Skip to main content Skip to main navigation menu Skip to site footer
Law, Technology and Humans Queensland University of Technology 2652-4074 Law, Technology and Humans provides an inclusive and unique forum for exploration of the broader connections, history and emergent future of law and technology through supporting research that takes seriously the human, and humanity of law and technology. ISSN:  2652-4074 (Online)
Law, Technology and Humans 1 0

In Machines We Trust: Are Robo-Advisers More Trustworthy Than Human Financial Advisers?


This article examines the use of artificial intelligence (AI) and deep learning, specifically, to create financial robo-advisers. These machines have the potential to be perfectly honest fiduciaries, acting in their client’s best interests without conflicting self-interest or greed, unlike their human counterparts. However, the application of AI technology to create financial robo-advisers is not without risk. This article will focus on the unique risks posed by deep learning technology. One of the main fears regarding deep learning is that it is a “black box”, its decision-making process is opaque and not open to scrutiny even by the people who developed it. This poses a significant challenge to financial regulators, whom would not be able to examine the underlying rationale and rules of the robo-adviser to determine its safety for public use.

The rise of deep learning has been met with calls for ‘explainability’ of how deep learning agents make their decisions. This paper argues that greater explainability can be achieved by describing the ‘personality’ of deep learning robo-advisers, and further proposes a framework for describing the parameters of the deep learning model using concepts that can be readily understood by people without technical expertise. This regards whether the robo-adviser is ‘greedy’, ‘selfish’ or ‘prudent’. Greater understanding will enable regulators and consumers to better judge the safety and suitability of deep learning financial robo-advisers.

Pages:129 to 141
Section: Articles
0 citation(s) in Scopus
0 citation(s) in Web of Science
How to Cite
Chia, H. (2019). In Machines We Trust: Are Robo-Advisers More Trustworthy Than Human Financial Advisers?. Law, Technology and Humans, 1, 129-141.


Total Abstract Views: 3457  Total PDF Downloads: 1085

Author Biography

Melbourne Law School, The University of Melbourne
Australia Australia

Hui is an experienced legal researcher who has published in the areas of corporate law and employment law. Combining her backgrounds in law and science, she has consulted on the legal and ethical implications of genomic databases, and has a particular interest in the regulation of emerging technologies. Her current research work is on the legal and ethical implications of artificial intelligence.

Open Access Journal
ISSN 2652-4074