By Anson Lee and Janika Fernando (USYD)
Silence. The Federal Court of Australia is now in session. Please be seated.
“Yes, Smith for the Applicant.”
The barrister is cloaked in a white tunic and black robe. All eyes are on them. The Applicant? A father claiming for his rights to child support.
Advocacy. This is the heart of the barrister’s role, their duty to their client and ultimately, the Court.[1]
But let’s rewind and imagine an AI device in the barrister’s place. What would change?
…
“AI appearing for the Applicant, identifier C9M…”.
Introducing AI, the lightsaber to the legal world! It glows with many possibilities, yet promises many dangers if wielded improperly. AI is capable of assisting with legal research, evidence gathering and drafting submissions, but further development is required for it to operate autonomously as an advocate.
Journey through Trial
Any competent AI barrister must map facts of a case and solicitors’ instructions onto the relevant legal principles to frame its arguments. Broadly, AI systems rely on existing data to make decisions in novel scenarios.[2] Handwriting recognition systems are fed millions of handwritten letters to discover patterns, allowing them to convert our scribbles into print. However, the letter of the law in NSW, being an amalgam of common law and statute, is far more complex than the letter ‘a’.
As a starting point, the AI barrister could perform searches in a legal database or encyclopaedia to find existing cases with similar facts. It would then independently distil the relevant principles and generate submissions applying them to the specific case. This final step is the hurdle current AI must overcome; despite improving at a rapid rate, even the best text synthesis AIs appear amateurish beside a practiced mooter. More interdisciplinary collaboration is necessary to connect the niche realm of legal language with these approaches – which are built on a broader collection of text – to make our AI articulate.
The general virtues of AI lie in its efficiency. Human exhaustion and certain cognitive biases are escaped,[3] potentially reducing weeks of cursory research and evidence gathering to mere minutes using techniques like sentiment analysis.[4] However, these tools struggle in detecting subtle cues such as ambiguous or niche language, reducing the quality of analysis.
AI also risks inheriting our human biases in the form of ‘algorithmic bias’,[5] where socioeconomic inequalities in the training data are imported into the model.[6] Women, for example, represent just 11% of Senior Counsel in NSW,[7] meaning the rhetoric employed by men will have an outsized influence on the AI’s own. Conversely, by approaching model training with diversity in mind, we can make a conscious effort to combat these stereotypes by selecting more equitable samples.
The ethics of it all
According to the Uniform Laws,[8] a barrister owes a paramount duty to the court and the administering justice. However, an AI barrister may undermine respect for this duty because rules are difficult to enforce against a non-sentient actor. If an AI misbehaves, the fault is untraceable to an individual due to its organic development. This ambiguity is multiplied when an identical AI program is installed across multiple devices and users; must all copies be modified or destroyed because of a few bad apples?
The fact that AI barristers can be replicated at minimal cost suggests the resolution of certain access to justice problems for vulnerable community members. Conversely, low-cost internet services often monetise user data with third parties, and the data exchanged between clients and lawyers is often the most revealing kind, raising significant privacy concerns. Quite separately, current confidentiality standards are directly counterposed to the data-driven way in which AI learns; its skill to draw inferences from evidence stagnates if it cannot not use privileged data as its learning material. To protect clients’ interests consistently with the barrister’s ethical duties demands significant regulation of such AI legal services.
The proliferation of AI could also strip justice of an intrinsically human element. While AI offers efficient analysis of law and evidence, the human barrister has the ultimate and more reliable capacity to make judgement. Judgement includes a myriad of empathy, creativity and experience.[9] Imagine an immigration matter with a non-English speaking applicant. Yes, an AI device has its machine learning case law analysis demonstrating experience, but empathy is required for judgement. The appearance of justice is arguably as crucial as its execution.[10] The parties must feel included, whereby the barrister helps the applicant understand their submissions, thereby facilitating access to justice.
Taking a long view
For better or worse, human norms are responsible for what a ‘barrister’ looks like. While our intrepid AI barrister may eventually create a sea-change in this perception, it will initially compete alongside us. Humans display a well-observed scepticism towards imperfect imitations – the ‘uncanny valley’ effect.[11] Even amongst judges, Richard Susskind identifies a historically conditioned trust of traditional hearings over technologically-enabled ones that obstruct the way of AI-human parity for years to come.[12] Nevertheless, watershed moments have created seismic shifts in public perception before, like when IBM’s Deep Blue computer defeated Garry Kasparov in chess.[13] Equally, a unanimous High Court judgment in favour of an AI-staffed Appellant could breathe change into our baroque chambers.
Our hypothesis is that the AI barrister will begin its career in an assistive capacity, preparing draft submissions and combing through evidence. As the models for speech synthesis improve, it will develop a more autonomous practice, culminating in polished courtroom advocacy. It’s too early to tell whether or not the AI barrister is ‘to be or not to be’. The AI barrister is certainly more than the shadow it casts. One can see that the AI barrister is enshrined in its efficiencies, from wielding the light to performing legal research and case management faster than ever before! Not to mention the endless programming possibilities that hold the key to coding languages and recognising diverse characteristics. But given the complexity of coding laws, privacy and the need to preserve human advocacy, challenges lie for the AI to ‘play its many parts’ in its grand ‘stage’ of the Court.
Endnotes
[1] Hon. Marilyn Warren AC, ‘THE DUTY OWED TO THE COURT – SOMETIMES FORGOTTEN’ (Speech, Judicial Conference of Australia Colloquium, Melbourne, 9 October 2009).
[2] Steven Bozinovski, ‘Teaching space: A representation concept for adaptive pattern classification’ (1981) 81(28) COINS Technical Report.
[3] Michael Legg & Felicity Bell, ‘Artificial Intelligence and the Legal Profession: Becoming the AI-enhanced Lawyer’ (2019) 38 (2) University of Tasmania Law Review, 34-59.
[4] As I describe this to the embattled barrister sitting across from me, his eyes sparkle.
[5] Lisa Toohey, Monique Moore, Katelane Dart and Dan Toohey ‘Meeting the Access to Civil Justice Challenge: Digital Inclusion, Algorithmic Justice, and Human-Centred Design’ (2019) 19 Macquarie Law Journal 133,148.
[6] For an example of this in popular culture, see: Davey Alba, “It’s Your Fault Microsoft’s Teen AI Turned Into Such a Jerk”, Wired (Webpage, 2016).
[7] NSW Government Equitable Briefing Report, 2018-2019 Financial Year: NSW Government Equitable Briefing Policy for Women Barristers, (Report No 1, 2018-2019) 4.
[8] Legal Profession Uniform Conduct (Barristers) Rules 2015 (NSW), s 4.
[9] Legal Profession Uniform Conduct (Barristers) Rules 2015 (NSW), s 4.
[10] Rex v Sussex Justices [1924] 1 KB 256.
[11] Maya B. Marthur & David B. Reichling, ‘Navigating a social world with robot partners: A quantitative cartography of the Uncanny Valley,’ (2016) Vol. 146, ScienceDirect Journal, 22-32.
[12] Richard Susskind, ‘Online Courts and the Future of Justice’ (Oxford University Press, 2019) 206-7.
[13] ‘Game Over: Kasparov And The Machine’ (ThinkFilm, 2003).