Cre­ative de­struc­tion at work

Financial Mirror (Cyprus) - - FRONT PAGE -

Through­out his­tory, tech­no­log­i­cal progress has cre­ated enor­mous wealth but also caused great dis­rup­tion. The United States’ steel in­dus­try, for ex­am­ple, un­der­went a ma­jor trans­for­ma­tion in the 1960s, when large, in­te­grated steel mills were grad­u­ally put out of busi­ness by mini mills, de­stroy­ing the ex­ist­ing eco­nomic base of cities like Pitts­burgh, Penn­syl­va­nia, and Youngstown, Ohio. The mini mills, how­ever, vastly in­creased pro­duc­tiv­ity, and cre­ated new types of work else­where.

The story of US steel il­lus­trates an im­por­tant les­son about what the econ­o­mist Joseph Schum­peter called “cre­ative de­struc­tion”: Long-run eco­nomic growth in­volves more than just in­creas­ing out­put in ex­ist­ing fac­to­ries; it is also im­plies struc­tural changes in em­ploy­ment.

We can ob­serve a sim­i­lar phe­nom­e­non in the cur­rent in­for­ma­tion and com­mu­ni­ca­tions tech­nol­ogy (ICT) revo­lu­tion, which has af­fected most ar­eas of the mod­ern workplace, even those not di­rectly as­so­ci­ated with com­puter pro­gram­ming or soft­ware en­gi­neer­ing. Com­puter tech­nolo­gies have cre­ated pros­per­ous new businesses (even busi­ness clus­ters) while mak­ing cer­tain man­u­fac­tur­ing work­ers re­dun­dant and send­ing older man­u­fac­tur­ing cities into de­cline.

But the likes of Detroit, Lille, or Leeds have not suf­fered be­cause of fall­ing man­u­fac­tur­ing out­put; on the con­trary, out­put has been grow­ing in these cities over the past decade. In­stead, their de­cline stems di­rectly from their fail­ure to at­tract dif­fer­ent types of jobs. To a large ex­tent, this is a fail­ure of pol­icy. Rather than try­ing to pre­serve the past by prop­ping up old in­dus­tries, of­fi­cials should fo­cus on man­ag­ing the tran­si­tion to new forms of work. This re­quires a bet­ter un­der­stand­ing of emerg­ing tech­nolo­gies, and how they dif­fer from those that they are sup­plant­ing.

An im­por­tant fea­ture of the In­dus­trial Revo­lu­tion’s early man­u­fac­tur­ing tech­nolo­gies was that they re­placed rel­a­tively skilled ar­ti­sans, which in turn in­creased de­mand for un­skilled fac­tory work­ers. Sim­i­larly, Henry Ford’s as­sem­bly line for man­u­fac­tur­ing cars – in­tro­duced in 1913 – was specif­i­cally de­signed for un­skilled work­ers to op­er­ate ma­chin­ery, thereby al­low­ing the com­pany to pro­duce its pop­u­lar Model T – the first car that mid­dle-class Amer­i­cans could af­ford.

In­deed, much of the story of in­dus­trial de­vel­op­ment over the last century can be seen in terms of com­pe­ti­tion be­tween an in­creas­ingly ed­u­cated work­force and new tech­nol­ogy that would dis­pense with their skills. We have al­ready seen the im­pact – not least in the car in­dus­try – of ro­bots that can carry out the rou­tine jobs that were once per­formed by thou­sands of mid­dle-in­come as­sem­bly-line work­ers.

Even greater workplace dis­rup­tion lies ahead. Though his­tory coun­sels cau­tion in pre­dict­ing how tech­no­log­i­cal progress will play out, we al­ready have a rea­son­able idea of what com­put­ers will be able to do in the near fu­ture, be­cause the tech­nolo­gies are al­ready be­ing de­vel­oped. We know, for ex­am­ple, that a wide range of skilled pro­fes­sions can be sim­pli­fied with the help of “big data” and so­phis­ti­cated al­go­rithms.

One fre­quently cited ex­am­ple of this process is the Sy­man­tec Clear­well eDis­cov­ery plat­form, which uses lan­guage anal­y­sis to iden­tify gen­eral con­cepts in documents, and boasts of an­a­lyz­ing and sort­ing more than 570,000 documents in just two days. Clear­well is trans­form­ing the le­gal pro­fes­sion by us­ing com­put­ers to as­sist in pre-trial re­search and per­form tasks nor­mally un­der­taken by par­ale­gals – and even by con­tract or patent lawyers.

In the same way, im­proved sen­sory tech­nol­ogy means that many trans­porta­tion and lo­gis­tics jobs will soon be fully au­to­mated. And it is not far-fetched to imag­ine the likes of Google’s self-driv­ing cars mak­ing bus and taxi driv­ers re­dun­dant one day. Even hitherto se­cure, low-skilled ser­vice oc­cu­pa­tions may not es­cape au­to­ma­tion. De­mand for per­sonal and house­hold ser­vice ro­bots, for ex­am­ple, is al­ready grow­ing by about 20% an­nu­ally.

La­bor mar­kets may once again be en­ter­ing a new era of tech­no­log­i­cal tur­bu­lence and widen­ing wage in­equal­ity. And this high­lights a larger ques­tion: Where will new types of work be cre­ated? There are al­ready signs of what the fu­ture holds. Tech­no­log­i­cal progress is gen­er­at­ing de­mand for big data ar­chi­tects and an­a­lysts, cloud ser­vices spe­cial­ists, soft­ware de­vel­op­ers, and dig­i­tal mar­ket­ing pro­fes­sion­als – oc­cu­pa­tions that barely ex­isted just five years ago.

Fin­land of­fers valu­able lessons in how cities and coun­tries should adapt to these de­vel­op­ments. Its econ­omy ini­tially suf­fered from the fail­ure of its big­gest com­pany, Nokia, to adapt to smart­phone tech­nolo­gies. Yet sev­eral Fin­nish star­tups have since built new en­ter­prises on smart­phone plat­forms.

In­deed, by 2011, for­mer Nokia staff had cre­ated 220 such businesses, and Rovio, which has sold more than 12 mil­lion copies of its smart­phone-based video game, “An­gry Birds,” is crowded with for­mer Nokia em­ploy­ees.

This trans­for­ma­tion is no co­in­ci­dence. Fin­land’s in­ten­sive in­vest­ment in ed­u­ca­tion has cre­ated a re­silient la­bor force. By in­vest­ing in trans­fer­able skills that are not limited to spe­cific businesses or in­dus­tries, or sus­cep­ti­ble to com­put­er­i­za­tion, Fin­land has pro­vided a blue­print for how to adapt to tech­no­log­i­cal up­heaval.

De­spite the dif­fu­sion of big-data-driven tech­nolo­gies, re­search sug­gests that la­bor will con­tinue to have a com­par­a­tive ad­van­tage in so­cial in­tel­li­gence and cre­ativ­ity. Govern­ment de­vel­op­ment strate­gies should there­fore fo­cus on en­hanc­ing these skills, so that they com­ple­ment, rather than com­pete with, com­puter tech­nolo­gies.

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