Iyini i-AI Ethics?

Iyini i-AI Ethics?

Igama lizwakala liphakeme, kodwa umgomo uyasebenza kakhulu: ukwenza amasistimu e-AI abantu bangawathemba-ngoba aklanywe, akhiwe, futhi asetshenziswa ngezindlela ezihlonipha amalungelo abantu, ezinciphisa ukulimala, futhi zilethe inzuzo yangempela. Yilokho-kahle, ikakhulukazi. 

Izindatshana ongathanda ukuzifunda ngemva kwalesi:

🔗 Iyini i-MCP ku-AI
Ichaza iphrothokholi yekhompuyutha eyi-modular kanye nendima yayo ku-AI.

🔗 Iyini i-AI enqenqemeni
Imboza ukuthi ukucubungula okusekelwe emaphethelweni kunika amandla kanjani izinqumo zasendaweni ze-AI ezisheshayo.

🔗 Iyini i-AI ekhiqizayo
Sethula amamodeli adala umbhalo, izithombe, nokunye okuqukethwe koqobo.

🔗 Iyini i-AI ye-agent
Ichaza ama-agent e-AI azimele akwazi ukwenza izinqumo eziqhutshwa umgomo.

Iyini i-AI Ethics? Incazelo elula 🧭

I-AI Ethics iyisethi yezimiso, izinqubo, kanye nemithetho yokuqapha eqondisa ukuthi siyiklama kanjani, siyithuthukisa kanjani, sikhipha, futhi siyilawula kanjani i-AI ukuze iphakamise amalungelo abantu, ukulunga, ukuziphendulela, ukubeka izinto obala, kanye nokulunga komphakathi. Kucabange njengemithetho yansuku zonke yomgwaqo yama-algorithms-nokuhlolwa okwengeziwe kwamakhona ayinqaba lapho izinto zingahambi kahle.

Amatshe okuthinta umhlaba wonke asekela lokhu: Izincomo ze-UNESCO zigxile ngamalungelo abantu, ukugada kwabantu, kanye nobulungiswa, ngokusobala nangokungenzeleli njengokungaxoxiswana ngakho [1]. Izimiso ze-AI ze-OECD zihlose enokwethenjelwa ehlonipha izimiso zentando yeningi kuyilapho ihlala isebenza emaqenjini enqubomgomo nawonjiniyela [2].

Ngamafuphi, i-AI Ethics ayiyona iphosta odongeni. Kuyincwadi yokudlala esetshenziswa amaqembu ukubikezela izingozi, ukufakazela ukwethembeka, nokuvikela abantu. I-NIST's AI Risk Management Framework iphatha izimiso zokuziphatha njengokulawula ubungozi okusebenzayo kuwo wonke umjikelezo wempilo we-AI [3].

Yini eyenza i-AI Ethics enhle ✅

Nansi inguqulo engacacile. Uhlelo oluhle lwe-AI Ethics:

  • Iyaphila, hhayi i-laminated - izinqubomgomo ezishayela izinqubo zangempela zobunjiniyela nezibuyekezo.

  • Iqala ekufakeni inkinga - uma inhloso icishiwe, akukho ukulungisa okuzoyisindisa.

  • Izinqumo zamadokhumenti - kungani le datha, kungani le modeli, kungani lo mkhawulo.

  • Izivivinyo ezinomongo - zihlola ngeqembu elincane, hhayi nje ukunemba okuphelele (itimu ewumongo ye-NIST) [3].

  • Ibonisa umsebenzi wayo - amakhadi angamamodeli, imibhalo yesethi yedatha, kanye namakhommu abasebenzisi acacile [5].

  • Kwakha ukuziphendulela - abanikazi abaqanjwe ngamagama, izindlela ezikhuphukayo, ukucwaningwa kwamabhuku.

  • Ibhalansisa ukuhwebelana endaweni evulekile - ukuphepha vs. usizo vs. ubumfihlo, kubhalwe phansi.

  • Ixhumeka kumthetho - izimfuneko ezisekelwe engozini ezikala izilawuli ezinomthelela (bona uMthetho we-EU AI) [4].

Uma ingashintshi isinqumo somkhiqizo owodwa, ayizona izimiso zokuziphatha-yimhlobiso.

Impendulo esheshayo embuzweni omkhulu: Iyini i-AI Ethics? 🥤

Kuyindlela amaqembu aphendula ngayo imibuzo emithathu ephindaphindayo, ngokuphindaphindiwe:

  1. Ingabe kufanele sakhe lokhu?

  2. Uma kunjalo, sinciphisa kanjani ukulimala futhi sikufakazele?

  3. Lapho izinto zihamba eceleni, ubani okufanele aziphendulele futhi kwenzekani ngokulandelayo?

Ukusebenza okuyisidina. Kunzima ngokumangalisayo. Kuyakufaneleka.

Ikesi elincane lamasekhondi angu-60 (isipiliyoni sokusebenza) 📎

Ithimba le-fintech lithumela imodeli yokukhwabanisa enembayo yonke enembayo. Emasontweni amabili kamuva, amathikithi osekelo ayakhuphuka avela ezinkokhelweni ezisemthethweni zesifunda ayavinjwa. Isibuyekezo seqembu elingaphansi sibonisa ukukhumbula kwaleyo ndawo ngamaphoyinti angu-12 ngaphansi kwesilinganiso. Ithimba livakashela kabusha ukufakwa kwedatha, liziqeqesha kabusha ngokumeleleka okungcono, futhi lishicilele ikhadi lemodeli elibhala ngoshintsho, izexwayiso ezaziwayo, nendlela yokukhalaza yomsebenzisi. Ukunemba kwehlisa iphuzu elilodwa; ukweqa kwekhasimende. Lokhu kuyizimiso zokuziphatha njengokulawulwa kobungozi kanye nenhlonipho yomsebenzisi , hhayi iphosta [3][5].

Amathuluzi nezinhlaka ongazisebenzisa 📋

(Izingqinamba ezincane ezifakiwe ngenjongo-lokho ukuphila kwangempela.)

Ithuluzi noma Uhlaka Izilaleli Inani Kungani kusebenza Amanothi
I-NIST AI Uhlaka Lokulawulwa Kwengozi Umkhiqizo, ingozi, inqubomgomo Mahhala Sula imisebenzi- Govern, Map, Kala, Phatha -hlanganisa amaqembu Ngokuzithandela, okubhekiselwa kuyo kabanzi [3]
Izimiso ze-OECD AI Execs, abenzi benqubomgomo Mahhala Amanani + ama-recs asebenzayo we-AI ethembekile Ukubusa okuqinile kwasenyakatho-inkanyezi [2]
Umthetho we-EU AI (osekelwe engcupheni) Ezomthetho, ukuthobela, ama-CTO Mahhala* Izigaba zobungozi zibeka izilawuli ezilinganayo zokusetshenziswa komthelela omkhulu Izindleko zokuthobela imithetho ziyahlukahluka [4]
Amamodeli Amakhadi ML onjiniyela, PMs Mahhala Ilinganisa ukuthi imodeli iyini, yenzani, nalapho yehluleka khona Iphepha + izibonelo zikhona [5]
Amadokhumenti esethi yedatha (“ama-datasheets”) Ososayensi bedatha Mahhala Ichaza umsuka wedatha, ukufakwa, imvume, nobungozi Kuphathe njengelebula lokudla okunempilo

I-Deep dive 1 - Izimiso ezinyakazayo, hhayi kumbono 🏃

  • Ukulunga - Linganisa ukusebenza kuzo zonke izinhlobo zabantu nezimo; amamethrikhi esewonke afihla ukulimala [3].

  • Ukuziphendulela - Nikeza abanikazi bedatha, imodeli, nezinqumo zokusatshalaliswa. Gcina amalogi esinqumo.

  • Ukungafihli - Sebenzisa amakhadi amamodeli; tshela abasebenzisi ukuthi isinqumo sizenzakalela kanjani nokuthi iyiphi insiza ekhona [5].

  • Ukwengamela komuntu - Faka abantu ku-loop ukuze uthole izinqumo ezinobungozi obukhulu, ngamandla angempela okumisa/okukhipha (okubekwe ngaphambili ngokucacile yi-UNESCO) [1].

  • Ubumfihlo nokuvikeleka - Nciphisa futhi uvikele idatha; cabanga ukuvuza kwesikhathi sokucabanga kanye nokusetshenziswa kabi komfula.

  • Inzuzo - Bonisa inzuzo yomphakathi, hhayi nje ama-KPI ahlanzekile (i-OECD ifaka uhlaka lwale bhalansi) [2].

Ukwehla kancane: amathimba kwesinye isikhathi aphikisana amahora amaningi mayelana namagama e-metric ngenkathi eshaya indiva umbuzo wangempela wokulimaza. Kuyahlekisa ukuthi lokho kwenzeka kanjani.

I-Deep dive 2 - Izingozi nokuthi zingakalwa kanjani 📏

I-Ethical AI iba ukhonkolo lapho uphatha ukulimala njengengozi elinganisekayo:

  • Imephu yokuqukethwe - Ubani othintekayo, ngokuqondile nangokungaqondile? Imaphi amandla okunquma uhlelo olunawo?

  • Ukufaneleka kwedatha - Ukumelwa, ukukhukhuleka, ikhwalithi yokulebula, izindlela zemvume.

  • Ukuziphatha okuyimodeli - Amamodi okuhluleka ngaphansi kweshifti yokusabalalisa, ukwaziswa kokuphikisana, noma okokufaka okunonya.

  • Ukuhlolwa komthelela - Ubukhulu × ukuba nokwenzeka, ukuncishiswa, kanye nensalela yengozi.

  • Izilawuli ze-Lifecycle - Ukusuka ekufakeni inkinga ukuya ekuqaphelweni kwangemuva kokuthunyelwa.

I-NIST ihlukanisa lokhu kube amathimba emisebenzi amane angasebenzisa ngaphandle kokusungula kabusha isondo: Govern, Map, Measure, Phatha [3].

I-Deep dive 3 - Amadokhumenti akulondoloza kamuva 🗂️

Ama-artifact amabili athobekile enza okungaphezu kwanoma yisiphi isiqubulo:

  • Amakhadi Emodeli - Ukuthi imodeli ingeyani, yahlolwa kanjani, lapho yehluleka khona, ukucatshangelwa kwezimiso zokuziphatha, kanye nama-caveats-amafushane, ahlelekile, afundekayo [5].

  • Amadokhumenti esethi yedatha (“ama-datasheets”) - Kungani le datha ikhona, ukuthi yaqoqwa kanjani, ubani omelwe, izikhala ezaziwayo, nokusetshenziswa okunconyiwe.

Uma ngabe kudingeke ukuthi uchazele abalawuli noma izintatheli ukuthi kungani imodeli ingaziphathanga kahle, uzombonga owakho okwedlule ngokubhala lezi. Ikusasa-uzothenga ikhofi elidlule.

I-Deep dive 4 - Ukuphatha okulumayo 🧩

  • Chaza izigaba zobungozi - Boleka umbono osuselwe engozini ukuze izimo zokusebenzisa umthelela ophezulu zicutshungulwe ngokujulile [4].

  • Amasango esiteji - Ukubuyekezwa kokuziphatha ekuthathweni, ngaphambi kokwethulwa, nangemuva kokwethulwa. Hhayi amasango ayishumi nanhlanu. Okuthathu kuningi.

  • Ukuhlukaniswa kwemisebenzi - Onjiniyela baphakamisa, ukubuyekezwa kozakwethu abasengozini, abaholi basayine. Sula imigqa.

  • Impendulo yesigameko - Ubani omisa kancane imodeli, ukuthi abasebenzisi baziswa kanjani, ukuthi ukulungiswa kubukeka kanjani.

  • Ukucwaningwa kwamabhuku okuzimele - Kwangaphakathi kuqala; ngaphandle lapho iziteki zifunwa khona.

  • Ukuqeqeshwa kanye nezisusa - Vuza izinkinga zokuvela kusenesikhathi, ungazifihli.

Masikhulume iqiniso: uma ukubusa kungasho lutho , akukhona ukuphatha.

I-Deep dive 5 - Abantu abakulophu, hhayi njengezinsizakusebenza 👩⚖️

Ukwengamela komuntu akulona ibhokisi likaqhwi-kuyisinqumo somklamo:

  • Lapho abantu benquma - Sula ama-threshold lapho umuntu kufanele abuyekeze, ikakhulukazi emiphumeleni enobungozi obukhulu.

  • Ukuchazeleka kwabathatha izinqumo - Nikeza umuntu kokubili ukuthi kungani kanye nokungaqiniseki .

  • Izihibe zempendulo yomsebenzisi - Vumela abasebenzisi baqhudelane noma balungise izinqumo ezizenzakalelayo.

  • Ukufinyeleleka - Izixhumi ezibonakalayo abasebenzisi abahlukene abangaziqonda futhi bazisebenzise.

Isiqondiso se-UNESCO silula lapha: isithunzi somuntu kanye nokwengamela kuyingqikithi, hhayi ukuzikhethela. Yakha umkhiqizo ukuze abantu bakwazi ukungenelela ngaphambi kokulimaza izindawo [1].

Inothi eseceleni - Umngcele olandelayo: neurotech 🧠

Njengoba i-AI ihlangana ne-neurotechnology, ubumfihlo bengqondo nenkululeko yokucabanga kuba ukucatshangelwa komklamo wangempela. Ibhuku lokudlala elifanayo liyasebenza: izimiso ezigxile kumalungelo [1], ukubusa okunokwethenjelwa ngedizayini [2], nokuvikela okulinganayo kokusetshenziswa okunobungozi obukhulu [4]. Yakha ama- guardrails kusenesikhathi kunokuba uwabophe kamuva.

Amaqembu aphendula kanjani Yini i-AI Ethics? ngokusebenza - ukuhamba komsebenzi 🧪

Zama le loop elula. Ayiphelele, kodwa isebenza ngenkani:

  1. Ukuhlola inhloso - Iyiphi inkinga yomuntu esiyixazululayo, futhi ubani ozuzayo noma obeka engcupheni?

  2. Imephu yokuqukethwe - Ababambiqhaza, indawo, izingqinamba, izingozi ezaziwayo.

  3. Uhlelo lwedatha - Imithombo, imvume, ukumelela, ukugcinwa, imibhalo.

  4. Idizayini yokuphepha - Ukuhlolwa kwe-Adversary, ithimba elibomvu, ubumfihlo-ngokudizayina.

  5. Chaza ukulunga - Khetha amamethrikhi afanele isizinda; ukuhwebelana kwamadokhumenti.

  6. Uhlelo lokuchaza - Yini ezochazwa, kubani, nokuthi uzoqinisekisa kanjani ukuthi uwusizo.

  7. Ikhadi eliyimodeli - Dlulisa ngaphambi kwesikhathi, buyekeza njengoba uhamba, shicilela lapho kwethulwa [5].

  8. Amasango okuphatha - Ukubuyekezwa kwengozi nabanikazi abaphendulayo; isakhiwo sisebenzisa imisebenzi ye-NIST [3].

  9. Ukuqapha ngemva kokwethulwa - Amamethrikhi, izexwayiso ze-drift, izincwadi zokudlala zesigameko, izikhalazo zabasebenzisi.

Uma isinyathelo sizwakala sisinda, silinganisele engozini. Yilokho iqhinga. Ubunjiniyela obudlulele be-bot yokulungisa isipelingi akusizi muntu.

Izimiso zokuziphatha uma kuqhathaniswa nokuhambisana - umehluko obabayo kodwa odingekayo 🌶️

  • I-Ethics iyabuza: ingabe lokhu kuyinto efanele abantu?

  • Ukuthobela kuyabuza: ingabe lokhu kuyahlangabezana nencwadi yomthetho?

Udinga kokubili. Imodeli ye-EU esekelwe engcupheni ingaba umgogodla wakho wokuthobela, kodwa uhlelo lwakho lwezimiso zokuziphatha kufanele ludlulele ngale kwesilinganiso esincane-ikakhulukazi ezimweni ezingaqondakali noma ezintsha zokusetshenziswa [4].

Isingathekiso esisheshayo (esinamaphutha): ukuthobelana wucingo; isimilo ungumalusi. Ucingo lukugcina emingceleni; umelusi uyakugcina uhambe ngendlela.

Izingibe ezivamile - nokuthi yini okufanele uyenze esikhundleni salokho 🚧

  • I-Pitfall: ithiyetha yezimiso zokuziphatha - izimiso ezinhle ezingenazo izinsiza.
    Lungisa: nikela isikhathi, abanikazi, futhi ubuyekeze izindawo zokuhlola.

  • I-Pitfall: ukulimala okulinganiselwe - ama-metrics amakhulu afihla ukwehluleka kweqembu elincane.
    Lungisa: hlala uhlola ngama-subpopulations afanelekile [3].

  • I-Pitfall: imfihlo izenza ukuphepha - ukufihla imininingwane kubasebenzisi.
    Lungisa: dalula amakhono, imikhawulo, kanye nosizo ngolimi olulula [5].

  • I-Pitfall: ukucwaninga ekugcineni - ukuthola izinkinga ngaphambi kokwethulwa.
    Lungisa: shintsha izimiso zokuziphatha zibe yingxenye yomklamo nokuqoqwa kwedatha.

  • I-pitfall: izinhlu zokuhlola ngaphandle kokwahlulela - amafomu alandelayo, hhayi umqondo.
    Lungisa: hlanganisa izifanekiso nokubuyekezwa kochwepheshe kanye nocwaningo lwabasebenzisi.

Imibuzo Evame Ukubuzwa - izinto ozobuzwa noma kunjalo ❓

Ingabe i-AI Ethics iphikisana nokuqamba izinto ezintsha?
Cha. Kuyindlela emisha ewusizo. Izimiso zokuziphatha zigwema izinjongo ezifile njengamasistimu achemile adala ukuhlehla noma inkinga yezomthetho. Uhlaka lwe-OECD lukhuthaza ngokusobala ukuqamba okusha ngokuphepha [2].

Ingabe siyakudinga lokhu uma umkhiqizo wethu usengozini encane?
Yebo, kodwa kulula. Sebenzisa izilawuli ezilinganayo. Lowo mbono osuselwe engozini ujwayelekile endleleni ye-EU [4].

Yimaphi amadokhumenti okufanele ube nawo?
Okungenani: amadokhumenti esethi yedatha yamasethi akho edatha amakhulu, ikhadi eliyimodeli lemodeli ngayinye, kanye nerekhodi lesinqumo sokukhishwa [5].

Ubani umnikazi we-AI Ethics?
Wonke umuntu unokuziphatha, kodwa umkhiqizo, isayensi yedatha, namaqembu engcuphe adinga izibopho eziqanjiwe. Imisebenzi ye-NIST iyisikafula esihle [3].

Kude Kakhulu Kangizange Ngikufunde - Amazwi okugcina 💡

Uma ukuhlole konke lokhu, nansi inhliziyo: Iyini i-AI Ethics? Kuyisiyalo esisebenzayo sokwakha i-AI abantu abangayethemba. Gxila ekuqondisweni okwamukelwe kabanzi-umbono we-UNESCO ogxile kumalungelo kanye nemigomo ethembekile ye-AI ye-OECD. Sebenzisa uhlaka lobungcuphe lwe-NIST ukuze ulusebenzise, ​​futhi uthumele ngamakhadi oyimodeli namadokhumenti esethi yedatha ukuze ukukhetha kwakho kufundeke. Bese ugcine abasebenzisi abalalelayo, ababambiqhaza, ekuqaphelweni kwakho-futhi ulungise. I-Ethics ayikona okokwenza-kodwa; kuwumkhuba.

Futhi yebo, ngezinye izikhathi uzolungisa-isifundo. Akukhona ukwehluleka lokho. Yilowo umsebenzi. 🌱

Izithenjwa

  1. I-UNESCO - Isincomo ku-Ethics of Artificial Intelligence (2021). Isixhumanisi

  2. I-OECD - AI Principles (2019). Isixhumanisi

  3. I-NIST - I-Artificial Intelligence Risk Management Framework (AI RMF 1.0) (2023) (PDF). Isixhumanisi

  4. I-EUR-Lex - Umthethonqubo (EU) 2024/1689 (AI Act). Isixhumanisi

  5. UMitchell et al. - "Amakhadi Emodeli Wokubika Kwemodeli" (ACM, 2019). Isixhumanisi

Thola i-AI yakamuva esitolo esisemthethweni somsizi we-AI

Mayelana NATHI

Buyela kubhulogi