The volatility and subjectivity inherent in human decision-making open a wide-ranging discussion about the potential incorporation of Artificial Intelligence (AI) into legal and financial sectors. At the end of the day, a trial is essentially a data-processing operation. Lawyers on both sides focus on presenting information favorably to their clients, at the same time excluding unfavorable information. Finally, a judge or jury processes the information and delivers a result.
In civil trials where a preponderance of the evidence standard is applied, the judge or jury is expected to determine which side holds at least 51% probability of being in the right. Depending on the severity and nature of the case, this percentage threshold increases. The burden of proof is greater in cases with a clear and convincing evidentiary standard, and highest for a criminal conviction, which requires proof beyond a reasonable doubt.
The primary challenge with this system is the struggle to find a completely objective human being. Even though judges strive to apply the law evenly and fairly and the jury selection process usually weeds out the most biased potential jurors, the influence of human bias is hard to remove entirely. For instance, research suggests that judges who are hungrier often impose harsher sentences on criminal defendants, drawing attention to the impact of extraneous factors on human judgement.
Conversely, computers do not experience fatigue or hunger. They remain neutral, unaffected by human biases. Computers can make decisions based on information, uninfluenced by extraneous factors that might colour human judgement. This opens up a world of possibilities where AI could make decisions in legal proceedings, potentially with more precision and objectivity. For example, AI has demonstrated impressive results in games such as chess where the rules are well defined and an abundance of data is available to train the AI model. This might be the path to consider for a judicial system.
However, in the legal sphere, lawyers govern their own profession and it is the prerogative of human judges to decide the constitutionality of assigning a real case to an AI judge. Therefore, any kind of comprehensive AI takeover of the legal field might face significant obstacles. Other fields with lower entry barriers like finance might be more suitable for AI integration.
The Federal Reserve’s attempt to control inflation with an only tool, i.e. raising interest rates, provides an interesting case study. This decision-making process is mostly conducted by a group of highly educated and intelligent individuals evaluating data. Nevertheless, this evaluation is essentially a guess. As human judgement isn’t always perfect in making such guesses, it might be beneficial to consider AI’s ability to make better decisions when fed good information, as proven in the past.
Ultimately, whether we actually reach a stage where it’s feasible to present a court case to a supercomputer remains to be seen. It seems a little unrealistic currently. However, the potential of AI in replacing human decision makers in complex sectors like law and finance cannot be overlooked.
The idea of AI integration in these sectors raises interesting questions and poses significant challenges. It is an area that certainly requires more research, discussion and exploration. The potential benefits should be weighed against ethical considerations to ensuring fairness and accountability in AI systems.