A World Without Work: Difference between revisions

[[File:Dole-queue.jpg|450px|thumb|center|Passtimes of the future, as imagined by {{author|Daniel Susskind}}]]}}

Dr. Susskind, scion of the storied futurology dynasty, will doubtless find enough [[general counsel]] anxious to be seen at the technological vanguard — and interested mugs like me, who are suckers for sci-fi alternative histories — to recoup his advance, but {{br|A World Without Work}} will not signpost much less dent the  immutable trajectory of modern employment, misunderstanding as it does how humans, organisations or economies work, while ignoring — neigh, ''contradicting'' — the whole history of technology, from the plough. An excellent counterpoint, though equally flawed in other ways, is the late {{author|David Graeber}}’s highly provocative {{Br|Bullshit Jobs: A Theory}}, which has a far more realistic, if no less glum, prognosis: soul-destroying jobs aren’t going away: they are only going to be more and more of them. This feels more plausible to me.

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 them (for the former) and effectively manage them (for the latter).  

Nothing that the information revolution has yet thrown up suggests any of that has changed. The more [[technology]] is deployed, the more the fog of confusion and [[complexity]] — as in [[complexity theory]], and not just [[complicated]]ness — engulfs us.  

Hand-waving about [[Chess]] and [[Go]]-playing supercomputers — there is a lot of that in {{br|A World Without Work}} — does not change anything. In the world of [[systems analysis]], [[Chess]] and [[Go]] are [[complicated]], not [[complex]], problems. Both are hermetically and — ahh — ''[[hermeneutics|hermeneutically]]'' sealed zero-sum games on small, finite boards with simple sets of unvarying rules between two players sharing a common and static objective. Their risk payoff is normal, not exponential. They can, in theory, be “brute force” managed by skilled operation of an [[algorithm]], and the consequences of failure are predictable and contained — you lose.

Gameplay is entirely deterministic: you can see that, at the limit, the player with the better number-crunching power ''must'' win. Even here, the natural imagination of human players, otherwise at a colossal disadvantage from an information processing perspective, makes beating them surprisingly hard.  

This ought to be the lesson: even for thoroughly simplistic binary games, it takes a ton of dumb processing power to beat a puny imagineer.  

But somehow, Susskind reads it instead as a signpost to the [[Apocalypse]].

Life is ''not'' a two-person board-game on a small-board with fixed rules and a static, common, zero-sum objective. Not even at university. Life is complex.  ''[[Complex]]'' problems — those one finds at the frontier, when one has boldly gone somewhere no-one has gone before, in dynamic systems, where information is not perfect, where risk outcomes are [[convexity|convex]] — so-called “[[wicked environment]]s” — are not like problems in [[Chess]].<ref>There is more on this topic at [[complex systems]].</ref> Here [[algorithm]]s are no good. One needs experience, wisdom and judgment. ''[[Algorithm]]s get in the way''.

By design, computers can only follow rules. A machine that could not process instructions with absolute fidelity would be a ''bad'' computer. ''Good'' computers cannot think, they cannot imagine, they cannot handle ambiguity — if they 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.<ref>See: [[Code and language - technology article|Code and language]].</ref> Machines are linguistically, structurally ''incapable'' of interpreting, let alone ''coining'' [[metaphor|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  — and conceptually there is no reason a machine ''couldn’t'', but that’s just not how modern computers have been designed — they can only aid, and in most circumstances, ''complicate'', the already over-complicated networks we all inhabit.  

But, but, but — how can we explain this seemingly relentless encroachment of the dumb algorithm on the inviolable province of consciousness?  What will be left for us to do? Well, there’s an alternative explanation, and it’s a bit more prosaic: it is not so much that [[AI]] is breaching the mystical ramparts of consciousness, but that much of what we ''thought'' required the ineffable, ''doesn’t''. Much of what we thought was “human magic” turned out to be just, in Arthur C. Clarke’s worlds, “sufficiently advanced technology”.   

And even this is before considering the purblind, irrational sociology that propels all organisations, because it propels all ''individuals'' in those organisations. Like the academy in which {{author|Daniel Susskind}}’s millenarianism thrives, computers work best in a theoretical, [[Platonic form|Platonic]] universe, governed by unchanging and unambiguous physical rules, and populated by rational agents. In that world, Susskind ''might'' have a point — though even there, I doubt it.  

But in the conflicted, dirty, unpredictable, [[complex]] 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 coupling|tightly-coupled]] complexity of our networks doesn’t [[Lentil convexity|wipe us out first]].

Susskind’s conception of “work” as a succession of definable, atomisable and impliedly dull tasks — a framework, of course, which suits it perfectly to adaptation by machine — is a kind of Taylorism. It is a common view in management layers of the corporate world, of course — we might almost call it a [[dogma]] — but that hardly makes a case for it.  

The better response is to recognise that definable, atomisable and dull tasks do not define what ''is'' employment, but what it should ''not'' be. The [[JC]]’s [[third law of worker entropy]] is exactly that: [[tedium]] is as sure a sign of [[waste]] in an organisation.  If your workers are bored, you have a problem. If they’re boring ''each other'',<ref>Hello, financial services!</ref> then it’s an exponential problem.

{{ref}}