Canada 4.0: The Digital Transformation and its Impact on our Society and Economy

Catalogue number: Catalogue number: 11-629-x

Issue number: 2019003

Release date: February 10, 2020

Canada 4.0: The Digital Transformation and its Impact on our Society and Economy - Transcript

André Laronger: Et nous espérons profiter de la révolution numérique pour crée des opportunités à la faire d'avantage. Au jourd'hui, nous avons la chance d'avoir parmis nous le statisicien chief du Canada, Anil Arora, qui animera la discussion (inaudible) Mister Arora has over twenty years experience…

Anil Arora: Thank you very much André…eh. Um. Welcome everybody. Uberiz-uberization, uh, another word. Cloud computing, artificial intelligence, autonomous vehicles, digitalization is having a profound impact on Canadian society and the economy. While driving, our data is driving society, the economy and soon to be your car, there has been very little data that's been produced that informs Canadians about how everything digital is having an impact on their spending, their incomes, the prices they face, uh, their security, health, and overall well-being. Important data needs and data gaps are emerging. National statistical organizations like ours here at Statistics Canada are being pushed to go beyond our comfort zones and traditional roles to better measure social and economic issues and their inter-relationships in order to better define, describe and quantify these transformational changes. Through the Canada 4.0 initiative, Statistics Canada is helping Canadians to better placed through data and insights to understand the impact of digitalization. The init-initiative in partnership with Innovation, Science and Economic Development Canada is intended to gather the views of Canadians, our businesses, governments and international experts on their emerging data needs in this era of increased digitalization. Given we are measuring digitalization, it seems only fitting that we lead in a series of digitally-delivered expert panel discussions to be held over the next six months. Each panel discussion will explore a different digital topic, such as cybersecurity, the gig employment, and the value of data itself. The panel discussions will be streamed live as well as recorded and posted on Statistics Canada's website. Each panel discussion will last approximately one hour. The first session today would be to compare a typical morning commute to work ten years ago with that of a typical commuter going to work today. Ten years ago you may have taken the bus and paid using paper bus tickets, you would have probably pulled out a newspaper out of your briefcase and caught up on the latest news. You may have stopped for a coffee, paying cash, and then quickly called your daughter and reminded her to print off her latest book report so it would be submitted on time. Well, not that long after, ten years, today, you get on the bus using an Epass that debits your account immediately and in fact tracks your travel habits. You read multiple newspapers through an app on the bus along with your favourite social media feeds, with each click of course being recorded. You buy a coffee by tapping your debit card or holding your iPhone on a reader, sending digital signals to a myriad of actors. And you text your kids, you don't phone them, you text them now, and remind them to submit their book report via the school's electronic blackboard before today's deadline, and of course, you e-transfer them money to pay for the upcoming hockey camp. The world we live in is changing rapidly and with it, we are changing how we measure it, the way we measure it, and what we measure. This is what Canada 4.0 initiative is all about. It is about developing an information roadmap to help Canadians have the information they need to better understand this fast changing world. Today's discussion, in many ways, sets the stage for our future panel discussions as well. This session will touch on the broad changes that we're experiencing as a society and an economy. Our distinguished panelists today will discuss key cha-changes they're observing, and share with us their perspectives on what is coming on the digital horizon. This session will be followed by monthly sessions, where we explore key issues such as cybersecurity and gig employment in further detail. So, let's start by introducing our panelists. Mister Eric Santor. Mister Eric Santor was appointed advisor to the governor of Bank of Canada on digitalization in March of this year, 2019. In this new role he leads the Bank's digitalization work, including research into the impact of digitalization on the economy and our financial systems. Mister Santor leads the initiative to incorporate technologies such as artificial intelligence and machine learning, as well as big data into the bank's operations. This involves leveraging programs such as partnerships in innovation and technology, or PIVT, and the bank's relationship with the creative, sorry the creative destruction lab. Mister Santor joined the bank in 2001 as an economist in the former monteray and financial, sorry monetary and financial analysis department. He moved to the international economic analysis department in 2003 where he assumed increasing responsibilities until becoming managing director in 2013. Before his appointment as advisor to the governor on digitalization, Mister Santor served as managing director of the bank's Canadian economic analysis department. Our next panelist is Sarah Lubik.

Sarah Lubik is executive director at the Chang Institute for Entrepreneurship at Simon Fraser University, responsible for aligning, supporting, and accelerating entrepreneurship, education and early stage incubation at SFU. She's also a certified expert business coach and a mentor at SFU's Venture Connection incubator. In 2016, Doctor Lubik was named one of ten Canadian innovation leaders assisting with the government of Canada's inclusive innovation agenda. Prior to joining the Beedie School of Business, Doctor Lubik worked in the centre for strategy and performance at the Institute for Manufacturing at the University of Cambridge. She has also worked as a business coach, specializing in market analysis and project manager and coordinator on a number of international European projects supporting start-up firms through incubation, finance and policy. She's also actively involved in entrepreneurship as a co-founder and marketing director of Lungfish Dive Systems. Doctor Lubik holds a B.B.A. honours from SFU, concentrating in international business and marketing as well as a Masters and PhD from the University of Cambridge, where she was also a NanoForum Fellow. In 2014 Doctor Lubik was named one of Business in Vancouver's Top 40 under 40. In 2016 she was awarded the TD Canada Trust distinguished teaching award. Next is Erich Strassner. Erich Strassner is Associate Director for National Economic Accounts at the Bureau of Economic Analysis in the United States. Mister Strassner oversees the calculation of official economic statistics that track the performance of the US economy. These include BEA's flagship economic measure, Gross Domestic Product, as well as its major components such as consumer spending and business investment. Mister Strassner has led several new innovative data projects, he shaped the creation of statistics measuring the fast-changing cultural economy and capturing the effects of outdoor recreational activities on the country's economic performance. And Mister Strassner is leading efforts to explore economic measures beyond GDP to better gauge Americans' wellbeing. He has received a number of awards for leadership and management including the US department of commerce gold and silver medals, the department's highest honours, and the Arthur S. Fleming award for outstanding public service. Mr. Strassner holds a MBA from the McDonough School of Business at Georgetown University and a MA in economics from the George Washington University. And next we have Daniel Ker of the OECD. He is co-author of Measuring the Digital Transformation: A Roadmap for the Future, which the OECD launched along with an accompanying online toolkit at its Going Digital summit in March of this year, 2019. Together, these enable a holistic assessment of the digital transformation across the OECD and BRICs countries as well as identifying areas for future and further development in setting out a roadmap for addressing measurements. Prior to this, Daniel led the team responsible for the R and D statistics and survey framework at the OECD. Having previously been responsible for work to capitalize R and D in the UK National Accounts. And prior to that Daniel was co-deputy director of public sector statistics at the UK office for National Statistics. The views of the panelists reflect their own personal views and not necessarily the views of the organizations that they represent here today. So please join me in welcoming these panelists today. Applause. Mister Santor, let's start with you.

Eric Santor: Okay.

Anil Arora: Digitalization is pervasive, touching almost every aspect of society and our economy today. What do you see as the most significant impacts on society and the economy?

Eric Santor: Well, the uh, thank you Anil, thank you for the opportunity to be here. It's really fantastic to discuss these issues. I mean, digitalization's everywhere, as someone sagely said the digital economy is the economy and so it's affecting all aspects of how we look at the economy and what's happening in all the activity that's going on. When you, when you break it down, you think well, well from the household's side what we consume and how we consume it, is rapidly changing. There's digital services, uh ten years ago that just didn't exist, we can buy almost anything online 24/7 from anywhere around the world and you know, if your household's anything like mine there's a package arriving you know, a couple of times a week or more uh from something we've bought online. Umm, and there's also a lot of the goods we buy now have a lot of services embedded in them. Just think about the car, your car you have and all the software that's now ru-running inside of it, relative to ten years ago. More profoundly, it's also affecting how businesses operate and one of the great insights that's been made recently is that one of the key technologies driving the change in the economy, the digital transformation, is the use of artificial intelligence, machine learning, and big data. And uh, Ajay Agrawal at the University of Toronto's…and his co-authors Joshua Gans and uh, Avi Goldfarb really summarize it nicely, saying these technologies essentially reduce the cost of prediction. What that means is you can take any decision you're going to make and make it better by using IA, AI, ML and big data. And also you can take decisions or things that were not prediction problems and make them prediction problems. What that means is that firms can now think better, make better decisions about what they're going to produce for the customers, how they're going to produce for the customers and what prices they're going to charge for the customers in a much more effective way than they did before, a much more efficient way. So this is dramatically changing how they operate, disrupting industries, letting competitors move into other industries they weren't currently in and so we see this, you know, going through the economy. And what's really nice is recently Stats Can actually did a measure of the digital sector and found just how big it was. I mean, it's really impressive, it was bigger than mining, oil and gas extraction and quarrying combined and so that's really, makes, uh that's a big deal. The last big impact is of course on the labour market, we'll go-go into that later, simply digitalization's affecting how we work, where we work, and most importantly, what skills are we going to need, and what skills are our children going to need to operate in a digital economy. Needless to say, for the Bank of Canada, this matters a lot because we have to figure out, you know, what's going on in demand, how much supply there is in the economy, how much potential output, what this means for inflation of course, has big implications for the conduct of monetary policy in the coming years. Thanks.

Anil Arora: Thank you very much Eric. Um, Miss Lubik, um, you've got a unique perspective as both an academic as well as an entrepreneur in your own right. Um, what do you see as uh, the most significant changes that are being brought about by digitalization?

Sarah Lubik: This is a multifaceted question that I keep changing my mind on it. But at the moment I say it's, the amount of fear and uncertainty you hear when speaking to Canadians about the digital future and how many people are fearful of being replaced, of transferring to a gig-gig economy or those types of roles and a lack of trust in media and a lack of trust in what our data is being used for that needs to be addressed as we go forward. Uh, there's also challenge that we see in Canada around the adoption of innovation, so when you look at reports that Deloitte puts out we're seeing more and more of a need to adopt new innovations to keep up but not necessarily seeing the average company in Canada to be able to do that or being willing to do that or knowing what support is out there to do it. And finally, picking up on Mister Santor's point, that digital skills mean a lot more than coding, they mean a lot to do with digital literacy and about being comfortable with the changes that tech is going to have on our world.

Anil Arora: Well thank you, thank you very much. Let's move to Mister Strassner. Many of the digital innovations that we interact with everyday uh, in fact originate from the United States, just south of here. From your perspective, what do you see as the most significant impact of all these digital ideas?

Erich Strassner: Well let me begin by saying thanks very much for the invitation to participate in this panel to discuss these important issues. So when I reflect on your question Anil, what I really think about first and foremost is that digitalization is making the world a smaller place by connecting businesses and households all over the globe on a scale that quite frankly hasn't been possible even in the recent past. And it may sound like a cliché to answer this way, but the launch of the iPhone was quite, quite significant because it put a computer in many people's pockets, providing at one's fingertips access to traditional news outlets, social media, productivity apps, a camera of course. And in your introduction, Anil, you spoke about many of the ways in which uh, we transact today and and, perhaps most importantly when we think about the iPhone, it created the ability for new businesses to emerge and to disrupt traditional industries, really facilitating the creation of the so-called gig, or sharing economy and wh-when we think about, uh, this from the perspective of measurement as economists and statisticians who work on the national accounts, who work on the GDP accounts, this digital disruption really chall-challenges our traditional measurement approaches. It challenges it in terms of our data collections, which are generally not well-positioned to capture these changes. Uh, it really challenges the calculus for domestic requests, border transactions that used to be uh, more easily measurable with observable movements of goods and provisions of services that could be collected more easily in surveys or administrative data, so for example the emergence of free products, uh, often created through unobserved transactions. These free products that are often supported by advertising, marketing, or data arrangements, they're, they're hard to tackle within our traditional sources, so this poses some serious challenges to us within the measurement community.

Anil Arora: Thank you very much Erich. Um, let's move to Daniel, um, Mister Ker, you've done some real thinking about this, um, and you've looked at it in, in the OECD context, what do you see as some of the more significant impacts of digitalization?

Daniel Ker: Um, yes, hello and may I start as well by um saying it's a pleasure to be invited to spend this well, evening it is over here, with you, um, discussing the digital transformation. Um, clearly there are a great many impacts from the digital transformation which we, uh, which we are all intimately familiar, frankly, within our personal lives and our work lives. And if we're not uh, completely familiar with them, perhaps our publication, if I may same-shamelessly plug it to you, um, might help. Um, but, but I want to, a bit like several of the others, focus a bit more on the world of work, it's, it's interesting that when we look at contributions to the increases in, in employment seen in most OECD countries over the last ten years, that it's the highly digitally- intensive sectors that have tended to contribute especially strongly, with about four in ten of the, of the new jobs created coming from those sectors. Um, the, perhaps … I should mention that it's more like one in four in Canada. Um, that, that strong contribution comes from a lot of things, but it at least seems to be arising from impacts (inaudible) and we see sectors that are more digitally intensive um, um, more dynamic and faster growing. Um, we also see certain new kinds of forms, so online platforms really opening up markets and creating new markets. Um, that can act as an important enabler for business, particularly small businesses. But, but I just want to focus briefly back on those jobs, they're not necessarily like the jobs that came before, um, at the (inaudible) I'm sure we will talk about it more later uh, we see quite a number of people doing precarious work, you know, driving for Uber, delievering for Deliveroo and, and deb-debate about whether that's good or bad, will doubtless come up later. But actually we see jobs across the economy becoming more ICT task intensive. So that's intensive in tasks ranging from use of email to programming and maintaining ICT systems, and in fact if we look at it, for every person working in an ICT specialist position, so that's an occupation that is very focused on ICT, there's another three workers in occupations that are ICT task intensive. Um, so not specialists, but still very um, involved in ICT tasks. All this change is really uh, impacting, impacting the world of work, it's the workplace, it's putting emphasis on skills and training, um, and I think that Eric said that he will talk about this a bit more later, but one thing we see over on this side of the Atlantic is that ten percent of EU-28 workers feel that they need more ICT training to cope with the advance of their jobs. But interestingly, at the same time more than 20 percent of workers feel that they have ICT skills that are under-utilized. So those are sort of distributional or efficiency aspects here that we need to try and get, get uh, get to grips with. Um, one last thing I just want to quickly, I quickly highlight is that people perceive that digital technologies are really driving, sort of, material-like, ground level impacts in their work environments. With people on balance, generally feeling that independence in organizing tasks and use of collaboration have increased. Um, but still use technology to monitor performance and to uh, technology is better used as a driver of increased, uh, in regular working hours, um, so maybe that's not too good. At that same time, technology we should say is allowing people to change where they work with uh, with uh, about four in ten people, one third of people now teleworking from home once a week in Europe. Um, so perhaps I should conclude by saying that the world of work is, is, is one area that is, or one nexus of key impact in our, in our lives and, and our phones. But we still, but we still need more detailed statistics and analysis to actually kind of understand the nuance about what this means in terms of the links to well-being of productivity.

Anil Arora: Thank you very much. So, as you can see, um, what we're hearing is that the changes are real and that they're profound. And what we're talking about are data, technology, and ideas coalescing to actually change the way in which we work, the way in which we interact, uh, the mechanisms, and they're having a very disruptive effect, um, in the sense that it's creative destruction in some sense. Um, and while on the one hand we're seeing an explosion, on the other hand we're also uh, living in this paradox where there isn't enough information or insights about what these changes look like and so that is fuelling greater demand, uh, for statistics and a role for national statistical offices. So let me just push ahead a little bit, um, and maybe I could start with you, uh, Sarah, where do you see things on the horizon? I mean, where we should we be? I mean obviously we have to deal with the issues of today and we have to integrate uh, better insights and data into what we produce today, but if we want to get ahead as statisticians and, and being able to measure these phenomena, what do you see is the next thing on the horizon that we need to take into account?

Sarah Lubik: This is an important question, I think one of the most important things to think about for the future, because we already have talked about skills, is realizing that we're tracking very specific skills. So we're tracking the STEM skills gap often but we're not looking at changes in attitude, we're not looking at changes in mindset, which are things you can track, and changes in uh, how people are feeling about the future. So, there is a huge opportunity to be looking past those easier or more obvious metrics. So for example, we hear a lot about coding should be the third language of Canada and this is how many jobs are going to require those kind of skills and that's both catchy and potentially shortsighted cos a lot of digital skills are great for now but those are likely to be automated over time. So we need to separate between being comfortable with digital skills and thinking there are specific skills that won't date. Because if you look at the kind of skills that are going to be skills, attitudes, that are going to be important in the future, you still look at things like compassion, non-linear thinking, interdisciplinary problem solving, so looking at the kind of programs that address those and seeing how we do among those, it's going to be important. Because we have to realize that getting ahead in the digital world doesn't just mean leading in tech, it means leading in what we do with that tech. So in a recent event held at SFU on how to scale a hundred million dollar companies in Canada with people who had done it, you rarely heard well I needed more people with tech skills, of course we need that, but we also heard you also need people who know how to solve global problems and who know how to understand our customers and users better than anyone else. And so making sure that we're looking not just at digital skills and all of the numbers that go along with that, but all of the complementary things that will make us good at being competitive and problem-solvers in the future.

Anil Arora: And what advice would you have for national statistical offices to be able to measure as you said, uh, not just what are hard skills, but some of the more softer uh, uh, attributes, what kind of research are you doing, or what kind of models have you looked at that would help us as national statistical offices in getting a better handle on what those needs are and what those gaps are going forward?

Sarah Lubik: So, looking at things like the, the business skills that go along with those tech skills, so we looked at how many jobs need to be filled with tech skills, right? There's also how many of those comparable jobs need to be filled with say, marketing and sales? Because we have a little bit of that when you talk to people say, in Silicon Valley, they're saying that it's much easier to find people with that skillset there than when they move back to Canada. One of the other ones if we're talking more along the lines of education, attitude, for innovation and for the digital world, there's a number of studies that look at things like mindset and looking at how prepared people feel for the future.

Anil Arora: Thank you for that. Uh, let me turn to Erich Strassner. We've got two Eric's so I've got to kind of use both names here. Um, how is the Bureau of Economic Analysis in the United States positioning itself to get ahead of this curve? So what are the kinds of things that you're being pushed to uh, try and fill uh, some of these data gaps and how are you going about uh, to, uh, better uh, address if you like, this digitalization, uh, that you're seeing in the United States?

Erich Strassner: Well at the BEA and throughout the US statistical system, we are pursuing non-traditional data sources like never before. We're pursuing new public-private partnerships for things like private sector credit card transaction data, uh, making use of other uh, administrative data sets in new ways, and alternative big data sets to see whether or not by blending non-traditional data sets with traditional sourced data that's available to statistical agencies, that we can tackle some of these real measurement challenges that we face due to digitalization. We're also looking at making use of current data collections like that on our surveys of multi-national enterprises to determine whether we can better leverage that data to understand the size and scope of these MNEs. A lot of these MNEs who operate in this digital space, we're looking to see if we can understand uh, how these MNEs play a role in the US economy and also to better understand uh, global intellectual property flows that are resulting from uh, these MNEs. We've also within the BEA and other stats agencies in the US, we've begun to employ a lot more data science techniques like machine learning to inform things like judgment on early estimates of major components of GDP. This is all an attempt to make sure that we're keeping pace with this ever-evolving economy, keeping pace to keep these statistics accurate. One of our key overall projects has been to establish a multidimensional framework on the digital economy, this is in the form of satellite account, this is really a way to address the need of users to get more granular data on the digital economy. A spotlight on that to understand its overall size, its trends over times, its impacts on production, on consumption, on labour markets. The beauty of course, of a satellite account, or an economic account that's not the core account is that it allows us to quickly publish estimates, to rapidly respond to user interests whether or not we call them, for example, experimental or prototype estimates as a starting point. Also with a satellite account framework, it's a laboratory for further experimentation, so we can look at some of these thorny issues like quality adjustment of high-tech prices for goods and services, depreciation profiles for high-tech goods and services, thinking about the world of these so-called free goods and services that are supported by marketing or advertising and data and thinking about alternative ways to measure uh, to measure the accounts. And also uh, with partnering with Stats Canada, we're thinking about the role of data, digital data and the fact that in 2019 that role of digital data is profoundly different than say ten years ago, so we need to think about whether or not it's time to uh, look at our measurement frameworks and reconsider that role of data overall.

Anil Arora: Perhaps I can push a couple of the thoughts that you've put on the table. The first one is uh, you talked about uh, looking and going deeper into alternative uh, sources of administrative data and even data that's uh, held by the private sector. Well clearly uh, uh, social acceptability of using what are sensitive data, uh, has to be earned, how are you going about having that conversation uh, with Americans about the use of that uh, uh, that information? I mean we as national statistical offices uh, have worked hard to build trust and what are you doing uh, to continue to uh, to build that trust and secondly um, what are you doing when uh, you talk about experimental or prototype types of estimates? How are you ensuring that people understand, if you like, some of the strengths and also the limitations of uh, some of these types, uh, new types, if you like, of analyses that we're putting out?

Erich Strassner: Yeah, thanks for these questions, they're important questions for us to be considering along the way, and I think that one way to respond uh, to both questions is, is to be transparent about what we're doing. I think that's the best way we can move forward within uh, this framework, to be transparent in working with our data vendors, to identify sources of data, uh, that we can make use within our accounts, to be very cognizant of, of privacy and, and with all of the work we do at BEA, we protect uh, data confidentially, we we we don't disclose microdata, we don't disclose characteristics of anything, of any individuals or businesses, there's very strong laws in the United States that support these efforts so we try to be transparent as best we can in how we make use of these alternative datasets, these non-traditional datasets. And that, that goes also, this transparency response around uh, what these experiments are and are not and so we try to be very clear as we produce new estimates or alternative estimates, we, we try to do this in a way that's replicable, that's clear, that is explainable, we do a lot around trying to communicate uh, what we're doing through various channels and and uh, and and and then respond if we need to do better.

Anil Arora: Thank you very much. Daniel, perhaps I can turn to you, the OECD's been known to uh, shine its crystal ball uh, and look forward uh, and you're always uh, making sure that that radar uh, is, is functioning properly. What do you see on the horizon uh, from your work with OECD countries and some of the uh, some of the uh, the deeper research that you've been doing?

Daniel Ker: So I'm pleased to say we're in the process of developing a new crystal ball in the form of a technology (inaudible) that we're in the process of establishing that aims to spot and monitor, you know the big trends that are emerging in technology specifically but in digitaliz-digitalization more generally. Um, at the moment, in this bi-annum, we have a very strong focus on AI and on block chain. On the AI side, which is, is, the area that is led within my directorate, the directorate for science, technology and innovation. Um, much of the focus is on trying to reach international understanding on, on what AI is, sort of in a definitional sense, um, but also on its practical and ethical implications and on recommendations for policy around its use. Um, but we're also trying to work out how we track and monitor both its development and supply um, as well as its, as its, as well as its adoption and diffusion, uh, primarily in firms but also in terms of individuals who are often the end users of, of some forms of AI technology. Um, you know the the, the talking speaker in your house is the one example. Um, the, the idea is that technology foresight forum will continue to develop and look at other technologies as they emerge, looking further into the future I'm really hoping we're going to do something looking at um, new forms of manufacturing, in particular, 3D printing and technologies like that. Because this kind of technology really has the power, potential uh, to disrupt both how and where production takes place. So um, at the moment if I want a coat hook for my house say, I go to the DIY store and I buy one off the shelf or I go to Amazon and I, or you know, another online retailer and uh, choose a product from there and then I wait a few days and it arrives. In the future, I may well be able to go online, find uh a piece of IP that gives me a blueprint for a coat hook that I really like, like better than anything I could find in any of those shops, and I could print it directly in my home or have it printed at a local mater, maker station. So this is really going to change the way production looks and uh, that would further blur the boundaries between businesses and households in our statistical frameworks. So that will, that will create um, or accentuate some of the challenges that we're already encountering. Um, just there also other things that have been quite, around quite a while, uh, but we still need to get grip on measuring and understanding, so online platforms and Cloud services are an example of this and we were very pleased to, with the support of the government of Canada host a workshop last year that provided a step in working out how we look at these um, phenomena, um, work out what we want to know about them, uh, etcetera. Now one clear message that came out of that was firstly everyone agrees that these are important things that we need to look at and understand but also that some of the necessary foundations for statistics aren't really there or, in the way that we might like. So as an example, the OECD has recently developed a definition of online platforms but we need to develop taxonomies and classifications that will help us um, look at grouping different types of platforms based on meaningful characteristics to get uh, to produce statistics that can help us understand what is going on in the platform space and how they're affecting our business sectors and our economies.

Anil Arora: Thank you for that, Daniel. Just a couple of follow up questions. Firstly, uh, you know, uh as you talk about you know the kinds of models and how uh, AI is continuing to shape and will, will accelerate in a sense some of the changes that we're seeing, how can statistical offices get better embedded or should they and to what degree and how, uh, into data strategies and data flows? And secondly, where do you see, you know you talked about that sort of device that you can speak to that is making its way into more and more homes, I know in our home it's a, it's it's an integral part of what we do now. Um, what is that doing also in terms of a pull function, or increasing the demand for data and information, and again, what role do you think NSOs can play uh, national statistical offices, can play uh, so both from a pull and uh, a push? I would love to get your perspective on that.

Daniel Ker: Oh-okay, so to take the, take the question connected to speakers first, so you uh, if I understood correctly you're asking about what that's doing to um, data flows and uh, the information that's being generated.

Anil Arora: Well it's essentially uh, creating this demand for instantaneous information from a credible source. Um, so it's no longer just you know, statistical offices are, are really good at putting tables up and, and you know, the odd sort of pie graph, pie chart, um, what is this going to do uh, in uh uh, a world where there are uh, an increasing number of producers of data and the demands for instantaneous information and that's what the next generation, I think, is what you're saying, is becoming used to. So that's pulling in a sense uh, the traditional role of the national statistical offices.

Daniel Ker: So to some extent it's a continuation of what we saw with the development of twenty four hour news right, it's that, that people are gradually wanting everything, information faster and faster and faster and constantly. So for, for stats offices, of course that creates the issues that um, that we need to find ways of producing information uh, and sate that demand as quickly as possible. Um, one interesting point with uh, the, the home speaker type technologies, the intelligent speaker technologies is of course that you mentioned that people want uh, information from a trusted source and that's one way that they're getting it. Now of course through those kind of speakers you don't necessarily get the answer from a trusted source, you get the answer from whichever source Google or Amazon has decided is the most relevant to the question you've asked. And the way they decide that may be related to money that they've received. Um, so maybe there's a question about whether stats offices find a way of playing the game, maybe they pay the money to be the uh, to be the first answer to certain questions, or um, accept that certain questions that get asked, instead of an answer coming from our tables that may be great and robust, but not maybe penetrable enough, or machine readable enough to really uh, come out through those channels. Um, that that, other actors will, will fill that space, um.

Anil Arora: Thank you for that. Um, turning to you uh, Eric, um, Eric Santor. Um, you're an advisor to the governor, uh, Stephen Poloz, um, and what exactly are you advising him on uh, in this verge of you know, digital disruption, and in fact what do you, what, what advice do you give him in terms of the changing role of the bank itself?

Eric Santor: In terms of uh, the role of the bank, I mean, for us to, I know, conduct mone-, conduct our policies for the economic potential of all Canadians, we need to understand what's happening out there, both in terms of, as I mentioned before, it's (inaudible) the real economy but also understanding what's, what are the changes going on in the financial system and so again we see that you know, the use of AI, machine learning, big data, and is affecting the financial system in a number of ways that's changing rapidly. So to pick out three off the top of my head, there'd be you know, Fintech firms, they're innovating, they're looking to see, to seize parts of the value chain of any particular financial product or service and so that's going to put change into it that you know, will make the financial system evolve. Uh, there's robo-advisors, there's AI's selecting portfolios, and so this is all running there, and algorithmic trading's been around for a while, so that's going to be affecting financial markets. Uh, in the insurance spaces, it really lends itself well to uh, machine learning and big data where, you know, if you think about the cost of prediction going down, people (inaudible) insure tech is going to expand the zone of insurability, because they're going to be able to better target products and calculate risk and deliver those services to uh, an ever-widening range of things that can be insured. So that's going to cause some financial market development. And the last one, of course, is payments. You know, there's been an explosion of peer-to-peer, peer-to-peer lending, peer-to-peer payments, and you know, today, this morning, there was an announcement by a major player about their own currency, crypto-currency that they're thinking about and crypto assets. We need to be understanding all of what's going on in order to make sure that we're able to conduct our policy uh, effectively in this space.

Anil Arora: And how are you doing that role so far?

Eric Santor: So, heh, it's uh, it's um, I'm drinking from the fire hose, uh but no, it's, what we're doing, you know, is uh, we have an idea that we're going to be digital first in every aspect of our business and the simple idea here is we're going to be bringing on board these new technologies: machine learning, big data, AI, to best inform our analysis to help us make our decisions to inform it. Both to think about the data that's coming in, to understand it, but also at a very fundamental level, by using these tools we hope to better understand how the economy's operating in this new digital world.

Anil Arora: I guess, you know, how can we be helpful as a statistical agency as you, as you provide this type of advice?

Eric Santor: So the best thing that you can do is provide us the data that, the inputs, the feed stock into what we use to do our analysis. And uh, you know, in that sense, you've been very transparent about identifying where you think some of the big gaps are right now. So you know, some of those gaps are turns in investment, you know, you used to investment, used to be in plant and equipment, now it's really in IT and tangible investments, it's investment in data, it's investment in software as a service, to how we are handling that in the national accounts to get the better sense of investment decisions that firms are making. Trade in digital services, if you think of all the services that are being provided now, digitally, often in micro-transaction space, we need to better measure that. And it's easy to measure things you put on your foot, harder to measure uh, digital services. Prices of course, you know, with a lot of prices being online now, we need to make sure that as, adequately capture that, that you know, that's another gap that you've identified. Um, and the last one is of course is household to household production. You know, when the national accounts were set up, didn't really, it didn't really anticipate just how much households could directly link to other households not just inside Canada but across borders in the production of goods and services that are going to be transacted between them. And of course wrapping all this we have to understand how the labour market's going to evolve and very good measures of the, cos people are going to be disrupted by this, and people are going to benefit from this, so we need the better, the best measurement of how that's evolving in order to make sure that as a society we provide the proper support, social safety net, training, and other support to help people transition uh, themselves through this very interesting time.

Anil Arora: Well thank you very much, I see, and we feel those demands, just you know, up front, and and uh, I think that is uh, leading to a lot of the modernization efforts not only at Statistics Canada but I think similarly in many other uh, international agencies as well. But look, it would be an opportunity, you know, to capture here, I've got sort of four really broad thinkers, um, not only on the economics but also on the entrepreneurial and also on the academic sphere, um, and we have to take advantage of… There's been a lot of talk about the digital economy and perhaps not as much on the digital society and the social implications and impacts of things like screen time and, and our reliance on you know, as, as was mentioned earlier, that computer, that we now just you know, is kind of connected to our body. What do you see as some of those broader changes?

Eric Santor: Uh, so, just from our, my personal experience, what we know is that no, I'm pretty digital myself but I think we don't fully appreciate how digital our children are and how digital our children are going to be and you know, the anecdote I often like to use is my twelve year old son's only phoned me twice at work. Both times to tell me Dad, the Internet's out, because the power's out. Okay, that's the order of importance for the generation that's coming after us. They care about being connected, and so we have to, and that's for better or for worse, and so we have to understand just how they're going to operate in that world. What that means in terms of the labour market, and this is where we have a lot of focus right now, is how is the gig economy going to evolve in that space. And it's good to put this in context uh, in the gig, I mean we did a, we don't have good measures of the gig economy, uh, specifically, and so we do a survey at the bank of consumer expectations and we put a paper out earlier in the year called How Big is the Gig to try and measure that. Uh, and we found that you know, there is a significant portion of people who are in gig type jobs, you know, part-time, who would prefer to be in full-time jobs. And so the question is to what extent will digitalization affect that you know, that mix, that part of the labour market. The thing to keep in context though, and I think it was mentioned earlier by Daniel is well, on the one hand we have people being disrupted and we need to support them and on the other hand there's a lot of job growth in the digital sector. And so by your own estimate of the digital sector you know, the job growth in the digital sector in Canada since 2010 was forty percent, well just shy of forty percent. The rest of the economy is running about eight or nine percent job growth and what's important to remember is that people in those jobs earning incomes, they're going to buy all the stuff in the rest of the economy that we buy, like homes and cars, they go to restaurants, and buy services. And so what we need to keep in mind is when there's big transformations like this, over history, you know, this is 4.0, it means there's been 1.0 and 2.0 and 3.0, we found that overall it's been a net benefit. There's been net increase in jobs because of the effect that the people doing the new technology are creating demand in the rest of the economy. We just need to make sure that people who are being disrupted are being appropriately supported, uh, in that process. So when I think about, you know, the, we're living in this digital age, we need to make sure that people are ready to live in it and to work in it as best we can.

Anil Arora: Thank you for that, um, maybe I'll turn to you Daniel. I mean… The question to you was to build on what Eric just said, which is on the one hand, there's a need to nurture and grow uh, you know these opportunities for new jobs and, and new models and business models and societal models, um, and on the other side there's a real need to preserve and to protect uh, uh, those that are going to be disrupted. So what kind of research is the OECD doing? What kind of projects do you have underway on some of these broader societal issues and trends?

Daniel Ker: So this is one area where we still very much need to try and find out where the balance lies, um, you know, uh, one example of the work we have in this area, um, is the (inaudible) in the OECD produced a publication called house life in the digital transformation, um, which gathers all the metrics they could find, or indicators they could find related to how the digital transformation is affecting people's wellbeing. Um, and this sort of, the story there is that it's not clear what, what direction things are going in, you know, there are many things that could be good, um, in terms of uh, things like social networks allowing people to be more connected to each other, to um, keep contact with each other, um, but there are many things that could be bad such as technology inclu, intruding into the um, well bringing work into the homeplace, like I mentioned earlier, so that people are always connected and uh, ending up depressed and miserable as a result. Um, one of the real things, messages that comes out of that for us as statisticians is that there's a real need to try and develop more detailed, again more detailed, um, indicators, more nuanced indicators around that. And one path forward on that could be to include questions that probe at wellbeing on ICTU surveys so we can try and start to get a look at, on the same vehicle, um, the links between use of different types of technology and uh, some sort of high-level metrics on wellbeing. Another area I think is worth highlighting is trust, I mean it's quite clear that digital technologies, but especially social networks and e-commerce are making it really difficult for people to know who or what organizations or what information they can trust online. So the OECD is working with national statistics offices and other organizations to try and work out how we can develop metrics around this and we have some. There's a whole chapter in the publication on trust, but um, you, if you look you'll see the indicators are quite sort of around the edges, we still haven't quite managed to find the unicorn and measure it yet. Um, and that's because trust is really hard to define, let alone measure it, it's contextual, it's interpreted differently by different peoples, so there's still a lot, a lot of focus on that. Now just one final broader impact that I want to bring up, because I think it's, it's actually quite often overlooked and quite poorly understood, is the impact of digital technology on the environment. You know, we have anecdotal evidence that bitcoin mining is using more power than some countries, um, but when it came to trying to find indicators for our publication, the best we could do really, um, was to use some estimates on e-waste generated to get one angle on environmental impacts related to digital technology. By the way, they showed that Canada, uh, in 2016 produced twenty kilograms of e-waste per person. Um, which seems like quite a lot to me. Um, but I should say that by no way, by no means the worst, uh, Norway produced thirty kilograms per person in 2016. Uh, there are many questions about how we deal with that, and that's just one tiny element of the environmental impacts of digital transformation and our use of digital technology and our insatious appetite for these uh, these almost disposable devices that we have in our pockets these days. So we really need to understand the full picture of how this technology is impacting the, the environment around us.

Anil Arora: Thank you very much, uh, for that Daniel, um, as you say is nothing is free. Um, so Eric, if I could turn to you, Eric Santor, we've got about five minutes left in this session. What are you doing to make some of the invisible visible, especially in the areas of labour markets, uh, and jobs? Eric Santor, yeah.

Eric Santor: Uh well, in terms of uh, what we're doing at the bank is uh, so we have our own survey, so we have the consumer survey, the consumer survey of Canadian expectations. We're using that survey to ask questions about how people are working, what kind of job they have, how much of it's part-time, would they prefer to be full-time, how much is related to gig activity, strictly defined in a digital space and not, so we're using that, trying to use that survey to um, uh, uh, to capture that and we published some of that research online so we're doing that. Um, we're working with Stats Can, uh, to try and you know, improve our measures and understanding of what's happening in the labour market using microdata, um, but also you know, providing advice and support for looking at better measures of labour market activity. Um, and just more generally we're also trying to leverage big data and (inaudible) analysis and looking at other indicators of uh, uh, people's economic activity and behaviour, um, using big data and to do that we're introducing you know, new technologies into the bank in the space of machine learning and big data and AI. And building an infrastructure around that to use it, to use it you know, wisely and uh, useful.

Anil Arora: Thank you very much. Um, Sarah, perhaps I could turn to you. We've all talked about, you know, this uh, this concept of trust, we're seeing you know, greater demand for uh, the role of national statistical offices to better use data, even data exhaust, and yet at the same time we've got uh, real challenges in terms of public acceptability when it comes to privacy. What advice would you have for national statistical offices in achieving uh, that balance?

Sarah Lubik: You know, when you put it that way, I think one of the pieces where there's a huge opportunity is to align what we see as our current opportunities with the either policy frameworks, analytical frameworks etcetera, that we need to set up in order to make sure everyone feels like they understand what data is important, what data isn't important and that we know where we're going. Because so often we get very excited because we create so much data but at the same time there's a lot of data that's just not all that useful so we don't have to worry as much about it. So when we talk about building, building trust, I also think it's important to realize that the Canadian population isn't just one set of people, so how you build trust for say, entrepreneurs in genomics might have more to do with policy and making sure that their customers feel safe and that the things they can do with their data are uh, ethical and won't end up creating problems in the future. So one of the Canadian examples is the company that was doing uh, genomics testing, and then realized they had to make sure we had policy in place that said no one could use this data to then not, to be able to say you're customers now can't get insurance. So making sure that the policy implications of what we're creating, um, are actually setting up our entrepreneurs etcetera for success. And then to also realize that other, there are other populations, for example students, who need to know more things about, who we need to look at as generations. So for example even the millennial generation was very in love with social media and had no problem with putting their data online and just kind of figured that that is something people do. Where as we're seeing now, at least in a study done by the Vancouver Chamber of Commerce, showed that high school students are falling out of love with social media and that they're much, very much worried about social isolation and so they're concerned with what is the intersection of um, their data and digital use with mental health. So I think that it's looking at, making sure we look at the Canadian population as a number of different um, stakeholder groups.

Anil Arora: Thank you very much. So, in the few minutes that we've got remaining I'm going to turn to each of you to give us one piece of advice uh, in this digital world and increasingly digital world uh, to Statistics Canada and of course other national statistical offices who are participating virtually today. Um, so I'll turn to each of you, as I said, for one parting piece of advice. Perhaps I'll start with you Daniel.

Daniel Ker: Um, thank you, yes, so uh, never want to miss up an opportunity to shamelessly plug the publication we launched in March. I would encourage you to have a look at the measurement roadmap that's in there. It's got nine actions in it, um, four of which are overarching, um, and five of which are more specific about um, you know, looking at certain technologies or certain phenomena that we see out there. Uh, and really without having the time to go through that, just to say that I think that Canada and Statistics Canada in particular should continue to show leadership in this area alongside um, uh, Erich Strassner in the BEA and others. Um, you know, one of the actions in there is about making the digital economy visible in economic statistics, um, you know we need, we need leaders like you to be driving forward efforts around developing digital satellite accounts for example. Um, helping us with efforts to develop and promote the OECD framework for digital supply use tables, um, that we hope will uh, be something that's, the international community can congeal around. And also just want to highlight, there's another action about um, improving the measurement of data and data flows and we've heard several of the discussions today um, mention how important data, you know, they, first, a while ago they said that data is the new oil, apparently data's not the new oil anymore, it's not really the same. But we know it's important, and we want to work out how to theorize about data and its role and measure and capture its role properly and uh, Stats Canada last week shared a very exciting draft on how uh, on one approach to measuring the value of data, um, within the national accounts framework and I think it's really great to see that kind of leadership.

Anil Arora: Thank you very much Daniel, and uh, we look forward to our continued partnership, uh, in moving forward. Uh, next I'll turn to Erich Strassner, one piece of advice again, we're partnering on so many initiatives, one key takeaway from you.

Erich Strassner: Yeah, so, digitalization has joined topics like globalization and economic impacts, really as a catalyst to look for improving new measures of the economy, that take into account things like economic wellbeing and economic sustainability. And so really from our perspective, two of the major things on our agenda are to develop this digital economy satellite account that we've been speaking about today, to experiment around new measures, new methods that allow us to understand changes resulting from the digital economy. But stopping not there, stopping not at top-line impacts, say on GDP or personal income, understanding the distributions of income, distributions of wealth, distributions of consumption so that we have a better understanding going so-called beyond GDP. To know more about these economic wellbeing, economic sustainability impacts, and so these are really at the forefront of BEA and the US systems agenda and we think it ought to be that of most nations.

Anil Arora: Thank you very much Erich, uh, as many people may not know we have a long and deep partnership with the Bureau of Economic Analysis, uh, and we continue to work on many projects and I thank you Erich for joining us today. Next I'll turn to Sarah, Sarah, one piece of advice, one takeaway.

Sarah Lubik: Uh, I think that I'm going to build on what Erich was talking about, in that I think it's important to take a wide lense when it comes to the data you're gathering on skills and attitudes of the future. So the emphasis on STEM is not going away any time soon but changing it to things like steam, looking at mindset, looking at attitudes towards the future are going to be very important to make sure we have the, that we have the data that we need to make decisions on education, skills, and policy.

Anil Arora: Excellent, thank you, once again, uh, that expanded partnership and we've talked a lot about exhaust and steam today, so that's very good, so thank you very much Sarah for joining us today. Last but certainly not least, Eric uh, here, uh in, at our, uh, at our Statistics Canada offices.

Eric Santor: So um, a piece of advice, would be, from our own experience, when you think about how we can benefit from the technologies ourselves, to take a look at all the processes that we have and ask ourselves how can we use AI, ML, big data, to make better decisions. But when you're doing that and making those better, think about, cos the cost of prediction is lower, how you can make those better decisions really what it does, lowering the cost prediction means that the relative value of our judgment goes up. And so making sure that we put our judgment where we need to, and make sure that the leaders, the managers, know how to use that judgment, and I imagine a world one day where you ask a manager "what do you do?", "well I manage a team of fifteen people, four algorithms, and five hundred terabytes of data". And so, you want to think about how we're going to lead that, and how we're going to manage all of this and to do that effectively so we can really benefit from this technology and the way that we work ourselves as we serve Canadians.

Anil Arora: Thank you very much Eric. Um, uh, unfortunately time is running short. I know we've had a few questions from people uh, I know it's uh, literally more than a thousand people that are joining us virtually today, I know there have been a few questions that have come our way. I hope we've been able to answer some of your questions uh, through the dialogue and discussion that we've had. A very rich one, I may add. And uh, if I may invite all of you uh, to join us, uh, next week, where we have another one, uh, a session on June 25th on cybersecurity. And so all registered attendees will receive more information on the next week's session and future sessions that we will continue to host to broaden and further deepen this conversation. So I thank all our panelists, I thank people who joined us physically here, as well as everybody virtually. I hope it provides you with a better sense of the role that Statistics Canada and other national statistical offices are playing an important role in better understanding the various implications of a new bold digital world. So I thank you everybody. Merci beaucoup.