Future of AI

Canada has a solid claim as the birthplace of modern artificial intelligence (AI). Work starting in the ’80s, by Canadian researchers like Geoffrey Hinton and Richard Sutton laid the foundation for the neural networks and deep learning models now deeply embedded in all aspects of contemporary life.

Since 1982, the Canadian Institute for Advanced Research (CIFAR) has been bringing experts together to address the most complex and important questions in science, and was an early supporter of AI research. In 2017 when CIFAR was asked by the Government of Canada to lead the world’s first national AI strategy, CIFAR was up for the challenge. Elissa Strome is the Executive Director of the Pan-Canadian Artificial Intelligence Strategy at CIFAR.

Conversations about artificial intelligence often get bogged down in competing definitions of the term. What do you mean when you say AI?

Strome: AI is a computational approach to

examining, understanding, and interpreting very large amounts of data in order to be able to discern patterns and make recommendations. Anywhere there’s a very large body of data that can’t be understood by a single human being, a body of data that’s too complex, too large, too broad for typical statistical approaches, that’s where machine learning is very, very effective.

AI is ubiquitous in our lives today. It has been developed and adopted as a technology to inform so many things that we do in our everyday actions. Things as simple as navigating traffic or translating text. And things as high-stakes as managing the electricity grid or diagnosing illness.

What is the Pan-Canadian Artificial Intelligence Strategy?

When the strategy was fi rst launched five years ago, we focused on two objectives: creating really rich, diverse, robust AI ecosystems across Canada; and building a deep pool of talented individuals with AI skills and expertise. We wanted to make sure that we were retaining the great researchers that we have in Canada while also training the next generation of AI researchers. Today we boast 119 Canada CIFAR AI Chairs at Amii in Edmonton, Mila in Montreal, and the Vector Institute in Toronto. In turn, they are training the next generation of emerging talents.

As we head into the second phase of the strategy, which began this year, we can’t take our foot off the gas pedal on those things, but

we want to also think hard about ensuring the AI we produce is responsible. We look for where AI can have a positive social impact on Canada and the world, while minimizing harms. We’re working to understand from a social sciences perspective, from a policy, legal, ethical, and economic perspective, how AI is impacting society. Central to this is a strategic priority on increasing and advancing equity, diversity, and inclusion in AI.

How can Canadians learn more? AI is increasingly impacting all of our lives, so it’s important that all Canadians should have at least a basic understanding of how it works and what its impacts are and will be in their lives. That’s why CIFAR has just opened public access to Destination AI, a fully bilingual, free online course for Canadians. When you complete the course, which takes about six hours, you get a certificate that you can show your teachers or employers. But what’s more important is that you’ll get an understanding of what the capabilities of AI are, what some of the risks and the challenges are, and also where the opportunities for this technology lie, looking into the future. AI is fast-moving technology that is without a doubt here to stay in all our lives, and each one of us needs to understand its impacts.

This article was sponsored by CIFAR

How Artificial Intelligence Is Solving Real-World Problems

Ken

AI and machine learning can be used to solve a variety of challenges, but it was the labour shortage plaguing the global mushroom industry that inspired Ontario-based Mycionics to create a robotic harvesting system for mushroom farms. While this cutting-edge technology has proven to solve labour challenges, it has also improved mushroom quality and the harvest yield.

“Our technology is paired with deep learning, so we can not only understand growth rates and distribution, CO2 levels, and airflow, but machines can precisely pick, trim, weigh, and pack the mushrooms,” says Michael Curry, CEO of Mycionics. “Farmers now have data to make decisions, which can lead to discoveries that will create businesses efficiencies.”

Accelerating AI growth

Curry adds that its technology integrates seamlessly into an existing operation and isn’t dependent on the size of an organization but on the problem that needs solving. “There’s no reason why small businesses couldn’t benefit from AI,” he says. “It’s only when you start to research and understand the power of AI that you can begin to see the opportunities.”

Artificial intelligence is an emerging technology that requires continuous development and adoption across all levels of the Canadian economy to attract the best talent from around the world. The Vector Institute has gained global accolades since its launch five years ago.

“This is the most important technology of our lifetime, and the use of AI is being seen across all sectors — fighting climate change, predicting natural disasters, managing global supply chains, and even recommending what we watch on our favourite streaming service,” says Craig Stewart, Executive Director of Applied AI Programs at the Vector Institute. “We don’t want to miss out on the economic and social benefits that AI can deliver.”

Taking the guesswork out of AI AI has the potential to unlock growth for Canadian businesses, and Vector’s approach is to make the technology accessible for small and medium-sized businesses through its FastLane program. Even if an organization is new to AI or already an adopter, companies gain expertise in building and scaling applied AI solutions.

The program offers AI capabilities enabled by Vector’s engineering team, access to leading research, the support of Vector’s Industry Innovation team that has experience accelerating applied AI across multiple sectors, and support connecting companies with high-calibre AI talent.

Toronto-based Quickplay, which helps media companies build streaming services, utilizes AI across multiple layers of its business and has found success in its partnership with Vector. “I would encourage businesses to tap into these programs. Vector helped us acquire talent and establish tools that accelerated our use of AI,” says Juan Martin,

Co-Founder and Chief Technology Officer of Quickplay. “It’s not about whether you should use AI, but where it will bring value to your organization. AI is already silently working behind the scenes in much of our lives; the challenge is fi nding the opportunities and applying the science to get the value.”

“AI has never been as accessible and attainable as it is now in Canada,” says Stewart. “And government funded programs are available to help de-risk the investment. The future for Canadian business is bright if we adopt AI, but we must get going and fast.”

Amii is a renowned AI and ML non-profit based in Alberta. For two decades, they've strengthened the AI industry through research, industry adoption, and educational programming.

The Alberta Machine Intelligence Institute (Amii) is an Albertabased non-profit that supports world-leading research in machine learning and translates scientific advancement into industry adoption.

As one of three national AI Institutes, Amii advances the mission of the Pan-Canadian AI Strategy, led by the Canadian Institute for Advanced Research (CIFAR).

AI success starts with people Phase two of the Pan-Canadian AI Strategy includes an increased focus on translating research into commercial application and growing the capacity of businesses to adopt AI.

Amii believes meeting these objectives starts with investing in the growth and development of people.

To be successful, businesses adopting AI for the fi rst time need foundational teamwide training right from the start. Then they need access to skilled technical talent to do the work.

Amii offers AI education and talent development programming to support both.

Training and courses

AI is a powerful tool that the general public and many business professionals don't fully understand. Amii addresses this knowledge gap by offering courses taught by world-class scientists and science educators that provide

technical and non-technical teams with the common language and understanding of machine learning they need to get started with AI.

Internships and residencies

The demand for AI expertise is high and available talent is low. Through its Internship and Residencies program, Amii helps emerging AI professionals kick-start their careers while supporting companies to source the right technical talent for their machine learning projects.

AI Career Accelerator

An internship and residencies feeder program, Amii’s Career Accelerator helps students and recent grads build the technical and soft skills they need to be successful in their AI careers.

Upper Bound Poised to become Canada’s largest annual AI event, Upper Bound is a one-of-a-kind experience that strengthens the community, encourages knowledge exchange, and sparks investment.

From deep tech talks to pop culture, Upper Bound offers sessions and speakers for anyone interested in AI. The event takes place in Edmonton, May 23–26 in the new year.

To help remove barriers to entry into the profession, Upper Bound Talent Bursaries are available by application. Up to 1,000 AI professionals, national and international, will receive a free all-access ticket and travel stipend. A minimum of 30 per cent are awarded to applicants identifying from under-represented groups in STEM.

Build your business or career with Amii In our rapidly changing world, artificial intelligence is creating significant corporate and career advantages. If you’re looking to break into AI, this 20-yearsyoung institution is brimming with opportunities to build AI into your business or profession.

To learn more about Amii and how they can support your AI adaption, visit amii.ca

Canada has become a global hub for artificial intelligence (AI) research and talent and its adoption is already transforming business and our lives. But there is an urgency to keep this momentum going, so more Canadian businesses, no matter the size, can achieve efficiencies and elevate their competitive advantage.

Donohue

It’s not about whether you should use AI, but where it will bring value to your organization.

Get started by applying to the FastLane Program at vectorinstitute.ai/fastlane-program

The Vector Institute is funded by the Government of Canada, the Government of Ontario, and industry sponsors from across Canada.

This article was sponsored by the Vector Institute

Michael Curry CEO, Mycionics

Craig Stewart Executive Director of Applied AI Programs, Vector Institute

Juan Martin Co-Founder & Chief Technology Officer, Quickplay

This article was sponsored by the Alberta Machine Intelligence Institute

Sabrina Seecharran

The demand for AI expertise is high and available talent is low.

PHOTO COURTESY OF AMII

Cam Linke CEO, Alberta Machine Intelligence Institute

How AI Can Be Harnessed to Create Smart, Sustainable Cities

Digital transformation is occurring at breakneck speed, and artificial intelligence (AI) is a big part of it. Cities and urban areas are fast becoming testing grounds for many new forms and applications of AI — from transportation, energy, and waste management to public safety, health care, and city governance.

To benefit cities and urban areas, AI needs to be integrated ethically and responsibly. That’s the central thesis behind a new white paper called AI & Cities: Risks, Applications and Governance . Published by UN-Habitat, the United Nations organization working on sustainable urbanization, and Mila — Quebec Artificial Intelligence Institute, this collaborative effort offers insights and guidance on how to harness AI to build socially and environmentally sustainable cities.

How AI can be implemented to benefit society

“As a general-purpose system technology like electricity or the combustion engine, AI has both direct applications and the

ability to complement other innovations,” says Shaz Jameson, PhD student (Tilburg Institute of Law and Technology, UdeM, Mila) and one of the report’s lead authors. “This means that there are many things that AI can do to support us in urban settings. For example, AI is very good as a predictive tool, particularly around electricity, water, and resources in the context of our changing climate landscape,” she says. In the area of energy, AI can be used in forecasting energy generation, optimizing the system, or predicting when maintenance might be required on energy infrastructure. “AI can also be a good predictive risk management tool in numerous public safety applications like fi re or flood risks,” she says.

In transportation and mobility, AI can be applied to make public transportation faster and easier to use, or to predict road and track degradation on transportation infrastructure. It can be used to improve vehicle routes for waste collection or mon-

itoring and optimizing water treatment processes. There are also many beneficial applications of AI in the health-care sector, from drug discovery to supporting case workers to allocating resources for patient care. And in areas of urban planning, AI can be used for data generation for mapping settlements or monitoring population growth.

Awareness of risks key to successful AI implementation

While AI and AI-enabled solutions offer myriad new opportunities for cities, they also pose potential for risks, such as bias and discrimination, amplification of existing inequalities, privacy concerns, and human rights violations through surveillance. “Another risk is that AI doesn’t include nuance,” says Jameson. “It cannot self-evaluate and doesn’t have an idea of good or bad. While it has an idea of its objective and whether it’s deviating from this objective, it’s up to human oversight to put that into context in relation to what

we as a society consider to be desirable. That’s why Mila focuses on a responsible approach that considers the values we all care about in each of the AI design steps,” says Jameson.

The aim of the white paper is to provide local authorities with the tools to assess where and how AI adds value and contributes to the development of people-centred sustainable cities and human settlements and where there might be risks. “AI is not a simple plug and play, all-in-one solution, but part of a larger strategy that, when designed well and contextually integrated with input from people on the ground, can be an incredibly supportive tool with a tremendous amount of potential,” says Jameson.

To download the AI & Cities white paper, visit unhabitat.org/ai-cities-risksapplications-and-governance

Artificial intelligence (AI) is already transforming our lives. Businesses are keen to adopt the technology to develop new products and services and create efficiencies.

Governments are casting glances toward AI to solve some of the most pressing problems facing our communities. While there are important benefits that come with AI, equally important is considering and responding to the risks of AI, including privacy, equality, and the environment.

Given that digital technologies, and in particular AI, are developing fast, there’s been a recognition by some groups that an appropriate ethical framework was being left behind. This responsible approach to AI is essential to minimize the negative impacts and ensure that the technology is used to improve individual and collective well-being.

“We need to always ask questions about the use of AI,” says Catherine Régis, a Law professor at the Université de Montréal. “Is AI appropriate for a particular issue? Are there risks associated with its use? How can we reduce such risks? And who will benefit from this technology?”

A guide for responsible AI

Talking about the Montreal Declaration, Régis adds that an ethical framework was needed to frame the responsible development and deployment of AI. It provides a compass to guide our choices regarding AI, and whether or how we should use it in different contexts.

“This framework is important, and it must evolve with binding norms, such as legislation, that define clear expectations and potential sanctions for the AI community when those norms are not respected,” she says.

Given that Canada is a global leader in AI research and talent, it isn’t surprising that Canadian institutions are leading the conversation on the development of responsible AI. Five years ago, the Université de Montréal and the Québec Research Funds launched a co-construction process, which included reflection and consultation with over 500 citizens, academic experts, entrepreneurs, and professionals. The result was the Montreal Declaration for a Responsible Development of Artificial Intelligence.

Accelerating ethical AI awareness

The Declaration is not merely a statement but rather guides any person or organization that wishes to participate in the responsible development of artificial intelligence. Several research centres, including IVADO, Mila, Algora Lab, and the International Observatory on the Societal Impacts of AI and Digital Technology, are already building on the Mont-

real Declaration for different projects. And education and training programs are available to train the next generation of AI experts.

More than 2,200 individuals and 200 organizations have signed the Declaration, and what emerged from recent consultation with many signatories is that organizations are often embracing the Declaration’s principles to create their own tools, sometimes adapted to their operational needs and organizational constraints. While some organizations have the necessary resources for this, there’s also strong demand for implementation support, including further developments of practical tools that give life to the Montreal Declaration principles in different contexts.

“The Declaration was not designed as a turnkey tool to solve all AI-related problems,” says Régis. “And while there’s a perceived tension between ethics and competitiveness for industry, the Declaration formulates general principles that can accompany an organization’s thinking, rather than constrain them with rigid requirements.”

According to Régis, the impact of the Declaration is notably the awareness and sensitization to AI ethical issues it creates. “This is a necessary first step to reduce potential negative impacts of AI and to think about solutions to develop and deploy it in a responsible way,” she says.

This article was sponsored by Mila.

Anne Papmehl

To benefit cities and urban areas, AI needs to be integrated ethically and responsibly.

Ken Donohue

This article was sponsored by the Université de Montréal

Catherine Régis Law Professor, Université de Montréal

for

How Smart Collaboration Is Driving the AI Revolution in Health Care

AI with Roche is on a mission to harness the power of AI to deliver better health outcomes to patients worldwide.

Tania Amardeil

Artificial intelligence (AI) is essentially the use of computers to “think” like humans so that machines or devices can perform tasks that normally require human intelligence — such as visual perception, speech recognition, decision-making, and language translation — at a speed that human minds can only fathom. The power of AI is already being harnessed all around us, in applications from personalizing content and space exploration to traffic direction apps. Increasingly, AI is also being utilized in health care delivery.

AI and machine learning solutions have the potential to enable patients, providers, and systems to make better, faster, more informed decisions for accelerated and equitable access to health. One of the key ways that AI can impact our health care system is in gathering and making sense of all the health data we have in a fraction of the time and cost needed today. Big picture, AI can potentially augment clinicians’ knowledge, automate time-consuming processes, and help generate next-generation therapies.

Introducing AI with Roche AI with Roche (AIR) is a centre of excellence aimed at delivering better health outcomes to people through the discovery and application of AI research. Underpinned by an open and collaborative exchange uniquely supported by Roche expertise, AIR is promoting the development of AI for health care by fostering collaborations and partnerships within Canada and beyond.

“Canada has tremendous academic expertise and talent in AI which may be leveraged to improve health solutions, for more patients, faster,” says Fanny Sie, Head of Artificial Intelligence and Emerging Technology External Collaborations for Roche. “The goal is to bring innovations to market together as an ecosystem of partners. By doing so, we aim to increase access to new and better diagnostic tools, therapeutic agents, and digital health solutions.”

AI innovations in health care require support from the initial onset of the idea, all the way to a final product, in order to reach their full potential to benefit patients. The road to making health innovations a reality for patients is long and hard, but can be eased by nurturing an ecosystem of active stakeholders focused on collaboration.

The power of collaboration AIR thrives at developing and nurturing this collaborative ecosystem. It’s about building toward a learning health system inclusive of patients, health care providers, and the AI community. The ecosystem will flourish when all parties work together to generate meaningful and higher-quality data, deploy tools to assist in transforming data-insights into action, and build safe spaces for experimentation with

new innovations.

AIR supports the Canadian AI ecosystem through its foundational collaborations with the three pan-Canadian AI institutes: the Alberta Machine Intelligence Institute (Amii), the Quebec Artificial Intelligence Institute (Mila), and the Vector Institute (Vector).

By creating “a consortium of like-minded individuals and organizations,” as Sie calls it, AIR is bringing differ ent stakeholders together to solve big challenges. It focuses on broad health challenges, from COVID19 to amyotrophic lateral sclerosis (ALS) and other rare neurological conditions.

Community-driven science “We’re aiming to accelerate solutions to market by creating these trusted and responsible environments,” says Sie. “Everyone is coordinated, accountable, transparent, and inclusive, and all the inputs and outputs are placed in a public forum where everyone can access them.”

One such coordin ated initiative is AIR’s ongoing collaboration with Everything ALS, a patient-focused non-profit that aims to bring technological innovations and data science to support efforts, from care to cure, for people with ALS. The organization was founded by Indu Navar, an experienced tech entrepreneur who recently lost her husband to ALS.

“I watched my husband degrade and his disease progress for years because there’s no real method to diagnose ALS,” says Navar. “Our goal with Everything ALS is to build the data infrastructure and to analyze data collected through our patient advocacy group to identify the biomarkers for ALS.” This work will allow health care practitioners to better identify ALS and diagnose patients faster as well as to predict ALS incidence.

Supporting patients directly “Roche is leading the way because they’re able to collaborate very effectively with patient advocacy groups,” says Navar. “Often, patients are left behind — they’re on a different island than the rest of the community and they become just receivers as opposed to collaborators. This model is very effective because as a patient advocacy group, we’re collaborating with Roche and the AI community directly. Roche brings a lot of resources and know-how and we come in with people’s stories. I always say it’s the heart and the brain — it’s emotion and analytics coming together.”

Responsible and ethical AI principles are a key part of what leads to these types of trusted relationships.

Canada has tremendous academic expertise and talent in AI which may be leveraged to improve health solutions, for more patients, faster.

Fanny Sie, Head of Artificial Intelligence and Emerging Technology External Collaborations, Roche Indu Navar Founder, Everything ALS Doina Precup Canada-CIFAR AI Chair, McGill University & Mila

Ethical AI principles

The Roche team makes thoughtful considerations to ensure that health AI is designed and adopted in a manner that’s responsible and that leads to improved translation from research to practice.

“We have internal groups that coordinate efforts, from research and development to quality assurance to regulatory, with all of the legislation globally in mind as well as all of the new regulatory policies that are being implemented in different geographies all over the world,” says Sie. “These are always top of mind for us. There are also ethical principles of responsible AI which are paramount to the development and deployment of trusted solutions within the tech industry. We hold the Montreal Declaration for Responsible AI Development of 2018 in high regard within this domain.”

Through its internal groups and leadership, AIR contributes to the global effort for responsible rules of engagement within its collaborations, clinical implementation practices, and solution design of AI.

Safety and transparency

“In medicine, responsible AI practices are about enabling clinicians to abide by their Hippocratic Oath and humanizing the technology,” says Sie. "To do so, Roche needs to work closely with our regulatory, healthcare delivery and research environment to reassure stakeholders we are developing and implementing innovations in health care settings with the highest stan-

dards of safety and privacy prioritized at every step.”As researchers and scientists are at the forefront of innovation, establishing long-term collaborations with the academic community, rooted in responsible and ethical AI practices, can lead to powerful knowledge transfers and the improvement of AI solutions to drive new scientific discoveries.

Doina Precup, Associate Professor at McGill University and Core Academic Member at Mila, has enjoyed partnering with AIR from an academic research perspective. As an AI and machine learning researcher, she’s conducting fundamental research on reinforcement learning and working in particular on machine learning techniques to discover new medicines.

Leading-edge AI research “Discovering new medicines is a very expensive and lengthy process, so the goal of this effort is to try and leverage machine learning and data in order to make the process faster, cheaper, and more reliable,” says Precup. “It’s an interesting problem because it’s like looking for a needle in a haystack — looking for a molecule that has some specific properties — and we can do this by looking at the giant space of all possible molecules.”

Every collaborator and stakeholder holds a vital piece of the puzzle, and in working together, the health care ecosystem has the best chance of ensuring that health AI research, infrastructure, and policy evolve in a way that fosters innovation, ensures AI products are developed responsibly and ethically, and provides equitable access to solutions for all people living in Canada.

learn more about AI with Roche, visit aiwithroche.ca

PART OF A VIBRANT AI COMMUNITY

The AI community is a multi-disciplinary one which we are proud to be a part of. The diversity of people; of thought; of approach helps our work and we believe in tapping into this robust and vibrant community, we can best deliver on our core purpose to improve health outcomes.

To

This article was sponsored by Roche

We live in the AI Age. Just as in prior eras defined by technological innovation, the value of the central technology itself is inextricably bound to the further innovation it allows. The Bronze Age had bronze, yes. But what truly catapulted humanity into the future was the innovations in irrigation and agriculture that the bronze plow made possible. So too, today. It’s tempting to focus our attention primarily on the incredible pace of progress within the field of AI itself. But the real global transformation is happening in the cross-domain reinvention AI is enabling among innovators in all industries. The advent of affordable, intuitive, and accessible AI analytics has made it possible for professionals of all stripes to see and navigate their landscape of data in incredible new ways, revealing multidimensional paths forward that would have been entirely obscured or impassable without this technology. Sometimes, this route may not even lead to a new destination, but it may represent a much quicker or more efficient way to get there. This process innovation cannot be underestimated as a driver of success.

When research creates too much data to handle When the University of Alberta set out to increase its research capacity, they were faced with an intractably immense (and growing) volume of unstructured data. A jungle no conventional system could blaze a trail through. By implementing a modern AI-driven data management and analysis system, the university was able to set the stage for an ongoing cascade of new innovations, including an algorithm — currently in development by researchers — to reduce the number of CT scans required for children with neurological symptoms by at least 30 per cent, streamlining diagnosis and lowering exposure to radiation. And because the university’s solution was built on SAS Viya, the system was easy to deploy and simple to train on, growing from existing skills in established technologies. “My advice to other universities considering a research platform is to consider the types of tools that their students will be using in the real world,” says Dr. Lawrence Richer, Vice-

Dean of Research at the University of Alberta. “Also, the flexibility of tools, like SAS Viya, to meet the needs of people with varied skill levels is crucial.”

Distributing AI solutions through the cloud Systems like SAS Viya take advantage of another key innovation of the AI Age, cloud computing. Through integration with ubiquitous cloud technologies like Microsoft Azure, these solutions make the innovative power of AI available to organizations of all sizes without the need to bring complicated machine learning architecture in-house, where it will require continual maintenance and improvement. In health-care settings particularly, this has allowed once stagnant processes to leapfrog to the cutting edge painlessly, securely, and affordably.

“As your data grows, your solution should too,” said DJ Penix, President and CEO of SAS partner Pinnacle Solutions. And as your solution grows, navigating legislation that protects people’s privacy becomes crucial as well. "SAS, which invests a lot in R&D in its analytic tools, is thoroughly tested and meets regulatory requirements.”

At this moment, leaders across all sectors can be at the forefront of the AI-enabled innovation shaping the future. And companies like SAS are ensuring that seizing that opportunity is as easy as possible. As SAS Chief Technology Officer Bryan Harris puts it: “We want to make sure that those customers have a path of least resistance to accelerate the adoption of AI and move to the cloud.”

In a complex and changing world, access to information and knowledge can help businesses be more efficient, innovative, and better prepared for the future. However, many small and medium-sized businesses are not aware of the untapped knowledge within their own organizations — the wealth of information and data available — as well as the talent and potential of their teams.

Simon Fraser University (SFU) has been helping businesses build data and artificial intelligence literacy to tap into their own data to ask questions, improve products and services, and ensure their business processes are built upon the best information available. At the same time, it can help upskill teams in the use of data and information while connecting them with the latest data driven tools, technologies, and trends. To date, SFU has helped over 100 organizations, spanning

education, fi nance, government, health care, and much more.

Empowering organizations on their digital transformation journeys Digital transformations start with ensuring teams have the right skills to rethink old operating models, to experiment more, and to become more agile when responding to customers. For instance, SFU is helping BC Assessment (BCA) undertake a major digital transformation and IT implementation project while addressing staff skill gaps. By developing a series of customized and scalable training content tailored to BCA’s

operations, they’re making data skills and AI-influenced technologies more accessible across teams and departments. This is helping to elevate their core competencies in working with data, creating best practices for their data workflows, and improving evidence-based decision making.

Training that meets you where you are Customized training offers something that off-the-shelf training workshops cannot: understanding of organizational needs and business context to ensure teams gain the skills and knowledge that can make an immediate impact. This tailored approach with SFU partner

Babcock Canada — a global marine, aviation, nuclear, and land systems company — empowered the organization to develop a common language that facilitates superior collaboration and improved data inputs. This will help them achieve their goals of producing more meaningful insights and reporting, and ultimately facilitate better data-driven decision-making incorporating AI technologies in appropriate ways.

Big Data Hub works

SFU’s

How

We start with listening and learning about your unique business challenges and opportunities. We then provide you with dedicated experts that will design customized solutions and resources to meet your needs. Workshops are tailored to address your specific challenges and are valuable for all skill levels.

D.F. McCourt

data grows,

This article was sponsored by SAS This article was sponsored by Simon Fraser University

Fred Popowich

PHOTO COURTESY

OF SFU

Fred Popowich Scientific Director, SFU’s Big Data Hub

Emerging from the Birthplace of Deep Learning Breakthroughs to Global Leadership in Artificial Intelligence (AI)

AI has emerged substantially in the past years, ranging from voice, speech, and facial recognition to chatbots, among countless other deployments. AI is increasingly part of everyday life, and every organization is examining the use of AI at some stage. However, this begs the question: is AI an opportunity or risk, or is it both? Given this “two-dimensional outlook”, people are curious about what the future development and deployment of AI — in particular, responsible, trustworthy AI — will look like. These are the questions industry thought leaders, observers, and end-users have raised.

In an interview with Ulrike Bahr-Gedalia, Senior Director of Digital Economy, Technology, and Innovation at the Canadian Chamber of Commerce, and Jodie Wallis, Global Chief Analytics Officer at Manulife, we dive deeper into this topic with a closer look at the future role of AI and a focus on Canadian industrial business development.

Ulrike Bahr-Gedalia: Let’s start high level. What do you see as the future role of AI in Canada’s economy?

Jodie Wallis: Canada is the birthplace of many deep learning breakthroughs. Early investment decades ago made Canada a leader in AI, ranking fourth in investment, innovation, and implementation in the Global AI Index.

This head start creates a huge competitive advantage for Canada’s economy, where we can build on existing infrastructure and talent pool. If we can leverage this opportunity, Canada can play a major role in guiding future AI development, creating thousands of sustainable, forward-looking jobs.

In the past decade, we’ve already seen rapid development and application of it across industries. Today it is already used across Canada’s economy, from customer service to manufacturing to transportation and health care.

Bahr-Gedalia: You mentioned recent mas-

sive growth. Where do you see AI going in the next decade?

Wallis: Over the past decade, an effort has centred on proving AI’s value to businesses. However, we’re quickly coming to a point where we will see the focus shifting to expanding and scaling up its use. Ten years from now, we will see AI increasingly play a role in everyday business across industries.

That expansion is already underway in some places. For example, while we are all familiar with AI use by tech firms, large companies like Manulife have also been inspired to use AI to create new ways to better serve customers and improve productivity.

More broadly, AI will improve productivity and quality of life if we can achieve a balanced combination of advanced academic research, scaled industry use, and rigorous governance to improve customer experience.

Bahr-Gedalia: How can Canadian businesses capitalize on this opportunity while mitigating potential risk and acknowledging that there is a stark difference between risk and risky.

Wallis: The first step is to shift your mindset. AI is no longer an interesting innovation but a critical component to success in today’s economy and part of your overall business strategy. Therefore, your AI strategy should be tied to business outcomes that are meaningful to your organization.

Companies should be accountable to ensure consumer data and privacy are protected, there is transparency about how AI is used, and decisions can be explained in clear and easy to understand language.

At Manulife, AI not only optimizes what we already do, such as improving fraud detec-

tion, but it also allows us to do things we had never imagined before. For example, it has assisted us in transforming a large amount of complex raw data into insight to enhance business decisions.

Secondly, talent is crucial. While recruiting external expertise is important, companies should also prepare for the future by building the skills of existing employees.

To truly capitalize on the AI opportunity, business leaders need to understand what it can bring to the table and how to leverage it to transform objectives and growth. This is an area Manulife has invested in substantially in recent years.

Bahr-Gedalia: Going back to the idea of shifting our mindset, what do we need to ensure Canada remains an AI leader?

Wallis: AI development is moving fast, and other countries are quickly recognizing its potential. AI is an important economic driver and creates employment across industries. Canada needs to move quickly but thoughtfully to create a responsible policy environment that makes sure we maintain our lead in both research and business adoption, not just in technology but across all industries.

This will include:

• Continued open exchange of knowledge, ideas, and practices, which have driven Canada’s current AI success

• Silo reduction by encouraging cross-discipline and academic-industry collaboration

• Comprehensive governance practices to protect Canadian consumers

• Data and AI literacy across Canadian society to ensure our economy is ready for the future.

As the increasing use of artificial intelligence (AI) continues to make its mark on a range of fields — from health, environmental sciences, and agriculture to banking, manufacturing, the bio-economy, and beyond — it’s increasingly important that individuals and businesses understand how to use AI ethically and responsibly. Ethical AI challenges include everything from privacy to plagiarism in AI-generated content.

The Centre for Advancing Responsible and Ethical Artificial Intelligence (CARE-AI) at the University of Guelph is working to advance AI training and ethical AI research and practices. It integrates ethics, governance, and social responsibility with technical leadership, expanding the University of Guelph’s research community’s expertise and fostering a network of over 100 on-campus researchers and scholars.

Leading the way

“CARE-AI is built on three pillars: AI methodologies (what can you do with AI in the future), AI applications (what you can do with AI now), and AI ethics and responsibility (what you should do with AI),” says Kevin Matsui, Managing Director of CARE-AI.

CARE-AI is connected to several of the University of Guelph’s academic programs, including the Master of Data Science and a Collaborative Specialization in AI — a thesis-based master’s program. “It lets students develop domain expertise in a field like biomedical engineering or computer science while also adding a specialization in AI and machine learning,” explains Matsui.

In 2023, CARE-AI will launch a new training program in ethical AI, funded by TD Bank Group. Named Care About AI, the program will offer AI training modules for in-career professionals and entrepreneurs.

To learn more, visit care-ai.ca

How the University of Guelph Has Become a Leader in Ethical AI

Visit chamber.ca to learn more about the Canadian Chamber of Commerce’s approach to the digital economy.

This article was sponsored by the University of Guelph

This article was made possible with support from The Canadian Chamber of Commerce

CARE-AI at the University of Guelph is leading the way in research, education, and training related to the ethical use of AI.

Tania Amardeil

Kevin Matsui Managing Director, CARE-AI

Ulrike Bahr-Gedalia Senior Director of Digital Economy, Technology, and Innovation, Canadian Chamber of Commerce

Jodie Wallis Global Chief Analytics Officer, Manulife

Canada is the birthplace of many deep learning breakthroughs. Early investment decades ago made Canada a leader in AI, ranking fourth in investment, innovation, and implementation in the Global AI Index.

PHOTO COURTESY OF THE UNIVERSITY OF GUELPH

Traders and AI scientists at RBC Capital Markets and Borealis AI Collaborate to Deliver an AI Trading Solution

RBC Capital Markets announced the launch of Aiden® Arrival, the second algorithm on the firm’s AI-based electronic trading platform.

Aiden® Arrival builds on the success of the Aiden® platform’s first solution, a volume-weighted average price (VWAP) algorithm, to reduce arrival price slippage and offer an expanded trading action set that enhances the platform’s flexibility and control over the execution trajectory.

“Since launching the Aiden® platform in 2020, we partnered closely with clients to develop a more holistic tool for primary benchmarks and solve for greater simplicity,” says Bobby Grubert, Head of Digital Solutions & Client Insights at RBC Capital Markets. “The launch of Aiden® Arrival signals an important milestone in the expansion of our innovative Aiden® trading platform. Together with Aiden® VWAP, this is just the beginning of the full opportunity for clients to have better performing trading tools.”

The Aiden® platform was developed in a collaborative effort by RBC Capital Markets and Borealis AI, a world-class AI research and development center created by RBC. The platform uses the computational power of deep reinforcement learning in its pursuit of improved trading results and insights for clients.

“When RBC Capital Markets brought Aiden® platform to market for our clients, it was a big scientific milestone that demonstrated how a brand-new AI technology could succeed in extremely complex environments,” says Dr. Foteini Agrafioti, Chief Science Officer at RBC and Head of Borealis AI. “One of the key factors in developing this game-changing product successfully at RBC was our early investment in research and development capabilities, creating an environment where top scientists, engineers, experts, and practitioners from the Capital Markets business were able to work side by side to bring this game-changing product to life.”

Aiden® Arrival builds on this work by exploring new trading relationships within the prevailing market conditions and guardrails by continuously assessing market information to dynamically control multiple aspects of every action throughout the order lifecycle. The algorithm uses deep reinforcement learning to gain experience in real-time, learning how to trade better over hundreds of thousands of decisions.

“We are at the forefront of leveraging reinforcement learning technology in a responsible fashion to benefit clients,” says Jas Sandhu, Global Head of Agency Electronic Solutions, RBC Capital Markets. “Aiden® Arrival leverages more than 300 data inputs, combinations of actions, and post-execution optimization to solve for the

arrival price challenge and reduce slippage.”

The Aiden® trading platform is part of a broader longterm strategy to deliver the potential of AI to clients. “RBC is reimagining the future of financial services, with a focus on anticipating client needs and solving for them in innovative ways,” Grubert added. “With significant investment in new technologies, including AI, we’re making tremendous strides to bring more insight and value to clients and communities to help power their ambitions.”

About RBC

Royal Bank of Canada is a global financial institution with a purpose-driven, principles-led approach to delivering leading performance. Our success comes from the 95,000+ employees who leverage their imaginations and insights to bring our vision, values and strategy to life so we can help our clients thrive and communities prosper. As Canada’s biggest bank and one of the largest in the world, based on market capitalization, we have a diversified business model with a focus on innovation and providing exceptional experiences to our 17 million clients in Canada, the U.S. and 27 other countries. Learn more at rbc.com.

We are proud to support a broad range of community initiatives through donations, community investments and employee volunteer activities. See how at rbc.com/community-social-impact.

About Borealis AI Borealis AI is a world-class AI research center backed by RBC. Recognized for scientific excellence, Borealis AI uses the latest in machine learning (ML) capabilities to solve challenging problems in the financial industry. Led by award-winning inventor and entrepreneur Foteini Agrafioti, and with top North American scientists and engineers, Borealis AI is at the core of the bank’s innovation strategy and benefits from RBC’s scale, data, and trusted brand. With a focus on time series modelling, applying ML to financial markets, and responsible AI, Borealis AI is committed to building solutions using machine learning and artificial intelligence that will transform the way individuals manage their finances and their futures. As part of its commitment to advancing the development of responsible AI and ML, Borealis AI developed RESPECT AI, an online hub that brings open-source research code, tutorials, academic research and lectures to the AI community, helping to make ethical AI available to all. For more information, please see borealisai.com.

We are at the forefront of leveraging reinforcement learning technology in a responsible fashion to benefit clients.