Abstract
The rise of automated decision-making in government poses both benefits and challenges. This article identifies and examines legal considerations relevant to governments and businesses in automating existing decision-making processes,
focussing on planning permits and building approvals as a case study. It examines issues of transparency, algorithmic bias, privacy, data and intellectual property rights, as well as the implications of the use of generative Artificial Intelligence (AI).
It also considers legal issues including whether decisions can be automated and if so, whether they are susceptible to judicial and administrative review; legal liability for damage caused by the use of AI in government decision-making; and the admissibility of AI-generated information. It is argued that although the use of AI provides significant benefits in terms of speed, efficiency and quality of decision-making, attention to the considerations of transparency, responsibility, privacy, liability and admissibility is required to minimise the risks of utilising AI systems.
focussing on planning permits and building approvals as a case study. It examines issues of transparency, algorithmic bias, privacy, data and intellectual property rights, as well as the implications of the use of generative Artificial Intelligence (AI).
It also considers legal issues including whether decisions can be automated and if so, whether they are susceptible to judicial and administrative review; legal liability for damage caused by the use of AI in government decision-making; and the admissibility of AI-generated information. It is argued that although the use of AI provides significant benefits in terms of speed, efficiency and quality of decision-making, attention to the considerations of transparency, responsibility, privacy, liability and admissibility is required to minimise the risks of utilising AI systems.
Original language | English |
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Pages (from-to) | 143-168 |
Number of pages | 26 |
Journal | Bond Law Review |
Volume | 35 |
Issue number | 1 |
DOIs | |
Publication status | Published - 5 Sept 2023 |
Keywords
- automation
- machine learning
- artificial intelligence (AI)
- building
- planning
- automated decision-making
- algorithms