Principles, frameworks, and codes for the responsible, ethical and/or trustworthy use of AI abound – tools that provide a decent starting point for organisations to consider deeper questions concerning the governance, transparency, and accountability of AI systems.
These tools can easily appear meaningless and hollow unless they are widely understood and observed across the organisation itself, and swiftly followed up with substantive, concrete action.
Transparency is often cited as a core principle of ethical AI, responsible AI, and trustworthy AI. Yet it is often practised in a partial, piecemeal, and reactive manner. There are many reasons for this, including the legitimate need to protect IP, stymie manipulation and gaming of the system, and minimise legal liability.
Opacity also provides convenient cover for any organisation not wanting to state publicly it doesn’t understand how its system works, to say one thing and do another, or to market it misleadingly or inaccurately.
The opacity of AI and algorithmic systems erodes confidence and trust. Given the importance of these technologies to government and economies across the world, policymakers are starting to mandate the transparency of AI and algorithmic systems.
Given these obligations are not widely known or understood and often differ by jurisdiction and by topic, AIAAIC has created a legal transparency repository to help students, researchers, NGOs, policymakers, and others understand the actual and potential legal landscape.
The repository comprises a basic synthesis of known laws directly and indirectly governing AI and algorithmic transparency, and is intended to help answer questions such as:
What are the legal transparency obligations for AI and algorithms today?
What do proposed legal transparency obligations look like?
Other than standalone AI law, which types of law apply to AI and algorithmic transparency?
What are the similarities and differences between different legal transparency obligations across the world?
Relevant transparency laws were identified by a scan of the AIAAIC repository for incidents and controversies involving litigation, followed by a scan of the internet and social media using relevant keywords and phrases.
Legal students and others are encouraged to help expand the repository to cover more jurisdictions and enable deeper analysis of different legal approaches to AI and algorithmic transparency.