Interesting stats

Thanks to Acuity

 

We cannot write about the Future of Work

 The vocabulary to describe the beyond the future of work does not exist yet. 

Abstract words we are currently using in attempt to imagine this foreign landscape include  “unprecedented”, “technological transformation” and “adaptability”.  

Employees have to unlearn their native language surrounding what it means to have their own job, profession and career. They need to relearn how to be resilient, adaptable and open to change.

 

In the past, the predictable timeline began with education, transitioned smoothly to career, concluding in retirement. 

Today, instead of learning to work, we have to work to learn. How else can the average professional worker of this generation experience 17 different jobs across 5 different industries or survive multiple paradigm shifts?

 

Instead of associating our identity with our job, our company, our education, we begin to think of ourselves in a whole new way. 

To conceptualize a job as the skills it requires, rather then the title at hand, is the mindset in which to strive. Employees are empowered to view themselves as a partner as they realize the profound value in a portable skillset and an ability to learn from the tools as well as with them.

 

While the human species is getting smarter and more efficient, the individual has the same cognitive capacity and bandwidth. The individual will need to shift toward utilizing the emotional and imaginative faculty of critical thinking and problem solving as machines replace every possible aspect of manual tasks. To access our cognitive bandwidth is to employ automated technology that will replace non-creative tasks. There is a misconception that high level jobs are safe from automation and low level jobs are at risk.

 

As degrees don’t guarantee jobs, we enter a renaissance period of learning, which values learning agility and mindset as what is needed are highly skilled people who can solve ambiguous and complex problems with creativity and collaboration. 

Spongelike learning and wisdom and knowing have now converged   

  

The domain of the elite is making ones passion productive, which can be done by being open to every industry, as we carve the line between ‘what is human work’ and ‘what is machine work’.  Human work will involve innovative entrepreneurial problem solving. Soft skills. The ability to help others. 

 

Platforms are more valuable then products as they aim first to create value then deliver supply to a market. Thus, to move out of scalable production to scalable learning is a step toward employee empowerment. Employees  will be viewed as partners with the freedom to explore the entire spectrum of industries.

 

Concepts Gleaned 

1. Reinventing the notion of a firm – alternate value creation not product division. Create value rather then deliver products and services to a market. Supply chains.
2. Moving out of scalable production to scalable learning 

 

 

 

TED TALKS to watch 

·      the unbicycle - how to unlearn 

·      the importance of why - Simon senior 

·      utopia for realists

·      cognitive bandwidth – creatively contribute (school model to create value)

·      work to learn. 

 ​

Beyond the Future of Work is Learning #FOW

 

Three trends are conspiring to make 2017 a year of higher job insecurity and higher odds of individual economic ruin. First, jobs everywhere now require more analytical, social, and emotional skills than ever before. In the 1930s, "shovel ready" jobs were literally that: give a person a shovel and put them to work. Today, even jobs that don't require college educations require a much higher level of skill. Roads aren't built by a crew of shovelers; they require skilled equipment operators. 

Second, the gig economy is a brittle one. While some prefer the flexibility, for too many it's a way to pile on even more hours in a struggle to make ends meet. That exacts a physical and psychological toll. And it often comes without health care, vacation, and other benefits, which buffer individuals from the random bad stuff that happens in life. 

Third, the rise of artificial intelligence will reduce the need for people in many roles, ranging from driving services to customer support to finance. That's the baseline. That's already underway.

But there's a scenario where it gets much worse. The US educational system isn't geared to address the analytical, social, and emotional skill gap. It’s a system that was designed for a different age: a time when memorizing facts was the right preparation for jobs that were often highly structured and repetitive, at companies that faced far less competitive pressure and both chose to and could more easily afford to offer lifetime employment, pensions, and even a holiday turkey for every family.

The gig economy could also get worse. As it grows, average worker income will drop because not only will an increasing supply of more gig workers (who often come to gig work for lack of alternatives) drive down the average labor rate, but the companies coordinating the work will seek to extract more profit.

And artificial intelligence will be here faster than anyone expects. 10 years ago there was no iPhone, let alone self-driving cars, let alone an Alexa device that lets you do all your shopping from home by talking to it. It's an odd moment to realize that 70 years of science fiction -- Star Trek's communicators, Knight Rider's autonomous car, and Asimov's all-knowing, voice-operated Multivac -- happened in the last decade. It's hard to imagine how much further technology will go in the next 10 years.

Put all this together, and we'll see a growing gap between workers' skills and employers' needs, an increase in job and wage insecurity, and a potentially rapid elimination of even the service jobs (driver, restaurant server, broker, etc.) that we thought were safe. And it will come far faster than we expect.

All this leaves one feeling like Woody Allen, when he said, 

"More than any other time in history, mankind faces a crossroads. One path leads to despair and utter hopelessness. The other, to total extinction. Let us pray we have the wisdom to choose correctly." 

But there might be a third way. A difficult, nose-to-the-grindstone, un-sexy, non-heroic path. It will require three enormous, ponderous communities to work together. The educational system needs to become more focused on analytical, social, and emotional skills. I don't mean spending 100% of teaching time on these areas. But hypothetically, even going from 8% of time spent on these areas to 10% would be a 25% increase. And if resume writing and interviewing practice became standard, that wouldn't hurt either. 

Employers too need to invest in this kind of training. The workforce doesn't today have all the right skills in all the right places. That's why unemployment hovers around 5% but millions of people are facing stagnant or declining wages. 

Employers also need to hire differently, and get better at assessing potential, instead of writing someone off because they don't have the right experience. 

Finally, the government needs to encourage this. It should provide incentives for employers to take bets on people and make longer-term investments, and support and reward non-profit educational institutions that experiment with and implement new curricula. 

That's the path out. And there's no glory in it. Just a steady, relentless, vital, necessary slog. But otherwise the future is going to increasingly be one of workers who won and workers who lost. Today we're at Woody Allen's crossroads. Unless ... 

=============================

"Warning to All" image copyright Isaac Asimov (1956) from his short story "The Last Question"

Written by

Laszlo BockCEO and co-founder of Humu. Former SVP of People Operations at Google. Author of "Work Rules!". Advisor. Dad.

BSI Learning explores the future of work from the correctional centre to the boardroom

Press Release

 

Minister for Corrections David Elliott on the 24th of May, 2017 announced BSI Learning had won the contract to deliver the majority of the education and training in prisons. BSI Learningas the registered training organisation was appointed following a rigorous tender process.

This initiative by the Government would increase the number of inmates participating in education and training by 20 per cent. This will help make offenders job-ready upon release, more equipped to integrate into society and less likely to reoffend.

BSI Learning has been a major provider of educational services to government departments, corporates, non for profits, job services and correctional services. BSI Learning has worked in the Queensland correctional system for more than 16 years and has delivered the VET in Prisons Program over the past 10 years.

“We are excited to have the opportunity to partner with CSI and CSNSW to deliver the inmate education program to improve employment prospects and give them an opportunity to make their own choices,” Mr Ivan Kaye, Chairman and Founder of the BSI Group of Companies said. “However, this is just one of many unrelated communities that need our help in one form or another.”

“We live in a rapidly changing world and no matter whether you are an inmate, an entrepreneur or in the public sector, you are not going to thrive without continuous learning, collaboration and peer support.”

“The era of artificial intelligence will disrupt the way almost everyone works, and the more we talk about it and recognise how things will change, the better prepared we will be,” said BSI Chairman Ivan Kaye. “Education is the key.” 

BSI Learning will lead discussions on preparing for the future by hosting six events between now and November for HR executives covering the topic ‘Beyond the Future of Work’.

 

For any media enquiries please contact Peter McKeon, Group CEO - BSI on 02 9216 4000 or pmckeon@bsi.com.au .

Don't fear intelligent machines, work with them

Gary Kasparov's final 2.5 minutes of his latest Ted Talk

 https://www.ted.com/talks/garry_kasparov_don_t_fear_intelligent_machines_work_with_them/ 
12:18Twenty years after my match with Deep Blue, second match, this sensational "The Brain's Last Stand" headline has become commonplace as intelligent machines move in every sector, seemingly every day. But unlike in the past,when machines replaced farm animals, manual labor, now they are coming after people with college degrees and political influence. 

And as someone who fought machines and lost, I am here to tell you this is excellent, excellent news. 

Eventually, every profession will have to feel these pressures or else it will mean humanity has ceased to make progress. 

We don't get to choose when and where technological progress stops. We cannot slow down. In fact, we have to speed up. 

Our technology excels at removing difficulties and uncertainties from our lives, and so we must seek out ever more difficult, ever more uncertain challenges. 

Machines have calculations. We have understanding. 

Machines have instructions. We have purpose. 

Machines have objectivity. We have passion. 

We should not worry about what our machines can do today. Instead, we should worry about what they still cannot do today, because we will need the help of the new, intelligent machines to turn our grandest dreams into reality. 

And if we fail, if we fail, it's not because our machines are too intelligent, or not intelligent enough. If we fail, it's because we grew complacent and limited our ambitions. 

Our humanity is not defined by any skill, like swinging a hammer or even playing chess.

15:05

There's one thing only a human can do. That's dream. So let us dream big.

How come a billion brains are making all the decisions about my health?

written by - Philippa Lewis, Managing Director, Elementum

The word revolution means a forcible overthrow of a social order, in favour of a new system. In healthcare, the word is used all the time but has anyone actually explained what this new system might look like? Does anyone actually know?

Try asking the question at the next gathering of uber smart, tech savvy people who know about the so called healthcare revolution. See if they can define the healthcare revolution and explain this new system. I guarantee the answers will be circular, not linear. There will be lots of “if” and “then” and “could” and “should” words. Their comments will be difficult to contextualise. They will most likely terrify or excite you but for sure they will confuse you.

What most of us want to know is will this revolution be a good thing or a bad thing?

The answer is “maybe”.

The digitisation of almost everything is creating a form of revolution everywhere. It’s causing a revolt amongst a number of healthcare stakeholders. Clinicians and physicians fear their role will be replaced by bots and algorithms. Breaking news; it’s already happening.

Regulators are having to scratch their heads to find ways to qualify outcomes and claims because the validity of the old ways is weakening every day as new paradigms surface and are adopted as mainstream.

Providers of digital solutions in the form of bots, apps, medical devices, algorithms and therapeutics are subject to excessive yet often unproductive scrutiny. This delays their adoption and blocks the building of the data set and the ultimate integration of data and devices.

Fear not; we have witnessed other revolutions. The industrial revolution which affected so many sectors, like manufacturing and supply chain, created a major disruption and a new world order. Nothing to be affeered of there.

Then during the ’50s and ’60s IT revolutionised things like accounting, payroll and HR.

So when it comes to healthcare, be prepared because this particular revolution is tantamount to the deconstruction of medicine as we know it.

Thanks to movements like Quantified Self, the Human Genome Project and other health hacking organisations, the patient and their personal profile are starting to determine decisions.

No cookie cutting here. “I am as unique as my DNA” … So, don’t try clustering me into the group of 200 patients who formed the research cohort that secured the FDA approval in 1963. I either want big data to justify the protocol (i.e., millions if not billions of data points on the subject to prove its efficacy) or I want it to be about me and just me.

And not forgetting that trusty GP, Doctor Google; medicine is now patient directed rather than doctor directed.

The digitisation of everything to do with health is about real-time collection and interpretation of information. Principally, it’s about the precision, accuracy and the accountability of data.

Personalised, digitised and democratised.

Big data collects such a huge amount of information, it requires algorithms and machine learning to interpret it. The collection and interpretation might seem messy, but the sheer amount of data collected makes it worthwhile to forgo exactitude, especially when it comes to healthcare.

Bed-less hospitals, mobile virtual treatment, bots taking the place of surgeons, radiologists, oncologists and every other specialist you can name. Greater accuracy with diagnostics and big data making decisions which were once made by the doctor at the bedside. A single decision maker versus a billion decision makers.

I’m not so clear; so who do I sue?

To this extent, Artificial Intelligence is the cornerstone of this revolution. It isn’t yet an entity in its own right (one whom you can sue, yet) but it is becoming as respected as the health professional. AI is becoming the doctor of choice because it able to coalesce the data that is being collected from “a billion brains” to analyse across data sets of such magnitude, it eradicates the need for individualisation by comparing and contrasting the individual against a huge and continually growing data set.

Your chest x-ray or the MRI on your brain will be interpreted based on billions of other x-rays and MRIs. So the opinion expressed as to diagnosis and therapy is not just that of your doctor and his or her limited experience but that of the tens of thousands of doctors and their patient records collected over decades, integrated into one diagnostic tool.

So, there we have it; big data is the collective intelligence generated by billions of brains and growing. It’s counter intuitive to the notion of individualisation, but on the contrary, personalised medicine somehow does fit into this world.

Confused? Let me explain a bit more.

Think about the commercially bought wearable.

The Fitbit is collecting billions of data points across the globe about fitness and movement. It also knows where you are, where you live, your social media status, your sleep patterns, weight and height and with a very simple stretch of data analysis, your risk of diabetes or cardiac disease. It might hold more valuable and powerful healthcare data than a government. Will corporations hold more information about you than the government or your insurer?

Mobile, body-worn healthcare devices are the fastest growing sector of wearables. They will outstrip all other wearables by 2019, just two years from now. The question is, what happens to all the so called big data they collect?

The underpinning system that is fuelling the healthcare revolution is big data. To understand big data and its power, you have to first understand what small data was.

Small data was part of the analogue world. Since the 19th century, it’s what science, research and medicine was based on. The protocol of taking small samples and investigating against that small sample was regarded as acceptable and even robust. Where n might equal 30 or 50 or 100, things were easy to prove. Getting a therapy, diagnosis or treatment protocol was simple when the test group was a few hundred or even a few thousand.

The invention and development of Electronic Healthcare Records has been done by corporations who see this as a business rather than a critical strategy for healthcare. Are they fit for purpose? Depends what purpose you are referring to.

However, when the base line of data is small, absolute accuracy is required. Small data requires a narrow classification of investigation and therefore defines or at least limits the outcomes. But it was with small samples we have made major healthcare decisions when it comes to treatments, drugs and general protocols.

Now enter big data. It seems messy but it collects such a huge amount of information, sometimes randomly, that it requires algorithms and machine learning to interpret it. This vast volume of data is not possible without digital technology. Without digital technology we couldn’t collect it in the first place and even if we did, we couldn’t interpret it. The collection and interpretation of big data might seem, again, messy, but the sheer amount of data collected makes it worthwhile to forgo exactitude, especially when it comes to healthcare.

All this data collection and interpretation creates a new risk for society: cyber security. This element of the revolution isn’t remotely solved.

Domestic, criminal, international; the black-market risk of data leakage and data theft is a daily reality. Literally 1,000s of healthcare environments are hacked daily. It’s costing billions every year and hacking in healthcare is growing at 200% in the US. Australia is listed as second in world for healthcare data security break ins/theft, second only to the US.

Control of the information has all stakeholders up in arms because we don’t have the answers yet. We can’t guarantee we actually know who has the right to the data, who owns the data.

Should your dentist know your reproductive status? Should your insurer know your metabolic status? Should your gym know your cardiac history?

The answer is another “maybe”. But if you as the patient own the data, are you providing this data to your health professional and if so, under what legal instrument? And what about that Fitbit your wearing? Have you licensed Google to access your data from Fitbit to use on its population studies, regional data augmentation or simply to hold your personal data?

The practical challenge of harnessing big data can be summed up in one word – integration. How to corral the data collected and ask the right questions? How to centralise all the data collected from all these medical devices and make sense of it? Who is building the algorithm to interpret this information and who will have access to it? Will it be monetised and if so by whom?

The answers to these questions are not yet defined. There is no one body taking principle responsibility on these matters. Where corporations have greater data than governments and where ownership of that data is still foggy, where regulators are struggling to keep up with innovation and public demand, the control of big data is murky. You have to expect chaos.

Let’s look at one of the most practical and tangible elements of the healthcare data revolution: the Electronic Healthcare Record (EHR). When you know about the complexities of the revolution it’s no wonder we have resistance to its adoption from so many corners. That’s because it’s all about the big data; it’s collection, interpretation, diagnosis, triage, insurance, monetisation.

The collection and importantly, the actual interpretation of medical history of the patient is a fundamental element of the revolution. Knowing all about you, your conditions, surgeries, treatments and therapies feeds into risks, costs and qualifications. You may wish this information to remain private but this is unlikely. You are forming part of the billion brains; you can’t avoid it because your data will be mined. This record will follow you wherever you go within the healthcare system, for life.

The EHR risk is all about access. Will it always be anonymised? Perhaps. Will it get hacked, stolen or even sold? A resounding “yes!”.

Whilst an Electronic Health Record sounds like a sensible and easy protocol to follow and the benefits of real-time patient information are self-evident, why has it not been taken up ubiquitously around the world?

Why don’t you have one?

It should be noted that to date, the only country that has been able to implement cradle to grave electronic healthcare records is Denmark. A small population, totally government controlled country.

In the rest of the world, EHRs are fundamentally the territory of private enterprise, albeit governments are trying to implement policies and laws to control their deployment.

Their invention and development has been done by corporations who see this as a business rather than a critical strategy for healthcare. So are they fit for purpose? Depends what purpose you are referring to.

The EHR is actually an obstacle to the deployment of technology in healthcare and in particular bio feedback medical devices because they rarely integrate seamlessly with the digitally generated data.

So some data is automated or instrumented and other clusters of data are manual. Arggh…

The introduction of medical devices that collect valuable data about a human has become the one of the biggest integration challenges for the EHRs. If the EHR is attached to a person or group of patients, the data collected from the medial devices they wear must find a place on the platform.

This is where there is major dispute.

How does that data get onto the EHR platform, who owns it once it’s there? How does the big data on the EHR platform get interpreted and who gets to monetise it? Does the medical device corporation own the data generated by its device and patented algorithms? Does the owner of the device or patient own the data which is placed on the EHR? Who is the beneficial owner? Who is responsible for its security? And what about the regulators and legislators? Will they test efficacy?

In any event the integration of all the random data collected from body-worn medical devices has to be corralled somewhere, doesn’t it?

…Or does it?

The good news is that you can continue to love your GP, but realise that the billion brains are already working hard on your healthcare world and they may not agree with your beloved GP.

You could call them the serfdom of the revolution. Ready and willing to take the jobs of others and to work 365 days a year. Preparing to take over the aristocracy and change the ecosystem entirely. However whichever way to cut it, this revolution is reaching maximum entropy. It will remain so until there is consolidated consensus by the many stakeholders willing to collaborate rather than compete. This will only happen if there is agreement to base the revolution on concepts and regulations that feed the greater good and force the formation of a robust infrastructure of rules, laws, and the standardisation of efficacy and its process.

About the author: Philippa Lewis is the founder and Managing Director of Elementum. Together with the team of Virtual Experts, Elementum provides advice, guidance and services to start ups and early stage businesses who wish to achieve commercial success in their given field.

Robotic process automation market to reach AU$870m in ANZ by 2020: Telsyte

 

By Tas Bindi |  May 30, 2017 -- 01:45 GMT (18:45 PDT) | Topic: Enterprise Software https://www-zdnet-com.cdn.ampproject.org/c/www.zdnet.com/google-amp/article/robotic-process-automation-market-to-reach-au870m-in-anz-by-2020-telsyte/

Enterprise investment in robotic process automation (RPA) is set to soar in Australia and New Zealand, according to new research from analyst firm Telsyte. 

The analyst firm said RPA -- which enables software robots to replicate the actions of human workers for routine tasks -- is now being used or investigated by six out of 10 ANZ organisations with more than 20 employees. 

The finance and insurance industries are expected to be the fastest adopters of RPA in the short term, according to Telsyte, although RPA can also be applied to industries with large customer support and request processing requirements, such as telecommunications and government. 

Telsyte managing director Foad Fadaghi said RPA is not just about cutting overhead costs; it can also change the way organisations operate.

"A proof of concept is important for organisations to first understand the nature of processes that can be best solved through RPA, before progressing to an enterprise-wide strategy," Fadaghi suggested.

"Equally important is the use of pilot programs to understand the change management requirements before a further rollout."

Telsyte also recommended that organisations assess the processes they would like to automate by their level of complexity. 

"Complexity has a positive correlation with automation costs, and targeting lower-complexity processes initially can result in better initial returns," Telsyte said. 

Fellow analyst firm Gartner has previously referred to RPA tools as "gateway technologies" or "surface tools", because they simply skim the surface of the larger intelligent automation services market.

"The attraction is the RPA tool just sits on top of the legacy system" such as enterprise resource planning(ERP), and there is no need for any special integration, Gartner research vice president and analyst at Frances Karamouzis told ZDNet.

"They're also easy to use and have a relatively low cost. For all those reasons [RPA] has by far the highest adoption of automation tools that we've seen," Karamouzis added. 

With the increase in enterprise investment in RPA, DXC Technology, a New York Stock Exchange-listed IT services company, announced the introduction of 60 new RPA experts in Australia and New Zealand.

"Organisations are looking for a way to bridge the gap between large funded digital transformation projects and the long tail of business processes attached to aging systems. RPA can achieve this with a virtual workforce that streamlines existing processes, lays the foundation for intelligent automation, and frees up employees for more engaging work," said Seelan Nayagam, managing director at DXC Technology ANZ.

Additionally, 38 percent of organisations with more than 500 employees have active RPA programs in place. 

Based on insights provided by 302 CIOs and IT decision makers, the Telsyte ANZ Robotic Process Automation Study 2017 predicts the ANZ RPA market will grow at a compound annual growth rate (CAGR) of 45 percent from AU$216 million in 2016 to AU$870 million in 2020.