Improving public services using artificial intelligence: possibilities, pitfalls, governance

Abstract

Artificial intelligence arising from the use of machine learning is rapidly being developed and deployed by governments to enhance operations, public services, and compliance and security activities. This article reviews how artificial intelligence is being used in public sector for automated decision making, for chatbots to provide information and advice, and for public safety and security. It then outlines four public administration challenges to deploying artificial intelligence in public administration: accuracy, bias and discrimination; legality, due process and administrative justice; responsibility, accountability, transparency and explainability; and power, compliance and control. The article outlines technological and governance innovations that are being developed to address these challenges.

Keywords:

• artificial intelligence (AI)
• chatbots
• automated decision making
• ethical AI
• algorithms
• digital government

Acknowledgements

This article was originally delivered at The China-Australia Dialogue on Public Administration 2019 Workshop ‘Taking advantage of new technologies’, held at Sun Yat sen University, Guangzhou, China on 5-7 November 2019. I gratefully acknowledge the financial support provided by the organisers to enable my attendance and participation, and for Workshop attendees for their comments on the earlier draft of this article. This paper was prepared while working in the UQ-CSIRO Responsible Innovation collaboration.

Disclosure statement

No potential conflict of interest was reported by the author.

Notes

1. https://www.dhs.gov/science-and-technology/news/2018/07/09/news-release-st-announces-winners-15m-prize-competition.

2. https://www.nccdglobal.org/assessment/structured-decision-making-sdm-model.

3. https://www.csiro.au/en/Research/BF/Areas/Digital-health/Supporting-hospital-and-health-systems/Waiting-times.

4. https://www.data61.csiro.au/en/Our-Research/Our-Work/Safety-and-Security/Disaster-Management/Spark.

5. https://www.torque.com.sg/news/traffic-jams-in-singapore-may-lessen-with-use-of-a-i/.

6. http://www.globaltimes.cn/content/1070546.shtml.

7. https://www.businessinsider.com.au/the-ato-launched-a-siri-for-tax-and-has-called-it-alex-2016-12.

8. https://www.zdnet.com/article/ip-australias-alex-is-more-than-just-a-chatbot/.

9. The black boxed nature of algorithms can also occur as a result of the nature of data being used, whereby data collected for one purpose in particular circumstances is repurposed for other datasets and algorithms, but in doing so misunderstand the nature and meaning of the original data. For example, Eubanks (2018) observed how the variable “failure to cooperate” poorly represented what actually had occurred. Similarly, in criminal justice systems “breach parole” can result from deliberate non-compliant behaviour, or an inability to afford public transport to reporting locations.