Does 'Justice' Mean 'Just Outcomes' or 'Just Reasoning'?

Cristie Ford, Associate Professor and Director, Centre for Business Law, Peter A. Allard School of Law, University of British Columbia

Published April 19, 2018 by Technologies of Justice.

Cristie Ford spoke on data mining and justice outcomes, exploring the question: Does justice mean 'just outcomes' or 'just reasoning'? The session took place on January 26, 2018, at the Technologies of Justice conference, hosted at the University of Ontario Institute of Technology.

 

 

Ford discussed artificial intelligence (AI) usage, machine learning, patterns and language as well as financial innovation and innovation in law, and their relation to her Early Stage research paper on how this technology can be brought into the legal system. She discussed administrative law and administrative tribunals, and how administrative tribunals are a possible key target for technology usage in law because of the way they are structured. She posed the question “What is the definition of reasonable, and how does it relate to law?”
 
Ford talked about the use of process in court and its relation to technologies: how technology, like legal process, is an ongoing process and not the end goal. She brought up the topic of augmenting or using algorithms in decisio- making and how we think of using software to determine outcomes. She highlighted the need to decide if this process is something that would be considered 'just.' She asked the audience, “Is outcome predicting an improvement to the legal system if we are not using traditional or known reasoning processes?” She brought up the possibility of mistakes or misinterpretations of an AI or neural network. She also asked, “What makes a decision reasonable?" when justification, intelligibility and transparency are considered baseline and the ethos of justification and a minimum moral content of law are not visible in a human context. She brought up the question of comparing normal humans to AI in decision-making as opposed to an idealistic view, and how perhaps the solution could be software-assisted human decision-making. She concluded her discussion by emphasizing the need to determine our feelings on non-human decision-making and a non-human process of law, as well as the way predictive capacity in decision-making by AI could uniquely change the future of law.