Ọzọkwa nkọwa

Nke a translation e kere site na kọmputa. ×

You are reading the Open Review Edition of Bit by Bit. Click here to read the 1st Edition.

Ọzọkwa nkọwa

Ngalaba a na-iji ike mee ka a kwuru okwu ya, kama na-agụ dị ka a kọrọ.

Okwu Mmalite (Nkebi nke 6.1)

Research ụkpụrụ ọma ka omenala na-gụnyere n'isiokwu ndị dị ka ndị ọkà mmụta sayensị igwu wayo na oke nke akwụmụgwọ. Isiokwu ndị na-tụlere n'ụzọ sara mbara karị Engineering (2009) .

Isiokwu a ga-ike-akpụzi ọnọdụ na United States. Maka ozi na usoro ziri ezi nyochaa usoro ná mba ndị ọzọ, gụọ Isi nke 6, 7, 8, na nke 9 Desposato (2016b) . N'ihi esemokwu na Biomedical usoro ziri ezi ụkpụrụ ndị metụtara isiokwu a bụ ókè American,-ahụ Holm (1995) . N'ihi na ihe mere eme na nyochaa nke ulo oru Review Boards na US,-ahụ Stark (2012) .

The Belmont Report na ụdi ụkpụrụ na US mere a iche n'etiti nnyocha na omume. Nke a dị iche e-akatọ ekemende (Beauchamp and Saghai 2012; boyd 2016; Metcalf and Crawford 2016; Meyer 2015) . M na-adịghị eme ka a dị iche n'isiokwu a n'ihi na m na-eche na usoro ziri ezi ụkpụrụ na frameworks emetụta ma ndị ntọala. N'ihi na ihe na nyocha nlekọta n'ọnu Facebook,-ahụ Jackman and Kanerva (2016) . N'ihi na a amaghị na n'ihi research nlekọta n'ọnu ụlọ ọrụ na oru Ngo a, gụọ Polonetsky, Tene, and Jerome (2015) na Tene and Polonetsky (2016) .

N'ihi na ihe banyere okwu ikpe nke Ebola akasiaha ke 2014,-ahụ McDonald (2016) , na n'ihi na ihe banyere nzuzo ize ndụ nke ekwentị mkpanaaka data, ịhụ Mayer, Mutchler, and Mitchell (2016) . N'ihi na ihe atụ nke nsogbu metụtara nnyocha iji ekwentị mkpanaaka data, ịhụ Bengtsson et al. (2011) na Lu, Bengtsson, and Holme (2012) .

Atụ atọ (Nkebi 6.2)

Ọtụtụ ndị na-dere banyere mmetụta uche Contagion. Magazin Research Ethics raara ha dum nke na January 2016-ekwu banyere nnwale; -ahụ Hunter and Evans (2016) maka ihe nnyocha. The Ikpe nke National Akwụkwọ nke Science bipụtara abụọ iberibe banyere nnwale: Kahn, Vayena, and Mastroianni (2014) na Fiske and Hauser (2014) . Ọzọ iberibe banyere nnwale na-agụnye: Puschmann and Bozdag (2014) ; Meyer (2014) ; Grimmelmann (2015) ; Meyer (2015) ; Selinger and Hartzog (2015) ; Kleinsman and Buckley (2015) ; Shaw (2015) ; Flick (2015) .

Maka ozi on encore,-ahụ Jones and Feamster (2015) .

Digital bụ dị iche iche (Nkebi 6.3)

Na okwu nke uka onyunyo, sara overviews na-nyere na Mayer-Schönberger (2009) na Marx (2016) . N'ihi na a ihe atụ nke na-agbanwe agbanwe-akwụ ụgwọ nke onyunyo, Bankston and Soltani (2013) -eme atụmatụ na nsuso a mpụ na-enyo enyo na-eji ekwe ntị bụ banyere 50 ugboro dị ọnụ ala karịa iji anụ ahụ onyunyo. Bell and Gemmell (2009) na-enye a ọzọ nchekwube n'ọnọdụ na ak `u onyunyo. Tụkwasị n'ịbụ enwe ike soro ịhụ anya akpa àgwà ndị dị n'ihu ọha ma ọ bụ na-ezughị ezu ọha (eg, Ire, Ties, na Time), ndị nnyocha pụrụ esiwanye infer ihe ọtụtụ ndị keere òkè weere na ha onwe. Dị ka ihe atụ, Michal Kosinski na ndị ọrụ ibe gosiri na ha nwere ike infer mwute ozi banyere ndị mmadụ, ndị dị ka mmekọahụ nghazi na ojiji nke na-eri ahụ bekee site yiri nkịtị digital Chọpụta data (Facebook nwere mmasị) (Kosinski, Stillwell, and Graepel 2013) . Nke a ike ụda kpokọtara, ma obibia Kosinski na ndị ọrụ ibe ji mee ihe-nke na-agwakọta digital metụtara, nnyocha ndị e mere, na chịkwara amụta-bụ n'ezie ihe na m na-ama gwara gị banyere. Cheta na n'Isi nke 3 (Ịjụ ajụjụ) na m gwara gị otú Josh Blumenstock na ibe (2015) jikọtara nnyocha e mere data na ekwentị mkpanaaka data na-eme atụmatụ ịda ogbenye na Rwanda. Nke a kpọmkwem otu ihe ahụ obibia, nke a pụrụ iji rụọ ọrụ nke ọma tụọ ịda ogbenye na a na-emepe emepe, nwekwara ike-eji maka nwere nzuzo emebi inferences.

Ekwekọghị n'iwu ma na norms pụrụ iduga nnyocha nke na-adịghị asọpụrụ ọchịchọ nke sonyere, na ọ nwere ike bute "usoro iwu shopping" site na-eme nnyocha (Grimmelmann 2015; Nickerson and Hyde 2016) . Karịsịa, ndị nnyocha ụfọdụ ndị na-ezere IRB nlekọta nwere mmekọ ndị na-agaghị kpuchie IRBs (eg, ndị mmadụ na ụlọ ọrụ ma ọ bụ NGO) anakọta ma de-mata data. Mgbe ahụ, ndị nnyocha pụrụ nyochaa a de-kwuru na ọ bụ data na-enweghị IRB nlekọta, ọ dịghị ihe ọzọ dị ka ụfọdụ ịkọwa nke ugbu a iwu. Nke a na ụdị IRB ozize yiri ka ekwekọghị a ụkpụrụ ndị dabeere na obibia.

N'ihi na ihe na-ekwekọghị ekwekọ na heterogeneous echiche na ndị mmadụ nwere banyere ahụ ike data, ịhụ Fiore-Gartland and Neff (2015) . N'ihi na ihe na nsogbu na heterogeneity emepụta maka nnyocha ụkpụrụ ọma mkpebi ahụ Meyer (2013) .

One dị iche n'etiti analọg afọ na dijitalụ afọ research bụ na dijitalụ afọ research mmekọrịta sonyere bụ n'ebe dị anya,. Ndị a interactions na-eme site na intermediary dị ka a ụlọ ọrụ, na e nwere a nnukwu anụ ahụ-na-elekọta mmadụ-anya n'etiti nnyocha na ndị sonyere. Nke a anya na mmekọrịta na-eme ka ụfọdụ ihe ndị na-mfe na analọg afọ nnyocha siri ike na dijitalụ afọ nnyocha, dị ka screening si sonyere ndị achọ ka e chebe, ịchọputa oghom ihe, na remediating nsogbu ma ọ bụrụ na ya emee. Dị ka ihe atụ, ka ọdịiche mmetụta uche Contagion na a hypothetical lab nnwale na otu isiokwu. Ke ụlọ nyocha nnwale, na-eme nnyocha nwee ike chọpụta si onye ọ bụla rutere n'Ụlọ lab egosi doro anya ihe ịrịba ama nke nsogbu mmetụta uche. Ọzọkwa, ọ bụrụ na lab nnwale kere ihe oghom omume, na-eme nnyocha ga-ahụ ya, nye ọrụ na-remediate ihe ọjọọ, wee mee mgbanwe na ibuo protocol iji gbochie n'ọdịnihu Harms. The anya ọdịdị nke na mmekọrịta na-ahụ n'ezie mmetụta uche Contagion nnwale na-eme ka onye ọ bụla n'ime ndị a dị mfe ma ezi uche nzọụkwụ nnọọ ike. Ọzọkwa, M chee na ihe dị n'etiti nnyocha na ndị sonyere na-eme ka na-eme nnyocha na-erughị enwe mmetụta ọsọ ọsọ na-enye ha nsogbu sonyere.

Isi mmalite ndị ọzọ nke ekwekọghị norms na iwu. Ụfọdụ ihe ndị a inconsistency abịa site eziokwu na nke a nnyocha a na-eme n'ụwa nile. Dị ka ihe atụ, encore aka ndị si n'ụwa nile, ya mere ọ pụrụ ịbụ na isiokwu ahụ data nchebe na nzuzo iwu nke mba dị iche iche. Gịnị ma ọ bụrụ na norms na-achị atọ ndị ọzọ web arịrịọ (ihe encore na-eme) dị iche iche na Germany, na United States, Kenya, na China? Gịnị ma ọ bụrụ na norms na-adịghị ọbụna na-agbanwe agbanwe n'ime otu mba? A abụọ isi iyi nke inconsistency abịa site collaborations n'etiti eme nnyocha na mahadum na ụlọ ọrụ; n'ihi na ihe atụ, mmetụta uche Contagion bụ a mmekota n'etiti a data ọkà mmụta sayensị na Facebook na a prọfesọ na gụsịrị akwụkwọ na-amụrụ na Cornell. Na Facebook na-agba ọsọ nnukwu nwere bụ na-eme na, n'oge ahụ, achọghị ka ọ bụla atọ ọzọ usoro ziri ezi nyochaa. Na Cornell ndị norms na iwu ndị dị nnọọ iche; fọrọ nke nta niile nwere a ga-enyocha site na Cornell IRB. Ya mere, nke set nke iwu kwesịrị ịchịkwa mmetụta uche Contagion-Facebook si ma ọ bụ Cornell si?

Maka ozi on mgbalị agụgharị Common Ọma ahụ, na-ahụ Evans (2013) , Council (2014) , Metcalf (2016) , na Hudson and Collins (2015) .

Anọ ụkpụrụ (Nkebi 6.4)

Kpochapụwo ụkpụrụ ndị dabeere na obibia Biomedical ụkpụrụ ọma bụ Beauchamp and Childress (2012) . Ha gwa Abigel na anọ bụ isi ụkpụrụ kwesịrị iduzi Biomedical ụkpụrụ ọma: Nkwanye Ùgwù maka nnwere onwe, Nonmaleficence, Beneficence, na ikpe ziri ezi. Ụkpụrụ nke nonmaleficence-agba ume otu ka e zere eme ihe ọjọọ ndị ọzọ. Echiche a na-miri jikọọ Hippocratic echiche nke "eme ọ dịghị nsogbu." Na research ụkpụrụ ọma, ụkpụrụ a na-achọkwa na ụkpụrụ nke Beneficence, ma-ahụ Beauchamp and Childress (2012) (Chapter 5) n'ihi na ihe na dị iche n'etiti abụọ . N'ihi na a nnyocha ahụ ihe ndị na-gabiga ókè American,-ahụ Holm (1995) . Maka ozi on adịzi mgbe ụkpụrụ esemokwu, lee Gillon (2015) .

The anọ ụkpụrụ n'isiokwu a nakwa na e chọrọ na-eduzi usoro ziri ezi nlekọta maka nnyocha na-eme na ụlọ ọrụ ndị na otu oru Ngo (Polonetsky, Tene, and Jerome 2015) site n'ahụ akpọ "Consumer Isiokwu Review Boards" (CSRBs) (Calo 2013) .

Akwanyere Persons (Nkebi 6.4.1)

Na mgbakwunye na n'ihe banyere obodo kwụụrụ, ndị Belmont Report na-ekweta na a dịghị mmadụ ọ bụla bụ ike nke na ezi onwe mkpebi siri ike. Dị ka ihe atụ, ụmụ, ndị mmadụ na-arịa ọrịa, ma ọ mmadụ bi na ọnọdụ nke machibidoro nnwere gaghị enwe ike ime ihe dị ka n'ụzọ zuru ezu kwurula ndị mmadụ n'otu n'otu, na ndị a na-, ya mere, n'okpuru ka e chebe.

Ime ihe e Nkwanye Ùgwù maka Persons na dijitalụ afọ-esi ike. Dị ka ihe atụ, na dijitalụ afọ research, ọ pụrụ isi ike inye extra nchebe ndị na belata otú ike nke onwe-mkpebi siri ike n'ihi na-eme nnyocha na-mara dị nnọọ nta banyere ha sonyere. Ọzọkwa, ụbụrụ bụ na dijitalụ afọ elekọta mmadụ research bụ nnukwu ihe ịma aka. Mgbe ụfọdụ, n'ezie ụbụrụ bụ ha pụrụ inwe nghọta ọjọọ n'agbanyeghị (Nissenbaum 2011) , ebe ọmụma na-aghọta na-ese okwu. Olee ihe enyemaka, ma ọ bụrụ na-eme nnyocha na-enye ihe ọmụma zuru ezu banyere ọdịdị nke data collection, data analysis, na data nche omume, ọ ga-abụ siri ike n'ihi na ọtụtụ ndị keere òkè ike nghọta. Ma, ọ bụrụ na-eme nnyocha na-enye ighota ọmụma, ọ pụrụ ịbụ ihe dị mkpa oru ọmụma. Na nchọpụta ọgwụ na ahụ analọg ebighi-na-achịkwa ọnọdụ atụle site na Belmont Report-onye pụrụ iche a dọkịta na-ekwu okwu n'otu n'otu na onye ọ bụla soò na-enyere dozie nghọta ọjọọ n'agbanyeghị. Na online ọmụmụ metụtara ọtụtụ puku ma ọ bụ ọtụtụ nde mmadụ, ndị dị otú ahụ a ihu na ihu obibia agaghị ekwe omume. A abụọ nsogbu na nkwenye na dijitalụ afọ bụ na nnyocha ụfọdụ, dị ka analysis nke oke data repositories, ọ ga-abụ impractical iji nweta ụbụrụ bụ site ndị niile sonyere. M-atụle ihe ndị na ajụjụ ndị ọzọ banyere ụbụrụ bụ na ihe nkowa ná Nkebi 6.6.1. N'agbanyeghị ihe isi ike, Otú ọ dị, anyị kwesịrị icheta na ụbụrụ bụ nweghịkwa dị mkpa ma ọ bụ zuru ezu maka Nkwanye Ùgwù maka Persons.

Maka ozi on nchọpụta ọgwụ na tupu ụbụrụ bụ, ịhụ Miller (2014) . N'ihi na a akwụkwọ-ogologo ọgwụgwọ nke ụbụrụ bụ, ịhụ Manson and O'Neill (2007) . Gụọkwa aro agụ banyere ụbụrụ bụ n'okpuru.

Beneficence (Nkebi 6.4.2)

Harms ka onodu bụ ihe ọjọọ research nwere ike ime ka ha ghara kpọmkwem ndị mmadụ ma na-elekọta mmadụ ntọala. Echiche a bụ ihe a bit nkịtị, ma Aga m maa atụ ya na ihe atụ abụọ: otu analọg na otu digital.

Omuma atu putara ihe nke Harms ka onodu-abịa site Wichita juri Study [ Vaughan (1967) ; Katz, Capron, and Glass (1972) ; Ch 2.] - Na-akpọ mgbe ụfọdụ ebe Chicago juri Project (Cornwell 2010) . N'ọmụmụ ihe a na-eme nnyocha si University of Chicago, dị ka akụkụ nke a buru ibu ọmụmụ banyere ọha akụkụ nke usoro iwu, na nzuzo dere isii juri deliberations na Wichita, Kansas. Ndị ikpe na ndị maara Iwu na ndị ikpe ama mma na E, na e nwere iwu siri ike ọrụ nke ilekọta usoro. Otú ọ dị, jurors ahụ amaghị na teepụ na-ewere ọnọdụ. Ozugbo ọmụmụ chọpụtara, e nwere ọha iwe. The ikpe ziri ezi Ngalaba malitere ihe nchoputa nke ọmụmụ, na-eme nnyocha a kpọrọ ịgba akaebe n'ihu Congress. Mee elu mee ala, Congress gafere a iwu ọhụrụ na-eme ka ọ n'uzo na ezighi ezi na nzuzo idekọ juri deliberation.

The nchegbu nke ndị nkatọ na nke Wichita juri Study adịghị emerụ ka sonyere; kama, ọ bụ Harms ka onodu nke juri deliberation. Ya bụ, ndị mmadụ kweere na ọ bụrụ na juri so ekweghị na ha na-enwe nkwurịta okwu dị nchebe ma na-echebe ohere, ọ ga-abụ sikwuoro juri deliberations n'ihu n'ọdịnihu. Na mgbakwunye na juri deliberation, e nwere ndị ọzọ kpọmkwem na-elekọta mmadụ ebube na otu na-enye na e chebe dị ka ọka iwu-ahịa mmekọrịta na psychological na-elekọta (MacCarthy 2015) .

Ihe ize ndụ nke Harms ka onodu na ndị achụmnta usoro-abịa na ụfọdụ ubi nwere na Political Science (Desposato 2016b) . N'ihi na ihe atụ nke a ọzọ onodu-chebaara-eri-erite uru ngụkọta oge maka a ubi nnwale Political Science,-ahụ Zimmerman (2016) .

Ikpe ziri ezi (Nkebi 6.4.3)

Akwụ ụgwọ maka sonyere na e atụle n'isiokwu na a ọnụ ọgụgụ nke ntọala metụtara digital afọ research. Lanier (2014) chọrọ ịkwụ sonyere maka dijitalụ metụtara ha n'ịwa. Bederson and Quinn (2011) eneme ego na online ọrụ na ahịa. N'ikpeazụ, Desposato (2016a) obụp akwụ ụgwọ sonyere na ubi nwere. O kwukwara na ọ bụrụgodị na ndị keere òkè-apụghị akwụ ụgwọ ozugbo, a onyinye nwere ike mee ka otu ìgwè na-arụ ọrụ n'ihi ha. Dị ka ihe atụ, na encore na-eme nnyocha gaara emewo ka a onyinye otu ìgwè na-arụ ọrụ iji na-akwado ohere ka Internet.

Akwanyere Iwu na Public Interest (Nkebi 6.4.4)

Okwu-nke-ọrụ nkwekọrịta kwesịrị inwe obere arọ karịa contracts negotiated n'etiti hà ọzọ na iwu kere ziri ezi ọchịchị. Ọnọdụ ebe ndị nnyocha wedawo okwu-nke-ọrụ nkwekọrịta na n'oge gara aga n'ozuzu na-agụnye iji akpaghị aka gbara ajụjụ na oditi omume nke ụlọ ọrụ (dị nnọọ ka ubi nwere tụọ ịkpa ókè). N'ihi na ndị ọzọ ụka na-ahụ Vaccaro et al. (2015) , Bruckman (2016a) , Bruckman (2016b) . N'ihi na ihe atụ nke ahụrụ anya nnyocha na-atụle usoro nke ọrụ, na-ahụ Soeller et al. (2016) . Maka ozi na o kwere omume nsogbu ikpe na-eme nchọpụta na-eche ihu ma ọ bụrụ na ha na-emerụ usoro nke ọrụ ahụ Sandvig and Karahalios (2016) .

Abụọ usoro ziri ezi frameworks (Nkebi 6.5)

O doro anya na nnukwu ichekwa e dere banyere consequentialism na deontology. N'ihi na ihe atụ nke otú ndị a usoro ziri ezi frameworks, na ndị ọzọ, nwere ike ji mee ihe tụgharịa uche banyere digital afọ nnyocha, gụọ Zevenbergen et al. (2015) . N'ihi na ihe atụ nke otú ndị a usoro ziri ezi frameworks nwere ike a n'ọrụ ubi nwere na imepe akụnụba,-ahụ Baele (2013) .

Asian nkwenye (Nkebi 6.6.1)

Maka ozi on oditi ọmụmụ na ịkpọasị, lee Pager (2007) na Riach and Rich (2004) . Ọ bụghị nanị na ndị a ọmụmụ enweghị ụbụrụ bụ, ha na-agụnye aghụghọ na-enweghị debriefing.

Ma Desposato (2016a) na Humphreys (2015) na-enye banyere ubi nwere na-enweghị nkwenye.

Sommers and Miller (2013) reviews ọtụtụ ndị arụmụka na ihu ọma nke ọ bụghị debriefing sonyere mgbe aghụghọ, na rụrụ ụka na-eme nnyocha kwesịrị ịhapụ "debriefing n'okpuru a warara nke ukwuu ọnọdụ, nsogbu, ya bụ, na ubi nnyocha nke debriefing virus bukwanu uru ihe mgbochi ma na-eme nnyocha ga- ọ dịghị qualms banyere debriefing ma ọ bụrụ na ha nwere ike. Na-eme nnyocha e kwesịghị ikwe ịhapụ debriefing iji mee ka a ghọgbuo soò na ọdọ mmiri,-echebe onwe ha site na iso na iwe, ma ọ bụ chebe sonyere na ihe ojoo. "Ndị ọzọ na-arụ ụka na ọ bụrụ na debriefing-akpata nsogbu karịa mma ọ ga-ezere. Debriefing bụ a ikpe ebe ndị nnyocha ụfọdụ Hazie Nkwanye Ùgwù maka Persons n'elu Beneficence, na ndị nnyocha ụfọdụ na-eme ndị na-abụghị. One kwere omume ngwọta ga-enwe ike ịchọta ụzọ mee ka debriefing a na-amụta ahụmahụ maka ndị sonyere. Ya bụ, kama na-eche echiche nke debriefing dị ka ihe bụ ndị pụrụ imerụ, ikekwe debriefing nwekwara ike ịbụ ihe na-erite uru sonyere. N'ihi na ihe atụ nke ụdị agụmakwụkwọ debriefing,-ahụ Jagatic et al. (2007) on debriefing ụmụ akwụkwọ mgbe a na-elekọta mmadụ phishing nnwale. Ọkà n'akparamàgwà mmadụ mepụtara usoro maka debriefing (DS Holmes 1976a; DS Holmes 1976b; Mills 1976; Baumrind 1985; Oczak and Niedźwieńska 2007) na ụfọdụ n'ime ndị a nwere ike usefully etinyere digital afọ research. Humphreys (2015) na-enye na-akpali echiche banyere deferred nkwenye, nke a na njikọ chiri anya debriefing dị aghụghọ na m kọwara.

Echiche nke na-arịọ a sample nke ndị keere òkè n'ihi nkwenye ha metụtara ihe Humphreys (2015) na-akpọ inferred nkwenye.

A n'ihu echiche na e obụp mi yiri ka ụbụrụ bụ bụ iwu a panel nke ndị na-ekweta na ọ nọ online nwere (Crawford 2014) . Ufodu nesi arumaru na a panel ga-abụ a na-abụghị random sample nke ndị mmadụ. Ma, n'Isi nke 3 (Ịjụ ajụjụ) na-egosi na nsogbu ndị a bụ nwere addressable iji post-stratification na sample kenha. Ọzọkwa, nkwenye na-na panel nwere ike ekpuchi a dịgasị iche iche nke nwere. Yabụ, sonyere nwere ike adịghị mkpa iji kwenye na onye ọ bụla nnwale n'otu n'otu, a echiche akpọ sara nkwenye (Sheehan 2011) .

Nghọta na hapụụrụ informational ize ndụ (Nkebi 6.6.2)

Abụtụghị ihe ọhụrụ, ndị Netflix Nrite na-egosipụta otu ihe dị mkpa oru onwunwe nke datasets na-ebu ọmụma zuru ezu banyere ndị mmadụ, ma si otú awade ihe banyere ekwe omume nke "anonymization" nke oge a na-elekọta mmadụ datasets. Faịlụ na ọtụtụ iberibe ọmụma banyere onye ọ bụla ga di ehighị nne, n'echiche kọwaa chie na Narayanan and Shmatikov (2008) . Ya bụ, ka onye ọ bụla ndekọ e nwere ndị mba ndia na bụ otu, na eziokwu na e nweghị ihe ndekọ na ndị yiri nnọọ: onye ọ bụla dị anya n'ebe ha kacha nso agbata obi na dataset. Otu nwere ike iche na Netflix data nwere ike ịbụ ehighị nne n'ihi na ihe dị ka 20,000 nkiri na a 5 kpakpando ọnụ ọgụgụ, e nwere ihe \ (6 ^ {20,000} \)-ekwe omume ụkpụrụ na onye ọ bụla nwere ike (6 n'ihi na gbakwunyere na onye na-5 kpakpando , onye nwere ike bụghị gosiri ihe nkiri mgbe nile). A ọnụ ọgụgụ buru ibu nke ukwuu, ọ bụ ike iji ọbụna ịghọta.

Sparsity nwere isi ihe abụọ pụtara. Nke mbụ, ọ pụtara na agbali "anonymize" ndị dataset dabere na random perturbation ga-abụ na-ada. Ya bụ, ọbụna ma ọ bụrụ Netflix na-enweghị usoro mgbanwe ụfọdụ n'ime ratings (nke ha mere), a agaghị ezu n'ihi na perturbed ndekọ ka bụ ezigbo kwere omume ndekọ na ozi na ebibi nwere. Nke abụọ, sparsity pụtara na de-anonymization kwere omume ọbụna ma ọ bụrụ na ebibi nwere na-ezughị okè ma ọ bụ ele mmadụ anya n'ihu ihe ọmụma. Dị ka ihe atụ, na Netflix data, ka e were ya na ebibi maara gị ratings abụọ fim na ya bụ ụbọchị gị mere ka ndị ratings +/- 3 ụbọchị; dị nnọọ ka ọmụma nanị ya bụ zuru ezu iji iche mata 68% nke ndị mmadụ na Netflix data. Ọ bụrụ na ndị kpara maara 8 fim ahụ i gosiri +/- 14 ụbọchị, mgbe ahụ, ọbụna ma ọ bụrụ abụọ n'ime ndị a mara ratings bụ kpam kpam ihe ọjọọ, 99% nke ihe ndekọ a pụrụ iche mata na dataset. Yabụ, sparsity bụ a isi nsogbu maka mgbalị "anonymize" data, nke bụ nzukọ n'ihi kasị oge a na-elekọta mmadụ dataset bụ ehighị nne.

Ekwentị metadata nwekwara ike iyi ndị na-"amaonye" na-adịghị enwe mmetụta ọsọ ọsọ, ma na ọ dịghị otú ahụ. Ekwentị metadata bụ amata mmetụta ọsọ ọsọ (Mayer, Mutchler, and Mitchell 2016; Landau 2016) .

Na ọgụgụ 6,6, m sketched si a ahia-apụ n'etiti ize ndụ iji sonyere na uru ka nnyocha si data ntọhapụ. N'ihi na a tụnyere n'etiti nanị ohere na-eru nso (eg, a walled ubi) na nanị data na-eru nso (eg, ụdị ụfọdụ nke anonymization)-ahụ Reiter and Kinney (2011) . N'ihi na a chọrọ categorization usoro ihe ize ndụ na ọkwa nke data, ịhụ Sweeney, Crosas, and Bar-Sinai (2015) . N'ikpeazụ, n'ihi na a ọzọ a n'ozuzu ntụle nke nkekọrịta data, ịhụ Yakowitz (2011) .

N'ihi ọzọ zuru ezu analysis nke a ahia-apụ n'etiti ihe ize ndụ na mmekọ nke data, ịhụ Brickell and Shmatikov (2008) , Ohm (2010) , Wu (2013) , Reiter (2012) , na Goroff (2015) . Ịhụ nke a ahia-apụ etinyere n'ezie data site na massively emeghe online ọmụmụ (MOOCs),-ahụ Daries et al. (2014) na Angiuli, Blitzstein, and Waldo (2015) .

Esi nzuzo na-enye onye ọzọ obibia nke nwere ike ikpokọta ma elu uru ọha mmadụ na ala ize ndụ iji sonyere,-ahụ Dwork and Roth (2014) na Narayanan, Huey, and Felten (2016) .

Maka ozi on echiche nke onwe-akọwapụta ọmụma (PII), nke dị n'etiti ọtụtụ n'ime ndị na-achịkwa ihe research ụkpụrụ ọma, na-ahụ Narayanan and Shmatikov (2010) na Schwartz and Solove (2011) . N'ihi na ihe niile data ịbụ nwere mmetụta ọsọ ọsọ, na-ahụ Ohm (2015) .

Ná nkebi a, m na-kọwara ndị linkage nke dị iche iche datasets dị ka ihe ndị pụrụ iduga informational n'ihe ize ndụ. Otú ọ dị, ọ na nwekwara ike ike ọhụrụ ohere maka nchọpụta, dị ka rụrụ ụka na Currie (2013) .

Maka ozi na ise safes,-ahụ Desai, Ritchie, and Welpton (2016) . N'ihi na ihe atụ nke otú ndapụta nwere ike ịmata ihe, na-ahụ Brownstein, Cassa, and Mandl (2006) , nke na-egosi otú map nke ọrịa njupụta nwere ike ịmata. Dwork et al. (2017) tụlekwara ọgụ megide nchịkọta data, dị ka ọnụ ọgụgụ banyere otú ọtụtụ ndị mmadụ n'otu n'otu nwere ihe ụfọdụ na ọrịa.

Nzuzo (Nkebi 6.6.3)

Warren and Brandeis (1890) bụ a dị ịrịba ama iwu isiokwu banyere nzuzo, na isiokwu na-kasị ejikọta ya na echiche na nzuzo bụ a nri a ga-ahapụ naanị gị. More na nso nso akwụkwọ ogologo agwọ ọrịa nke nzuzo na M ga-ikwu na-agụnye Solove (2010) na Nissenbaum (2010) .

N'ihi na a nyochaa nke ahụrụ anya nnyocha na otú ndị mmadụ na-eche banyere nzuzo, lee Acquisti, Brandimarte, and Loewenstein (2015) . Na magazin Science bipụtara a pụrụ iche akpọ "The End of Privacy", nke agwa okwu nke nzuzo na ọmụma n'ihe ize ndụ site a dịgasị iche iche nke dị iche iche echiche; n'ihi na a nchịkọta ahụ Enserink and Chin (2015) . Calo (2011) awade a kpuchie n'ihi na-eche echiche banyere Harms na-abịa site nzuzo imebi. N'oge atụ nke nchegbu banyere nzuzo na banyere mmalite nke dijitalụ afọ bụ Packard (1964) .

-Eme mkpebi n'okpuru ejighị ihe n'aka (Nkebi 6.6.4)

Otu nsogbu mgbe na-agbalị itinye ntakiri n'ihe ize ndụ ọkọlọtọ bụ na ọ bụ anya onye kwa ụbọchị ndụ a ga-eji na-Benchmarking (Council 2014) . Dị ka ihe atụ, enweghị ebe obibi nwere ọkwa dị elu nke mîkenemke ihe ha mụtara. Ma, nke ahụ adịghị enye echiche na ọ bụ ethically ime iji kpughee enweghị ebe obibi na elu n'ihe ize ndụ nnyocha. N'ihi nke a, e nwere yiri ka a na-eto eto otutu mmadu kwenyere na di ntakiri n'ihe ize ndụ ga-benchmarked megide a n'ozuzu bi ọkọlọtọ, ọ bụghị otu bi ọkọlọtọ. Ka m nọ na-adịkarị na-ekweta na echiche nke a n'ozuzu bi ọkọlọtọ, m na-eche na n'ihi na nnukwu online nyiwe dị ka Facebook, a kapịrị ọnụ ọgụgụ ọkọlọtọ bụ ihe ezi uche. Ya bụ, mgbe atụle mmetụta uche Contagion, M na-eche na ọ bụ ihe ezi uche benchmark megide kwa ụbọchị ize ndụ on Facebook. A kpọmkwem bi ọkọlọtọ na nke a dị nnọọ mfe inwale na yighị ka emegideghị ụkpụrụ nke ikpe ziri ezi, nke na-achọ iji gbochie ibu arọ nke research gwụsịrị emegbu on disadvantaged iche iche (eg, ndị mkpọrọ na ụmụ mgbei).

Bara uru Atụmatụ (Nkebi 6.7)

Ndị ọzọ ndị ọkà mmụta na-akpọ maka ndị ọzọ akwụkwọ na-agụnye usoro ziri ezi appendices (Schultze and Mason 2012; Kosinski et al. 2015) . King and Sands (2015) na-enye bara uru Atụmatụ.