i, Lex Robot – Artificial Intelligence in the Courts

A quick snapshot of the world today reveals that technology capable of machine-learning has been interwoven into society. From navigation to household appliances, we cannot seem to live efficiently without technology. 

i, Lex Robot – Artificial Intelligence in the Courts

How can AI assist the Judiciary in its decisions?

What just happened?

A quick snapshot of the world today reveals that technology capable of machine-learning has been interwoven into society. From navigation to household appliances, we cannot seem to live efficiently without technology. 

The Judiciary is not an exception. Casecruncher Alpha, invented by AI tech startup Casecrunch, is already predicting judicial decisions with high accuracy. In October 2017, Casecruncher Alpha went up against a team of human lawyers to predict outcomes of commercial cases. Casecruncher Alpha won with an accuracy of 86.6% of predictions made, whereas the human counterparts only achieved 62.3% accuracy. [1] This stark difference is a reflection of the precision and accuracy that AI offers. 

Unsurprisingly, technology-assisted legal review is starting to receive judicial stamps of approval in countries such as the United States, [2] with Roberts CJ of the US Supreme Court noting that judicial decision making was already being influenced by AI-assisted legal assessments and courtroom fact-finding. [3]
 

What does this mean?

AI is able to respond to questions posed from human operators. An operator may be able to input particularities of scenarios to receive sound decisions about how a particular type of case, with its inherent facts, be resolved.

This is beneficial for judges in the courts, as AI will take existing legal texts and legislation to output to judges the different outcomes that could arise from a case. This enables us to go down the pathway of autonomous judgements, and will be useful in areas like tax law, where AI will be able to calculate taxes more fairly and accurately than human judges. The outcome of judicial decisions assisted by AI systems could potentially be more coherent, fair, and transparent than human judges deciding on cases without the help of AI.

Nevertheless, AI is not perfect and must still be closely monitored by humans to ensure that judgements remain coherent and just. This is in order to maintain and uphold the integrity of legal systems in the various jurisdictions that decide to incorporate AI as a legal assistant in their courts.

What is the legal impact? 

While AI can assist in legal research and decision-making, legal research cannot be reduced to merely collecting related cases or articles. Expertise in legal research is based upon connections and links drawn and inferred from individual pieces of information. [4] Delegating research tasks to AI may risk losing decision-making ability as AI will only provide an answer based upon the trends it has analysed, but does not provide a human touch and understanding needed in every case. 

Furthermore, AI’s usefulness may vary between plain cases and hard cases. A plain case is when judges are faced with terms that are unproblematic in terms of interpretation and where there is agreeability amongst judges as to the application of terms to their decisions. [5] Conversely, hard cases are when the answer needed from the law is unclear and open to interpretation of different kinds. [6] For the latter, one could interpret a decision being overturned by a higher court as wrong, but this argument is only valid when one turns to the highest court and its decisions itself. 

Also, when it comes to hard cases, an understandable justification is more important than a higher probability of correctness. [7] AI’s evidence-based reasoning may not be flexible in interpreting decisions in hard cases from different angles and aspects, something a human judge will be able to achieve. Consequently, the superiority of AI adjudication ends where hard cases arise. Ultimately, the limiting factor of AI is not technology but humanity. 

 

By Nickolaus Ng

 

The Legists Content Team

Assessing Firms:

#CliffordChance, #DLAPiper, #Bird&Bird

Footnotes:

[1] Thomas Buocz, ‘Artificial Intelligence in Court: Legitimacy Problems of AI assistance in the Judiciary’ (2018) Copenhagen Journal of Legal Studies Volume 2 Number 1, 41, 43

[2] Dean L Dalke, ‘Can Computers Replace Lawyers, Mediators and Judges?’ (2013) 

[3] Adam Liptak, ‘Sent to Prison by a Software Program’s Secret Algorithms’ New York Times (New York, 1 May 2017) <https://www.nytimes.com/2017/05/01/us/politics/sent-to-prison-by-a-software-programs-secret-algorithms.html>

[4] Jason Millar and Ian Kerr, ‘Delegation, relinquishment, and responsibility: The prospect of expert robots’ in Ryan Calo, A. Michael Froomkin and Ian Kerr (eds), Robot Law (Edward Elgar Publishing 2016) 109ff

[5] HLA Hart, The Concept of Law (2nd edn, Clarendon Press 1994) 123

[6] ibid, 137

[7] n1, 57

banner

Articles

  • Notice (8): Undefined variable: blog [APP/View/Blogs/detail.ctp, line 190]
    Notice (8): Trying to access array offset on value of type null [APP/View/Blogs/detail.ctp, line 190]
    Notice (8): Trying to access array offset on value of type null [APP/View/Blogs/detail.ctp, line 190]
    " alt="Long-awaited ‘whiplash reforms’ came into force from 31 May 2021" width="460" height="205">

    Long-awaited ‘whiplash reforms’ came into force from 31 May 2021

    Issues affecting the Legal Profession 18.06.2021

    Reforms to the whiplash claims process for road traffic accidents have come into force from the 31 May 2021

  • Notice (8): Undefined variable: blog [APP/View/Blogs/detail.ctp, line 190]
    Notice (8): Trying to access array offset on value of type null [APP/View/Blogs/detail.ctp, line 190]
    Notice (8): Trying to access array offset on value of type null [APP/View/Blogs/detail.ctp, line 190]
    " alt="“He Did It!” - Are Human creators to blame for AI issues?" width="460" height="205">

    “He Did It!” - Are Human creators to blame for AI issues?

    Issues affecting the Legal Profession 05.06.2021

    In February 2021, the Chinese company Baidu opened its LinearFold AI algorithm for scientific and medical teams working to fight COVID-19. LinearFold predicts the secondary structure of the

  • Notice (8): Undefined variable: blog [APP/View/Blogs/detail.ctp, line 190]