Public reading tracker
Reading Log
Public notes from laws, policies, frameworks, academic papers, and cybersecurity guidance shaping my research.
10Total sources
3Sources summarised
4Sources currently reading
2Sources used in proposal
Reading Categories
AI Governance Frameworks
Cybersecurity Frameworks
Agentic AI and Autonomous Systems
AI Risk and Compliance
Australia AI Law and Policy
Literature Review Papers
Supervisor Papers — Australia
Useful Quotes
Sources
Used in Proposal
law
Primary Laws and Policies
2024
EU AI Act 2024
European Union
Why it mattersEstablishes a risk-based legal model for AI regulation.
Key ideaHigh-risk AI requires governance, transparency, and oversight.
Cybersecurity relevanceRelevant to secure deployment, logging, provider duties, and systemic risk.
Use in my researchComparative benchmark for Australian AI cyber law.
Summarised
guidance
Australia AI Law and Policy
2024
Australia Voluntary AI Safety Standard
Department of Industry, Science and Resources
Why it mattersShows Australia’s voluntary baseline for responsible AI.
Key ideaOrganisations should adopt practical guardrails before mandatory rules mature.
Cybersecurity relevanceConnects AI safety with governance, monitoring, and accountability.
Use in my researchAustralian baseline source.
Used in Proposal
policy
Australia AI Law and Policy
2024
Australia Mandatory Guardrails for AI in High-Risk Settings
Department of Industry, Science and Resources
Why it mattersSets out proposed mandatory guardrails for high-risk AI.
Key ideaVoluntary ethics may be insufficient for high-risk AI settings.
Cybersecurity relevanceImportant for high-risk AI controls, assurance, and auditability.
Use in my researchCore Australian policy source.
Reading
guidance
Australia AI Law and Policy
2024
OAIC Guidance on Commercially Available AI Products
Office of the Australian Information Commissioner
Why it mattersConnects AI adoption with Australian privacy obligations.
Key ideaAI product use must still comply with privacy principles and data handling duties.
Cybersecurity relevanceRelevant to privacy, data security, and vendor risk.
Use in my researchPrivacy and data protection track.
Summarised
framework
AI Governance Frameworks
2023
NIST AI Risk Management Framework 1.0
NIST
Why it mattersProvides a structured AI risk governance model.
Key ideaAI risk should be governed, mapped, measured, and managed.
Cybersecurity relevanceUseful for control mapping and risk assessment.
Use in my researchFramework comparison.
Reading
framework
AI Risk and Compliance
2024
NIST Generative AI Profile
NIST
Why it mattersApplies AI RMF concepts to generative AI risks.
Key ideaGenerative AI requires specific risk profiles and mitigations.
Cybersecurity relevanceRelevant to prompt injection, data leakage, misuse, and monitoring.
Use in my researchGenerative AI risk track.
Summarised
framework
Cybersecurity Frameworks
2024
NIST Cybersecurity Framework 2.0
NIST
Why it mattersCybersecurity governance baseline for organisations.
Key ideaGovern, identify, protect, detect, respond, and recover.
Cybersecurity relevanceCore cyber control reference for AI compliance mapping.
Use in my researchCybersecurity control mapping.
Reading
guidance
Cybersecurity Frameworks
2025
OWASP Top 10 for LLM Applications 2025
OWASP
Why it mattersIdentifies leading security risks for LLM applications.
Key ideaLLM apps introduce distinct threats such as prompt injection and sensitive data exposure.
Cybersecurity relevanceDirectly relevant to AI application security controls.
Use in my researchThreat and control mapping.
To Read
standard
Agentic AI and Autonomous Systems
2025
NIST AI Agent Standards Initiative
NIST
Why it mattersSignals emerging standards work for AI agents.
Key ideaAgentic systems need identity, evaluation, interoperability, and safety standards.
Cybersecurity relevanceRelevant to agent accountability and secure tool use.
Use in my researchAgentic AI governance track.
Reading
framework
Agentic AI and Autonomous Systems
2025
IMDA Model AI Governance Framework for Agentic AI
IMDA / AI Verify Foundation
Why it mattersFocuses governance attention on agentic AI systems.
Key ideaAgentic AI requires lifecycle controls, accountability, and safety practices.
Cybersecurity relevanceUseful for autonomous system risk and compliance controls.
Use in my researchComparative framework analysis.