The transition to working from home

Centre for the Edge is collaborating with Griffith University and Geelong Grammar School to try and understand why some organisations made a successful transition to working from home at the start of the pandemic, and why others were not so successful. What was more influential:

  • to be prepared by ensuring that workers and teams have a suitable suite of digital tools and training, or
  • to empower workers and teams to find and adapt digital tools to their changing needs, pulling in tools and training as needed.

The work will be based on a survey that the Deloitte Dtermine team have kindly put together. It would be greatly appreciated if you could complete the survey, and share the link with contacts both in or outside Deloitte. The survey is public and anyone is welcome to submit a response. The more responses the better!

We’d greatly appreciate it if you would complete the survey, and recommend it to your friends and colleagues.

The report presenting the results is scheduled for publication early 2021 via Deloitte Insights. There will be a virtual launch event which we’ll announce on the mailing list.

A moral license for AI

We have a new essay published in Deloitte Insights, A moral license for AI: Ethics as a dialogue between firms and communities. This collaboration with CSIRO’s Data61 looks into the challenge of creating ethical AI, picking apart the problems and proposing a way forward. There’s a launch event on the 2nd of September, 2020, which you can register for via Zoom.

Initially the focus of work on ethical AI was on to regulating the technology, but this failed to bear fruit. The focus then shifted to defining the principles, requirements, technical standards and best practices that it’s hoped will result in ethical AI. While progress has been steady and there has been a global convergence around principles for ethical AI, there remain substantive differences on what these principles mean in practice.

The problem (as we discuss in Framing the challenge) is that ethics and AI is a bit like thermodynamics, in that you can’t win, you can’t break even, and you can’t leave the game. From the conclusion of that section:

We can’t win, because if we choose to frame “ethical” in terms of a single social world—an assumed secular society—then we must privilege that social world over others. We can’t break even, because even if we can find a middle ground, a bridge between social worlds, our technical solution will be rife with exceptions, corner cases, and problems that we might consider unethical. Nor can we leave the game, banning or regulating undesirable technologies, because what we’re experiencing is a shift from a world containing isolated automated decisions to one largely defined by the networks of interacting automated decisions it contains.

We’re caught between the impossible task of defining “fair” or “ethical” algorithmically (a blind spot for the technologists) and the assumption that everyone sees the same world as we do ourselves but just approach it with different values, when this is not necessarily the case (a blind spot for many social
commentators). Rather than trying to create ethical AI we need to address a different challenge: understanding when an imperfect solution in an (already) imperfect world is good enough that it is, on balance, preferable to the imperfect world on its own.

As we admit in the essay’s conclusion, while the essay is notionally about “ethical AI” it never addresses the question of ethics and AI directly, attempting to define what is and isn’t ethical (an impossible task). Instead, it proposes that firms need to work with communities they touch to obtain and maintain an moral license for AI. The outline of a framework to do this is provided, integrating ideas from social license to operate, requirements modelling, sociology, and general morphological analysis to guide a firm’s interactions with the communities it touches. Such a framework could also provide a starting point for regulating ethical AI.

The essay concludes by point out that:

Ethical AI—the development of regulation, techniques, and methodologies to manage the bias and failings of particular technologies and solutions—isn’t enough on its own. Ethics are the rules, actions, or behaviors that we’ll use to get there. Our goal should be moral AI. We must keep a clear view of our ends as well as our means. In a diverse, open society, the only way to determine if we should do something is to work openly with the community that will be affected by our actions to gain their trust and then acceptance for our proposal.

You can find the essay on Deloitte Insights, while registration for the launch event is on Zoom.

Building the peloton

We have a new essay published in Deloitte Insights, Building the peloton: High performance team-building in the future of work. Jess Watson is the lead author of a report that looks into how we need to think a bit differently about teams, team work and leadership as the drive to create more agile organisations breaks down established organisation structures.

The report uses the analogy of a cycling peloton—the team-of-teams that competes and cooperates in a road cycling race—to integrate current research on team formation and operation in a world where firms function as a team-of-teams.

Highlights from the work include:

  • The factors long recognised as key to creating successful teams—of all types—have evolved as business has become more complex, driving organizations to work across departmental and organisational silos rather than within them.
  • It is important to establish a supportive environment and a clear, consistent, and compelling direction for a team if it is to be successful.
  • A team is built around its vision and it’s critical that all members of the team share the same vision and goals.
  • Diversity is also important. Business teams have long consisted of a range of different roles, but in addition to diversity of roles, identity diversity and cognitive diversity (or diversity of thinking) are now emerging as a clear differentiator between mediocre teams and those that are highly effective.
  • Effective practices are similarly essential to high performance in both a cycling and a business peloton.
  • Finally, the research is now abundantly clear that psychological safety is a powerful differentiator of effective teams.

You can find the entire text over at Deloitte Insights. Feel free to leave a comment here with your thoughts.

Innovating your way out of the crisis

We have a new blog post up on the Deloitte blog, Innovating our way out of the crisis.

In the past few weeks we’ve written about need for management to get out of the bunker mentality that uncertainty and a rapidly unfolding crisis had pushed us into, and how we have a perfect storm for innovation with demand collapsing for the old thing while new demand is popping up as we adapt, and the government is (effectively) subsidising innovation by providing unsecured loans and underwriting payroll (via JobKeeper). Put these together and you have the potential for (some) firms to emerge from the crisis stronger and more capable than they went in. New winners and losers will be created, and so on. That leaves one question unanswered: Where should a firm look for these new opportunities?

Now we’ve had a go at creating an innovation mud map to help find where a firm might innovate. Our hope is for this to be a conversation starter inside firms.

Published on the Deloitte Risk Advisory blog as Innovating our way out of the crisis.

The government is paying you to innovate

We have a new blog post up on the Deloitte blog, The government is paying you to innovate. The post points out that, due to a number of factors, now might be the perfect time to innovate.

There is a few reasons for this.

First is that we seem to have a perfect storm for innovation. The pandemic means that doing the old thing is not an option for many firms, with many of us stuck at home and the government restricting how businesses operate. At the same time, new demand is appearing and we all learn how to live in the new normal.

Second, and as we pointed out in Getting out of the crisis, the business environment post shutdown is unlikely to be the same as pre shutdown. The best way to prepare is to experiment now, to learn how consumer behaviour is changing, and start building the assets and services that will you’ll use in the new normal.

Third, and finally, the government is providing unsecured loans and is even willing to underwrite payroll. The government is effectively paying you to innovate.

There’s already early evidence that firms who are experimenting and adapting will emerge from this shutdown more efficient and effective than they went in. Now would appear to be the perfect time to innovate.

Published on the Deloitte Innovation blog, 20th of May 2020, as The government is paying you to innovate.

Getting out of the crisis: Learning now for the future

We have a new blog posts up on the Deloitte C19 blog, Getting out of the crisis. the post makes the point that:

The middle of a crisis might not seem to be the best time to think about the longer term. It can be important though, once immediate problems are dealt with, for management teams to consider how their firm will trade its way out of the crisis, rather than just reacting to events as they unfold.

The common assumption of a “V”-shaped economic contraction is unlikely to be true as when restrictions are lifted they’re likely to be lifted incrementally. The more a firm can do to innovation and keep the business running—rather than putting it into hibernation—the more likely the firm is to emerge from the other side. This means that:

An optimist would consider this a great time for experiment, to look for new opportunities, to find new ways to do old things, and to find new things to do.

You can find the post on the Deloitte C19 blog.

A mailing list for Centre for the Edge

We’re starting up a new mailing list for Centre for the Edge. It will be low volume, only announcements for C4tE-hosted events or new publications, with a quarterly summary.

If you’re interested then you can subscribe using the form below.

Subscribe

* indicates required



Email Format

Please select all the ways you would like to hear from Deloitte Centre for the Edge:


You can unsubscribe at any time by clicking the link in the footer of our emails. For information about our privacy practices, please visit our website.

We use Mailchimp as our marketing platform. By clicking below to subscribe, you acknowledge that your information will be transferred to Mailchimp for processing. Learn more about Mailchimp’s privacy practices here.

Digital agency and the skills gap

The concluding report from Deloitte Centre for the Edge and Geelong Grammar Schools’ collaboration looking into digital skills in the workplace, Digital agency and the skills gap,1)Evans-Greenwood, P & Patston, T 2019, Digital agency and the skills gap, Deloitte, Australia, <https://www2.deloitte.com/au/en/pages/public-sector/articles/to-code-or-not-to-code-coding-competence.html>. has been published by Deloitte, Australia. This report pulls together the results from across the project to provide an overview of the journey and the findings.

There’s a huge amount of angst in the community that our education system cannot keep up with rapid technological change, however this project shows that this is likely not the case. What we’re seeing is, in many cases, not a lack of skills, but an inability to navigate an increasingly complex digital environment. While digital skills are important, knowing when and why to use these skills is more important, particularly in a world where new knowledge is no further away than a search engine accessed via a smart phone.

Workers are unable to make the connection between the skills they have and the problem infant of them, making this a problem of unknown knowns. It’s not that workers lack skills, what they lack is discernment, the ability to read the digital environment around them and make sharp judgements about when and why particular digital tools and skills should be used. A lack of discernment limits a worker’s digital agency, their ability to act freely in a digital environment.

Solving this problem is not simply a question of teaching students and workers more, and more relevant digital skills. We need to focus on fostering in them the discernment required for them to develop the work habits that will enable them to make the most of digital technology.

The project was a long and fascinating journey so this concluding report itself is quite long, around 12,000 words. A much shorter business-friendly summary, The digital ready worker,2)Evans-Greenwood, P, Patston, T, & Flouch, A 2019, ‘The digital-ready worker: Digital agency and the pursuit of productivity’, Deloitte Insights, <https://www2.deloitte.com/us/en/insights/focus/technology-and-the-future-of-work/learned-helplessness-workforce.html>. was published last week by Deloitte Insights. A lot of valuable insights were dropped on the cutting room floor to create that summary, hence this report.

This report provides a summary of project’s journey, from the initial provocation through the roundtables, the more recent workshops, to the development of the project’s conclusions, as well as providing a detailed exploration of the findings. If you’re an educator (K12 or post-secondary) you might find this longer report more valuable as it digs into the details of the models presented, and does a better job of exploring the implications of the findings. If you were involved in any of the projects, the this report will join a number of dots and provide that ah-ha moment.

Revisiting the concept of learned helplessness, the report shows how the solution to learned helplessness is not to teach students more digital skills, but to foster their digital agency, their capacity to act independently and make their own free choices in the digital workplace. The concept of digital natives is explored in light of what the project discovered, resulting in a new model of digital competence in the workplace the identifies four archetypes: the digital naïf, digital pragmatist, digital explorer, and digital evangelist.

Finally, the report develops a progression capturing how one’s digital agency changes over time, and explores how digital agency might be fostered in both students and workers, and the changes this implies.

References   [ + ]

1. Evans-Greenwood, P & Patston, T 2019, Digital agency and the skills gap, Deloitte, Australia, <https://www2.deloitte.com/au/en/pages/public-sector/articles/to-code-or-not-to-code-coding-competence.html>.
2. Evans-Greenwood, P, Patston, T, & Flouch, A 2019, ‘The digital-ready worker: Digital agency and the pursuit of productivity’, Deloitte Insights, <https://www2.deloitte.com/us/en/insights/focus/technology-and-the-future-of-work/learned-helplessness-workforce.html>.

The digital-ready worker: Digital agency and the pursuit of productivity

We have a new essay published on Deloitte Insights, The digital-ready worker: Digital agency and the pursuit of productivity, which is the result of a collaboration between Centre for the Edge and Geelong Grammar School.1)Evans-Greenwood, P, Patston, T, & Flouch, A 2019, ‘The digital-ready worker: Digital agency and the pursuit of productivity’, Deloitte Insights, <https://www2.deloitte.com/us/en/insights/focus/technology-and-the-future-of-work/learned-helplessness-workforce.html>. As the blurb says, this essay looks into how:

To be effective in an increasingly technological workplace, workers must know, not just how to use digital tools, but when and why to use them. Critical to this ability is digital agency: the judgment and confidence required to navigate and be effective in unfamiliar digital environments.

There’s a lot of concern at the moment of a growing skills gap, the gap between the the skills held by graduates and those demanded by employers. Studies have been done to measure this growing gap, and significant resources have been devoted to updating curricula in an attempt to close the gap, all to no avail.

If we peal the lid of these studies we see they rely on aggregate skills data, typically from O*NET, which means that they’re limited to seeing a single negative view of how technology affects jobs, one where technology automates skills making workers redundant. The problem is that this isn’t the only pathway for technology to affect work. There’s also a positive pathway, where technology automates skills making the workers’ remaining skills more valuable, as well as a “no net change” pathway (or collection of pathways) which we have empirical evidence for but are yet to pull apart and understand.2)Spenner, KI 1983, ‘Deciphering Prometheus: Temporal Change in the Skill Level of Work’, American Sociological Review, vol. 48, no. 6, p. 824, <http://www.jstor.org/stable/2095328?origin=crossref>.

One of the key insights, if not the key insight, from Centre for the Edge and Geelong Grammar Schools’ To code or not to code collaboration, was that many of the problems we’re seeing in the workplace are likely due to learned helplessness,3)The term “learned helplessness” is borrowed from the psychology literature, drawing upon the work of Martin Seligman and many others. See, for instance, Martin E. P. Seligman, “Learned helplessness,” Annual Review of Medicine 23, no. 1 (1972): pp. 407–12. where a person suffers from a sense of powerlessness arising from a persistent failure to succeed. We’re teaching students how to use particular digital tools in particular ways, but we’re also teaching them that these tools are fragile and using them the wrong often results in problems and might even ‘brick’ the device. Rather than framing the problems we’re seeing in the workplace as the result of a growing skills gap due to the destruction of skills, it might be more appropriate to frame them as a problem of unknown knowns. It’s not that the worker doesn’t have the skills required, their problem is making the connection between the skill and the current problem they’re working on.

The solution to this problem isn’t to provide students with more, and more relevant, digital skills. Indeed, that approach is unlikely to help as the students are not lacking in skills. While it’s important to know how to use particular digital tools, it’s more important to know when and why these digital tools should be used. What students lack is discernment, the knowledge and experience required to make observations and sharp judgements about which digital tools might be useful and how they will affect the work. We need to foster in students the attitudes and behaviours—something we’ve taken to calling a predilection—that help them navigate the digital workplace and develop the habits that enable them to integrate digital tools into their work. Ultimately the solution is to foster digital agency in students, to help them develop the literacies, knowledge, skills and predilections the need to act independently and make their own free choices in the digital workplace.

The essay explores, in some detail, the concept of learned helplessness in the digital workplace, and how we might might foster digital agency in both students and workers. There’s also a few of useful models for thinking about this problem, helping us move beyond misleading dichotomies like Digitial Native vs Digital Immigrant which have proven to be wrong.

You can find the entire text over at Deloitte Insights. Feel free to leave a comment here with your thoughts.

References   [ + ]

1. Evans-Greenwood, P, Patston, T, & Flouch, A 2019, ‘The digital-ready worker: Digital agency and the pursuit of productivity’, Deloitte Insights, <https://www2.deloitte.com/us/en/insights/focus/technology-and-the-future-of-work/learned-helplessness-workforce.html>.
2. Spenner, KI 1983, ‘Deciphering Prometheus: Temporal Change in the Skill Level of Work’, American Sociological Review, vol. 48, no. 6, p. 824, <http://www.jstor.org/stable/2095328?origin=crossref>.
3. The term “learned helplessness” is borrowed from the psychology literature, drawing upon the work of Martin Seligman and many others. See, for instance, Martin E. P. Seligman, “Learned helplessness,” Annual Review of Medicine 23, no. 1 (1972): pp. 407–12.

On bland economic models and the colonial mindset

A team at Harvard has released a new version of the Atlas of Economic Complexity, an index of ‘economic complexity’. Journalists have pounced on the model to make that case—as they often do—that Australia is a second class country run by second rate politicians. The problem is that the model seems rather bland, only proving that Australia is a large country with a small population (and correspondingly small market) a long way from the major markets. We already knew this.

The atlas “interpret[s] trade data as a bipartite network in which countries are connected to the products they export, and show that it is possible to quantify the complexity of a country’s economy by characterizing the structure of this network”.1)Hidalgo, C.A. & Hausmann, R., 2009. The Building Blocks of Economic Complexity. Available at <http://www.tinyurl.com/y55fxc8s>. So complexity is a measure of integration into global and regional supply chains. This is assumed to correlate with the complexity of an economy.

Given that, any small populous country that is geographically situated near a large market (or cluster of markets) should do well. These countries are too small to export resources (due to lack of land and resources) while their domestic market is too small to soak up many finished goods. They are, however, well situated to be part of supply chains that feed the large market that they’re adjacent too, both importing and exporting intermediate goods. In a case of “no shit Sherlock”, countries like Singapore and Switzerland score quite well.

Large populous countries, such as the US, do ok as they can export products supported by their large domestic market as well as the large domestic market being a sink, importing products from other countries. Not as ‘complex’ as a less populous country importing and exporting intermediate goods, but there’s still a bit going on.

Small to mid-sized countries (in terms of population) that are far from major markets will do poorly. They’re too far from global or regional value chains to participate in them, and their domestic market is too small to support the development of finished goods for export. Here’s looking at you Australia.

Countries such as South Africa sort of fall into this bucket too, though being surrounded by a number of small markets does alleviate their problem somewhat. Australia, as we like to point out, is both a continent and an island. Being small and far from major markets is also why Australia doesn’t have a domestic car manufacturing industry: we’re not big enough to support a car assembly plant with domestic sales, while being too far away from major markets to export.

So the atlas does show a correlation, but it’s with population and geography more than anything else. Also, as the atlas is based on correlation, rather than a causal model, it don’t have anything to say about the future as they’re just extrapolating trends.

It’s a bit annoying that there’s not much to be learnt from the atlas. What is more annoying though is the colonial mindset in Australia that assumes that nothing good can come out of the colonies (Australia) as all good things come out of the colonial power (being Europe and the US).

References   [ + ]

1. Hidalgo, C.A. & Hausmann, R., 2009. The Building Blocks of Economic Complexity. Available at <http://www.tinyurl.com/y55fxc8s>.