A World Without Work
In which Daniel Susskind grasps a flagon of Ray Kurzweil’s home-made Kool-Aid and bets the farm.
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A World Without Work: Technology, Automation, and How We Should Respond, by Daniel Susskind 
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Help, help, we’re all going to die
Susskind will doubtless find enough gullible general counsel, anxious to seem at the technological vanguard — and interested mugs like me, who are suckers for sci fi alternative histories — at least to recoup his advance but, like the consistent output of his father over the last three decades, A World Without Work will not signpost, let alone dent, the immutable trajectory of modern employment, failing as it does to understand how humans, organisations and economies work, while ignoring — neigh, contradicting — the whole history of technology, from the plough.
Technology has never destroyed overall labour, and Susskind gives no good grounds for believing it will suddenly start now.
No innovation since the wheel has failed to create unexpected diversity, or opportunity — that’s more or less the definition of “innovation” — or more subsidiary complexity & inefficiency as a by-product. Both the opportunities and the inefficiencies “need” human midwifery, to exploit (for the former) and effectively manage (for the latter).
Nothing that the information revolution has yet thrown up suggests any of that has changed. There more technology is deployed, the more fog of confusion and complexity engulfs us.
But chess-playing supercomputers
Hand-waving about chess and go-playing supercomputers — there is a lot of that in A World Without Work — does not advance the argument. Both are hermetically sealed games on small, finite boards with simple sets of unvarying rules between two players sharing a common objective. Outcomes are entirely deterministic, and you can see that, at the limit, the player with the superior number-crunching power must win. Even here the natural imagination of human players, otherwise at a colossal disadvantage from an information processing perspective, made the job of beating them surprisingly hard. This ought to be the lesson: even in thoroughly simplistic binary games, it takes a ton of dumb processing power to beat a puny imagineer. Instead, Susskind reads this as a signpost to the apocalypse.
But life is not a two-person board-game on a small-board with fixed rules a static, common, zero-sum objective. Analogising from this — ironically, something a computer could not do — is not great police-work.
Computers can’t solve novel problems
By design, computers can only follow rules. One which could not be relied on to process instructions with absolute fidelity would be a bad computer. Good computers cannot think, they cannot imagine, they cannot handle ambiguity — if they even have a “mental life”, it exists in a flat space with no future or past. Computer language, by design, has no tense. It is not a symbolic structure, in that its vocabulary does not represent anything.[1] Machines are linguistically, structurally incapable of interpreting, let alone coining metaphors, and they cannot reason by analogy or manage any of the innate ambiguities that comprise human decision-making.
Until they can do these things, they can only aid — in most circumstances, complicate — the already over-complicated networks we all inhabit. and this is before one considers the purblind, irrational sociology that propels most organisations, because it propels individuals in those organisations. Like the academy, in which Daniel Susskind’s millenarianism thrives, computers function best in a theoretical, platonic universe governed by unchanging and unambiguous physical rules, and populated by rational agents. In that world, Susskind might have as point, but even there I doubt it.
But in the conflicted, dirty, unpredictable universe we find ourselves in out here in TV land, there will continue to be plenty of work, as there always has been, administrating, governing, auditing, advising, rent-seeking — not to mention speculating and bullshitting about the former — as long as the computer-enhanced tight-coupled complexity of our networks doesn't wipe us out first.
See also
References
- ↑ See: Code and language.