Australian insights into AI, machine learning and big data

2 minute read  04.05.2021 Anthony Borgese, Jason Watling, Amelia Norris
The adoption of artificial intelligence, big data and machine learning is impacting privacy, data security and liability.

 

Key takeouts


  • The law is challenged to keep up to date with digital transformation impacting business.
  • AI and big data can benefit organisations but also pose significant legal risks and ethical issues.
  • A key issue is who is liable for the output of the AI when an AI system leads to a decision that results in harm.

The digital revolution continues to transform businesses and markets around the world and the law is challenged to keep up with the pace of change.

Nowhere is this more evident than in the area of artificial intelligence (AI) and big data, which are reshaping the competitive landscape by generating new waves of technical capabilities and innovation.

There is widespread acknowledgment that effective use of big data can significantly benefit organisations by increasing the rapidity of processing, supporting decision making, improving efficiency, and creating new methods and solutions. This can be seen across a multitude of industries such as health, medical care, scientific research, education, sustainable development, agriculture, transport and security.

These benefits must be balanced against the significant challenges that AI and big data pose for businesses and consumers. Key risks exist as a result of holding ever larger volumes of data, the matching and re-identification of data held within, or shared between organisations and the re-purposing of data for unintended uses.

MinterEllison Technology Law Partner, Anthony Borgese, along with Lawyers Jonathan Thompson and Alice Scamps-Goodman, contributed the Australian Chapter to the Global Legal Insights: AI, Machine Learning & Big Data 2020.

In this comprehensive article, the team discusses how the adoption of AI, big data and machine learning is impacting privacy, data security and liability. Regular, day-to-day activities, that in the past would not have involved digital interaction, may now leave both individuals and organisations exposed to more legal risks and ethical issues. Key legal risks explored include data security, privacy, intellectual property issues and liability of the output of the AI, as well as determining who is liable for the output of the AI when an AI system leads to a decision that results in harm.

Following the publication of this article, two key areas surrounding consumer's rights to their data have seen significant progress. Firstly, the rollout of the consumer data right has advanced greatly, to the point where customers of major banks are able to request access to and share their banking data with others. Secondly, in April 2021, the Federal Court found that Google mislead consumers about its (historical) treatment of their location history.

Together, these developments have the potential to alter how big data is treated, by establishing rights for individuals over their own data, and requiring customer's informed consent for their data to be captured.

Read the full chapter: AI, Machine Learning & Big Data 2020 | Australia.

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https://www.minterellison.com/articles/australian-insights-ai-machine-learning-big-data

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