Impact of Technology on Administrative Law Lecture Slides with Audio - Update 2023

Impact of Technology on Administrative Law

1. Overview

  • Examination of how technology, particularly Artificial Intelligence (AI), influences administrative law.

2. Outline

  • Part I: Overview of Artificial Intelligence

  • Part II: Government's Use of Automated Decision-making

  • Part III: Potential Benefits and Risks

  • Part IV: Administrative Law Concerns

  • Part V: Regulatory Initiatives

3. What is Artificial Intelligence?

  • AI refers to computer-based technologies exhibiting processes similar to human intelligence.

  • Key characteristics include reasoning, learning, and environment perception (Source: Australian Human Rights Commission).

4. AI Timeline

  • 1955: First AI program introduced (Logic Theorist).

  • 1980: Emergence of expert systems.

  • 1997: Deep Blue defeats world chess champion, Gary Kasparov, marking AI's advanced capabilities.

5. Categories of AI

5.1 Types of AI

  • Narrow AI: Designed for specific tasks.

  • General AI: Theoretical AI that possesses human-like cognitive abilities.

5.2 Technologies

  • Expert Systems: Early AI with pre-programmed rules for decision-making.

  • Machine Learning: Algorithms that learn from data.

6. Robodebt Case Study

  • Involvement of AI in automated debt collection led to systemic failures – labeled as crude and unfair.

  • Key failures include ignoring legal advice and flawed assumptions in decision-making processes.

7. Machine Learning Process

  • Sequential steps including defining problems, data collection, and model training are crucial for effective machine learning.

8. Benefits and Risks of AI in Decision-making

8.1 Potential Benefits

  • Improved accuracy and consistency, cost reduction, and enhanced service delivery.

8.2 Risks

  • Data errors, programming biases, and the 'black box' problem where decision-making processes are opaque.

9. Administrative Law Concerns

9.1 Review and Justification

  • Incompatibility with judicial review principles due to the absence of human cognitive capacities in decision-makers.

  • Key case: Pintarich v Deputy Commissioner of Taxation (2018).

9.2 Transparency and Accountability

  • AI systems challenge traditional expectations of human mental processes in decisions, highlighting a need for new legal interpretations.

10. Regulatory Initiatives

10.1 Proposed Legislative Reforms

  • Introduction of a consistent legal framework for transparency in AI operations within governance.

  • Creation of a body to monitor AI decision-making regarding fairness and bias avoidance.