AI elements to help people ensure their trademarks are unique. You can read a 2018 case study on the Trade Mark search facility here.

Some government agencies are using AI to recognise and report objects in photographs and videos — guns, waterfowl, cracked concrete, pedestrians, semi-trucks, everything. Others are using AI to help translate between languages dynamically. Some want to use it to analyse the tone of emails. Some are using it to try to keep up with cybersecurity threats even as they morph and evolve. After all, if AI can learn to beat professional poker players, then why can’t it learn how digital black hats operate?

The defence sector is increasingly interested in AI.  A 2019 Deloitte report The Path to Prosperity: Why The Future of Work is Human describes a case study from the Australian Department of Defence which augments their human workforce with AI Assistants, to improve military readiness and operational effectiveness in a fiscally constrained environment. The introduction of AI Assistants has minimised human errors, eliminated low value-adding human work and accelerated the speed of work, while creating a superior employment experience for the broader workforce. 

A 2017 paper from the Rand Corporation describes applications of AI to: training systems for defence vehicles; processing data in military surveillance; using augmented reality to close skill gaps in complex maintenance; facial recognition; solving logistics challenges; support war games; automate combat; speed weapon development and optimisation and identifying targets. Robert Dane – who heads Australian unmanned surface vessel specialist OCIUS – has flagged the crucial role AI will play in security surveillance activities. To hear more from Robert Dane tune into a podcast here.

Even though automation has been affecting humans in blue-collar  high-routine operations for more than 30 years, new developments  in AI and robotics are now affecting white collar jobs, such as law and accountancy. The good news is that new technologies are likely to substitute for some types of workers, and be complementary to, and hence increase demand for, other types of workers. Computer-based technologies appear to be complementary to workers who perform non-routine cognitive jobs. See a recent article by Geoff Borland in the Conversation for more on this thinking.

When the work of public servants can be done in less time, governments might look at AI to reduce staff numbers. Conversely, they may wisely choose to invest in the quality of service delivery. As the Harvard Business Review recommends “they can re-employ workers’ time towards more rewarding work that requires lateral thinking, empathy, and creativity — all things at which humans continue to outperform even the most sophisticated AI program.” Australia's Chief Scientist, Alan Finkel, talks about overcoming mistrust of AI in a post on the Conversation in May 2018, that includes the idea of voluntary certification for AI tools. Also in May, The Conversation counselled against thinking that AI can "solve everything". In July 2019, Alan Finkel released The Effective and Ethical Development of Artificial Intelligence: an opportunity to improve our wellbeing which acknowledges that, as AI becomes more advanced, its applications will become increasingly complex and will challenge our rights and regulatory environment. 

A June 2019 report by the European Commission has claimed that AI in the public service can “empower” public servants to make better policy and deliver more efficient services.The report argues that AI requires sustainability to protect the societal and natural environment, growth to secure employment and progress, and inclusion to ensure benefits for everyone. However, utilising AI “should not lead to a lower quality of human relationships within public services or a reduction of such services,” the report asserted.A human-centric use of AI should aid public servants to improve the quality and efficiency of public services by improving accessibility and availability of information, for example.

The Mandarin notes that each policy recommendation emphasises the importance of providing human-centric, trustworthy and ethical AI-based services for individuals. These are:

  • Install mechanisms which provide borderless, interoperable, personalised, user-friendly, and end-to-end digital services to all – at every level of public administration.
  • Adopt a proactive model of public service delivery that enhances effectiveness and quality.
  • An individual should be able to interact with a person when an AI-based service does not run properly, or when requested.
  • Set up a single point of contact for individuals. Deploy natural, conversational user interfaces that can redirect individuals to information or services easily, for example.
  • Develop mechanisms that allow users to give feedback on the interfaces.
  • Develop tools that ensure safe services can be deployed for all, with internet access for the entire population, regardless of capability or economic class.

Addressing both the technical and ethical apsects of AI is becoming of  increasing importance both in Australia and internationally. For example, Germany has rolled out government-led ethical advice on the ethics of automated vehicles and New York has put in place an automated decisions task force, to review key systems used by government agencies for accountability and fairness. The UK has a number of government advisory bodies, notably the Centre for Data Ethics and Innovation and the European Union has explicitly highlighted ethical AI development as a source of competitive advantage. The federal government released its own AI Ethics Principles in November 2019.

Data 61/CSIRO'S discussion paper Artifical Intelligence: Australia's Ethics Framework informed the government's approach to AI ethics.The report examined key issues through exploring a series of case studies and trends that have prompted ethical debate in Australia and worldwide. In a  2019 post on The Conversation, Anne Huggins argues that, although automation can improve the consistency and efficiency of government processes, if there is bias or error in the computer program or data set, a flawed decision-making logic will be applied systematically, meaning large numbers of people could be affected. She cites Centrelink’s employment income confirmation system, known as “robo-debt”, as a high profile example of what can go wrong with automated decision making.  In October 2019, the federal government announced the establishment of a research centre to investigate responsible, ethical and inclusive automated decision making.

AI generates consumer benefits and business value but it is also giving rise to a host of unwanted, and sometimes serious, consequences. This recent McKinsey Quarterly article looks at ways to mitigate the risks of applying AI and advanced analytics by applying the principles of clarity, breadth and nuance. In terms of government use of AI,  the Centre for Public Impact has developed a guide to assist legitimacy – the deep well of support that governments need in order to achieve positive public impact.

CSIRO’s Data61 has also developed an AI Technology Roadmap for the Australian government which outlines the importance of action for Australia to capture the benefits of AI, estimated to be worth AU$22.17 trillion to the global economy by 2030.

Specifically the roadmap:

  • highlights areas of focus to advance the development and adoption of AI technologies in Australia including skills, infrastructure, research, regulation and data governance
  • identifies three areas where Australia could build on its existing strengths and capabilities, with opportunities to solve national problems and export AI-driven solutions
  • will frame policy discussion to maximise the benefits for Australia.

Other recent AI projects include:

In March 2018, IPAA ACT presented Artificial Intelligence and the Public Sector with Professor Genevieve Bell, Director, 3A Institute as its keynote speaker.  A video of the event can be found here. The 3A Institute at the Australian National University tackles complex problems around artificial intelligence, data and technology and managing their impact on humanity. 

Professor Bell also gave the 2017 Boyer Lectures, with the fourth and final lecture possibly the most pertinent in showing how AI has permeated our lives. You can also watch a You Tube video of her discussion with the Digital Transformation Agency in February 2018. In May 2019  the website reported that Genevieve will lead a panel considering opportunities for Australia in the development of AI sovereign capability.


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