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Director of the Intelligent Robotics Laboratory, Osaka University; Winner best humanoid award four times in RoboCup; Named one of the top 100 geniuses alive in the world today
Astrobiologist, Jet Propulsion Lab, NASA; first female principal investigator on a Mars mission
Physician-scientist, inventor and innovator; Founder & Executive Director, Exponential Medicine; Medicine Track Faculty Chair, Singularity University; TED speaker
Leading expert on the robot revolution, artificial intelligence, job automation and the impact of accelerating technology on the economy and society; Author: Rise of the Robots
South Australian Scientist of the Year, Telstra Business Women of the Year, Prime Minister’s Malcolm McIntosh Prize for Physical Scientist of the Year
Computer scientist, futurist, award-winning author; Energy & Environmental Systems faculty member, Singularity University
Strategic transformation and disruptive innovation expert. Partner of Innosight and author of The Innovator’s Guide to Growth and The Little Black Book of Innovation
Professor at Bournemouth University and Universidad Camilo José Cela, Madrid; One of the most influential academics in the field of technology and education globally
Scientia Professor of Physics, University of New South Wales; Australian Research Council Laureate Fellow; NSW Scientist of the Year
Chairman of the Australia and New Zealand Banking Group Ltd and Coca-Cola Amatil Limited
Dr Finkel commenced as Australia’s Chief Scientist on 25 January 2016. He is Australia’s eighth Chief Scientist
Artificial intelligence and computing are currently as competent (in some areas) as their human counterparts. At what point will they surpass us and what are the consequences?
A Changing Landscape
The advance and implementation of artificial intelligence is a mixed bag. Some applications may never be developed past a robotic machine that operates merely as a repetitive, assembly-line program tasked with making only basic adjustments to accommodate their environment. Other AI uses, however, are on the cusp of exponential growth and may present humanity with a very real rival.
Applications utilizing cloud computing with AI create amazing opportunities for human-machine interaction. IBM’s Watson, Google’s Deepmind, and Microsoft’s Project Oxford are artificial intelligence programs that use language processing, voice recognition and computer analytics to provide an interface between the computer and a human via voice requests or commands. These areas offer an opportunity to enhance our lives, allowing us access to products, services and information on a global scale. But, they also move us closer to machines that function and interpret the world around us almost as well as humans.
Military applications, Blockchain technology and super-fast parallel processing via GPUs have an almost limitless horizon. Exoskeletons are under development that create an almost super-human military force. Personal assistants are being created that actually learn from their conversations with humans. The world of super-computing capabilities is currently so fast that even the most complex scientific, medical or technological problems can be solved in a matter of minutes or hours. We now speak of computer capability in terabytes – forget the old gigabyte… it’s so yesterday.
And, if the rapid expansion of internet inventions is a foretelling of future machine learning via cloud computing, we will soon experience forward progress on a scale that is difficult to imagine. The looming question for humanity: At what point will the computers surpass their human creators?
The Workplace Is Only the Beginning…
Whether you’re a customer at McDonald’s or an hourly employee in an automotive facility, the rise of artificial intelligence and robotics has already touched your life. Artificial intelligence coupled with robotics has opened opportunities for streamlining not only production in manufacturing but improving the customer experience when ordering fast food as well.
There are, of course, pros and cons when you consider the integration of AI and the machines into our workplaces. Artificial intelligence will increasingly impact human livelihoods, business bottom lines and social interactions. But, as with the invention of the ATM, declines in the person-to-person experience aren’t an overnight occurrence. Slowly, however, the workforce seems to be moving toward a more “machine” and less “human” diversity.
Potential Human Versus Machine Conflict
The potential for human resistance and conflict won’t necessarily be a direct result of Mary Jane Robot’s ability to speak five languages, solve complex problems and operate at super speeds. The real conflict will be a result of lost incomes, a lack of workforce opportunity (especially for unskilled labor) and the human perception of being “forgotten” creating the opportunity for an unhappy populace.
Of course, as with any transformation or transition, there are two potential outcomes. The opportunity exists to improve humanity with the addition of AI into many aspects of our lives. With the continued development and integration of AI, unforeseen opportunities and industries could arise to benefit all of humanity. After all, who in 1983 could have foreseen the tech giants of today, such as Amazon, Google and Microsoft? How many lives have been improved simply because of the opportunities these companies created? The opportunity also exists to misuse AI and open the door to discontent.
The day will arrive when we are forced to determine if artificial intelligence is a help or hindrance. If the latter proves to be the conclusion, conflict will be sure to follow.
Original Article on Inc.com By Avi Savar CEO and managing partner, Dreamit@avisavar
Avi Savar is CEO and Managing Partner of Dreamit, a top venture accelerator and early stage investment fund. He is the author of Content to Commerce and consults globally on trends in digital media, disruptive technologies and corporate innovation. He has been featured on Fox News, Forbes, Mashable, Business Insider, TechCrunch, VentureBeat, the New York Times and is a contributing editor for Inc.
The robot revolution is inevitable.
In fact, you could comfortably say it’s already upon us.
As automation and artificial intelligence evolve at breakneck speed, our policies and institutions are frantically chasing their tails to keep pace.
This disruption presents one of the most pointed challenges to modern economies – and Australia is not immune.
While ethical and existential questions have dominated most of the public discussion, a gravely overlooked area has been the impact on inequality and the distribution of wealth.
You thought Australia’s income gap was bad now…
Peter: We’re a lucky country by any standard, the second wealthiest country in the world on a per capita basis, reasonable education system, pretty good health system.
But when you look at what’s happened over the last 20-25 years, what you see is that while everyone has improved their incomes in real terms, there is a real skewering to people at the top end of the spectrum in terms of wealth
Then you look forward and you look at this whole issue of globalisation, plus automation, plus artificial intelligence. The likelihood is that at the very least jobs are going to turn over much quicker as current jobs become obsolete and people have to train for new jobs. That’s best case.
Worst case is a lot of jobs, more and more jobs will go offshore, or simply there won’t be new jobs because of artificial intelligence in Australia.
If you look at the trends in inequality, the trends could actually accelerate unless we manage this transition really effectively.
Tania: For example, people who are laid off in manufacturing will have to go into service jobs like caring.
But then you’ve got to ask yourself, are people who’ve done those other jobs before going to want to go into caring jobs?
So…which jobs are the robots gonna take?
Peter: Lawyers and accountants. Any sort of industry where you have a lot of processing taking place.
If you think about the work of a lawyer or an accountant, there’s a lot of processing taking place there, or data analysis. Data analysis is usually a little background, but it can actually be done in most cases far better by artificial intelligence than human beings.
Tania: Obviously more senior lawyers in more advisory roles, their jobs are less at risk than say more junior lawyers and junior accountants.
Peter: For example, due diligence processors.
Historically they used to get young lawyers to do that, they used to charge around $200/hr, and it was an enormous margin.
Now, an awful lot of that work can be done by AI, because with big data you can actually review thousands and thousands of documents for relevance very quickly.
What steps should we be taking? How about that robot tax Bill Gates keeps harping on about?
Peter: Things like robot taxes and basic incomes, they tend to be raised by technologists often out of the states. It’s almost like the technologists can see what’s coming and they realise they’ve actually got to do something or suggest things to actually ameliorate the pain.
A robot tax sounds like a really clever idea, but the problem with a robot tax is that if Australia imposes tax on robots and China doesn’t, then China products become more competitive than Australian products, which means that Australian companies employ fewer people, because they’ve got to become more efficient to make money.
Tania: How do you define a robot anyway?
Peter: That’s exactly right, because a lot of the stuff we use now, if I use Siri on my phone, am I using a robot? Where does it stop? A robot doesn’t have to be something that walks around.
What else should we be doing?
Tania: We need to have these conversations so that we can bring everyone along with us and try not to leave people behind. Lots of people talk about universal basic incomes and things, I’m more in favour of looking at how we empower people community by community to support one another.
So, looking at more volunteering jobs, looking at people potentially being rewarded more for volunteering and empowering people in local communities to set up social franchises and social businesses that start solving their problems at a local level rather than relying on top-down government welfare.
The government is already completely stressed out. We’re not seeing any leadership really. We need to actually empower ordinary citizens to support one another to create programmes. We need to really get entrepreneurship front and centre in the community, so that everyone, not that everyone can be an entrepreneur, but that we really do nurture and support people to be entrepreneurs and to solve social problems.
Peter: The second area is we need a far more pragmatic educational system. At the moment there seems to be a separation between education on the one side and business on the other.
Too often in business the catchcry we hear is that when people come out of the educational system, they are not business ready. We’re not preparing our students to either be entrepreneurs or to readily be able to transition between careers.
About the author
Riordan is Techly’s News and Social Editor. He promises to tweet more at @riordanl
BY GAIA & ANDREW GRANT
We have noticed a growing trend in innovation. The ‘innovation race’ appears to be rapidly accelerating into an unknown future, and everyone wants to know ‘What’s next?’
Many of us are keen to hear market leaders share their predictions, hoping to pick up the latest trends and stay head of the curve. Yet the pace of change is now so fast that the future can be extremely challenging to predict.
As we heard the US chief advisor to Clinton and Obama Jeffrey Bleich explain recently, we are now the victims of ‘runaway technologies’.
‘Digital technology – while solving crucial problems – is creating or compounding others… Many of us feel that we’ve lost control over the pace of it all,’ Bleich has said, ‘The technology is driving itself.’
There has been an outbreak of public concern recently about the impacts of technological change on employment. Some research suggests that 40 percent or more of all jobs are highly vulnerable to automation and computerisation in coming decades (Frey and Osborne, 2013). Some observers even suggest that work can no longer be the primary means for people to support themselves – leading to all sorts of radical policy responses ranging from taxing robots (Delaney, 2017) to the provision of universal basic income to all people, working or not (Arthur, 2016).
Of course, this general fear of technological unemployment isn’t new. Since the industrial revolution, workers have quite understandably worried about what will happen to their jobs when machines can do their work faster, cheaper, or better. Previous periods of accelerating technological change were also associated with other waves of concern; even relatively recently, futurists were predicting that technology would make work largely obsolete (for example, Rifkin, 1995).
Conventional market-oriented economists downplay these concerns: the magical workings of supply and demand forces should ensure that any labour displaced by technology is automatically redeployed in other, more appropriate endeavours, and people will be better off in the long run. The focus of policy should be to facilitate that transition through retraining and mobility assistance, allowing displaced workers to move more easily into better, alternative occupations.
There are many reasons to question this optimistic theoretical perspective. But actual historical experience gives more cause to doubt ultra-pessimistic forecasts of technological unemployment. In practice, previous waves of technological change have not been associated with mass unemployment, for a range of reasons. The labour-displacing effects of new technology can be offset, in whole or in part, by other factors: including new work associated with the development, production, and operation of the new technology itself; new tasks that become conceivable only as a result of the new technology; historic reductions in average working hours (a trend which has unfortunately stalled under neoliberalism); and the capacity of active macroeconomic policy to boost aggregate labour demand when needed.
So even from a critical economic perspective, there is little reason to conclude that “work will disappear”. This does not mean we should be complacent about the problems and risks posed to workers by accelerating technological change.But it does mean our response to those challenges should be grounded in a more balanced and complete assessment of what technology actually does to work – and where technology comes from in the first place.
Remember, technology is not some exogenous, uncontrollable force. What we call “technology” is actually the composite of human knowledge about how to produce a broader range of goods and services, using better tools and techniques. Humans put their minds to solving certain problems (so-called “mission-based innovation”, as termed by Mazzucato, 2011), based on their particular concerns and interests. And therefore, technology is never neutral: the problems we turn our creative attention to, reflect the interests and influence of the constituencies which get to decide and fund innovation activity.
For example, one nefarious use of modern technology in workplaces is the ubiquitous and largely uncontrolled application of surveillance and performance-tracking technology by employers, to more immediately and completely monitor the work effort of their employees. Increasingly intrusive systems now give bosses minute-by-minute data on the whereabouts, productivity, and even attitudes of their workers. This has wide-ranging impacts not only on privacy and the quality of work. It even affects compensation: when it is so easy and cheap to monitor employees (and sack them if their performance is unsatisfactory), employers have less reason to offer workers positive incentives (or “carrots”) for performance and retention – and are more likely to use a disciplinary “stick” instead. It is no accident that surveillance and monitoring technology has advanced in leaps and bounds: employers have a strong vested interest in using these techniques to intensify work and enhance profit margins. Yet at the same time, easily-solvable monitoring problems – like ensuring that franchise businesses actually pay their employees minimum wages, for example, or are making their legally mandated superannuation contributions – are not addressed with technological solutions. Why not?
This non-neutrality of technology reflects the increasingly lopsided power imbalances in the modern labour market: those with power can influence the direction of technology in ways that reinforce their power. Another example is the one-sided application of digital platforms for assigning work and collecting payment used by “gig”-economy businesses like Uber and Deliveroo. Their technology has not (so far) actually changed the core nature of the work involved in these businesses: passengers are still driven about in a car, and take-away food is still delivered on a bicycle. What technology has facilitated, rather, are big changes in how work is hired, supervised, and compensated. By using digital applications (which they developed and own), platform businesses try to distance themselves from traditional employer functions and responsibilities (like paying minimum wages, or offering any stability or continuity of work). Technology thus allows businesses to shift risk to those performing the work, and minimise their labour costs. These changes in the social relations of workare by no means inevitable – as is being proven as workers around the world fight back against the most exploitive practices of these businesses. (Singapore’s approach was fairly effective in this regard: simply banning Uber from operating altogether). Resisting the mis-use of technology to cheapen and degrade work, is very different from a Luddite-like effort to try to stop technology itself.
Some jobs will certainly disappear as technology replaces some tasks (and employers use it to enhance their ability to control and parcel out work most profitably). Some new jobs will be created: including good ones (like the creative, knowledge-intensive ones developing and managing new technologies), and some less good ones (like the menial digital work associated with many technologies). Many jobs, perhaps counterintuitively, will hardly be affected at all: including a range of caring services, cleaning, hospitality, and other functions which seem to inherently require hands-on human labour.
To be sure, the quantity of work available is always a concern, all the more so given the stagnation (globally and in Australia) which continues to dominate the global economy since the GFC. Governments should put top priority on stimulating job-creation, wielding the whole array of policy tools (fiscal, monetary, industry, trade, skills, and more) at their disposal. Spurring stronger demand for labour will automatically ease adjustment to new technologies and their labour-displacing effects.
But the quality of jobs is an equal concern, and it is in this realm that the impacts of new technology may be most severe. The quality of new jobs created as technology advances, and the quality of existing jobs that are largely untouched by technology, must be targeted for forceful, ambitious policy attention, to arrest and reverse the widespread degradation of work which is being permitted by weak labour market conditions, technology, and the enhanced and largely unchallenged power of employers.
After all, a sustained structural shift in bargaining power in the labour market, in favour of employers, has been a central goal of neoliberal economic and social policy. There has been an expansion of non-standard employment in all its forms: irregular hours, casual work, labour hire positions, precarious forms of contracting and self-employment, and more. This precarity has been facilitated by a combination of persistently weak labour market conditions (compelling desperate workers to take any job no matter how insecure); technologies which make it easier for firms to orient staffing around precarious and on-call work; and regulatory inattention and complacency. On this last point, regulatory levers for protecting workers have not kept up with employers’ efforts to sidestep traditional minimum standards. Even the simplest of standards (like the minimum wage) are widely unenforced.
In short, to address the impacts of technology – and, more importantly, the one-sided application of technology within workplaces – we must modernise and revitalise the concept of a social contract. We need a social contract for the digital age, that re-establishes mutual responsibilities and expectations, that commits to improving both the quantity and quality of work as a central goal of policy, and that actively supports the countervailing forces (like unions, employment standards, and cultural expectations of fairness) that are essential to achieving more security and fairness in the world of work.
The values of NSW Labor provide a solid foundation from which to embark on such a revitalisation. The party’s vision emphasises that ‘prosperity starts with good jobs’ and commits that the ‘benefits of rising prosperity are shared fairly’; working towards such collective prosperity is a stated goal (NSW Labor, 2017). Key to this prosperity from a Labor viewpoint is support for more equal opportunities in the labour market and an effective system for regulating work. These values are constant and are not altered by technology or innovation: they apply whether citizens are engaged to work in full-time, “old economy” jobs or precarious “gigging” in the digital economy. A challenge is posed, though, by the rhetoric of innovation that leads the launch of a shiny new app to distract from the business models that underpin it – often based on underpaid, insecure, or invisible labour. What is needed then is clarity and purpose to create a system for regulating work that is modern, but fair.
Australian governments at all levels have been creative regulators of the labour market since Federation: think of the tax provisions implemented in the early years following federation. The Commonwealth government was constrained by the Labour power [Section 51 (xxxv)] of the Constitution, meaning that it could not intervene directly to set wages and conditions of work. However, it could impose taxes. The Excise Tariff Act 1906 passed by the Deakin government included a provision for manufacturers of agricultural machinery to be exempt from the excise if the workers in that company were paid a ‘fair and reasonable’ wage (Hamilton, 2011). The Harvester judgement that ensued is embedded in industrial relations folklore and has become synonymous with the establishment of minimum wages in Australia. However, what is often overlooked is that the mechanism used to establish this landmark was not a mechanism of traditional labour law – it was, after all, triggered by tax law.
Labor Governments have not been alone in this regulatory innovation to address labour policy concerns. The Howard Government was just as inventive and driven in its determination to use the Corporations power [Section 51 (xx)] of the Constitution to create a national regulatory framework that downgraded collective bargaining and instituted statutory individual contracts. A further legacy of that re-orientation was the whittling away of State industrial relations jurisdictions. This might lead to the conclusion that a State Labor government has little capacity to influence the wages and conditions of workers beyond the public sector. However, this conclusion is too narrow, and underestimates the extent to which creative, ambitious interventions at the state level could contribute to the restoration of a progressive social contract.
Consider, for example, the current Victorian government’s attempts to eradicate the exploitation of workers in industries like horticulture, through the introduction of a legislated licensing scheme for labour hire companies. This is illustrative of the potential for action by a State government to curb the exploitation of vulnerable workers. But legislation is not the only choice; there is a vast array of options on the regulatory spectrum.
Another means of regulating for better outcomes outside the confines of labour law is to support industry-specific multi-stakeholder collaboration. A developing example of this is the Cleaning Accountability Framework. CAF is an independent, multi-stakeholder initiative comprising representatives from across the cleaning supply chain – including institutional property investors, building owners, facility managers, cleaning companies, cleaners (through United Voice) and industry associations. CAF seeks to improve labour standards by encouraging transparency throughout the cleaning supply chain. CAF will recognise stakeholders who adopt better practice in the cleaning industry through a building certification scheme. In doing so, CAF will work to improve the employment conditions of cleaners, support sustainable business models and responsible contracting practices, help building owners and investors manage risk, and assist tenants in ensuring that they are benefiting from quality cleaning services. Multi-stakeholder initiatives have been criticised for lacking enforceability, but CAF overcomes this by using the structure of the supply chain, specifically the power of building owners and managers to drive compliance.
None of these examples are centred in the “gig economy,” nor do they address sectors immediately threatened by automation. But they nevertheless provide an insight into “‘outside the box” efforts to improve the quality and fairness of jobs. Similar ambition and creativity could provide a better regulatory environment for the conduct of all types of work – not least in the digitally enabled economy. This could begin with a comprehensive mapping of State-based regulation to identify potential opportunities to leverage existing laws, regulations, procurement policies and industry codes.
This would be an ambitious project, but given the extent of State influence in major areas of the economy (health, education, transport), it would provide a plethora of policy options.
Alternatively, if changes to work (whether wrought by technology or ‘innovation’ in business models) are left unquestioned, and if we assign the determination of working conditions to algorithms, then the aspirations encapsulated in “Labor values” will remain unrealised and, a chance to re-imagine a social contract based on decent work will be squandered.
Arthur, Don 2016, “Basic Income: A Radical Idea Enters the Mainstream,” Parliament of Australia, Research Paper Series 2016-17, November 18, http://www.aph.gov.au/About_Parliament/Parliamentary_Departments/Parliamentary_Library/pubs/rp/rp1617/BasicIncome.
Delaney, Kevin J 2017, “The robot that takes your job should pay taxes, says Bill Gates,” Quartz, February 17, https://qz.com/911968/bill-gates-the-robot-that-takes-your-job-should-pay-taxes/.
Frey, Carl Benedikt, and Michael A. Osborne 2013, The Future of Employment: How Susceptible are Jobs to Computerisation? (Oxford: Oxford Martin School).
Hamilton, R. S. 2011, Waltzing Matilda and the Sunshine Harvester Factory: The early history of the Arbitration Court, the Australian minimum wage, working hours and paid leave (Melbourne: Fair Work Australia).
Mazzucato, Mariana 2011, The Entrepreneurial State: Debunking Public vs. Private Sector Myths (London: Anthem).
NSW Labor 2017, “Our Values,” http://www.nswlabor.org.au/our_values.
Rifkin, Jeremy 1995, The End of Work: The Decline of the Global Labor Force and the Dawn of the Post-Market Era (New York: Putnam & Sons).
Sarah Kaine is an Associate Professor at the UTS Business School, and a member of the Advisory Committee of the Centre for Future Work. Jim Stanford is Economist and Director of the Centre for Future Work, part of the Australia Institute.
Australia should double its pace of artificial intelligence and robotics automation to reap a $2.2 trillion opportunity by 2030, while also urgently preparing to support more than 3 million workers whose jobs may be at risk, according to a new report.
If the rate of automation is doubled, it will take away on average four hours of work each week from Australian workers over the next 15 years, according to a report by economics and strategy consulting firm AlphaBeta.
“The reality is automation changes every job,” economist and director of AlphaBeta Andrew Charlton said.
“It’s not so much about what jobs we will do, but how will we do our jobs, because automation isn’t going to affect some workers, but … every worker.”
But the benefits will only flow into the national economy if workers are redeployed, not retrenched.
For most of Australia’s 12 million workers, it means their jobs will likely change rather than disappear. But about one third of the workforce, including construction workers and machine operators, spend an average 70 per cent of their time on automatable tasks. They may need to find new jobs.
“We [must] ensure that all of that time that is lost to machines from the Australian workplace is redeployed and people are found new jobs and new tasks,” Mr Charlton said.
“If those workers aren’t successfully transitioned, then you lose all the productivity gains. And you have all of the problems associated with long-term unemployment.”
Machines will make work ‘more human’
For the first time, AlphaBeta analysed how Australians spent a total of 20 billion work hours each year, assigning each of those hours to one of more than 2,000 different work tasks and then asking how a worker’s time on tasks could change over the next 15 years.
The tasks most likely to be automated are typically the most dangerous, least enjoyable and often lowest paid, the report says.
Giving them to robots or AI could lead to an 11 per cent fall in workplace injuries, a 20 per cent rise in wages for workers who are redeployed to non-automatable tasks, and an increase in job satisfaction for 62 per cent of low-skill workers as they focus on more creative and interpersonal activities.
“Machines will make human work more ‘human’,” the report says.
AI and robotics are “powerful tools that will change the way we work, take away some of the drudgery and give us the power to do new and exciting things in our work,” Mr Charlton said.
For example, a retail worker might spend nine hours less on physical and routine tasks like stocking shelves and processing goods at the checkout and nine hours more on tasks like helping customers to find what they want and providing them with advice. Teachers might spend less time entering exam scores and more time with students.
Australia lagging on AI and may miss opportunities: Charlton
But Australia could miss out on these opportunities because business is not embracing AI automation fast enough, according to the report, which was commissioned by Google.
“Right now, Australia is lagging,” Mr Charlton said. “One in 10 Australian companies is embracing automation and this is roughly half the rate of some of our global peers.
“It is perhaps the biggest economic opportunity that Australia has over the next 30 years. It is by far the largest source of productivity growth that we can realise.”
If Australian companies want to remain competitive internationally, they need to “double the rate at which [they’re] adopting these technologies and only by doing that will firms create jobs for the future and deliver us a dynamic economy that sustains the wages we want,” Mr Charlton said.
Even at the current rate of automation, the report projects that Australians will spend on average two hours per week more on interpersonal, creative and information synthesis tasks, and less time on routine administrative and manual tasks as they are automated.
For younger generations, the transition could be painful, with fewer entry-level jobs available to support study or launch a career.
“Automation and artificial intelligence take away those simple tasks that used to be done by the youngest and earliest career people in those jobs,” he said.
Re-skilling throughout life will be ‘the new normal’
Education and training courses also need to change to get ahead of technological transformation and ensure future workers have the right skills.
“There will be a whole range of new jobs that can absorb those people — much more intensive in interpersonal relationships or creative activities — and those are the areas where new jobs spring up for young people to take advantage of, if they have the skills and if we prepare them appropriately for that change.”
Australia needs a bold and proactive national policy to support workers most at risk, the report notes.
“Young, well-educated and highly skilled [workers] will likely adapt easily,” the report says. “Others, including low-skilled workers and those nearing retirement age, will likely struggle more” when trying to change jobs.
Adrian Turner, chief executive of CSIRO’s Data61, said it was “clear that jobs will require new skills”.
“The new normal will be for more regular re-skilling throughout our working lives,” he said.
‘Australia has a bad record’ at transitioning workers
Mr Charlton said the biggest challenge for Australia would be transitioning the workforce to face the new reality of automation.
“Over the last 25 years, one in 10 unskilled men who lost their job never worked again,” he said. “Today, four in 10 unskilled men don’t participate in the labour market.
“So [Australia] has a bad record at successfully transitioning workers out of industries in decline and into new roles and that’s the biggest threat — that we don’t effectively transition workers as these changes move through our economy.”
Mr Charlton told the ABC that both government and business had a vital role to play in the success of the future with automation.
“The role of companies is essential. Their workforces will change and they need to change in order for them to remain competitive and successful,” he said.
“But they also need to recognise the skills and experience of their existing workforce and build on those skills through better in-work training.
“The Government has a role as well in supporting people to have flexibility in their careers — to be on the move between roles and to give them information about new opportunities.”
Jim Stanford, director of the Centre for Future Work, believes benefits from artificial intelligence can only be realised if the impact on workers and communities is taken into consideration.
“If technology is designed and implemented unilaterally by private businesses, with no requirement on them to negotiate with workers and communities, meet minimum standards of behaviour, and even pay taxes, then it will undermine living standards of most people,” he said.
By Lin Evlin and Margot O’Neill – Vist the original article here