An AI-dri­ven pop­u­la­tion cen­sus is the most wide-rang­ing da­ta col­lec­tion ex­er­cise a state can un­der­take. The cen­sus is a dash­board for sta­tis­tics, mea­sure­ments, and in­di­ca­tors pro­duced dur­ing the in­ter­censal pe­ri­od. It en­ables the sta­tis­ti­cal in­sti­tute of the State to col­lect in­for­ma­tion from near­ly every mem­ber of the pop­u­la­tion on a wide range of top­ics.

The Age of AI calls for the dig­i­tal­i­sa­tion of “in­ter alia”, all ad­min­is­tra­tive records, in­clud­ing those held by the Land Reg­istry, the Reg­is­trar of Mar­riages, Births and Deaths, Lands and Sur­veys, State Lands, Dis­trict Rev­enue Ser­vices, build­ing foot­prints us­ing GIS and drone tech­nolo­gies, Postal Codes, and da­ta from the Of­fice of the Reg­is­trar of Mi­grants.

The cen­sus is the spine of the na­tion­al sta­tis­ti­cal sys­tem and the sta­tis­ti­cal in­sti­tute of the State. It con­tributes to strength­en­ing the State’s ca­pac­i­ty to gath­er qual­i­ty so­cio-eco­nom­ic and de­mo­graph­ic da­ta re­gard­ing re­li­a­bil­i­ty, time­li­ness, and rel­e­vance.

An end-to-end dig­i­tal cen­sus mod­el en­tails us­ing dig­i­tal wal­lets for enu­mer­a­tors in the field, Cen­sus Apps to send no­ti­fi­ca­tions to the en­tire project team, and em­ploy­ing e-learn­ing method­olo­gies to train cen­sus staff and in­form cit­i­zens about the tools and tech­nolo­gies utilised in an AI-dri­ven and dig­i­tal­ly ground­ed cen­sus.

It en­com­pass­es web-based in­ter­views us­ing Com­put­er-As­sist­ed Per­son­al In­ter­view­ing (CAPI). This tool al­lows enu­mer­a­tors to con­duct the sur­vey us­ing smart­phones with AI-pow­ered fea­tures that en­hance the user ex­pe­ri­ence, in­clud­ing per­son­al as­sis­tance, as well as tablets to ad­min­is­ter ques­tion­naires and record re­spons­es dur­ing face-to-face in­ter­views.

CAPI of­fers sev­er­al ad­van­tages, such as re­al-time da­ta en­try, re­duced in­ac­cu­ra­cies and mis­takes, and the abil­i­ty to in­cor­po­rate vi­su­al and au­dio aids dur­ing field ex­er­cis­es. To reach re­spon­dents who are at work, those in re­mote lo­ca­tions with in­ter­net ac­cess, and those trav­el­ling over­seas, Com­put­er-As­sist­ed Web In­ter­view­ing (CAWI) adds an­oth­er lay­er to the dig­i­tal cen­sus toolk­it.

CAWI en­ables re­spon­dents to com­plete on­line ques­tion­naires via a web link, which can be ac­cessed on smart­phones, desk­tops, and tablets. These links en­sure pri­va­cy and con­ve­nience, re­duce the need for face-to-face in­ter­ac­tions or phys­i­cal pa­per sur­veys, and boost pub­lic par­tic­i­pa­tion. 

Util­is­ing GIS tech­nolo­gies, a dig­i­tal cen­sus can ef­fec­tive­ly cre­ate Enu­mer­a­tion Dis­tricts (EDs) con­sist­ing of 150 to 200 hous­ing units. In a dig­i­tal cen­sus, a hous­ing unit serves as a “unique iden­ti­fi­er” for a house­hold, which is dis­tinct from an e-iden­ti­ty.

For a dig­i­tal cen­sus, in coun­tries like Uruguay, each hous­ing unit is as­signed a unique ID linked to the phys­i­cal ad­dress and the in­di­vid­u­als with­in. A hous­ing unit is thus de­fined as a sep­a­rate and in­de­pen­dent liv­ing area, typ­i­cal­ly a stu­dio, house, or even a room, where a per­son or a group of peo­ple re­sides in­de­pen­dent­ly from oth­ers.

It is gen­er­al­ly char­ac­terised by hav­ing a pri­vate en­trance, a kitchen, and a bath­room, or the abil­i­ty to iso­late it­self from oth­er liv­ing ar­eas with­in a larg­er struc­ture. The unique iden­ti­fi­ca­tion num­ber as­signed by the cen­sus con­nects the phys­i­cal ad­dress to its oc­cu­pants through­out the cen­sus process.

This en­sures ac­cu­ra­cy in da­ta col­lec­tion and analy­sis that can sub­se­quent­ly in­form pol­i­cy de­ci­sions, the con­struc­tion of vul­ner­a­bil­i­ty in­dices, and oth­er an­cil­lary dash­boards to man­age the well­ness and well-be­ing of the pop­u­la­tion.

All of these in­puts and tech­no­log­i­cal ad­vance­ments in con­duct­ing a na­tion­al cen­sus share a sin­gle aim–re­duc­ing er­rors and striv­ing for an ac­cu­rate rep­re­sen­ta­tion of the facts as they ex­ist on the ground.

It al­so pre­vents the tragedy of mis­counts and puts a spot­light on in­di­vid­u­als on the mar­gins, the over­looked, the un­banked, and the un­der­served. Progress in reach­ing the so­cial­ly min­imised has been slow, and the stakes are not low. In Latin Amer­i­ca and the Caribbean, ef­forts are un­der­way to mod­ernise cen­sus da­ta gath­er­ing, large­ly through au­toma­tion in the Age of AI. 

Ahead of the cen­sus, the State may ex­plore build­ing and train­ing an AI mod­el. The mod­el must be trained us­ing a range of ex­ist­ing da­ta lakes. To ac­tu­alise this in­ten­tion, the State may con­sid­er open and big da­ta mod­els. Gen­er­a­tive AI mod­els, which can en­hance the ac­ces­si­bil­i­ty of cen­sus da­ta, re­quire vast amounts of train­ing da­ta.

AI train­ing can utilise var­i­ous da­ta sources, but the qual­i­ty and rel­e­vance of the train­ing da­ta are cru­cial for the per­for­mance and re­li­a­bil­i­ty of the AI mod­el. Gen­er­a­tive AI can cre­ate syn­thet­ic da­ta, help­ing to pro­tect sen­si­tive in­for­ma­tion while mak­ing cen­sus da­ta ac­ces­si­ble to pol­i­cy­mak­ers.

Ex­plain­able AI (XAI) aids in iden­ti­fy­ing and mit­i­gat­ing bi­as­es with­in AI mod­els, en­sur­ing fair­ness and trust­wor­thi­ness in the analy­sis of cen­sus da­ta. Ma­chine Learn­ing (ML) mod­els can be trained to analyse spe­cif­ic de­mo­graph­ic groups, cen­sus fo­ci, and even pre­dict da­ta trends. AI mod­els can in­her­it bi­as­es from the da­ta they are trained on, so care­ful con­sid­er­a­tion of fair­ness and trust­wor­thi­ness is es­sen­tial.

Fi­nal­ly, pro­tect­ing the pri­va­cy of in­di­vid­u­als while us­ing AI to analyse cen­sus da­ta is cru­cial. This high­lights that the core fea­tures of a dig­i­tal cen­sus are da­ta se­cu­ri­ty, da­ta sov­er­eign­ty, cy­ber­se­cu­ri­ty, pri­va­cy, and the hu­man right to dig­i­tal era­sure.

Cen­sus da­ta pro­vides a ba­sis on which to for­mu­late poli­cies and make long-term plans for de­vel­op­ment, par­tic­u­lar­ly con­cern­ing de­mo­graph­ic, so­cial, and eco­nom­ic is­sues. Train­ing AI for a na­tion­al cen­sus in­volves equip­ping AI mod­els with the abil­i­ty to analyse and un­der­stand cen­sus da­ta, po­ten­tial­ly im­prov­ing da­ta col­lec­tion, analy­sis, and ac­ces­si­bil­i­ty. 

Dr Fazal Ali com­plet­ed his Mas­ters in Phi­los­o­phy at the Uni­ver­si­ty of the West In­dies, he was a Com­mon­wealth Schol­ar who at­tend­ed the Uni­ver­si­ty of Cam­bridge, Hugh­es Hall, provost of the Uni­ver­si­ty of Trinidad and To­ba­go and the act­ing pres­i­dent and chair­man of the Teach­ing Ser­vice Com­mis­sion. He is present­ly a con­sul­tant with the IDB. He can be reached at faza­lal­itsc@gmail.com