Mak­ing the fu­ture work for us

Financial Mirror (Cyprus) - - FRONT PAGE -

What does the fu­ture of work hold in store, and how should we pre­pare for it? The de­bate so far has fo­cused on de­vel­oped coun­tries, but it is a ques­tion that will af­fect the en­tire world.

To pes­simists, the in­tro­duc­tion of these so-called gen­eral-pur­pose tech­nolo­gies – in­clud­ing 3-D print­ing, ar­ti­fi­cial in­tel­li­gence, and the In­ter­net of Things – threat­ens the de­mand for labour; with­out new forms of so­cial sol­i­dar­ity, such as a univer­sal ba­sic in­come, the fu­ture will be one of wide­spread destitution. To op­ti­mists, the lat­est tech­no­log­i­cal de­vel­op­ments, like oth­ers that have pro­pelled hu­man­ity for­ward, prom­ise to de­liver un­prece­dented lev­els of pros­per­ity.

It is prob­a­bly im­pos­si­ble at this stage to say which side is right. As the physi­cist Niels Bohr said: “It is very hard to pre­dict, es­pe­cially the fu­ture.” For a com­plex sys­tem such as the world econ­omy, un­der­stand­ing the past – for ex­am­ple, the mas­sive de­cline in man­u­fac­tur­ing em­ploy­ment in al­most all coun­tries over the past two decades – is al­ready hard enough. What is more eas­ily as­cer­tained are the causal links that might de­ter­mine the out­come.

Rapid dis­place­ment of mas­sive amounts of hu­man labour is not a new oc­cur­rence. The early-nine­teenth-cen­tury Lud­dites re­volted against the me­chan­i­cal looms that were sup­plant­ing ar­ti­sanal tex­tile pro­duc­tion. Al­most 60 years later, agri­cul­tural em­ploy­ment in the US peaked at 53% of to­tal em­ploy­ment. Today, it is less than 3%.

In fact, since as re­cently as 1980, most coun­tries have ex­pe­ri­enced large de­clines in agri­cul­tural em­ploy­ment. In some, like Por­tu­gal, Malaysia, Tur­key and In­done­sia, the share of agri­cul­tural em­ploy­ment de­clined by more than 20%. In oth­ers, like Greece, Italy, Bul­garia, Hun­gary, Es­to­nia, Poland, Malaysia, Philip­pines and Sri Lanka, the de­cline ex­ceeded 10%.

And it’s not just agri­cul­ture. Ac­cord­ing to the World Bank’s World De­vel­op­ment Indi­ca­tors, the share of man­u­fac­tur­ing in GDP fell in 100 of the 124 coun­tries re­port­ing data since 1990.

But if large shifts in the com­po­si­tion of em­ploy­ment have been the norm, what makes today’s tech­nol­ogy-driven shifts so scary?

Fun­da­men­tally, tech­nol­ogy is a way to trans­form “the world as I found it” into “the world as I want it to be” – from pas­tures to milk, from soy­beans to chicken ten­ders, from sil­i­con to smart­phones. And it de­pends on three forms of knowl­edge: em­bed­ded knowl­edge in tools; cod­i­fied knowl­edge in recipes, man­u­als and pro­to­cols; and tacit knowl­edge, or knowhow, in brains.

Most of the time, these three forms of knowl­edge com­ple­ment one an­other: like cof­fee and su­gar, the more of one you have, the more of the oth­ers you want. But tech­no­log­i­cal progress oc­ca­sion­ally sub­sti­tutes one for an­other, as with cof­fee and tea. Once upon a time, peo­ple stuck their hands in the ground to plant the next crop. Now, seed drills and planters do that much more quickly and ef­fort­lessly. Not long ago, air­line check-in clerks wrote out board­ing passes. Now they are de­liv­ered to our smart­phones. It is these sub­sti­tu­tions – the em­bod­ied knowl­edge of the ma­chine for the knowhow of tra­di­tional hand­i­work – that make us fear­ful.

But while each new tech­nol­ogy dis­places one form of knowhow, it cre­ates oth­ers. The first in­dus­trial rev­o­lu­tion so re­duced the cost of tex­tiles that it led to a boom in de­mand, pro­duc­tion and em­ploy­ment. Like­wise, as David Au­tor of MIT has pointed out, the au­to­matic teller ma­chine (ATM) dis­placed hu­man bank tell­ers, but so re­duced the cost of branches that their num­ber rose, fu­elling an in­crease in em­ploy­ees fo­cused on cus­tomer re­la­tion­ship man­age­ment (for which ATMs are less than ideal). Today, web­sites have dis­placed printed ma­te­ri­als, giv­ing rise to an in­dus­try of web de­sign­ers.

But while it is clear which jobs new tech­nolo­gies dis­place, it is harder to an­tic­i­pate how the new pos­si­bil­i­ties will be ex­ploited. Back in 2001, many thought the In­ter­net’s fiber-op­tic back­bone had been over­built, given low de­mand for band­width. But then along came iTunes, YouTube, Face­book, Twit­ter, Skype and Net­flix. Sim­i­larly, today we are try­ing to pre­dict the na­ture of fu­ture work be­fore the jobs of the fu­ture have been in­vented.

The most im­por­tant un­cer­tain as­pect of the new tech­nolo­gies is their dif­fu­sion ca­pac­ity. If they do not dif­fuse world­wide, they will widen the in­come di­vide be­tween coun­tries and re­gions. Land­line tele­phone ser­vice and elec­tric­ity have dif­fused far less than guns and cell­phones.

One de­ter­mi­nant of a tech­nol­ogy’s “dif­fus­abil­ity” is its knowhow in­ten­sity. Tools and codes are easy to ship; mov­ing the knowhow needed to use them is a dif­fer­ent mat­ter. Guns re­quire just a lit­tle train­ing to op­er­ate, whereas an elec­tri­cal util­ity re­quires a large team of peo­ple with var­ied ex­per­tise to run the gen­er­a­tors, in­stall and ser­vice the trans­mis­sion lines and sub-sta­tions, limit theft, and com­pel cus­tomers to pay their bills on time. Tech­nolo­gies that re­quire more di­verse knowhow, re­flected in the size and het­ero­gene­ity of the team needed to im­ple­ment them, dif­fuse much more slowly or not at all.

A new tech­nol­ogy’s dif­fu­sion is also af­fected by its de­pen­dence on the previous dif­fu­sion of other tech­nolo­gies. Uber de­pends on the previous dif­fu­sion of cell phones, cars, and credit cards. If im­ple­ment­ing a tech­nol­ogy re­quires less knowhow and fewer other tech­nolo­gies, it is likely to dif­fuse even faster than the tech­nolo­gies it re­places.

This is what peo­ple call tech­no­log­i­cal leapfrog­ging. As was the case with com­put­eraided de­sign and man­u­fac­tur­ing, it is eas­ier to run a 3-D printer than to mas­ter all the steps needed to make the same part the tra­di­tional way.

Ar­ti­fi­cial in­tel­li­gence may make tech­nol­ogy less re­liant on knowhow and con­se­quently eas­ier to dif­fuse. By con­trast, the In­ter­net of Things will prob­a­bly re­quire prior dif­fu­sion of many other tech­nolo­gies. In 66 coun­tries, elec­tric­ity pen­e­tra­tion is less than 60%; in 26 coun­tries, it is less than 30%.

Fi­nally, dif­fu­sion de­pends on whether coun­tries can af­ford to pur­chase the new tech­nol­ogy. And that, in turn, de­pends on whether it fa­cil­i­tates or com­pli­cates their search for goods and ser­vices that they can sell in­ter­na­tion­ally. The glob­al­i­sa­tion of value chains has made it eas­ier for more coun­tries and re­gions to par­tic­i­pate in in­ter­na­tional trade, be­cause each coun­try needs to as­sem­ble less com­plex teams; but it has been bad for places like Detroit, where fully in­te­grated in­dus­tries used to clus­ter.

In the end, pre­dict­ing the fu­ture is be­side the point. Most coun­tries’ fu­ture is more likely to be bright if they fo­cus on en­sur­ing that they can mas­ter ev­ery new tech­nol­ogy and ex­ploit ev­ery new op­por­tu­nity that comes their way.

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