Advancing responsible AI adoption
AI permeates our daily lives and ensuring it is developed and used in a responsible way is a top priority for RBC and RBC Borealis.
RESPECT AI™ is a hub for the AI community and business executives looking for practical advice and solutions to enable a more responsible adoption of this technology.
On this platform we share tutorials, programs, academic research and open source research code that can help make ethical AI available to all.
AI & Big Data: Empowering Tomorrow
AI is rapidly transforming the financial sector. At RBC Borealis, we are driving the use of cutting-edge science to inform operations all within a responsible AI framework. We strive to ensure that our clients banking is protected and lives ultimately improved.
News
RESPECT AI: Making machines think more like humans with Prof. Yoshua Bengio
RBC Borealis speaks with Professor Yoshua Bengio, about the link between human brains and AI, key future research areas and risks to avoid.
News
RESPECT AI: Mozilla looks to open-source solutions to responsible AI
In this article, we talk with Mark Surman, President and Executive Director of Mozilla Foundation, about his organization’s focus and the importance of using open source approaches.
News
RESPECT AI: Decarbonizing AI with Dr. Sasha Luccioni, Climate Lead and AI Researcher of Hugging Face
we talk with Dr. Sasha Luccioni, Climate Lead and AI Researcher at Hugging Face, about the link between AI and the environment and explore opportunities for the AI community to make a positive impact.
-
RESPECT AI: Collaborating with generative AI for the greater good with Dr. Graham Taylor
RESPECT AI: Collaborating with generative AI for the greater good with Dr. Graham Taylor
-
RESPECT AI: Building AI ethics into the business with Giovanni Leoni of Credo AI
RESPECT AI: Building AI ethics into the business with Giovanni Leoni of Credo AI
-
RESPECT AI: Governance for growth with Abhishek Gupta of Montreal AI Ethics Institute
RESPECT AI: Governance for growth with Abhishek Gupta of Montreal AI Ethics Institute
-
RESPECT AI: Responsible for future success with Dr. Karina Alexanyan of All Tech is Human
RESPECT AI: Responsible for future success with Dr. Karina Alexanyan of All Tech is Human
-
RESPECT AI: Building trust in an AI-enabled world with Preeti Shivpuri, Deloitte
RESPECT AI: Building trust in an AI-enabled world with Preeti Shivpuri, Deloitte
-
RESPECT AI: The evolving world of AI regulation with Carole Piovesan, INQ Law
RESPECT AI: The evolving world of AI regulation with Carole Piovesan, INQ Law
-
RESPECT AI: Improving the efficiency of Differential Privacy with Zhiqi Bu, Amazon AWS AI
RESPECT AI: Improving the efficiency of Differential Privacy with Zhiqi Bu, Amazon AWS AI
-
RESPECT AI | Resetting regulation: A new approach to regulating machine learning
RESPECT AI | Resetting regulation: A new approach to regulating machine learning
G. Hadfield.
At RBC we believe that AI is one of the most transformative technologies impacting today’s world. As developers and users of this technology we are responsible for ensuring that AI systems adhere to our core values. RBC’s Responsible AI Principles guide every aspect of our research & development activities at RBC Borealis.
RBC Responsible AI Principles
-
At RBC, we are committed to responsible data practices – from how we use data to how we protect it. We maintain data integrity and confidentiality through robust information security and data handling practices.
RBC Borealis focuses on differential privacy in our research, and built Private Data Generation™ toolbox to offer synthetic ML data samples, a method that allows scientists to use large data sets without risking the exposure of personal identifiable information. This tool can be used by researchers to advance the field of AI privacy by proposing novel solutions to this critical issue. We have also published tutorials on differential privacy, among other topics.
We have also built Advertorch™, a well-established adversarial robustness research code, which implements a series of attack and defence strategies that can be used to protect against risks. This tool is offered to AI researchers and scientists that aim to advance the field of robustness in machine learning.
-
We follow protocols to ensure that AI systems are compliant with industry standards and regulatory guidelines. All AI systems must meet requirements throughout the development lifecycle, including testing, validation and monitoring.
-
Our AI systems must uphold RBC’s core values of diversity, inclusion and integrity and mitigate unfair biases. To uphold these core values, RBC tests for fairness and strives to continuously improve models.
We at RBC Borealis have published technical tutorials on bias and provide guidance for organizations to address it.
-
We want our clients and stakeholders to understand how and when we use AI. We seek to provide relevant information so that those affected by the outcome of an AI system can understand the factors that led to a decision.
The Responsible AI Centre of Excellence
Combined with powerful ideas, AI has the potential to change what a bank is capable of and enable us to make things better for you tomorrow than we did today.
At RBC, we aim to be an AI leader in financial services and use cutting-edge science to inform business and client interactions, while ensuring that the use of AI upholds the highest ethical standards, while consistently driving value for our clients.
To achieve this, our Responsible AI Centre of Excellence forms as an enterprise body, operating as our AI committee, overseeing how to implement Responsible AI throughout the organization.
In Numbers
92%
According to the survey, conducted on behalf of RBC by Maru/Matchbox, companies currently using AI/analytics agree it is important for businesses to implement AI in an ethical way. However, 92 per cent have concerns in dealing with the ethical challenges that AI represents, and just over half have someone responsible for ethical development of data and AI technology.
88%
The results of the survey also highlighted some significant challenges that businesses face in terms of bias such as race and gender. The vast majority (88 per cent) of companies believe they have bias within their organization, but almost half of them do not understand the challenges that bias presents in AI.
Blog
Explainability I: local post-hoc explanations
In part I of our blog series on explainability we cover the importance of explainability for AI systems, methods for creating local post-hoc explanations and a taxonomy of approaches.
Blog
Explainability II: global explanations, proxy models, and interpretable models
In part II of our blog series on explainability we discuss the remaining three types of approaches to explainability. These approaches include global post-hoc explanations, proxy models and interpretable models.
Careers
The work that we do at RBC Borealis impacts millions of people across Canada and beyond. New and diverse perspectives, awareness of challenges specific to local communities, backgrounds, and commitment to making a difference are needed today more than ever.
Join the teamCareers
The work that we do at RBC Borealis impacts millions of people across Canada and beyond. New and diverse perspectives, awareness of challenges specific to local communities, backgrounds, and commitment to making a difference are needed today more than ever.
Join the teamLet’s SOLVE it
Let’s SOLVE it is a RBC Borealis mentorship program that provides undergraduate students from diverse backgrounds with mentorship, contacts, training and guidance they would need to make their project a reality.
Learn moreLet’s SOLVE it
Let’s SOLVE it is a RBC Borealis mentorship program that provides undergraduate students from diverse backgrounds with mentorship, contacts, training and guidance they would need to make their project a reality.
Learn more