
Publication
Training AI models and copyrighted materials
For the first time, a US court has found that copyright was infringed by copying works for the purpose of training an AI legal research tool.
Australia | Publication | June 14, 2019
APRA’s recently released Information Paper, regarding the recent self-assessments undertaken by financial institutions, indicates focus areas for APRA in the upcoming period of regulatory supervision.
APRA called for self-assessments on a range of ADIs, insurers and super funds and asked those entities to assess their present capabilities in non-financial risk management as well as in matters of culture and governance. APRA released the paper to further assist the sector in addressing the challenges of embedding effective risk governance practices within their organisations.
APRA observed some key emerging themes from the self-assessments:
Significant uplift is required across industries to bring governance and the management of non-financial risks to an appropriate standard. APRA – 22 May 2019
In a clear signal to the sector, APRA foreshadowed increased supervisory intensity for governance, accountability and culture for all regulated institutions. Given Hayne’s robust commentary on the performance of regulators, we can expect APRA to walk the talk on this.
The questions for institutions to now ask themselves include:
There is no doubt that regulatory focus on whether institutions are proactively improving the management of non-financial risk, and prioritising risk culture, governance and remuneration will continue to sharpen. There is also no question that, in this regard, all organisations – and particularly financial institutions – must be able to demonstrate, both to regulators and, increasingly, the public, an effective and continuing response to these challenges.
Publication
For the first time, a US court has found that copyright was infringed by copying works for the purpose of training an AI legal research tool.
Publication
Federally regulated employers may soon be required to review and possibly raise pay rates for part-time, seasonal or casual workers under new “Equal Treatment” wage rules.
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Developing high-performance generative AI systems and other AI systems based on machine learning often requires access to vast amounts of data for training (AI training data) and improving their accuracy and performance, and data scraping is an approach that is taken to generate large enough data sets.
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