135. In 3 – No. 8 The key takeaways from our meeting with Daniel Susskind – author of “A World Without Work”

We have brigaded the numerous takeaways under 3 main headings:

  1. The Context


  • People need to take the threat seriously
  • People need to understand that their contribution to society will change

In 1950, machines could perform 100,000 (or 10⁵) computations per second; in 2000 that figure was 1,000,000,000,000.

And technology will only get more advanced.

Machines will takeover a lot of the routine (as opposed to the non-routine) tasks.

Modern Artificial Intelligence (AI) doesn’t try to copy or replicate rational human thinking as previously in the pure (1960s) models

  • The pragmatist approach is to allow machines to perform tasks in a different way – their own way by crunching loads of data
  • Result – more tasks are going to be in reach of machines
  1. The Threat

Look as what has already happened to the farming industry – far fewer labourers on farms. And medicine where machines are as good as or better than consultants diagnosing some ailments. Or legals where machines can do a lot of the stuff a just qualified lawyer can do and do it far, far more quickly.

AI presents frictional challenges. There are going to be a lot more mismatches of :

o   Skills – with hollowing out of those with ‘middling’ skills

o   Place – where you live matters more than ever

o   Identity – for example, (US) men are too proud and would rather not work than take up ‘pink-collar’ roles – roles where women predominate now

How developed is AI?

    • Beware of an army of ‘hedgehogs’ (those machines who know only one big thing -i.e. individual tasks only)
    • Foxes’ (machines who know many things) are not a short-term prospect
    • Entire jobs will not be eliminated
      • More gradual replacement of some tasks
      • 5% of jobs at risk
      • 60 % involve tasks, 30% can be automated

Will AI break through without understanding both rational & irrational (tacit)?

o   Human beings may struggle to articulate what we do

For example, a doctor diagnoses using intuition, judgement, etc – Machines can already do this just as well – yet people prefer real doctors!

There is both income inequality and labour inequality now – this is only going to get more exaggerated. (For example, the richest 0.1% of (US) people have the same collective wealth as the poorest 90%).

There are 2 sorts of capital that economists see:

  • Human Capital – our ability to earn an income from our education, skills and experience alone
  • Traditional Capital – our non-human capital that earns income (tangible and intangible)

As machines take over, the ability to earn a wage is going to diminish for a lot of people; and many do not have traditional capital to fall back on.

  1. The Response

So how can we all thrive in a world with less work? Daniel reminds us that technological progress could bring about unprecedented prosperity, solving one of mankind’s oldest problems: how to ensure everyone has enough to live on. The challenge will be to distribute this prosperity fairly, constrain the power of Big Tech, and provide meaning in a world where work is no longer the centre of our lives.

Daniel shows us the way by considering the following four areas:


  • How do we prepare our kids?
    • Educate in complementary skills
    • Graduate jobs involve less and less creative tasks
    • Encourage them to solve the problems they are interested in
  • What’s the safest job out there? Flip the question.

o   Entire jobs may not disappear as a job consists of many tasks

o   Individual tasks may disappear

o   So focus on solutions and working in different ways

Gear up the Big State

  • As the labour market will not provide a living wage for a lot of people, we need a new approach to the distribution of wealth – should we campaign for higher taxes for those with the top 0.01% income?
  • Big state needs to take a larger role
    • Taxation
    • Wealth funds taking ownership

Managing Big Tech

There is an issue of power the big boys (think Apple, Google, Microsoft, Amazon, Facebook) are already wielding:

o   Economic as currently

o   Political, more importantly going forward

Meaning and Purpose

It’s not just the economic/financial side

  • How do we deal with fewer of us finding meaning in work?

If work currently has minimal meaning and purpose then:

  • Work is only a means to an end
  • Some might actually enjoy idleness
  • The 2020 Pandemic was a bit of a dry run and showed us
    • what enforced idleness feels like
    • gainful unemployment
  • Two tier society?

o   More extreme than now

o   Social solidarity

  • Pulling your income earning weight
  • Non-economic contribution
    • Conditional basic income
    • 15m (50% of employees) volunteer
    • Seen by others to be contributing
  • How can we best embrace AI?

o   Blank sheet of paper

§  Solve problems fundamentally differently

§  Agnostic about how

o   Be positive – we are not talking about a jobless future

What should business leaders do now?

  • Train for skills mismatch for non-routine tasks to
      • Complement AI
      • Build AI
  • Mindset needs to be open, optimistic, flexible and fluid
  • We need to transform how we solve problems
    • Different people, different skills
    • Exciting prospect
    • Transforms how roles are done


The key takeaway is that machines are going to do far more than they do now and for some there is not going to be the work for them. So the current distribution of income model which is mainly predicated on a wage for work done is no longer fit for purpose. It is not doom and gloom – we need to be positive and prepare the next generation for what we can see is coming.

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Posted in In Three, Digital/Systems, People and Leadership.