Bugu da ari, sharhin

Wannan sashe da aka tsara za a yi amfani a matsayin tunani, maimakon a karanta a matsayin labari.

• Gabatarwa (Sashe 6.1)

Research xa'a ya al'ada kuma hada batutuwa kamar kimiyya da zamba da kuma kasafi na bashi. Wadannan batutuwa da ake tattauna a mafi girma, daki-daki, a Engineering (2009) .

Wannan babi ne karfi da dimbin yawa da halin da ake ciki, a {asar Amirka. Don ƙarin a kan da'a review hanyoyin a wasu kasashen, duba babi na 6, 7, 8, da kuma 9 na Desposato (2016b) . Domin an shaida cewa ilimin halittu da aikin likita da'a ka'idojin da suka rinjayi wannan babi ne ɓarna, Amirka, ga Holm (1995) . Don ƙarin tarihi review na hukumomi Review Boards a Amurka, ganin Stark (2012) .

The Belmont Report kuma m dokokin a Amurka sun yi bambanci tsakanin bincike da kuma yi. Wannan bambanci da aka soki baya (Beauchamp and Saghai 2012; boyd 2016; Metcalf and Crawford 2016; Meyer 2015) . Ba na yi wannan bambanci a wannan babi domin na ganin da'a akida, da kuma frameworks tambaya ga duka saituna. Don ƙarin a kan bincike dubawa a Facebook, gani Jackman and Kanerva (2016) . Ga wani tsari domin gudanar da bincike dubawa a kamfanoni da kungiyoyi masu zaman kansu, ga Polonetsky, Tene, and Jerome (2015) da kuma Tene and Polonetsky (2016) .

Don ƙarin a kan yanayin da Ebola fashewa a 2014, ga McDonald (2016) , da kuma game da tsare sirri kasada na wayar hannu data, ga Mayer, Mutchler, and Mitchell (2016) . Domin misalin rikicin da alaka da bincike ta amfani da wayar hannu data, ga Bengtsson et al. (2011) da kuma Lu, Bengtsson, and Holme (2012) .

• Three misalai (Sashe 6.2)

Mutane da yawa sun rubuta game da Wani tunanin Contagion. The mujallar Research Ethics sadaukar da dukan batun a watan Janairu 2016 tattauna gwajin. ganin Hunter and Evans (2016) ga wani bayyani. The gabatarwar da National Malamai masu koyarwa na Science buga guda biyu game da gwaji: Kahn, Vayena, and Mastroianni (2014) da kuma Fiske and Hauser (2014) . Other guda game da gwaji sun hada da: Puschmann and Bozdag (2014) . Meyer (2014) . Grimmelmann (2015) . Meyer (2015) . Selinger and Hartzog (2015) . Kleinsman and Buckley (2015) . Shaw (2015) . Flick (2015) .

Don ƙarin on Encore, gani Jones and Feamster (2015) .

• Digital ne daban-daban (Sashe 6.3)

A cikin sharuddan salla kula, m overviews suna bayar a Mayer-Schönberger (2009) da kuma Marx (2016) . Ga wani kankare misali na canja halin kaka na lura, Bankston and Soltani (2013) ya yi kiyasin cewa tracking mai laifi da ake zargin ta yin amfani da wayar salula ne game da sau 50 rahusa fiye amfani da jiki kula. Bell and Gemmell (2009) na samar da wani more kaffa hangen zaman gaba a kan kai- kula. Bugu da ƙari, kasancewa iya waƙa Fitowan hali da yake jama'a ko partially jama'a (misali, Ku ɗanɗani, huldar, kuma Time), masu bincike za a iya ƙara infer abubuwa da yawa mahalarta la'akari da su zama masu zaman kansu. Alal misali, Mikal Kosinski da kuma abokan aiki ya nuna cewa su iya infer m bayani game da mutane, kamar jima'i fuskantarwa da kuma amfani da jaraba abubuwa daga alama talakawa digital alama data (Facebook Likes) (Kosinski, Stillwell, and Graepel 2013) . Wannan zai sauti sihiri, amma m Kosinski da kuma abokan aiki amfani-da hadawa digital burbushi, safiyo, da kuma dubawa koyo-shi ne ainihin wani abu da na riga gaya muku game da. Ka tuna cewa a Babi na 3 (tambayoyi) na faɗa muku yadda Josh Blumenstock da kuma abokan aiki (2015) a hade binciken data tare da wayar hannu bayanai zuwa kimanta talauci a Rwanda. Wannan ainihin wannan m, wanda za a iya amfani da su yadda ya kamata auna talauci a cikin wani tasowa kasar, kuma za a iya amfani da yiwuwar bayanin tsare saba inferences.

Saba dokokin da norms iya kai ga bincike da cewa ba ya girmama buri na mahalarta, kuma tana iya kai wa ga "kullum shopping" by bincike (Grimmelmann 2015; Nickerson and Hyde 2016) . Musamman ma, wasu masu bincike suke so don kauce wa IRB dubawa da abõkan tãrayya waɗanda suka ba su rufe IRBs (misali, mutane a kamfanoni ko kungiyoyi masu zaman kansu) tattara da kuma de-gane data. Sa'an nan kuma, masu bincike na iya bincika wannan de-gano data ba tare da IRB dubawa, a kalla a cewar wasu fassarori a halin yanzu dokoki. Wannan irin IRB kin biyan bayyana a saba da ka'idojin tushen m.

Don ƙarin a kan saba da iri-irin ideas cewa mutane da game da kiwon lafiya data, ga Fiore-Gartland and Neff (2015) . Don ƙarin a kan matsalar da heterogeneity halitta domin gudanar da bincike xa'a yanke shawara ga Meyer (2013) .

Daya bambanci tsakanin analog shekaru da digital shekaru bincike shi ne cewa a cikin digital shekaru bincike hulda da mahalarta ne mafi m. Wadannan interactions sau da yawa faruwa, ta hanyar wani tsakiya kamar kamfanin, kuma akwai yawanci babban jiki-da zamantakewa-nisa tsakanin masu bincike da kuma mahalarta. Wannan m hulda da ke sa wasu abubuwa da suke da saukin a analog shekaru bincike wuya a digital shekaru bincike, kamar nunawa daga mahalarta suka bukata karin kariya, ganowa m events, kuma remediating cuta idan ta auku. Alal misali, bari mu bambanci Wani tunanin Contagion da tamkar Lab gwaji a kan wannan topic. A cikin Lab gwaji, masu bincike zai iya tsare daga duk wanda ya isa a Lab nuna shakka akwai ayoyi na tunanin wahala. Bugu da ari, idan Lab gwaji halitta wani m taron, masu bincike zai gan shi, samar da ayyuka ga remediate da wata cũta, kuma sai ku yi sabawa ga gwaji yarjejeniya hana m illolin. The m yanayin hulda a ainihin Wani tunanin Contagion gwajin sa kowane daga cikin wadannan sauki da kuma m matakai musamman wuya. Har ila yau, na zargin cewa da nisa tsakanin masu bincike da kuma mahalarta sa masu bincike kasa kula da damuwar da suke da mahalarta.

Da sauran hanyoyin saba norms da dokoki. Wasu daga cikin wannan inconsistency ya zo daga gaskiyar cewa wannan bincike da ke faruwa a duk faɗin duniya. Alal misali, Encore hannu da mutane daga ko'ina cikin duniya, sabili da haka shi zai zama batun da bayanai kariya da kuma bayanin tsare dokokin mutane da yawa daban-daban ƙasashe. Idan da norms hukumar uku-jam'iyyar yanar gizo buƙatun (abin Encore aka yi) su ne daban-daban a kasar Jamus, da Amurka, da Kenya, da kuma China? Idan da norms ne ba ma m cikin guda kasar? A karo na biyu tushen inconsistency zo daga haɗin gwiwar da ke tsakanin masu bincike, a jami'o'i da kamfanonin. misali, wani tunanin Contagion wani haɗin gwiwar tsakanin data masanin kimiyya a Facebook da kuma farfesa kuma digiri na biyu dalibi a Cornell. A Facebook guje manyan gwajen ne na yau da kullum da kuma, a wancan lokaci, ba ya bukatar wani ɓangare na uku mai da'a review. A Cornell da norms da dokoki ne quite daban-daban. kusan duk gwaje-gwajen dole ne a sake nazari da Cornell IRB. To, wanda ya kafa dokoki ya kamata mulki Wani tunanin Contagion-Facebook ta ko Cornell ta?

Don ƙarin a kan} o} arin sake duba Common Rule, gani Evans (2013) , Council (2014) , Metcalf (2016) , da kuma Hudson and Collins (2015) .

• Four ka'idojin (Sashe 6.4)

The classic ka'idojin tushen tsarin kula da ilimin halittu da aikin likita xa'a ne Beauchamp and Childress (2012) . Suka ba da shawara cewa hudu main ka'idodin ya kamata shiryar da ilimin halittu da aikin likita xa'a: Mutunta mulkin kai, Nonmaleficence, karimci, da adalci. Ka'idar nonmaleficence bukaci daya zuwa kauce daga haddasa cutar da sauran mutane. Wannan ra'ayi ne warai da alaka da Hippocratic ra'ayin "Shin, wata cũta ba." A binciken da xa'a, wannan manufa ne sau da yawa a hade tare da qa'ida ta karimci, amma ga Beauchamp and Childress (2012) (Babi na 5) for more on bambanci tsakanin biyu . Ga wani zargi da cewa wadannan ka'idoji ne overly Amirka, ga Holm (1995) . Don ƙarin a kan daidaita a lõkacin da ka'idojin rikici, ga Gillon (2015) .

The hudu ka'idojin a wannan babi sun kuma an samarwa ya shiryar da da'a dubawa domin gudanar da bincike faruwa a kamfanoni da kungiyoyi masu zaman kansu (Polonetsky, Tene, and Jerome 2015) , ta hanyar jikin da ake kira "amfani da Subject Review Boards" (CSRBs) (Calo 2013) .

• Mutunta Mutanen (Sashe 6.4.1)

Bugu da ƙari, mutunta mulkin kai, da Belmont Report kuma ya sani cewa ba kowane mutum ne iya gaskiya kai al'amurra. Alal misali, da yara, mutanen da fama da rashin lafiya, ko mutane da suke zaune a yanayi na tsanani ƙuntata yanci iya ba su iya aiki a matsayin cikakken m mutane, da kuma wadannan mutane ne, saboda haka, batun karin kariya.

Da ake ji da manufa na Mutunta Mutanen a cikin digital shekaru na iya zama kalubale. Alal misali, a digital shekaru bincike, zai iya zama da wahala don samar da karin kare ga mutanen da rage damar kai kafiya domin bincike sau da yawa sani sosai kadan game da mahalarta. Bugu da ari, sanar da amsa a digital shekaru zamantakewa bincike ne mai babbar kalubale. A wasu lokuta, da gaske sanar amsa iya sha daga gaskiya paradox (Nissenbaum 2011) , inda bayanai da kuma fahimta a cikin rikici. Wajen, idan masu bincike samar cikakken bayani game da yanayin da data tarin, data analysis, da kuma data tsaro ayyuka, zai zama da wuya ga mutane da yawa mahalarta su fahimta. Amma, idan masu bincike samar comprehensible bayanai, shi yana iya rasa muhimmanci fasaha bayani. A likita bincike a cikin analog shekaru-da mamaye saitin dauke da Belmont Report-wanda zai iya kwatanta likita magana akayi daban-daban tare da kowane ɗan takara don taimakawa warware gaskiya paradox. A online karatu shafe dubban ko miliyoyin mutane, irin wannan fuska-da-fuska m ne ba zai yiwu ba. A karo na biyu matsala tare da amsa a cikin digital shekaru shi ne cewa a wasu karatu, kamar bincike na m data repositories, zai zama impractical kafin su sami informed yarda daga dukan mahalarta. Na tattauna wannan da kuma wasu tambayoyi game da sanar da amsa a more daki-daki, a Sashe 6.6.1. Duk da wadannan matsaloli, duk da haka, ya kamata mu tuna cewa informed yarda ne ba dole kuma ishe Mutunta Mutanen.

Don ƙarin a kan kiwon lafiya da bincike da informed yarda, gani Miller (2014) . Ga wani littafi-tsawon jiyya na sanar da yarda, gani Manson and O'Neill (2007) . Ka kuma duba shawarar karatu game da sanar da amsa kasa.

• Karimci (Sashe 6.4.2)

Harms to mahallin ne wata cũta cewa bincike zai iya sa ba zuwa takamaiman mutane amma ga zamantakewa saituna. Wannan ra'ayi ne mai bit m, amma zan nuna shi tare da misalai biyu: daya analog kuma daya digital.

A classic misali na illolin to mahallin zo daga Wichita shaidun kotu Nazarin [ Vaughan (1967) . Katz, Capron, and Glass (1972) . Ch 2.] - Har ila yau, wani lokacin ake kira da Chicago shaidun kotu Project (Cornwell 2010) . A cikin wannan binciken masu bincike daga Jami'ar Chicago, a matsayin wani ɓangare na wani ya fi girma binciken game da zamantakewa al'amurran da shari'a da tsarin, a asirce rubuta shida juri deliberations a Wichita, Kansas. The mahukunta da kuma lauyoyi a lokuta ya amince da rikodin, kuma akwai tsananin lura da tsari. Duk da haka, jurors kasance m cewa rikodin aka faruwa. Da zarar binciken da aka gano, akwai jama'a ƙeta doka. The Justice Department fara gudanar da bincike na nazari, da kuma masu bincike da aka kira su zuwa ga shaida a gaban Congress. Daga qarshe, Congress wuce a sabuwar doka da ta sa shi ba bisa doka ba a asirce rikodin juri deliberation.

The damuwa na sukar da Wichita shaidun kotu Nazarin da aka ba cutar da su mahalarta. wajen, shi ne illolin da mahallin juri deliberation. Wancan ne, mutane sun gaskata cewa idan juri members bai yi imani da cewa da suka kasance sunã da ciwon tattaunawa a cikin wani hadari da kuma kariya sarari, zai zama da wuya ga juri deliberations ci gaba a nan gaba. Bugu da ƙari, juri deliberation, akwai wasu takamaiman zamantakewa riƙa cewa jama'a na samar da karin kariya kamar lauya-abokin ciniki dangantaka da m care (MacCarthy 2015) .

The hadarin illolin to mahallin da rushewa daga social tsarin kuma ya zo a cikin wasu filin gwaje-gwajen a Kimiyyar Siyasa (Desposato 2016b) . Domin wani misali da wani more mahallin-m cost-amfani lissafi saura gwaji a Kimiyyar Siyasa, gani Zimmerman (2016) .

• Justice (Sashe 6.4.3)

Ramuwa ga mahalarta da aka tattauna a dama da saitunan alaka digital shekaru bincike. Lanier (2014) samarwa biyan mahalarta ga digital burbushi suka janye. Bederson and Quinn (2011) ya tattauna biya a online aiki kasuwanni. A karshe, Desposato (2016a) ta gabatar da biyan mahalarta a filin gwaje-gwajen. Ya nuna cewa, ko da idan mahalarta ba za a iya biya kai tsaye, a kyauta za a iya yi wa wata kungiya dake wakiltarsu. Alal misali, a Encore da masu bincike ne dã Mun sanya a kyauta zuwa rukuni aiki don taimaka damar yin amfani da yanar-gizo.

• Mutunta Attaura da Public Interest (Sashe 6.4.4)

Terms-of-sabis yarjejeniyar ya kamata da kasa nauyi fiye da kwangila shawarce tsakanin daidai jam'iyyun da dokokin halitta da istinbadi gwamnatoci. Yanayi inda masu bincike sun keta sharuddan-of-service yarjejeniyar a baya kullum unsa amfani sarrafa kansa queries bincikawa da hali na kamfanonin (da yawa kamar filin gwajen don auna da nuna bambanci). Don ƙarin tattaunawa ganin Vaccaro et al. (2015) , Bruckman (2016a) , Bruckman (2016b) . Domin misalin empirical bincike cewa tattauna sharuddan sabis, ga Soeller et al. (2016) . Don ƙarin a kan yiwu shari'a matsaloli masu bincike fuskanci idan suka warware sharuddan sabis ganin Sandvig and Karahalios (2016) .

• Biyu da'a frameworks (Sashe 6.5)

Babu shakka, babban yawa da aka rubuta game da consequentialism da deontology. Domin wani misali na yadda wadannan da'a frameworks, da sauransu, za a iya amfani da su yi hankali game da digital shekaru bincike, ganin Zevenbergen et al. (2015) . Domin wani misali na yadda wadannan da'a frameworks za a iya amfani da filin gwaje-gwajen a ci gaba tattalin arziki, ganin Baele (2013) .

• Ƙididdigewa yarda (Sashe 6.6.1)

Don ƙarin a duba karatu na nuna bambanci, ga Pager (2007) da kuma Riach and Rich (2004) . Ba wai kawai ba wadannan karatu ba su da informed amsa, su ma unsa yaudara ba tare da debriefing.

Dukansu Desposato (2016a) da Humphreys (2015) tayin shawara game da filin gwaje-gwajen ba tare da yardarka.

Sommers and Miller (2013) duba da yawa muhawara a cikin ni'imar da ba debriefing mahalarta bayan rikici, da kuma bayar da hujjar cewa masu bincike ya kamata forgo "debriefing karkashin wani sosai kunkuntar kafa yanayi, wato, a filin bincike a cikin abin da debriefing babban babba m shinge amma masu bincike za su yi ba qualms game debriefing idan za su iya. Masu bincike ba za a halatta forgo debriefing domin adana wani butulci yar pool, garkuwa kansu daga takara fushi, ko kare mahalarta daga cũta. "Wasu jayayya da cewa idan debriefing sa more cuta fiye da kyau ya kamata a kauce masa. Debriefing ne mai akwati inda wasu masu bincike prioritize Mutunta Mutanen kan karimci, da kuma wasu masu bincike yi akasin. Daya zai yiwu bayani zai zama don gano hanyoyin da za a yi debriefing a koyo kwarewa ga mahalarta. Wancan ne, maimakon tunanin debriefing matsayin wani abu da zai iya sa cuta, watakila debriefing kuma iya zama wani abu da za ta amfane mahalarta. Domin misalin irin wannan ilimi debriefing, gani Jagatic et al. (2007) a kan debriefing dalibai bayan zamantakewa mai leƙan asirri gwaji. Halayyar dan Adam sun ɓullo da dabarun domin debriefing (DS Holmes 1976a; DS Holmes 1976b; Mills 1976; Baumrind 1985; Oczak and Niedźwieńska 2007) da kuma wasu daga cikin wadannan za a iya usefully amfani da digital shekaru bincike. Humphreys (2015) yayi ban sha'awa tunani game da ajali amsa, wanda aka hankali alaka da debriefing dabarun da na bayyana.

A ra'ayin na tambayar wani sample mahalarta su amsa ne related to abin da Humphreys (2015) ya kira girman yarda.

A kara ra'ayin da aka samarwa related to informed yarda shi ne ya gina wani kwamitin mutanen da suka yarda da zama a online gwajen (Crawford 2014) . Wasu sun bayar da hujjar cewa wannan panel zai zama maras bazuwar samfurin mutane. Amma, Babi na 3 (tambayoyi) ya nuna cewa wadannan matsaloli ne yiwuwar addressable amfani post-stratification da samfurin iri daya. Har ila yau, yarda su zama a kan panel iya rufe da dama gwaje-gwajen. A wasu kalmomin, mahalarta zai ba bukatar yarda da juna gwaji akayi daban-daban, a ra'ayi da ake kira m yarda (Sheehan 2011) .

• Hankali da kuma Manajan bayani hadarin (Sashe 6.6.2)

Far daga na musamman, da Netflix Prize nuna wani muhimmin fasaha dũkiyar datasets cewa dauke da cikakken bayani game da mutane, kuma ta haka ne yayi muhimman darussa game da yiwuwar "anonymization" na zamani zamantakewa datasets. Files da yawa guda na bayani game da kowane mutum na iya zama sparse, a hankali a tsare ƙa'ida a Narayanan and Shmatikov (2008) . Wancan ne, ga kowane rikodin babu records da cewa su ne guda, kuma a gaskiya babu records da cewa su ne sosai kama: kowane mutum ne mai nisa daga mafi kusa makwabcin a dataset. Mutum na iya tunanin cewa Netflix data zai yi sparse saboda da game da 20,000 movies a kan 5 star sikelin, akwai game \ (6 ^ {20,000} \) yiwu dabi'u cewa kowane mutum zai iya samun (6 domin ban da daya zuwa 5 taurari , wani zai yi ba rated da movie a duk). Wannan lambar yana da babba, shi ne wuya ko fahimta.

Sparsity biyu main abubuwan. Na farko, yana nufin cewa yunƙurin "anonymize" da dataset bisa bazuwar perturbation zai iya kasa. Wancan ne, ko da Netflix su da ka daidaita wasu daga cikin ratings (abin da suka yi), wannan ba zai zama isa saboda perturbed rikodin shi ne har yanzu mafi kusa yiwu rikodin ga bayani cewa attacker yana. Na biyu, da sparsity nufin cewa de-anonymization yiwuwa ko da attacker yana ajizai ko m ilmi. Alal misali, a cikin Netflix data, bari mu kwatanta da attacker sanin ratings biyu movies da kwanakin kuka yi wadanda ratings +/- 3 days. kawai cewa bayanai kadai ya ishe su uniquely gane 68% na mutanen da a cikin Netflix data. Idan maharan san 8 movies da ka rated +/- 14 days, sa'an nan kuma ko da biyu daga cikin wadannan da aka sani ratings ne gaba daya ba daidai ba, 99% na records za a iya uniquely gano a cikin dataset. A wasu kalmomin, sparsity ne mai asali matsala ga kokarin "anonymize" data, wanda yake shi ne m, domin mafi yawan zamani zamantakewa dataset ne sparse.

Telephone metadata ma domin ya bayyana a zama "m" da kuma ba m, amma da yake ba haka al'amarin. Telephone metadata ne tabbatarwa kuma m (Mayer, Mutchler, and Mitchell 2016; Landau 2016) .

A Figure 6.6, na sketched fitar da wani ciniki-kashe tsakanin hadarin mahalarta da kuma amfani ga bincike daga data release. Ga wani kwatanta tsakanin ƙuntata access fuskanci (misali, a garu lambu) da kuma takaitawa data fuskanci (misali, wasu nau'i na anonymization) ga Reiter and Kinney (2011) . Ga wani samarwa categorization tsarin hadarin matakan data, ga Sweeney, Crosas, and Bar-Sinai (2015) . A karshe, wani karin a general tattaunawa na data sharing, gani Yakowitz (2011) .

Don ƙarin cikakken bincike na wannan ciniki-kashe tsakanin hadarin da mai amfani da bayanai, gani Brickell and Shmatikov (2008) , Ohm (2010) , Wu (2013) , Reiter (2012) , da kuma Goroff (2015) . Don ganin wannan ciniki-kashe shafi real bayanai daga massively bude online Darussan (MOOCs), gani Daries et al. (2014) da kuma Angiuli, Blitzstein, and Waldo (2015) .

Bambanci bayanin tsare kuma yayi wani madadin m da za a iya hada biyu high amfani ga al'umma da kuma low hadarin mahalarta, ga Dwork and Roth (2014) da kuma Narayanan, Huey, and Felten (2016) .

Don ƙarin a kan manufar da kaina gano bayanai (PII), wanda yake shi ne tsakiyar ga mutane da yawa daga cikin dokoki game da bincike xa'a, gani Narayanan and Shmatikov (2010) da kuma Schwartz and Solove (2011) . Don ƙarin a kan dukkan data kasancewa yiwuwar m, gani Ohm (2015) .

A wannan sashe, Na Zagayawar da hada huldodi daban-daban datasets matsayin wani abu da zai iya kai ga bayani hadarin. Duk da haka, zai iya kuma haifar da sabuwar dama ga bincike, kamar yadda jãyayya a Currie (2013) .

Don ƙarin a kan biyar safes, gani Desai, Ritchie, and Welpton (2016) . Domin wani misali na yadda jimloli za a iya gano, duba Brownstein, Cassa, and Mandl (2006) , wanda ya nuna yadda maps of cutar ruwan dare za a iya gano. Dwork et al. (2017) kuma ya ɗauki harin da tara bayanai, irin su statistics game da yadda mutane da yawa da wasu cuta.

• Privacy (Sashe 6.6.3)

Warren and Brandeis (1890) ne a landmark shari'a kasida game da tsare sirri, da kuma labarin ne mafi hade da ra'ayin cewa sirrinka ne a daidai a bar shi kadai. More kwanan littafin tsawon jiyya na tsare sirri da cewa Ina bayar da shawarar hada Solove (2010) da kuma Nissenbaum (2010) .

Ga wani review na empirical bincike a kan yadda mutane suna tunanin game da tsare sirri, duba Acquisti, Brandimarte, and Loewenstein (2015) . The mujallar Science buga na musamman batun mai taken "The End of Privacy", wanda bayani da al'amurran da suka shafi na tsare sirri da kuma bayanai hadarin daga wani iri-iri daban-daban ra'ayoyi. ga wani summary ga Enserink and Chin (2015) . Calo (2011) yayi wani tsarin tunani game da illolin da ya zo daga bayanin tsare take hakki. An farkon misali na damuwa game da tsare sirri a cikin sosai farkon na digital shekaru ne Packard (1964) .

• Yin yanke shawara a karkashin rashin tabbas (Sashe 6.6.4)

Daya kalubale a lokacin da kokarin amfani da kadan hadarin misali shi ne cewa shi ne, ba bayyana wanda rayuwar yau da kullum ne da za a yi amfani da benchmarking (Council 2014) . Alal misali, rashin gida mutane da hakan matakan rashin jin daɗi a cikin rayuwarsu ta kullum. Amma, abin da ba ya nufa cewa shi ne ethically halatta a bijirar rashin gida mutane zuwa mafi girma hadarin bincike. Saboda wannan dalili, akwai alama ya zama mai girma yarjejeniya da kadan hadarin ya kamata a benchmarked da a general yawan misali, ba da wani yawan misali. Duk da yake na kullum yarda da ra'ayin wani general yawan misali, ina ganin cewa na manyan online dandamali, irin su Facebook, da wani yawan misali ne m. Wancan ne, a lokacin da la'akari da Wani tunanin Contagion, ina ganin cewa shi ne m to nasa tarihin da yau da kullum hadarin on Facebook. A takamaiman yawan misali a cikin wannan harka shi ne sauƙin kimanta kuma yana da wuya a samu rikici, a qa'ida ta shari'a, wanda ya nẽmi su hana zunuban bincike kasawa riƙa a disadvantaged kungiyoyin (misali, fursunoni da marãyu).

• Practical tips (Sashe 6.7)

Sauran malamai sun kuma yi kira ga mafi takardunku to sun hada da da'a shafuka (Schultze and Mason 2012; Kosinski et al. 2015) . King and Sands (2015) kuma yayi m tips.