#FutureWorks2016 - Digital Technology, Productivity and Skills

Tom Standage, the Economist's Technology and Deputy Editor presented his ideas on the most critical technologies impacting the future of work and with the potential to increase productivity.

 History suggests that increasing use of technology increases the number of jobs.  When we have lots of delivery drones flying or self driving themselves around these will take delivery jobs away.  Eg Uber are open about their current drivers only being a short-term strategy and have hired the robotics department of Carnegie Mellon University to design their own driverless cars.

However will create new jobs elsewhere.  Eg we won't order a coffee delivery from the local coffee shop because today the delivery will cost more than the coffee.  But what about if in the future the delivery costs 10p rather than £2?

We discussed the well known research suggesting 47% of US jobs are going to disappear.  Stefano Scarpetta from the OECD suggested the true figure for these is likely to be closer to 10% than 50%.  But there is a further 20% of jobs where 50% of the work could be done by machines.  So the jobs will still exist but the work they perform will change significantly.

Tom suggested that the authors of the well known research deny they ever suggested that 47% of jobs will be automated, simply that technology will make it possible to automate them (see tomorrow's Economist for more on this).


All of this is having impacts on organisations and workers.  The shape of companies is changing - how many people do Uber employ?  And risks are being pushed back onto individuals.

Eg individual people need to keep their own skills up to date.  Evidence suggests they're not currently doing this.  50% of the workforce has little or no technology skills and even 25% of people entering the workforce today have little or no technology skills.

This is partlicularly important as learnability becomes more important than hard skills (the suggestion of Jonas Prising, CEO at Manpower).

Some people value this independent lifestyle but many people don't.  How do we help them make the necessary shift in thinking?

The change also implies that our labour legislation and tax systems which today tend to treat independent workers like second class citizens will need to change.  Independent workers are not subject to this and hence not protected from unemployment or the risk of an accident etc.

We also discussed the potential of moving to some form of universal income, particularly if productivity does start to go up because more work is being done by machines (a good problem to have!).  There are some fundamental problems with this eg if everyone in the UK received £5k it would mean pensioners get a lot less, but the rich would receive more which they wouldn't notice.  See also the Economist's recent article on this.

However the current way of redistributing wealth clearly isn't working either.  A suggestion was made that social protection needs to follow the worker rather than the employer.  Eg for unemployment benefit to depend more on the type and activity which is performed rather than the form of the contract between worker and organisation.


Organisations also need to change the way we manage people to respond to this agenda.  Eg Jean Oelwang from Virgin Unite talked about the role of purpose to provide people meaning and reduce a culture of fear prevalent in too many workplaces.

Diane Gherson, CHRO at IBM talked about diversity - celebrating everyone as a human being and celebrating their differences.  IBM uses one on one feedback tool to review each other eg at the end of a meeting.

Employers also need to get better at using the skills of their people.  This is partly about investing in learning but also needs them to recognise the skills which people have.  And how they can motivate people when it sounds a bit like going back to school for ever.

Technology can help with this too, eg Diane described four example of AI in IBM to help with managing their workforce:

• Job matching, helping people find non-obvious jobs they could do
• Predictive analytics on who is likely to leave (saving IBM $330m in replacement costs)
•  Propensity to learn ie who is likely to benefit most if upskilled
• A 'Netflix for learning' providing personalised learning - what development people may want depending on what they've done before, their career trajectory and how they like to learn.