In the ever-evolving legal landscapes of Australia and New Zealand, a powerful force is at play—a community rallying around a shared goal. At Spotlight: ANZ 2024, legal and tech professionals converged in Sydney, Australia, not merely to keep pace, but to actively pioneer, innovate, and shape the future of law.
Our collective mission? To thrive in the new era of data complexities.
Beyond the surface, beneath the buzzwords, and amidst the digital whirlwind, Spotlight: ANZ provided a platform for trailblazers to dive deep, exchange insights, and connect. From a captivating keynote led by Relativity’s executive team to thought-provoking interactive sessions, the event highlighted regional and global trends. One standout topic? Generative AI—a game-changer that promises to redefine legal workflows.
But it wasn’t all theory. Attendees also got hands-on experience witnessing how RelativityOne is shaping the future of handling modern data types and meeting Australian market standards with streamlined PDF production workflows.
Post-event, I had the privilege of sitting down with AI Visionary Matthew Golab, renowned for his expertise in leveraging a range of data analytics, e-discovery automations, and other cutting-edge AI solutions. Our conversation examined Matthew’s highlights and takeaways from Spotlight: ANZ, exploring what excites him most about AI and what’s next.
Phoebe Cracknell: What aspects of today’s keynote or sessions resonate most with your work?
Matthew Golab: It was really impressive to see the roadmap, and of course the Australian enhancements. The most exciting was Relativity aiR and the various ways in which this could be utilised with aiR for Review, aiR for Privilege, and aiR for Case Strategy. I also really liked the Short & Sharp* sessions at the end, as these highlighted some of the excellent work that is being done in Australia.
*Author’s Note: At Spotlight: ANZ this year, we hosted five Short & Sharp sessions focused on Australia’s legal data landscape, covering topics related to the future of our work. These sessions were led by e-discovery professionals, trailblazing law firms, and cyber resilience experts.
How do you plan to implement these ideas and themes into your projects moving forward?
A large proportion of our e-discovery work is responding to regulatory notices and so we rely upon active learning and various technologies extensively to assist us in tight timeframes. We are extremely excited to get our hands on the products in the aiR suite to see how we might be able to augment and redesign our workflows with generative AI.
What trends do you foresee in the application of generative AI within legal technology in Australia, and how might it reshape legal processes and workflows?
Generative AI holds significant potential across various legal practice areas, from assisting in tenders and pitches to providing chronological summaries of documents during litigation. While it may eventually streamline large-scale document review, the current models’ sophistication limits this. The emergence of tailored, task-specific models like Microsoft’s Phi-2 are noteworthy, and potentially revolutionising legal tasks. Integrating text conversion and vector storage within RelativityOne could also enhance efficiency.
However, the full impact on legal processes and workflows will become clearer with increased implementation in RelativityOne and further advancements in AI models.
Who or what influences you most when it comes to future decisions or your approach to AI?
Here are the four things I pay attention to most when deciding our approach to AI:
- Ensuring that our clients’ sensitive data is securely protected, that any AI system is carefully vetted, and that we can reassure our clients that there are no additional risks with using AI versus not using AI.
- There is an unfortunate tendency for generative AI to hallucinate, so we also need to carefully scrutinise all output from a generative AI system to ensure that it is trustworthy and reliable.
- We need to have a high level of confidence that a prompt result is repeatable over time—meaning that, as models evolve, there is a risk that their behaviour and output may change.
- Finding the sweet spot between the performance and capability of a model versus the price of the model. We want to work out how to use models that are suited to a task, without paying for a model that is able to do everything.
As an AI Visionary, what are the AI projects you are working on right now? What are you most excited about?
My primary focus is on increasing efficiency in low-risk tasks in e-discovery. So, for an example: chronologies are a great one. It has been fascinating to watch the incredible pace of technical innovation in these generative AI models over the past two years, and so apart from (at times) feeling a little overwhelmed trying to keep up with all the changes, everything is exciting!
Missed Spotlight: ANZ?
Catch up on all the excitement from Spotlight: ANZ! Tune in to watch the keynote on demand and hear directly from Relativity’s CEO, Phil Saunders, and international MD and VP of sales, Georgia Foster, as they detail how Relativity’s AI is advancing and the nuanced way the APAC region can actively embrace its benefits. Chief Product Officer Chris Brown and other guests also share insights into the latest RelativityOne updates, highlighting the importance of removing friction, and the significance of seamless workflows to ensure success for both clients and partners.
Phoebe Cracknell is a member of Relativity’s marketing team in Australia.
