Pow­er­ing growth and Op­por­tu­ni­ties in con­tainer ship­ping

Dig­i­tal­i­sa­tion in ship­ping and lo­gis­tics is rid­ing on dis­rup­tive tech­nolo­gies such as Block Chain and Ar­ti­fi­cial In­tel­li­gence that have the power to mas­sively im­prove our ca­pa­bil­ity to de­liver goods and ser­vices

Maritime Gateway - - Contents - Inna Kuznetsova, Pres­i­dent and COO Peter Spellman, Chief Tech­nol­ogy Of­fi­cer Karim Jumma, In­terim Head of Prod­uct Man­age­ment and Vice Pres­i­dent, for New Prod­ucts De­vel­op­ment, INTTRA

Dig­i­tal­i­sa­tion in ship­ping and lo­gis­tics is rid­ing on dis­rup­tive tech­nolo­gies such as Block Chain and Ar­ti­fi­cial In­tel­li­gence that have the power to im­prove our ca­pa­bil­ity to de­liver goods and ser­vices.

Dig­i­tal­iza­tion is im­pact­ing ev­ery in­dus­try and ocean con­tainer ship­ping is no dif­fer­ent. The lat­est trends have or­ga­ni­za­tions fo­cus­ing on smart, tech­nol­ogy-driven man­age­ment to re­duce ex­penses and in­crease ef­fi­ciency. Ar­ti­fi­cial In­tel­li­gence (AI), Ma­chine Learn­ing (ML), IOT and blockchain are the most talked about trans­for­ma­tive and dis­rup­tive tech­nolo­gies.

These tech­nolo­gies will mas­sively im­prove our abil­ity to de­liver goods and ser­vices, as they’re ap­plied to ev­ery step of ship­ping, from land-side to ter­mi­nals to ocean. Dig­i­tal­iza­tion will ul­ti­mately con­nect buy­ers and sell­ers, au­to­mate pa­per trails, and im­prove­work­ing cap­i­tal through cen­tral­ized set­tle­ments. The op­por­tu­nity to tie the phys­i­cal op­er­at­ing process to the dig­i­tal fi­nan­cial op­er­at­ing process will ac­cel­er­ate to de­liver on the prom­ise of dig­i­tal­iza­tion.

INTTRA is the largest neu­tral dig­i­tal trans­ac­tion net­work in the ocean con­tainer ship­ping in­dus­try, with more than 800,000 con­tainer or­ders ini­ti­ated over INTTRA’S plat­form weekly through more than 60 car­ri­ers. The com­pany man­ages over one quar­ter of global con­tainer vol­ume, with ad­di­tional vis­i­bil­ity into nearly 40 per cent of global con­tainer trade.

Ar­ti­fi­cial in­tel­li­gence is the con­cept of ma­chines ac­com­plish­ing tasks that have his­tor­i­cally re­quired hu­man in­tel­li­gence. While AI has the po­ten­tial to mas­sively dis­rupt the con­tainer ship­ping in­dus­try, to­day’s ap­pli­ca­tions will as­sist in jobs rather than re­place jobs. For ex­am­ple, sci­en­tists at MIT il­lus­trated how Google’s im­age-recog­ni­tion AI could be fooled into be­liev­ing a base­ball was an espresso or a cat was gua­camole through slight dis­tor­tions that hu­mans would in­stantly rec­og­nize.

The re­sults show that AI pro­grams are sus­cep­ti­ble to misiden­ti­fy­ing ob­jects that are slightly dis­torted, whether ma­nip­u­lated in­ten­tion­ally or not. This echoes an ear­lier study show­ing Google’s AI could iden­tify cats in videos in more than 70 per cent of cases, yet a hu­man child could iden­tify them in 100 per cent of cases.

AI pro­grams will con­tinue to ad­vance, but their weak­nesses il­lus­trate why hu­mans will re­main a crit­i­cal part of AI im­ple­men­ta­tions as they’ll be re­quired to handle ex­cep­tions and higher-end tasks, ones that re­quire cre­ative and orig­i­nal think­ing, as well as ones re­quir­ing lead­er­ship roles.

AI prom­ises to im­prove ef­fi­cien­cies in ocean con­tainer ship­ping, but many fear it will lead to a loss of jobs; how­ever, it’s much more com­plex than that. Mckin­sey Global In­sti­tute es­ti­mates that up to 800 mil­lion global work­ers could lose their jobs by 2030 due to au­to­ma­tion; mean­while, Gart­ner sug­gests that by 2020 AI will au­to­mate 1.8 mil­lion peo­ple out of work, but it will cre­ate 2.3 mil­lion new jobs, adding that “AI will im­prove the pro­duc­tiv­ity of many jobs, and, used cre­atively, it has the po­ten­tial to en­rich ca­reers, reimag­ine old tasks and cre­ate new in­dus­tries.”

Any­thing that can be stan­dard­ized can be au­to­mated

AI will lead to a shift­ing in the types of jobs per­formed, and in the process cre­ate more op­por­tu­ni­ties. In IT there is a be­lief that any­thing that can be stan­dard­ized can be au­to­mated, but one of the chal­lenges in con­tainer ship­ping is there are a high num­ber of ex­cep­tions. AI will al­low work­ers to fo­cus more of their time on those ex­cep­tions.

The past is of­ten the best pre­dic­tor of the fu­ture. When cars re­placed horses, few pre­dicted the emer­gence of the au­to­mo­bile in­dus­try and the re­sult­ing mas­sive new job cre­ation, as well as the birth of the en­tire truck­ing and ship­ping in­dus­try that drives lo­gis­tics. An­other dis­rup­tion oc­curred with the in­ven­tion of pal­lets and then the mod­ern ship­ping con­tainer, which many feared would lead to in­creased job losses. Be­cause of that, decades back driv­ers de­liv­er­ing pal­lets were re­quired to un­pack them and then have the con­tents packed onto pal­lets again in an ef­fort to pre­serve jobs they thought were threat­ened. That in­ef­fi­ciency ended for ob­vi­ous rea­sons, yet the num­ber of em­ploy­ees in global ship­ping and mar­itime sky­rock­eted. There are ap­prox­i­mately 1.2 mil­lion peo­ple cur­rently em­ployed in the mar­itime in­dus­try. The fear was un­founded. Pal­lets and then ship­ping con­tain­ers helped ex­pand con­tainer ship­ping and foster glob­al­iza­tion.

Ar­ti­fi­cial In­tel­li­gence and Ma­chine Learn­ing will help re­move ad­di­tional in­ef­fi­cien­cies in the sys­tem by di­rect­ing tech­nol­ogy at areas that can be eas­ily stan­dard­ized. This includes the pre-fill­ing of var­i­ous forms, or as­pects of cus­tomer ser­vice at the searchengine level to help cus­tomers find in­for­ma­tion and sources be­fore they speak with a client. Ship­ping is al­ways full of ex­cep­tions due to hu­man er­ror, weather in­ter­fer­ence and un­ex­pected events. Hu­mans are bet­ter at deal­ing with ex­cep­tions, so the role of AI in lo­gis­tics is to free up work­ers for higher level tasks that will help clients.

The build­ing blocks to AI

AI of­fers a few dif­fer­ent di­men­sions that rest on the foun­da­tion of re­cent tech­nolo­gies to help an­swer two key ques­tions en­abling dig­i­tal­iza­tion and even­tu­ally AI:

1. Can I store it?

2. Can I process it?

In an­swer to the first ques­tion, we can now save vir­tu­ally ev­ery piece of data us­ing a sim­ple cloud so­lu­tion such as Ama­zon Web Ser­vices. This en­ables or­ga­ni­za­tions to ac­cu­mu­late data at a rea­son­able cost, to the point where they can keep and store all the data they touch, and be­cause they can keep and store all the data they touch, they can then rea­son with it. This en­ables one of the great ben­e­fits of Ar­ti­fi­cial In­tel­li­gence known as Ma­chine Learn­ing, which leads to the prom­ise of im­proved ef­fi­ciency through pre­dic­tive an­a­lyt­ics. So con­nect­ing the tech­nol­ogy dots to get to AI starts with dig­i­tal­iza­tion, which is hap­pen­ing now.

Ap­pli­ca­tions for AI in con­tainer ship­ping – to­day and to­mor­row

One very real, near-term ini­tia­tive that in­cor­po­rates AI are chat­bots us­ing NLP, or Nat­u­ral Lan­guage Pro­cess­ing. INTTRA is ex­plor­ing en­hanc­ing its cloud so­lu­tions with chat­bots to fur­ther en­hance a cus­tomer’s ex­pe­ri­ence. They won’t re­place work­ers, but in­stead will give users a more ef­fi­cient way to in­ter­act through chat for sup­port be­fore talk­ing to a hu­man. Chat­bots rep­re­sent the early face of AI and will im­pact all areas where there is com­mu­ni­ca­tion between hu­mans. The growth in chat­bots across all in­dus­tries will be ex­plo­sive. Ac­cord­ing to Gart­ner, by 2021, more than 50 per cent of en­ter­prises will be spend­ing more per year on bots and chat­bot creations than tra­di­tional mo­bile app de­vel­op­ments.

Gart­ner projects that by the end of this decade, the av­er­age per­son will have more con­ver­sa­tions with vir­tual as­sis­tants or bots than with im­me­di­ate fam­ily. Such pen­e­tra­tion of ar­ti­fi­cial in­tel­li­gence will de­pend on fur­ther ad­vances in the tech­nol­ogy to be­come smarter and eas­ier to in­ter­act with. While many ex­pect this progress to oc­cur from ad­vances in ma­chine learn­ing and deep learn­ing, there are new tech­niques be­ing in­tro­duced as well.

Imag­ine an AI ap­pli­ca­tion that con­fig­ures fore­casts with an au­to­mated, con­ver­sa­tional in­ter­face. By look­ing at a cus­tomer’s pre­vi­ous book­ings, the AI app could see the cus­tomer had three fla­vors of book­ings, en­abling the pa­ram­e­ters to be au­to­mat­i­cally pre­filled be­cause the ap­pli­ca­tion learned from past be­hav­iors. This will al­low or­ga­ni­za­tions to im­prove the book­ing process while free­ing sup­port peo­ple to fo­cus on higher tasks.

In the fu­ture, AI will in­creas­ingly help with other crit­i­cal tasks while work­ing in con­junc­tion with hu­mans. One area is with Har­mo­nized Sys­tem (HS) codes, which is based on an in­ter­na­tional stan­dard that clas­si­fies traded prod­ucts. An er­ror in the HS code, which is not un­com­mon, can cause sig­nif­i­cant de­lays and in­crease costs. AI cou­pled with MR will be able to cor­rect many of these er­rors up­front by as­sign­ing the proper HS codes, only in­volv­ing hu­mans on ex­cep­tions that can’t be eas­ily re­solved.

An­other area AI will help is with smart con­tain­ers. AI and IOT will al­low reefers to be mon­i­tored and han­dled re­motely, in­creas­ing and de­creas­ing tem­per­a­ture and air flow as re­quired. The Ai-en­abled sys­tem will only in­volve hu­mans for ex­cep­tions.

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