How artificial intelligence can define not destroy the future of work

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Work is a defining feature of our civilisation. We spend more time in our jobs than any other activity and the spoils of our labour provide us the means to survive. It gives identity, status and purpose.

So we can be forgiven if we get nervous when our jobs are threatened. And there has never been a clearer threat than increasing automation through robotics and AI.

I am of the camp that ultimately, in about 15 years, we will all be far better off, our notion of work evolved and with it our lives. Yet the transition up to that point is going to be very harsh for most, leaving plenty of scars of inequality and alienation on our society.

Talk of universal basic income, the taxation of robot output and a demotion of human capital to that of mere data suppliers is real. How our innovators introduce the coming disruption will shape its impact. How we manage this transition as a people will define us all.

Where AI is better than us

Eventually everything given enough progress and time.

But in the nearer term computers surpass us in tasks involving collecting information, structuring and digesting huge amounts of it quickly, understanding the correlations within, surfacing probabilities and optimising for results.

Jobs most vulnerable are ones where the information analysis above is done repeatedly and with little variation. Lawyers drafting contracts, accountants doing tax returns, travel agents planning holidays, IT staff running security checks, marketers buying ad spots, radiologists examining X-rays, journalists reporting news, etc.

Humans won’t be able to compete with the speed, efficiency and scale at which their computer counterparts will deliver.

Robots have already proven themselves masters of the assembly line and will continue to move up the chain yet at a slower pace than their pure-software brethren.

Jobs at risk range from monitoring power lines, securing borders, farming crops, mining, driving taxis, trucking or shipping goods, etc. Autonomous drones and vehicles will win us over with pinpoint accuracy, 24/7 reliability, enhanced functionality and safety.

Underlying it all is cost. Automated systems, whether hardware or software, will just beat humans to the bottom line to the point where including a person would be equivalent to holding on to your telephone operator to direct your phone calls.

Where we are better than AI

Areas that are highly complex for AI and robotics to gain a medium term edge on revolve around unique human-to-human interactions.

Things like knowing when not to speak, listening with empathy, exchanging a look or a smile or delivering a well-executed joke.

These strengths and the freeing up of labour from other industries could result in economies shifting greater monetary value to historically undervalued work, such as social services, aged care, volunteering and child development – relative to the value it brings to society, and which cannot be easily automated.

I’m not suggesting that stockbrokers need to transition to caring for the elderly, but within each job there is a humanistic element that will increase in importance relative to the pure production role that can be automated.

Education’s role in a successful transition

Cookie-cutter learning is automation. If students are to find new roles in the workforce of the future they must be nurtured to individualise their skill sets and importantly develop a framework of continued learning throughout their lives.

Fortunately the same technology that brings us personalised recommendations on Netflix and Amazon is finding its way into education. Crafting a unique journey for each student, chaperoned by a combination of teachers and machine learning designed to surface relevant content and topics to explore.

To view the growing trend of youths switching jobs as being fickle is a mistake. Properly executed and in partnership with ongoing education throughout working life it is the agility necessary to compete in the rapidly evolving world they are inheriting.

Fluid labor movement via new platforms

There is a role for a more sophisticated employment platform that better matches increasingly diversified candidates with jobs.

Lifelong careers in one role could become a thing of the past. Work might shift to specific tasks and projects where the best individual for the job can be sourced quickly and efficiently.

We are seeing the initial signs of a shift to more project-based work with the gig economy; with on-demand workforce such as Uber.

Yet while they carry a negative connotation as low-skilled and low-paid a similar framework could be successfully applied to highly skilled tasks.

Doctors are already being decentralised away from a day in the clinic to telemedicine and pro-active mobile health that has no geographic boundary.

An American specialist in gut health could spend the morning at home treating patients in Cape Town, be pulled in to consult on an Australian government microbiome initiative in the afternoon and finish her day working with Nestle on a healthy alternative to chocolate.

A fluid labour force need not translate to volatile work or uncertainty when your next pay cheque will arrive. Downtimes can be matched with short periods of education to keep increasing our value in the labour market.

Similar platforms can improve supply and demand between organisations too. Matching clients with vendors and eliminating the wastage they spend seeking out, piloting and contracting suppliers or buyers.

With respect to powering such platforms, machines could have an enabling impact on our labour market rather than a detrimental one.

Enhancing ourselves with technology

It would be remiss not to mention upgrading our human capabilities directly with future technology to keep up with the pace of advancements.

A wealth of research and development has been taking place from memory enhancement to brain internet connectivity and DNA manipulation.

In a way we are already merging with our technology, with our smartphones like appendages and VR headsets transporting us into digital worlds.

Yet legislators and the public have little understanding of the nascent technology and for now it remains on the outskirts of regulation or public guidance.

Without the right frameworks, leaving human enhancement up to the market will surely be the quickest way to widen the gap between the haves and the have nots.

Rapid progress is coming and we must not underestimate its scale and impact. As we enter unfamiliar territory we retain the power to shape the opportunities and mitigate the pitfalls ahead.


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