Good afternoon to you all it's time to get the seventh session of leadership in extraordinary times this season going. My name is Eero Vaara and I'm professor of organizations on impact at Saïd Business School at Oxford and it's a great pleasure to wish you all very welcome to our panel discussion on the future of recruitment and i really cannot think of a more important or exciting topic giving the ongoing changes in organizations and around them which we are experiencing as we speak and this really triggers a big need to reflect upon what the future of work will be like now this panel has been planned and organized by my colleague Dr Gretta Corporaal who is one of the world's leading experts in this area and it's really thanks to greta that we have this panel here and now and she will also moderate the discussion which makes my job easy minji gao is having on an eye on the questions for which we are very grateful I will keep this beginning part real uh short and but i want to briefly introduce our fantastic lineup of of experts and we really couldn't have a better one a better lineup for us today so the panelists include paul estes from mural he's uh leading industry expert in the open talent economy we have john healey vice president and managing director office of the future work at kelly services we have adam osimek who's chief economist at upwork and we have michael kearns uh ceo at verticent great to have you here and then janine legere on demand talent offering lead at deloitte pixel the panel will be dealing with several issues but we will focus in particular on two questions uh first the platform economy and the role of open talent and then secondly the potential of ai that's artificial intelligence in matching people with jobs and at this point i want to invite everyone in the audience to join in the panel discussion by submitting questions and comments through the chat function and as promised i'm keeping this brief and at this point without further due over to you greta thank you very much hiro thanks for a wonderful uh introduction and uh as eros at the first team we will talk about today is about uh the platform economy and the role of open talent and i'm very pleased to have adam osmic present with us and um to to give a bit of context um with the rise of digital platforms like google apple and facebook we increasingly see that economic activity is being mediated by by digital platforms and whereas we we know about some of these platforms we call gig economy such as uber and delivery we also see the emergence of what we call online labor platforms where companies can find specialized experts through these platforms and to do work with them engage them in the work that's taking place and what what i'm actually interested in adam is can you tell us what's your perspective regarding how the platform economy will affect work and recruitment uh yeah definitely so it's a great question and i think that there are two important features of platform economies to to consider one is that they're global and two is that they're highly flexible so these are sort of the distinguishing features now when you talk about flexible work what it's most similar to is you know the traditional staffing industry or just hiring independent contractors so that's sort of the you know the brick and mortar world version of it but when you add in the global nature of it that makes it something totally different right and that's what makes platform global platform economies like upwork such a unique thing and i think that the global nature is incredibly important because it means that businesses are no longer constrained to their local labor market and this is such an important important thing both for the businesses and for the workers and for you know the the availability of opportunity um across the world so traditionally a business looking to hire someone they're going to focus in their backyard they're going to look in the neighborhood of where their offices are and that means you are constrained by the conditions of your local labor markets and for a lot of businesses this becomes an important challenge especially if we look at you know 2019 um a lot of economies we're heading towards what we call full employment which basically means everyone who has a job wants one and in that environment it becomes very difficult to find high quality people and it becomes very difficult to hire and this difficulty is magnified by the fact that you're stuck looking in your backyard so especially when you're talking about businesses that are located in the most dynamic expensive high cost of living you know fast growth cities um you know think of you know London, San Francisco new york these cities are places where the economies are even the labor markets are even tighter than they are for average so it becomes very hard to find people so the first thing that the global platforms do is they unlock uh labor everywhere so that's really important because you have tremendous differences in the availability of workers by place and across the united states if you look at the tightest labor markets focusing on 2019 the tightest versus the sort of loosest labor markets there are places where there is a lot of talent available and especially when you're talking about paying them you know at levels that they pay in these you know superstar cities you know opening that door to hiring anywhere is incredibly powerful and then you add into that the flexibility that you don't need to make sort of long-term staffing decisions but you can scale up and down very quickly that's the other thing that sort of makes us unique so those two things really set this aside from the the rest of the labor market it's most similar to traditional staffing but in a lot of ways it's completely different than that in terms of the global scale that you get the speed of hiring that you get and the flexibility that you got

thank you so much adam super interesting and uh and very nice how you how you brought these different elements together and one of the elements that you said unlocking the potential unlocking labor is what i believe paul started to call the democratization of opportunity if i remember it well from the last time we spoke and paul with the rise of all my labor platforms these models of work that leverage open talent are really coming into the mainstream right and in your in your recent book you talk about uh the greek mindset and i i'm very happy to have a version of it here and can you tell can you explain to us what is this open talent work model actually about and what are its implications for it for workers and organizations

first thing i want to do is say it's an honor to be on a panel with you because it was i think five years ago uh that i attended an upwork event and you were on stage and you had written uh some research about how fortune 500 companies were adopting uh gig economy or freelance uh platforms you handed me that research which was in a hardbound book and i i took it it was one of the things that really helped me start the freelance program at microsoft so it's it's been a long journey in your work i just want to say thank you for the work that you you continue to do um you know when i talk to fortune 500 companies and i do it often as they're trying to think about innovation and i say this often i continue to believe that not having a gig economy strategy in 2020 is not is the same as not embracing the internet 1990 or the mobile revolution in 2010 and so we all know the stories about companies who did not see a structural shift in the way work would get done and then what happened to those companies and the companies that did embrace that and where they are today and so i believe in in many ways we're starting to see freelancers and the gig economy in these open platforms structurally change um many aspects of business you know you asked a question of how should workers think about it and how should companies think about it i think from a worker perspective what we're starting to see is a lot of people are having side hustles you know they're having more portfolio careers and um you know the idea that you're going to have one job and that's going to stay for 30 years we know that not the case and in reality it's never really been the case uh people workers are demanding flexibility companies are now providing that uh flexibility and you're starting to see that shift and so you know i think more and more people are going to reach into independent work freelancing as part of a portfolio career to re-skill uh and to keep some sort of stability uh in their lives when it comes to companies and i wrote a piece in march in fast company and i talk about location bias it always struck me as odd that companies have the best talent yet it had to be the best talent that was willing to move within 50 miles of their location and and that bias stops companies from really um you know reaching their full potential and serving customers right and in companies that have primarily human capital as their major spend they have a fiduciary responsibility to bring diversity into the work because we know every every university including oxford has done research saying diversity provides better outcomes and so if you're an executive and you're not bringing diversity and reaching out to the best talent wherever it may be you're neglecting that fiduciary responsibility to your shareholders to your employees um you know and and to society overall the talk now is hey how do we bring as adam spoke about equality um how do we address the inequality that's happening in the world and so i i firmly believe that companies that are not adapting uh to remote work and independent work are really neglecting their fiduciary responsibility uh to their companies and you know what we're seeing now is a lot of companies say oh remote work is okay remember six months ago it was an odd and even strange radical idea that that teams didn't have to be around the water course so that's a little bit about you know how i think about and talk to organizations about the open talent world

thank you so much paul very very interesting and one of the companies that is actually one of the front runners in his space is deloitte and very recently they got featured in a harvard business case study and i'm very glad janine is actually with us today and um deloitte established their own platform deloitte pixel and can you tell a bit about behind the scenes like how does deloitte leverage this open talent model of work what types of work lend itself to to bring in these external specialists that adam and paul have been talking about and how does this impact the organization or the structuration of work yeah thank you so much greta and you know thank you for putting together such an awesome panel of people in the open town space i think it's a really exciting time in talent and how it can change and you've been you know at the front making sure that everyone's getting involved everyone's engaging in these type of discussions so a big thank you to you for pulling this together so in short you know we at deloitte have been using open talent for the past four to five years and it started with just how do we access this how do we how do we actually bring on on demand talent in a way that's truly on demand versus weeks and weeks of contracting to bring someone on that acts and feels like a traditional employee and what we realized is you need to as a large enterprise you can go in so many different directions that focusing on one or two verticals to start and expanding from there is where you'll be able to get some success so we at deloitte have focused on how to use freelancers specifically in our strategy and analytics group and where we're focused predominantly is with data science as well as other skill sets in the analytics field that we could bring on freelancers in that area that are specialists that we might not have internally that our deloitte consulting teams could use so specifically you know bringing on a data scientist who has a niche capability that no one in deloitte has but our client needs a problem solved that they've hired us for we can bring in a freelancer to help support the project team in

the freelancers that we have uh the freelancers that we have uh individuals that you know the team can't find internally but can bring on in the same fashion that they would bring someone from from you know internally from deloitte onto the teamwork because if you don't have that seamless approach and it becomes really challenging and a huge time suck for a manager to bring on a freelancer versus bringing on someone internally they'll revert to old ways so that's a really important piece is making it a seamless hiring experience when bringing on external talent and to what paul said you know people and companies should really have a freelance strategy they need a team behind this to make sure that the company understands you know there is time and energy that goes into the back end to make bringing on freelance talent seamless and i also do believe that freelance marketplaces um across the board we try and work with a number of different ones in our ecosystem so we are freelance marketplace agnostic and we'll just bring in the best one based on the talent that we need and what we've seen is you know all of them are adjusting to figure out how do we make technology support and be a useful tool to make the onboarding as seamless as possible so huge strides have been made there by the platforms and excited to see how that continues your last question was you know how have we seen you know how has it impacted work and and for us it really is around taking away um constraints from the team so uh teens i'm also just going to restart my my video here it seems like i can't and sorry there were some technical difficulties of the day but first so here we go can you see me now

yes i'm going to take that as a yes so it's no longer about you know teens have this ability to say it's no longer about oh we don't have the talent i'm constrained in this way or that way so we can't do this project for clients it's okay we don't have the talents internally how do we look externally so it's expanded the access to skill sets and that we as deloitte have and can serve our clients with which is a huge win um in the consulting world and then the other aspect that has sort of changed significantly and covet has really helped with this is just working remote most consultants previously you know had a monday through thursday schedule where they would be in person with their clients and we've been pushing the lawyer to really rethink that rethink who you need to be in person and who can be remote and all the freelancers that we've worked with have been remote and that shift was something that we were doing pre-covered but now with covered has been a really easy way to get teams to adopt and use freelancers more regularly right that's great thank you janine and yeah as paul read it refer to my team at oxford basically since 20 since 2017 we have been studying the adoption of online labor platforms and and you know what what impact that has had on the on on on the labor markets um with me me and my colleagues especially looking at the the implications particularly for larger enterprises such as a fortune 500 and we saw that many of the organizations started to experiment with organizing work with open talent and yeah basically what we saw is that usually they started off with relatively simple tasks and projects but readily they also started to engage with platforms for larger and more complex projects and that seems like they're where you're talking about janine and also michael please uh join us in the conversation because you have a lot of insight and also from from ferguson's point of view like taking on these larger more complex projects what would it take for organizations to really leverage these platforms and bring in those external specialists for those more complex types of engagements sure you know i think one of the interesting things and and and adam sort of mentioned it earlier was that you know the the closest analog to the platforms are staffing so people have have always used outside experts to get work done right they just happen to come through staffing agencies or consulting firms and typically been kind of on premise um the difference now is just the platforms give you as everyone has talked about first just global reach right so rather than if i'm in cincinnati finding experts in cincinnati which is a limited pool i can find experts from all over the world um the second is typically the platforms are better right so the discovery process and different platforms do different things but rather than the old method was you talk to a person who gives you a few resumes etc right there's you can do it digitally you can look at more scale there's higher levels of vetting there's more precision around matching so it's less of a i think one of the challenges has been i think a lot of companies view this and frankly sometimes the industry positions it as this like radically new totally different thing the reality is it's it's just a better way to do what people have been doing always um and and so i think from an adoption perspective you know you hear you know we've surveyed um large companies around the world for years and um with my friend dr john younger and what we found is you know the resistance is more fear of the unknown or fear of what's different than than kind of tangible things right because it's well if they're if they're remote how do i know they're working right and my response to that is well you know the the it's cyber monday here well maybe not this year but typically it's always been cyber monday in the united states that's the biggest shopping day of the year which is the first monday after thanksgiving if it was indeed true that people in the office are always working and people at home we're always not then why does there's three days between us thanksgiving and cyber monday so why aren't the people doing all their holiday shopping over the weekend online it's because they wait until they go back to work in the office to do their online shopping same with you know facebook peak times or during the work day um so there's this idea of how do i know you know how do i know they're working if they're remote well it's actually presence is not equal to productivity so you should actually be a leader and kind of set expectations for people and measure progress measure output measure results right and that's true whether they're a motor right next to you um but also things like security and other things that you know there are answers to what people are concerned about so i think that you know for large companies what we always say is you know first start small but but also it's it's apply the same principles you know if i think what most companies will find is an a player 3000 miles away is orders of magnitude more effective than a c player sitting right next to you and that's the reality is as adam and others said you know i think that in a lot of the larger cities um you know the the it is so hard to find the right people and that's just math so if i'm looking in a city of 3 million versus the world mathematically my chances of finding exactly the right person are dramatically greater if i look across the world so you're basically trading kind of proximity for fit and and you know from my perspective that doesn't make sense and i think a lot of companies are seeing that that like a it's not really that different the the different components are it's a more effective matching process and you've got more options um and and yeah there is some proximity differences but i think as we're all seeing now because we're forced into it um you know those are easily solvable problems um and and i predict that you know we'll see you know this has been a steady trend of increasing year over year kind of every year i think it will accelerate obviously because a lot of people have been forced into remote work and i think most are seeing there's differences and there's problems to overcome but for the most part people are just if not more productive and kind of you know it gives workers the freedom to be more flexible and not be forced into the most expensive crowded cities um and it gives employers the flexibility to find the best person wherever they are um and i think we'll see that

thank you so much for that michael and um one thing i i'm not sure if you're familiar with that the work that people at stanford has been have been doing about flash teams where they they have the idea that you know when you have really complex projects you kind of need to give these freelancers a space to work together even though if it's outside the boundary of the firm so to say you can still create like organizational structures where they can hire recruit people depending on the task at hand and um i i was just wondering like what is your view on that like you we talked about types of work where you can hire a freelancer uh for instance virtusen's project a business model it's where you bring the entire project to virgin and verticent is going to compose a team for you and what is your view there like what are the different models out there in this ecosystem of open talent and the players there to see like okay what is the best way to structure work in this new era where we are where we don't have this button seat mentality anymore that some of my interviewees spoke about but you can basically create your own organizational structures i mean we so we follow kind of what what i've always preached which is you know you you want to you want to have a work structure and an org structure that matches what you do so for us we're a services firm as you mentioned that does highly complex work and and so for me you know i want to have the best possible team at all times so we use you know we have our own talent platform that either brings in and screens employees brings in screens freelancers i also partner with other firms and other freelance talent pools to just assemble every time the best team and right what's unique for us and the value we bring is a the ability to do that but b we have a lot of technology a lot of iep and a lot of expertise that we bring to bear to solve client problems and you know that doesn't mean that i need to have every single person working for me and my expertise may not be to find you know certain skill sets or certain things so so we actually have you know a very flexible town pool that you know some of the folks are our core employees some of the folks are people we have in an informal network and some come from platforms and other sources and we mix those and assemble those into a work team and what we find is that um you know it gives us the flexibility the flexibility for me running a business to be able to flex based on demand and specific skill needs right because because those those vary wildly um but also you know we always know it's not you know typically in a in a services firm like mine that's more traditional you kind of get the team the firm has not necessarily the team you need right because they're like well i have these three people on the bench and i think they can do it they might be the right skill set and like we'll trust that they're going to work hard and get it done whereas in a flexible model you can say no i need these exact things and i'm geared to make sure i have an avenue to find those those those specific skill sets so we can be much more precise in the team we deliver while kind of more flexibly managing our business and then i think from a from a a talent perspective it gives people not the opportunity to be shoehorned into a role because that's what the need is right now but they can focus on you know what they want to do whatever that is and so you know different people have different priorities some people want to be part of building a business some people want to hone their craft some people want variability and you know i think from a business perspective it's just it's a much better way to manage a business but also i think from from a from a team perspective you get the best possible team which you know which will drive the best possible outcome thank you so so much michael really fascinating and yeah let's see if we have some questions from the audience minji uh can you tell us a bit if we got some questions in coming in thank you greta we have received a lot of interesting questions from the audience i'll just take summarize some of the questions paul and jeannie talked about the importance of open talent as a form for organizational information and jenny you mentioned deloitte has been hiring a data scientist data thailand to help with your organization's work so one of the questions that our audience have what do you think about the future of data science careers

i can take that one and so yeah i think it's super interesting i think there is a ton of opportunity in the data science space to work in a lot of different ways so when it comes to the future of data science careers i think if we're talking about just undermine talent as a whole versus full-time i think you're going to see a bit of both i think you need certain roles within companies to be full-time i don't think that's ever going to change but i do think that there are going to be a lot more opportunities for people to work in an on-demand fashion to support both you know open source work and to support private work that organizations need support with to help with specific algorithms and be sort of outcomes driven um approaches and i i do think you know speaking to what michael kearns was speaking about is you're going to see a lot more teaming of people from different areas whether it's some full-time people with a few different freelancers or bringing in a few different freelancers from you know varying backgrounds and to support in different ways so overall i think there's a ton of opportunity in the space both full-time and freelance wise and we'll we'll see kind of where that goes thank you so much jenae do i have time for another question sure go ahead yeah so we've also received some concerns from the audience saying that while herring from anywhere may be possible but it might subject to certain type of careers so i guess this question is more for adam do you have any stats on how much of the labor market that remote work is sustainable are there any type of works that can be done remotely are there any certain types of work that cannot be operationalized as easily so it's a great question it's easiest to focus on sort of one labor market where we have good data so i'm going to talk about the u.s context here and what's interesting is before the pandemic you had estimates that maybe a third of jobs could be done remotely but then in the heart of the pandemic 60 of jobs were done remotely so that tells you that almost double the amount of jobs that we thought could be done remotely where at least on an emergency basis being done remotely and still today we have about a third of jobs being done remotely so i think that tells you that it's tough to look at what was done before and say can we do these jobs remotely because it turns out that just looking at you know the way things the way the way companies are organized and structured sort of underestimated the percent of remote work that can be done when you make changes around how you work um long run i think we're probably going to be looking at maybe 20 of jobs being done remotely and that's like where i think we'll be you know in a couple years as people you're going to continue to see people go back to work slowly the remote share is declining but i do think that a lot of these jobs are going to stay remote if you want to know what kinds of jobs are going to be more remote um you know it's it's professional jobs there is an education gradient here more skilled work tends to be more remotable i think the least sort of remotable jobs are going to tend to be in sales when you're talking about you know sort of higher paying opportunities uh you know sales continues to be a very face-to-face activity uh you also might have you know you know some jobs and the high innovation sort of hands-on technology that continue to be face-to-face where you need to be you know around equipment around remote you know around equipment around the white board but i think if you look at management and professional occupations in general that's where you're going to find you know whether it's finance architectural engineering those remain relatively high computer science programming so this is why a lot of the tech companies seem you know extremely comfortable with sending at least a good chunk of their their workers to live wherever so i hope that helps it's a tough question it's really going to be job by job but it's like an overview those are the kind of trends you can look for but i would just say adam i agree with you and i think that it's amazing to see how many things that weren't possible to be done remotely even a year or two ago are becoming more and more like i saw i think it was caterpillar they have machines where people are kind of running mining machines far far away from the mine for example and so i think that would have been something we'd say like driving a machine into mine you can't remote that but you know a year two later it's remote surgeries some are being done remote um so more and more things are getting done remotely every day

great and i think this is a very nice segue into the second theme we're discussing today with the leader great panel and that is looking at uh at matching like in in many of the of the things she brought up we we brought up this topic of matching matching people with jobs which is kind of the essence of recruitment and um let's zoom a bit into the potential thereof of ai of artificial intelligence to help there to leverage technology for for giving the right job to the right worker and get it finding the right worker for the right task at hand and as we have witnessed with with the guy from platforms those are like google apple facebook amazon and microsoft we see that the network technologies of platforms and in particular their algorithmic matching of supply and demand across the globe really has a potential to disrupt industries but what about platforms for work for online work remote work that we're talking about today and uh adam let's start with you first like how do online labor platforms actually leverage that ai and big data for matching people with jobs and what are the implications for for the processes of selection and recruitment for instance it's a great question so let me talk about you know sort of three three things here one is why are these platforms kind of ripe for machine learning type analysis um two is like what are the problems and three is what are the limitations so the why why are we why are we finding algorithms useful why are we finding machine learning algorithms ai whatever you want to call it why are they useful here it's really a lot to do with the nature of the data so when you have a traditional data set in statistics is based on a lot of individuals and a few observations on those individuals so you have like you know think of census data you'd have a couple million people and you'd know a couple dozen things about them so it's a long data set in platforms when we have our wide data sets now we do have a lot of people but the amount of people that we have is just dwarfed by the information that we know about them so if i wanted to it'd be very trivial for me to create a data set where i had millions of variables like just measuring you know daily activities of people search behavior all their work experience all their job posting you know applying um so it's like a really really wide data set and that really lends itself to machine learning techniques where you don't necessarily know what are your independent variables of interest so you know who the people are but you don't know what it is about them that you want to be looking at so that's why i think that there have been a lot of important use cases for machine learning in this context in compared to traditional statistics so that's sort of the why the what there are a lot of there are a lot of context in the two-sided global labor market where machine learning algorithms are potentially useful i'll give you a couple examples one is basically for every one person who makes it onto the upwork platform there's like a hundred who apply and so it's really in demand in that sense that people want to come here to work as a freelancer because there's a lot of great work to be done and so deciding um how we let people through the gate who is a high potential freelancer uh how do we let them in there's a lot of role for algorithms there another important context is when someone when a client is searching for a freelancer what do we show them so when someone starts showing google for something all you have to do is figure out what is the most relevant answer right that's the that's it just maximize relevancy right and then get rid of scams or something like that uh it's much more difficult on a two-sided labor market platform because you don't have to just worry about relevancy you also have to worry about availability and so if you just show people the most relevant freelancers you're going to show them you know the people who are busiest because they're relevant for a lot of people they have a lot of experience and you're going to end up with a lot of clients who just keep being directed to the same top rated freelancers who have like more work they could possibly do and they're not seeing uh the freelancers are actually available so this is important place for algorithms where you need to sort of trade off this availability versus relevancy right that's a complicated question um you need to know a lot about the people on both sides of the market there and how do you trade off these things um so those are you know two important contexts for machine learning but i do think that there are some you know really important caveats to this for people to understand is that one is that we still even with all the information that we have we are still subject to the problem identified by uh hayek the economist you know 87 years ago which is limitations of information information is incredibly dispersed we will never know we will never know everything about these freelancers that they know about themselves we will never know everything about clients that they know about themselves and there's so much heterogeneity in a marketplace like this even when you're focused on like take a take a very narrow segment of the marketplace here's a very particular kind of job in freelancer there's massive amount of heterogeneity there in terms of how skilled of a person are you looking for how experienced of a person are you looking for and you're just never going to you're never going to overcome this with data so it's important to sort of scope out what you do with algorithms and i think as a it's a general rule it's it's algorithms are really great machine learning is really great for giving people information to make their decisions but if you try to start making decisions for people you're not going to have enough information to do that regardless how big your data set is and you're also if you're not if you're not doing it right you're going to make people you know start working against the algorithms and if the algorithms don't work for them they're not going to reveal accurate information about themselves so you need the algorithms to provide information you need them to be what economists call incentive compatible so you want them to be revealing truthful information about themselves and in a lot of cases and this is my other caveat here a lot of cases you want to not necessarily be using algorithms but using market-based mechanisms you know the price system auctions these things utilize mass distributed information to people you know when you have people sort of bidding on an outcome they are using all of their information to decide what it's worth in a way that algorithms could never bring in the same amount of information so those are sort of that's my idea of like the potential the universe there's so many interesting uses for algorithms but what we do with them what we don't do with them and the limitations of them is just as important if not more important than what we do do with them so i would keep i would keep hayek in mind i would keep um the importance of markets and prices in mind those are i think some important lessons thank you so much adam that's really fascinating what you were describing here and um yeah when when we think about like the market that is that is being disrupted by by these online labor platforms that are coming into the space we as the name says it's we can think of the labor market itself but we can also think of of the staffing industry the hiring of temp temporary and employees and john first stepping companies this idea of open talent is is nothing new right it's it's it's at the beginning of the staffing industry but uh perhaps the use of technology how that's being used by platforms and these platform business models perhaps does bring some novelty there and um perhaps you can explain to us how how is the staffing world responding to these developments how does kelly adapt to this new world of work and is there still role to play for people and brick and mortar intermediary organizations in personnel recruitment it's a it's a very very fun conversation greta and uh i thank you for giving me the opportunity to share some thoughts on it and you know what i would encourage people to do is maybe just pause and think about history for a little bit um you know there's been conversation how this market is not necessarily new it's maybe an evolution of where we are if you think of supplemental labor or non-internal non-full-time employee labor it began with maybe seasonal labor being brought into organizations it it goes back to post-world war ii when the industry really formed itself and then you saw the consulting organizations coming in you saw white collar talent becoming something that was more in need and that was there and now all of a sudden you know offshoring became a big piece and then outsourcing became a big piece this is simply just another evolution accessing talent whether it's individuals or its clusters or teams in a different way so the idea of a labor market intermediary or a third-party kind of aiding and assisting the platforms have become another medium for doing that we still have deloitte is still an active third-party intermediary a lot of our organizations go out to deloitte and use them as a consultant to help us but they've learned that using third-party labor using the platform has been a better way to provide the services that they have create new and different pieces instead of having to go to a deloitte to get any project or outcome based activity michael and ferguson are bringing together teams to help you bring something together in a different way so we're seeing organizations adapt in different ways traditional temporary staffing companies if all you're doing is matching resumes to to buzzwords in a job description then you're offering no value so any intermediary has to evolve their value proposition to bring something new into the market where i think the technology question gets really interesting and kurt had a comment in the the q a about just being tired of of you know just buzzwords being blown adam from resumes and job postings well that's what ai can do very well for us ai can take care of the match part if i want to get my buzzwords of the job description to match your buzzwords and your work history that's a pretty easy thing to do right now the algorithms have gotten smart enough on it there's enough volume going through there but what i think we miss when we think about it and i think adam hit a little bit on this is the difference between a match that you have the technical capabilities and skills necessary to do the work and fit is this the right thing for me at this point in time different organizations are going to identify different things that are going to stand out they're going to create different opportunities whether you're joining in with an early adopter or or someone who has been a laggard and moving through something whether you need to just be closer to home or have greater flexibility in your schedule whether you want to be full-time versus part-time all different aspects of the the human psychology of why this work not this job but this piece of work is right for me at this point in time constructed in this contractual relationship and that's where you're going to still see kind of the role of the human you're going to still see the role of the intermediary in some way and if you just want evidence look at the highest paid people we have across our world um there are athletes and our entertainers and how many of them don't have an agent you know what when you're looking at you know the the the the top football players and wondering who they're going to go to and who's negotiating the contract you know what everyone needs a good midfielder and everyone needs a you know a goal scorer okay but what is the right fit for me and what's going to be right for my family for my personal life for everything i want not the things that are in my job description or my cv so that becomes a really big part of it and the other piece i i would just kind of offer into this is that the technology is going to have to go beyond the ai and the machine learning side of things we've got to look to the distributed data to build out a much broader ecosystem so if you want to get into blockchain technology we can have some fun in going through that but the idea of having a broader marketplace that allow people to interact and allow for greater trust in the the security of information and in the privacy of information and in the control of my personal information the information about who i am and what makes me make the choices that i make in my work history and my life history those are things that are going to really stand out and candidly to me going to create some massive opportunity so you know for all the students that are on the line and are thinking about okay so how do i leverage this and create a business in here what do i want to spawn i would be thinking about which groups you can be bringing together that can impact a whole ecosystem versus solving an individual problem for an individual person or an individual element of the process right now so i think there's some some higher level thinking that needs to take place beyond just the what can i do right now we've got a whole way of how people connect with work that is changing radically and being enabled in a much more positive way than it ever has been if we can get there

Thank you so much John really great and we also have uh Paul here and uh so great to have you and uh he is he's very eager to jump in the conversation please go ahead paul i just wanted to build on on two things john said an important word in adam did as well you know outcome based you know a lot of what companies are looking for now is is outcomes and so they're trying to then work backwards to try to figure that out and all of us all of us on call now expect things on demand so when you look at those changes you know one of the things you know we're in the first inning of these labor platforms providing value to uh large organizations but one thing that i'm starting to see all over the market is the vertical integration of companies bringing experts into their processes it was you know a couple years ago that ikea bought taskrabbit because it seemed that not everybody wanted to build their own ikea furniture we're seeing it in turbo tax if you've ever used an intuit product in fact i use mint to track my financials and yesterday on demand i was connected with chuck who's a 22 a year has 22 years of experience of being a cpa and we worked over some of my financial questions that i had so you're starting to see broad organizations build ex bring in experts on demand to help customers with those outcomes and so when you look at the labor platforms you actually have to start looking at large sas companies who are building that out you see it with aws iq godaddy which is a big web service here has godaddy pro grammarly i don't know how many people use grammarly but they have writers inside that product and the interesting thing that happens with those writers they're there to help customers but they're also there to make the algorithms better they're there to help build intent based ai and so one of the things that we experienced when i was at microsoft is did we know what cus the business intents that customers were trying to do and you looked at all of the data that the company had and it was the templates that a customer told us hey i'm having a birthday so i need a birthday card or i'm doing a sales thing and we looked and we created microsoft experts where we put designers and other experts in the actual products and so i think as you think about on demand there will be back office type of work that companies need and they'll they'll start to use more cloud-based um staffing agencies uh you know on-demand labor platforms but on the other side they're going to start putting people in their products independent workers freelancers who are experts in that domain that's represented by that company and they're curated by the company you know you go and look at a company like towel one of the magic things that they do is they do high curation of their labor pool it's a top three percent so that when they place a freelancer it's guaranteed that it'll it'll probably be a fit because they've done that work and so we're starting to see that with aws iq who says look i'm going to go qualify all of these amazing cloud experts and i'm going to apply them to aws it's similar to what mr kearns is doing over at verticent so i encourage people that are thinking about this space to think more broadly beyond the labor platforms and the transformation of staffing and look at how companies are vertically integrating using gig economy strategies because every other day i open a sas product i use asana to do all my uh project work and there was an expert there saying hey set up some time so i set up 30 minutes uh with a woman in actually pennsylvania where adam's from and so start to look at that trend because it is it is something that's happening and it's all designed to capture data and help the organization uh create differentiation in a mode and this part i believe is what you also see as part of this bigger bigger thing right the digital transformation of work and you know like when you talk about putting people into products you know and one hand if i would be a worker i would be a bit scared and this kind of brings me to the question like this new model of works that are that are emerging and they offer significant advantages like freedom and flexibility and autonomy and remote work enabling you to better integrate your work like with your home life it also brings challenges and one one of them is that it kind of clashes with established norms and expectations in society for instance when we think about social benefits or or pensions and i was just wondering like how do freelancers experience this transformation and what is your advice for it for people who perhaps are considering a freelance career yeah i think it's very it depends where you live in the world i mean you're in sweden where the the social contract with employees is very different than here in the us and i think in a lot of ways uh the friction and the conversation about inequality in the us is really about this idea of of how do we allow people uh should benefit be tied to a job which is still a very odd uh concept and it's got a whole history to it i think it for everyone it's a personal decision i i know many people who later in their career uh like i was a freelancer for a bit of time and you know my wife had a job and so we were able to rely on those benefits and so i think there are some people who are early in their career and you know their profile is different and the you know benefits that they need are different i i do think that more and more people are starting to ask the question and that's why i think it's more of a portfolio career i think we're going to start pushing against these corporate policies you know used to be called the bad you can't moonlight and then somewhere it became side hustle which was cool and so you're side hustling um i think more people are going to have a portfolio career and then go all in maybe on on one thing and it happens over time so for me i you know continued to try a bunch of different things and said hey i'm going to make a move but it was a four-year sort of transition i would never encourage uh someone to just you know jump without you know experiencing and really um working the other thing is everybody's gonna be a brand you know this idea that you're going to have to put yourself out and that some resume is going to somehow define you if you put yourself out on on linkedin and the social media platforms and you become a brand opportunities come to you and so i don't think we're in a world anymore where people are just able to have their resumes and then put it into some system and apply for a job you've got to be proactive and really have a unique point of view and brand yourself just very much like you you've done and and many people come and ask your advice and insight so that's the advice that i would give people that's great thank you paul and uh minji um i was just wondering do we have some questions coming in from the audience uh yes yes thanks granda agrada it seems like our viewers are both excited about but also skeptical of using artificial intelligence for uh recruitment so i'll take the liberty of summarizing the questions again we talked about the positive side now let's look at the dark side of artificial intelligence what might be the ethical and legal implications for organizations and as more companies starting to leverage the benefits of artificial intelligence it seems like more jobs will become precarious would it be possible to have a balanced interest between the recruiters and the employees thanks

I'll offer in on that minji i think that the ethics of what we're looking at with artificial intelligence and particularly machine learning right now is something that we have to really keep an eye on particularly when we're looking at social justice issues and equity issues all over the place algorithms are programmed by human beings um and one of the scariest things to me is the number of individuals who come to me promoting that they've got a new business because they have an algorithm with zero data that's been run against it and they think it's going to solve the world's problems um algorithms and the algorithms that are making a difference right now are ones that are being having massive amounts of data run through them to test and challenge against those biases that are built in and then relearning against the biases that are there you you heard the reference earlier to the idea that that the platform just keeps telling you keep coming back to the same four freelancers over and over and over well that's not the right answer if you have an emerging and growing marketplace so we need to change some things in there so i think how we use ai in organizations is something that every large organization and every large enterprise is really paying a lot of attention to the lawsuits haven't come out yet all of the lawsuits that say you know a bias has been created against me because the machine said x that's going to come up that is one of those course correction points that is going to occur in this marketplace where is it going to be we'll learn along the way but i think that's what you're seeing particularly hr organizations say let's let's wade into this carefully let's let the the algorithms give us maybe a projected answer but then let's use our brains and think about this and think is that the right answer how do we feel about that emotionally it's back to that match versus fit um you know is it the right thing how do i feel about this and maybe challenge do i need to look at that again so i think that that that's the piece to just tread carefully in as we go forward with this technology is is to not become overly dependent and also to look at where that cross-collaboration is taking place that can really ensure that the algorithms we become more and more dependent on are being trained by new invariant sources of data along the way yeah i think john just to jump in the uh amazon actually is a great use case they had secretly built a uh recruiting tool um that was bias against women and so if you just look at that case um it's here's a big company with all the resources in the world and all the smartest data people in the world uh that's unearthing those challenges and they shut down the tool and so we're starting to see the use cases just not the lawsuits yet but you know where even to paul's point there part of that program started because they were evaluating job descriptions that the job descriptions the physical job descriptions most of our companies have were also written with bias against women that's right and and so it's not that the technology has created something bad the technology exposed a problem that was there question is what are you going to do about it are you going to allow yourself to continue to enhance the problem are you going to change what you're doing the way we connect people with work is backwards in a lot of cases we're still in a a marketplace where we tend to think that the job order or the job description demand is key well in what adam referenced earlier we have segments of the marketplace where the supply demand equation is completely upside down if if you are one of those data scientists there is a lot more demand than there are of you so you have the power in that relationship to explore what's going to be possible well if the system is programmed in a linear way with an assumption that demand equals power something is broken there so we've got to be willing to re-engineer some processes and how we think about that that's the power to the person right now to rethink and change the way systems are running and that's the challenge to corporations is to think differently thank you so much john and this also refers uh back to what what adam brought up about how ai is really good in providing information but letting the algorithms make the decision isn't is another question and uh with that um i think it's uh it's about the hour so uh over to euro i invite you to to close the seminar you know you're still muted i'm getting so excited and i i wish we we had another hour for the conversation but wow uh thanks greta for for you know really sharing this conversation and i've been learning a great deal got some really great answers to the questions but perhaps even more importantly this has triggered a whole lot of new ideas and questions both more academic and more practical so i'm really glad that we we heard about the enabling and constraining aspects of gig economy and the open talent logic but also about the problems and challenges that this poses for individuals and and the new kinds of organizations that are developing and those who are developing and managing those and also really glad that we had this conversation just a moment ago about the darkest side of things so so all these are really important issues in practice but also offer a lot of opportunities for scholars in this area so while i i just hope that we will i'm sure that we will have the conversation going even if we have to be closing this session in a few seconds so at this point i just want to again thank you greta and thank you all the panelists and the audience for the great discussion and and this uh leaves me with one thing to do which is to advertise the next episode of leadership in extraordinary times and the next uh time will be on the 17th of november so soon enough uh it's going to be on cheap talk living up to the business roundtable statement and the chair will be uh taken by peter tufano our dean and the panelists will include alison bins who is executive director in sustainability research at moga stanley uh hero mizuno who is executive in residence at side business school and Bob Eccles who's visiting professor at our school as well now all the details about this as well as the recordings of of this uh great conversation can be found on our website with that thank you all for joining and goodbye

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