Category Archives: Series

Reconstructing jobs

Some coauthors and have a new report out: Reconstructing jobs: Creating good jobs in the age of artificial intelligence.  This essay builds on the previous two from our “future or work” series,  Cognitive collaboration and Reconstructing work, published on DU Press (now Deloitte Insights) as part of Deloitte Review #20 (DR20) and #21 (DR21) respectively.

Cognitive collaboration‘s main point was that there are synergies between humans and computers, and that solution crafted by a human and computer in collaboration is superior to, and different from, a solution made either human or computer in isolation. Reconstructing work built on this, pointing out the difference between human and machine was not in particular knowledge or skills exclusive to either; indeed, if we frame work in terms of prosecuting tasks than we must accept that there are no knowledge or skills required that are uniquely human. What separates us from the robots is our ability to work together to make sense of the world and create new knowledge, knowledge that can then be baked in machines to make it more precise and efficient. This insight provided the title of the second essay – Reconstructing work – as it argued that we need to think differently about how we construct work if we want the make the most of the opportunities provided by AI.

This third essay in the series, Reconstructing jobs, takes a step back and looks these jobs of the future might look like. The narrative is built around a series of concrete examples – from contact centres through wealth management to bus drivers – to show how we might create this next generation of jobs. These are jobs founded on an new division of labour: humans creating new knowledge, making sense of the world to identify and delineate problems; AI plans solutions to these problems; and good-old automation to delivers. To do this we must create good jobs, as it is good jobs that make the most of our human abilities as creative problem identifiers. These jobs are also good for firms as, when combined suitably with AI, they will provide superior productivity. They’re also good job for the community, as increased productivity can be used to provide more equitable services and to support *learning by doing* within the community, a rising tide that lives all boats.

The essay concludes by pointing out that there is no inevitability about the nature of work in the future. As we say in the essay:Clearly, the work will be different than it is today, though how it is different is an open question. Predictions of a jobless future, or a nirvana where we live a life of leisure, are most likely wrong. It’s true that the development of new technology has a significant effect on the shape society takes, though this is not a one-way street, as society’s preferences shape which technologies are pursued and which of their potential uses are socially acceptable.

The question is then, what do we want these jobs of the future to look like?

Reconstructing work

Some coauthors and I have a new(wish) report out – Reconstructing work: Automation, artificial intelligence, and the essential role of humans – on DU Press as part of Deloitte Review #21 (DR21). (I should note that I’ve been a bit lax in posting on this blog, so this is quite late.)

The topic of DR21 was ‘the future of work’. Our essay builds on the “Cognitive collaboration” piece published in the previous Deloitte Review (DR20).

The main point in Cognitive collaboration was that there are synergies between humans and computers. A solution crafted by a human and computer in collaboration is superior to, and different from, a solution made either human or computer in isolation. The poster child for this is freestyle chess where chess is a team sport with teams containing both humans and computers. Recently, during the development of our report on ‘should everyone learn how to code’ (To code to not to code, is that the question? out the other week, but more on that later), we found emerging evidence that this is a unique and teachable skill that crosses multiple domains.

With this new essay we started by thinking about how one might apply this freestyle chess model to more pedestrian work environments. We found that coming up with a clean division of labour between – breaking the problem into seperate tasks for human and machine – was clumsy at best. However if you think of AI as realising *behaviours* to solve *problems*, rather than prosecuting *tasks* to create *products*, then integrating human and machine is much easier. This aligns better with the nature of artificial intelligence (AI) technologies.

As we say is a forthcoming report:

AI or ‘cognitive computing’ […] are better thought of as automating behaviours rather than tasks. Recognising a kitten in a photo from the internet, or avoiding a pedestrian that has stumbled onto the road, might be construed as a task, though it is more natural to think of it as a behaviour. Task implies a piece of work to be done or undertaken, an action (a technique) we choose to do. Behaviour, on the other hand, implies responding to the changing world around us, a reflex. We don’t choose to recognise a kitten or avoid the pedestrian, though we might choose (or not) to hammer in a nail when one is presented. A behaviour is something we reflexively do in response to appropriate stimulus (an image of a kitten, or even a kitten itself poised in-front of us, or the errant pedestrian).

The radical conclusion from this is that there is no knowledge or skill unique to a human. That’s because knowledge and skill – in this context – are defined relative to a task. We’re at a point that if we can define a task then we can automate it (given cost-benefit) so consequently there are no knowledge or skills unique to humans.

What separates us from the robots is our ability to work together to make sense of the world and create new knowledge, knowledge that can then be baked in machines to make it more precise and efficient. If we want to move forward, and deliver on the promise of AI and cognitive computing, then we need to shift the foundation of work. Hence the title: we need to “reconstruct work”.

The full essay is on the DP site, so head over and check it out.

To code or not to code: Mapping digital competence

We’re kicking off the next phase of our “Should everyone learn how to code?” project. This time around it’s a series of public workshops over late January and early February in Melbourne, Geelong, Sydney, Western Sydney, Hobart, Brisbane, and Adelaide. The purpose of the workshops is to try and create a mud-map describing what a digitally competent workforce might look like.

As the pitch goes…

Australia’s prosperity depends on equipping the next generation with the skills needed to thrive in a digital environment. But does this mean that everyone needs to learn how to code?

In the national series of round tables Deloitte Centre for the Edge and Geelong Grammar School hosted in 2016, the answer was “Yes, enough that they know what coding is.”

The greater concern, though, was ensuring that everyone is comfortable integrating digital tools into their work whatever that work might be, something that we termed ‘digital competence’. This concept was unpacked in an essay published earlier this year.

Now we’re turning our attention to the question: What does digital competence look like in practice, and how do we integrate it into the curriculum?

We are holding an invitation only workshop for industry and education to explore the following ideas:

  • What are the attributes of a digitally competent professional?
  • How might their digital competence change over their career?
  • What are the common attributes of digital competence in the workplace?
  • How might we teach these attributes?

If you’re interested in attending, or if you know someone who might be interested in attending, then contact me and we’ll add you to the list. Note that there’s only 24-32 places in each workshop and we want to ensure a diverse mix of people in each workshop, so we might not be able to fit everyone who’s interested, but we’ll do our best.

Cognitive collaboration

I have a new report out on DU PressCognitive Collaboration: Why humans and computers think better together – where a couple of coauthors and I wade into the “will AI destroy the future or create utopia” debate.

Our big point is that AI doesn’t replicate human intelligence, it replicates specific human behaviours, and the mechanisms behind these behaviours are different to those behind their human equivalents. It’s in these differences that opportunity lies, as there’s evidence that machine and human intelligence are complimentary, rather than in competition. As we say in the report “humans and machines are [both] better together”. The poster child for this is freestyle chess.

Eight years later [after Deep Blue defeated Kasparov in 1997], it became clear that the story is considerably more interesting than “machine vanquishes man.” A competition called “freestyle chess” was held, allowing any combination of human and computer chess players to compete. The competition resulted in an upset victory that Kasparov later reflected upon:

The surprise came at the conclusion of the event. The winner was revealed to be not a grandmaster with a state-of-the-art PC but a pair of amateur American chess players using three computers at the same time. Their skill at manipulating and “coaching” their computers to look very deeply into positions effectively counteracted the superior chess understanding of their grandmaster opponents and the greater computational power of other participants. Weak human + machine + better process was superior to a strong computer alone and, more remarkably, superior to a strong human + machine + inferior process. . . . Human strategic guidance combined with the tactical acuity of a computer was overwhelming.1)Garry Kasparov, “The chess master and the computer,” New York Review of Books, February 11, 2010, www.nybooks.com/articles/2010/02/11/the-chess-master-and-the-computer/. View in article

So rather than thinking of AI as our enemy, we should think of it as supporting us in our failings.

We’re pretty happy with the report – so happy that we’re already working on a follow on – so wander over to DU Press and check it out.

References   [ + ]

1. Garry Kasparov, “The chess master and the computer,” New York Review of Books, February 11, 2010, www.nybooks.com/articles/2010/02/11/the-chess-master-and-the-computer/. View in article

To code or not to code, is that the question?

Centre for the Edge is dipping our toe into the education waters again after last years report, , Redefining EducationWe’re collaborating with Geelong Grammar‘s School of Creative Education to look into “Does everyone need to learn how to code?”

Computers are at the heart of the economy, and coding is at the heart of computers. Australia’s prosperity depends on equipping the next generation with the skills they need to thrive in this environment, but does this mean that we need to teach everyone how to code? Coding has a proud role in digital technology’s past, but is it an essential skill in the future? Our relationship with technology is evolving and coding, while still important, is just one of the many new skills that will be required.

Prime Minister Malcolm Turnbull has called for the country’s schools to introduce IT skills to students much earlier than they do now, suggesting that children as young as five or six should be introduced to coding. President Obama affirmed the need for coding education in his final state of the nation address. Some educators, however, are already pointing out that that teaching coding on its own might not be enough.

We will be holding a series of round table discussions across Geelong, Melbourne,  Sydney, Adelaide and Perth in May 2016 to explore the following questions:

  • What is the intention behind “we need to teach everyone to code”?
  • What educational and social outcomes we should be striving for?
  • Are there key skills from “learning to code” not covered in the current curriculum?
  • Is there a better definition for digital literacy?
  • How does digital literacy relate to coding and the rest of computer science?
  • How do we demystify digital technology and bring the community along?

Please contact me if you are interested in participating.

To code or not to code, is that the question?

Image: Ruiwen Chua.

The Enterprise of Tomorrow

David Glideh gave a talk at Unsexy Startups in London on the future of the enterprise, building on an using some of the key themes in the book. The video is embedded below.

Cloud, globalisation and social tools are changing the way Enterprises operate. Enterprises are going to be revolutionised and look extremely different in the future. How that looks will drive the success of new start-ups in the Enterprise space.

David Gildeh was Founder/CEO of SambaStream, an online collaboration tool for SMEs, which was acquired by Alfresco in 2011, the worlds leading open-source Enterprise Content Management system, where he currently leads their new Cloud business.

Observe, Orient, Decide, Act

OODA: Observe, Orient, Decide, Act
OODA: Observe, Orient, Decide, Act

It seems that I’ve shared this with four or five different groups of people over the last couple of weeks, so I thought it worthwhile putting it on the blog. Plus this is one of those instances where the Wikipedia page is not the best launching point.

Anyway, OODA (Observe, Orient, Decide, Act){{1}}, shown above, is a learning framework created by John Boyd{{2}}.

[[1]]John Boyd, The OODA LOOP, The Essence of Winning and Losing, slide 4 @ danford.net[[1]]

[[2]]A John Boyd Biography @ danford.net[[2]]

Colonel Boyd was an interesting bloke who had a huge influence on military tactics. One of his key insights was that success in a rapidly changing environment depends on your ability to adapt to the environment as it changes about you. The successful army is the one that can adapt as the world changes around it, and not necessarily the army with more resources at its disposal. This is interesting as the evidence is in and it shows that – for the vast majority of businesses – your competitors have very little influence on your success or failure; the largest factor is your ability to adapt and stay relevant as the market changes around you. Think Nokia, RIM and the iPhone. Or think in terms of high speed rail and point-to-point buses vs. discount air travel in Europe. The complication here is that today’s environment is changing so rapidly that your art – your product – might only have a shelf life of six months or so.

Continue reading Observe, Orient, Decide, Act

David has the edge on Goliath

David returns triumphant with the head of Goliath (Palazzo Ferrari, Genoa)
David returns triumphant with the head of Goliath (Palazzo Ferrari, Genoa)

Is success in business due to luck or hard work? It used to be that if you worked hard and invested astutely in your business that you could expect to be rewarded. Build it and they will come. Times have changed though, and more and more often it seems that all that hard work goes to waste when an unknown (and previously unseen) competitor emerges from nowhere to steal the market from under your nose. Success has become random with the business environment perpetually unstable and in constant flux. The market is hit-driven rather than being based on careful investment. Success now depends on coming up with the right product at the right time, and having a fairly large dose of luck. Business development used to mean investing in your business and building up the assets under its control. Now it means maximising your business’s luck (or minimising the luck of others).

Continue reading David has the edge on Goliath