Bayan Magana da Rubutu: Shin AI Na Iya Bari Mutane Su Musanya Tunani da Babban Sauri?

Nazarin kimiyya na artificial intelligence, brain-computer interfaces da musanya tunani kai tsaye tsakanin mutane

Mujallar bita ta kimiyya da tsarin binciken da aka gabatar | Nuwamba 2026

Takaitaccen Bayani

Kwamfutocin zamani na yau suna musanya bayanai da sauri da ya wuce tunani.

Haɗin Gigabit Ethernet na yau da kullun na iya canja wurin bayanai da bits biliyan ɗaya (1,000,000,000 bits) a dakika ɗaya. Fasahohin kwamfuta da data-centre na ci gaba suna aiki sauri sau da yawa fiye da haka.

Amma halin mutum daban ne gaba ɗaya.

Ko a yau, mutane galibi suna amfani da magana, rubutu, alamomi da motsin jiki don isar da tunaninsu, ra'ayoyinsu, matsayinsu da jikinsu ga wasu.

Duk da cewa babban sarrafa bayanan neural na faruwa a kwakwalwar mutum, ƙarfinmu na canja wurin wannan bayanin ga wani mutum ta hanya mai ma'ana ƙarami ne idan aka kwatanta.

Wannan yanayi na tayar da muhimmiyar tambaya ta kimiyya.

Ta amfani da artificial intelligence da fasahohin neural, shin mutane za su iya musanya tunaninsu da ra'ayoyinsu kai tsaye, daidai da kuma da babban sauri, ba tare da taimakon magana ko rubutu ba?

Wannan mujalla ta bincika saurin canja wurin bayanan mutum, fasahohin da ke fassara siginoli na neural na kwakwalwa, brain-computer interfaces, sadarwa ta brain-to-brain da ci gaban kimiyya da aka samu har Nuwamba 2026.

Haka kuma tana gabatar da sabon tsarin bincike don musanya tunanin mutum da niyyarsa da babban sauri da taimakon artificial intelligence.

Manufar asali ta wannan bincike ba kawai canja wurin ƙarin bayanan dijital ba ce.

Manufarta ta tsakiya ita ce bincika yiwuwar kimiyya na sabon hanyar sadarwa da ke isar da ma'anar abin da mutum yana son bayyana ga wasu, a cikin ɗan ƙaramin lokaci kuma da babban daidaito.

1. Gabatarwa: Matsalolin Sauri a Sadarwar Mutum

Yi la'akari da kwamfutoci biyu da aka haɗa da cibiyar sadarwar kwamfuta ta zamani.

Za su iya canza manyan bayanai zuwa siginolin lantarki kuma su musanya su a cikin milliseconds kaɗan.

Yanzu yi la'akari da mutane biyu da ke musanya ra'ayi mai wuya.

Mutum na farko dole ne ya kafa ra'ayi a zuciyarsa.

Sai ya mayar da wannan ra'ayi zuwa yare.

Dole ne ya zaɓi kalmomi masu dacewa.

Dole ne ya tsara waɗannan kalmomi zuwa jimla daidai.

Sai kawai zai iya yin magana ko rubutu.

Hakazalika, mutum na biyu dole ne ya ji ko ya karanta waɗannan kalmomi. Sai ya fahimci ma'anarsu kuma ya gano abin da mutum na farko ya yi niyyar faɗa da gaske.

Kowane mataki na wannan tsari yana ɗaukar lokaci.

A wasu lokuta rashin fahimta na iya tasowa. Sai a sake bayyana ra'ayin.

Babban matsalar a nan ba cewa kwakwalwar mutum tana aiki a hankali ba.

A maimakon haka, akwai babban rata tsakanin sarrafa bayanan neural da ke faruwa a kwakwalwar mutum da saurin da za a iya isar da wannan bayanin ga wasu.

Binciken da Coupé da abokan aikinsa suka yi, wanda aka buga a mujallar Science Advances a shekarar 2019, ya yi nazari kan harsuna 17 kuma ya ƙiyasta cewa matsayin canja wurin bayanai na harsunan magana na mutum ya kai kusan bits 39 a dakika ɗaya [1].

A wani muhimmin bincike, Zheng da Meister sun ƙiyasta matsayin sarrafa bayanan halayyar mutum a kusan bits 10 a dakika ɗaya. An buga wannan bincike a yanar gizo a 2024 kuma ya bayyana a mujallar Neuron a 2025 [2].

Waɗannan bincike biyu suna auna nau'o'in sarrafa bayanai daban-daban. Don haka ba za a iya amfani da lambobi biyu a matsayin juna ba.

Kuma ba su ne aunawa na ƙarshe na jimillar ƙarfin sarrafa neural na kwakwalwar mutum ba.

Duk da haka, suna nuna cewa matsayin bayanan ayyuka na sanarwa da sadarwa na mutum ya fi ƙasa da matsayin canja wurin bayanai na tsarin lantarki da yawa.

Wannan bambanci shine tushen sabon bincikenmu.

2. Saurin Canja Wurin Bayanan Kwamfuta da Saurin Sadarwar Mutum

Kwamfutoci suna canza bayanai zuwa nau'in dijital kuma suna musanya su bisa ƙa'idodin sadarwa da aka ayyana.

Misali:

• 1 gigabit a dakika ɗaya (1 Gbps) = bits 1,000,000,000 a dakika ɗaya.

• 10 Gbps = bits biliyan 10 a dakika ɗaya.

• 100 Gbps = bits biliyan 100 a dakika ɗaya.

• 800 Gbps = bits biliyan 800 a dakika ɗaya.

Waɗannan alkaluma suna bayyana ƙarfin canja wurin bayanai na cibiyar sadarwar kwamfuta.

Amma ba su faɗar komai game da yadda kwamfuta ke fahimtar ma'ana ta gaske ta bayanan da ake aikawa da sauri ba.

Sadarwar mutum daban take gaba ɗaya.

A musanya tsakanin mutane, abin da ya fi muhimmanci ba kawai adadin bayanai ba ne amma ma'anasu.

Misali, mutum ɗaya na iya bayyana shawara mai wuya sarai da 'yan kalmomi.

Wani mutum kuma na iya buƙatar ayoyi da yawa don bayyana wannan ra'ayi.

Don haka ana buƙatar kulawa mai yawa na kimiyya lokacin da ake kwatanta saurin canja wurin bayanan kwamfuta da saurin sadarwar mutum.

Kwamfuta na iya canja wurin bits biliyan a dakika ɗaya.

Amma wannan ba ya nufin tana fahimtar ma'anar wannan bayanin.

A lokaci guda, mutum na iya isar da ra'ayi mai zurfi ga wani ta amfani da 'yan kalmomi kawai.

Manufar bincikenmu don haka ba canza kwakwalwar mutum zuwa cibiyar sadarwar kwamfuta ta gigabit ba ce.

A maimakon haka, manufarmu ita ce ƙara saurin da za a iya musanya tunani da ra'ayoyi masu ma'ana tsakanin mutane ta hanya da ake fahimta daidai.

Wannan shine mafi muhimmancin tushe na kimiyya na wannan bincike.

3. Ci Gaban da Kimiyya Ta Samu Har Yanzu

3.1 Brain-Computer Interfaces

Brain-computer interface, ko BCI a takaice, fasaha ce da ke ƙirƙirar haɗi tsakanin ayyukan neural na kwakwalwar mutum da tsarin kwamfuta na waje.

Ta amfani da wannan fasaha, ana iya nazartar siginolin da aka samu daga kwakwalwa ta kwamfuta.

Akwai manyan hanyoyi biyu na yin rikodin ayyukan kwakwalwa.

Na farko, hanyoyi kamar EEG waɗanda ke yin rikodin ayyukan lantarki na kwakwalwa ba tare da tiyata ba.

Na biyu, hanyoyin da ke amfani da electrodes da aka shuka a cikin kwakwalwa ta hanyar tiyata.

Samfuran artificial intelligence suna nazartar waɗannan siginoli na neural kuma suna ƙoƙarin gano aikin da mutum yana niyyar yi, kalmar da yake son bayyana, ko umarnin sadarwa.

Binciken da Willett da abokan aikinsa suka yi, wanda aka buga a mujallar Nature a watan Agusta 2023, babban ci gaba ne a wannan fanni.

Wannan aiki ya ƙirƙira fasahar da ke mayar da ayyukan neural da ke faruwa lokacin da mutum yana ƙoƙarin yin magana zuwa rubutu.

Mahalarta ya iya sadarwa da matsayi na kusan kalmomi 62 a minti ɗaya.

Matsayin kuskuren kalmomi ya kasance 9.1% tare da ƙananan kalmomi 50 da 23.8% tare da babban ƙamus na kalmomi 125,000 [3].

Wannan bincike ya tabbatar da cewa za a iya amfani da siginolin kwakwalwa da ke tasowa lokacin da mutum yana ƙoƙarin yin magana don sadarwa da sauri gwargwado.

Amma wannan tsarin ba fasaha ce da za ta iya karanta kowane tunani da ke tasowa a zuciyar mutum ba cikin 'yanci.

Ya gano ayyukan neural da ke da alaƙa da ƙoƙarin yin magana.

3.2 Samar da Magana Kai Tsaye Daga Siginolin Kwakwalwa

Ƙarin ci gaba mai ban sha'awa a wannan fanni ya faru a 2025.

Littlejohn da abokan aikinsa sun ƙirƙira fasahar da ke sarrafa siginoli daga kwakwalwar mutum a cikin tazara na milliseconds 80 kuma suna mayar da su zuwa magana da taimakon artificial intelligence [4].

A wani bincike, Wairagkar da abokan aikinsa sun bayyana hanyar da ke amfani da siginolin neural na kwakwalwa don samar da magana ta synthetic mai cike da ra'ayi a lokaci na gaske.

Mahalarta a wannan bincike ya iya kuma sarrafa, har zuwa wani matakin, abubuwan bayyanawa kamar sautin murya [5].

Wannan ci gaba ne mai muhimmanci.

Sadarwar mutum ba kawai musanya kalmomi ba ce.

Saurin da muke yin magana, sautin murya, bayyanar motsin rai da yadda muke jaddada kalmomi duka suna bayyana ma'anar ra'ayi ta gaske.

Waɗannan bincike suna nuna yiwuwar sake gina magana ta halitta ta mutum daga siginolin neural.

Duk da haka, suna ci gaba da kasancewa fasahohin gwaje-gwaje da ake amfani da su a wuraren bincike na musamman.

3.3 Amfani na Aiwatar da Lokaci Mai Tsawo: Binciken Tarihi na 2026

Binciken da aka buga a mujallar Nature Medicine a watan Yuni 2026 ya nuna babban ci gaba a cikin amfani na aiki na fasahar brain-computer interface.

A wannan binciken da Card da abokan aikinsa suka yi, mutum mai fama da ciwon ganye na motor mai tsanani ya yi sadarwa da kansa na dogon lokaci da taimakon interface da aka shuka.

A cikin kusan shekaru biyu, ya yi amfani da fasahar a gida sama da awanni 3,800.

Ta hakan ya yi sadarwa da kusan kalmomi miliyan 1.96 da jimloli 183,060.

Matsakaicin saurin sadarwa ya kai kusan kalmomi 56 a minti ɗaya.

A gwaje-gwajen magana da aka sarrafa, daidaiton kalmomi ya wuce 99%. Amma a tattaunawar yau da kullum wannan daidaito bai kasance iri ɗaya a kowane lokaci ba [6].

Wannan bambanci yana da muhimmanci sosai.

Nasara ɗaya ce fasaha ta yi aiki da kyau a dakin gwaje-gwaje.

Wata nasara ce kuma wannan fasaha ta yi aiki da tabbaci na dogon lokaci a rayuwar yau da kullum ta mutane.

A bincikenmu na musanya tunanin mutum mai sauri, dole ne a tabbatar da waɗannan bangarori biyu daban-daban.

3.4 Shin Za A Iya Musanya Bayanai Kai Tsaye Tsakanin Kwakwalwar Mutum?

Haka kuma an samu wasu nasarori na farko a duniyar kimiyya game da sadarwa ta brain-to-brain.

An buga bincike mai suna BrainNet a shekarar 2019.

A wannan bincike, mutane uku sun yi aiki tare kan wasa mai sauƙi ta amfani da siginolin kwakwalwa.

An yi rikodin shawarwarin mahalarta biyu na farko ta amfani da fasahar EEG.

An aika wannan bayanin ga mahalarta na uku a matsayin siginoli da aka ayyana ta hanyar karfafa kwakwalwa da ake kira Transcranial Magnetic Stimulation (TMS).

Ƙungiyoyi biyar sun shiga wannan gwaji.

An rubuta matsakaicin daidaiton aikinsu a matsayin 81.25% [7].

Wannan bincike ya nuna yiwuwar canja wurin wasu bayanai tsakanin kwakwalwar mutum ta hanyar neural interfaces.

Amma abin da aka canja wurin shawarwari ne masu sauƙi kawai.

Ba a canja wurin tunani mai wuya, tunani ko ra'ayoyi cikakku kai tsaye ba.

Don haka akwai babban bambanci na kimiyya tsakanin canja wurin bayanai masu sauƙi na binary da canja wurin cikakken ra'ayin mutum ga wani.

3.5 Gano Magana da Ake Tunani A Zuciya

Binciken da Kunz da abokan aikinsa suka yi wanda aka buga a mujallar Cell a watan Agusta 2025 ya nuna cewa za a iya gano ayyukan neural da ke faruwa lokacin da mutum yana tunanin yin magana a zuciyarsa a sassa.

Wani muhimmin bangare na wannan bincike shi ne sirrin zuciya.

An kuma bincika barazanar da ke nufin bayyana maganar ciki ta sirri ta mutum, wadda baya son raba ta da wasu, ta hanyar fasaha ba da gangan ba.

Bugu da ƙari, an gwada hanyoyin kariya don bambanta tsakanin tunanin da aka ƙirƙira da gangan don sadarwa da ayyukan zuciya na sirri [8].

Wani bincike, wanda aka buga a mujallar Nature Neuroscience a watan Satumba 2026, ya bincika wasu gine-gine masu kama da juna a cikin ayyukan neural na magana da ake tunani da magana bayyane [9].

Waɗannan abubuwan da aka gano na iya ƙirƙirar damar da za a ta da a nan gaba don mutane su yi sadarwa da wasu bayanai ko ba tare da ƙoƙarin yin magana ba.

Amma babu shaidar kimiyya da za ta iya faɗar cewa fasahohin yau za su iya fahimtar dukkan tunani da ke tasowa a zuciyar kowane mutum daidai, ba tare da horo ko haɗin gwiwa na farko ba.

4. Sabon Ra'ayin Binciken da Aka Gabatar

Musanya Tunanin Mutum Mai Sauri da Taimakon Artificial Intelligence

Artificial Intelligence-Assisted High-Speed Thought Communication

Babbar manufar wannan bincike:

Bincika yiwuwar fasahar da ke gano, daga siginolin neural na kwakwalwa, tunani da ra'ayoyin da mutane suna son isarwa da son ransu, mayar da su zuwa nau'in dijital mai inganci, canja wurin su ga wani mutum, da kuma ba wannan mutum damar fahimtar ma'anar ra'ayin daidai.

Wannan bincike yana tattara fannoni da yawa na kimiyya tare.

Brain-Computer Interfaces: ana amfani da su don yin rikodi da nazartar siginolin da aka samu daga kwakwalwar mutum.

Artificial Intelligence: ana amfani da ita don ayyuka kamar gano tsari a siginolin neural, samar da yare, fahimtar ra'ayoyi da gyara kurakurai.

Information Theory: tana taimakawa wajen tantance ta lissafi yadda za a iya canja wurin bayanai da inganci da daidaito.

Secure Digital Networking: tana taimakawa wajen aika bayanan da aka samar da lafiya zuwa wani tsarin kwamfuta.

Brain stimulation da fasahohin neural: na iya taimakawa wajen bincika yiwuwar nan gaba na isar da takamaiman bayanai kai tsaye ga tsarin neural na mai karɓa. Muhimmi ne a yi gwaje-gwaje masu yawa na likitanci da kimiyya don wannan.

Muhimmiyar dama a wannan bincike na iya kasancewa a ƙirƙirar hanyar da ke isar da ma'anar abin da mutum yana son bayyana, ba tare da buƙatar samar da kuma canja wurin kowace kalma da yake son faɗa ba.

Misali, bari mu ce mutum yana tunani kamar haka:

"Na yarda da wannan shirin. Amma ina so in jinkirta aiwatar da shi har zuwa mako mai zuwa."

Fasahar nan gaba na iya ƙoƙarin gano muhimman abubuwa uku a wannan tunani.

Na farko, yarda da shirin.

Na biyu, rashin son aiwatar da shi nan da nan.

Na uku, buƙatar jinkirta shi zuwa mako mai zuwa.

Artificial intelligence na iya gano waɗannan ma'anoni na asali kuma ta gina jimla da wani mutum zai iya fahimta.

Amma akwai babban ƙalubale a nan.

Ba isa ba ne jimlar da artificial intelligence ke samarwa ta kasance mai kyau a harshe kawai.

Dole ne ta bayyana, ba tare da canzawa ba, ra'ayin da mutum na farko ya yi niyyar isarwa da gaske.

Wannan shine muhimmancin ra'ayin da ake kira Semantic Communication.

5. Tsarin Fasaha da Aka Gabatar

Za a iya raba tsarin farko na aiwatar da wannan bincike zuwa manyan matakai shida.

Mataki na 1: Yin Rikodin Siginolin Kwakwalwa

Mutum yan yanke shawarar, da cikakken izininsa, isar da bayanai ga wani.

A wannan lokaci, ana yin rikodin ayyukan kwakwalwa da ke da alaƙa da kalma, umarni ko ra'ayin da yake ƙoƙarin bayyana da gangan da taimakon daidaitaccen neural interface.

A binciken matakin farko, za a iya amfani da hanyoyin da ba na tiyata ba kamar EEG da bayanan bincike da aka riga aka buga.

Mataki na 2: Gano Tunanin da Artificial Intelligence

Samfuran machine-learning suna nazartar siginolin kwakwalwa da aka yi rikodi.

Manufa ita ce gano bayanan da mutum ya ƙoƙarta isarwa da gangan.

Dole ne bincike ya fara da gano ƙananan kalmomi, umarni ko ra'ayoyi.

Sai bayan an tabbatar da daidaiton wannan fasahar asali ne ake kamata a ci gaba da fahimtar tunani mai wuya.

Mataki na 3: Mayar da Tunani Zuwa Bayanai Masu Tushe a Ma'ana

Ana mayar da bayanan da aka gano, da taimakon artificial intelligence, zuwa nau'in dijital da aka tsara.

Wannan na iya haɗawa da manyan ra'ayoyin tunanin, dangantakar da ke tsakaninsu, yanayi da rashin tabbacin ƙiyasin.

Wannan yana sa ya zama yiwuwar wakiltar ma'ana ta asali ta bayanan a cikin tsarin kwamfuta ko kafin a samar da cikakkiyar jimla.

Mataki na 4: Canja Wurin Bayanai Mai Aminci da Sauri

Ana aika bayanan da aka samar zuwa wani tsarin ta hanyar tashar sadarwar dijital da aka ɓoye da aminci.

A wannan mataki, saurin cibiyar sadarwar kwamfuta bai kamata ya zama babban ƙalubale ba.

Cibiyoyin sadarwar kwamfuta na yau sun riga suna da ƙarfin canja wurin bayanai da babban sauri.

A maimakon haka, fahimtar siginolin kwakwalwa daidai, samar da ra'ayi mai dacewa da rage lokacin da dukkanin tsarin ke ɗauka na iya zama matsaloli masu wahala.

Mataki na 5: Sake Gina Saƙon Ga Mai Karɓa

Artificial intelligence tana mayar da bayanan da aka karɓa zuwa nau'in da wani mutum zai iya fahimta.

Na iya zama rubutu, magana ko wani nau'i na sadarwa da ya dace.

Dole ne a ba mai karɓa damar fahimtar ma'anar bayanan, tambayar ƙarin bayani idan yana da shakka, da kuma sanin rashin tabbacin da ke cikin ƙiyasin artificial intelligence.

Mataki na 6: Tabbatar da Cewa An Fahimci Saƙon

Dole ne a tabbatar da cewa mai karɓa ya fahimci ra'ayin daidai.

Inda akwai buƙata, dole ne a kuma samar da damar neman bayani ko gyara.

Idan za a ƙirƙira sadarwa kai tsaye ta brain-to-brain a nan gaba, dole ne a kuma haɓaka fasaha daban da za ta iya isar da bayanai ga tsarin neural na mai karɓa.

Dole ne a lura da wani muhimmin bambanci a nan.

Mayar da siginolin kwakwalwar mutum ɗaya zuwa rubutu ta kwamfuta kuma wani mutum ya karanta su a kan allo sadarwa ce ta brain-computer-human.

Ba za a iya kiranta cikakkiyar sadarwa kai tsaye ta brain-to-brain ba.

Dole ne a kiyaye wannan bambanci a sarari a kowane mataki na binciken.

6. Babbar Ƙaddamarwa ta Kimiyya ta Wannan Bincike

Ana gabatar da babbar ƙaddamarwa ta wannan bincike kamar haka.

Ta gano, da taimakon artificial intelligence, bayanan neural da mutane suke son isarwa da gangan, da kuma mayar da ma'anarsu zuwa nau'in dijital mai inganci, za a iya isar da wasu ra'ayoyi ga wasu a cikin ƙaramin lokaci fiye da magana ko rubutu, yayin da ake kiyaye daidaito da za a iya karɓa.

Za a iya gwada wannan ƙaddamarwa a kimiyance.

Don wannan, za a iya musanya nau'in bayanai guda ta hanyar magana ta yau da kullum, rubutu da neural interfaces da aka haɗa da artificial intelligence.

A duk inda ya yiwu, ya kamata a yi amfani da mahalarta iri ɗaya da bayanai iri ɗaya don kwatanta sakamakon.

Ayyuka masu zuwa suna da muhimmanci a wannan bincike.

1. End-to-End Latency

Lokacin daga lokacin da mutum ɗaya ya fara isar da bayanai har sai wani mutum ya karɓe su daidai.

2. Effective Information-Transfer Rate

Aunin yawan bayanai da aka canja wurin daidai a dakika ɗaya, bayan an lissafa kurakurai da gyare-gyare.

3. Semantic Fidelity

Kamancen ma'ana tsakanin ra'ayin da mutum na farko yake son isarwa da ra'ayin da mutum na biyu ya fahimta.

4. Error Rate

Yawan kalmomi, ra'ayoyi, dangantaka da kammalawa da aka gano ba daidai ba.

5. Receiver Comprehension

Aunin ko mutumin da ya karɓi bayanan ya fahimci ma'anarsu ta gaske daidai.

6. User Effort

Hankali, ƙalubalen zuciya ko gajiya, horo da sauƙin amfani da ake buƙata don amfani da fasahar.

7. Privacy Protection

Sa ido kan ko an bayyana tunani ko bayanai da mai amfani bai ba da izini ba a bisa kuskure.

Ba za a iya cewa fasaha ta ƙara saurin sadarwa tsakanin mutane kawai saboda haɗin cibiyar sadarwarta yana da sauri ba.

Hakazalika, gaskiyar cewa artificial intelligence tana samar da jimla da sauri ba shaida ce mai isar ba.

Dole ne a auna cikakken tsarin sadarwa na mutum-zuwa-mutum.

7. Shirin Binciken Gwaji da Aka Gabatar

Za a iya gudanar da wannan bincike a manyan matakai uku.

Mataki na Farko: Gano Niyyoyin Mutum

Da farko, dole ne a bincika ko za a iya gano wasu ƙa'idodin ra'ayoyi da mutane suke son isarwa da gangan daga siginolin kwakwalwa.

Za a iya amfani da bayanan EEG da aka riga aka buga, ko sababbin bincike da aka yi da izini da buƙatu daidai.

Misali, mahalarta na iya ƙoƙarin isar da ɗaya daga cikin waɗannan ra'ayoyi.

• Na yarda.

• Ban yarda ba.

• Ina buƙatar taimako.

• Ina buƙatar ƙarin bayani.

Za a iya amfani da samfuran machine-learning don bincika ko bambance-bambance suna bayyana a cikin siginolin kwakwalwa da ke da alaƙa da waɗannan ra'ayoyi.

Sai a kimanta aikin samfurin ta amfani da bayanan da ba a yi amfani da su a horo ba, zaɓaɓɓun gwaje-gwaje daban-daban da mahalarta masu zaman kansu.

Muhimmiyar tambaya a wannan mataki:

Shin yana yiwuwa a gano cikin tabbaci, daga siginolin kwakwalwa, ra'ayin da mutum yana son isarwa?

Mataki na Biyu: Canja Wurin Ma'ana da Taimakon Artificial Intelligence

Sai a yi ƙoƙarin mayar da bayanan da aka gano a mataki na farko zuwa cikakkun ra'ayoyi da taimakon artificial intelligence.

Dole ne a kwatanta bangarori uku a nan.

Na farko, ra'ayin da mai aikawa ya yi niyyar isarwa da gaske.

Na biyu, ra'ayin da artificial intelligence ta sake gina.

Na uku, ma'anar da mutumin da ya karɓi wannan bayanin ya fahimta.

Dole ne a bincika yadda waɗannan uku suke jituwa daidai ta hanyoyin lissafi da kididdiga.

Mafi muhimmanci, lokacin da ra'ayi bai bayyana ga artificial intelligence ba, dole ne ta nuna rashin tabbacinta maimakon samar da bayanai marasa dacewa.

Dole ne a kwatanta aikin wannan hanyar da rubutu na yau da kullum, magana da sauran hanyoyin sadarwa.

Mataki na Uku: Sadarwa Tsakanin Mutane

A mataki na uku, za a iya gudanar da gwaje-gwajen canja wurin bayanai tsakanin mutane biyu da suke shiga da cikakken izini.

Mutum na farko yana ƙoƙarin isar da bayanai da gangan ta hanyar siginolin kwakwalwa.

Artificial intelligence tana nazartar wannan sigina, tana gano bayanan da suka dace kuma tana aika su da lafiya.

Mutum na biyu yana karɓa kuma yana fahimtar wannan bayanin.

Sai a auna sauri, daidaito da tabbacin cikakken tsarin sadarwa.

Isar da bayanai kai tsaye ga kwakwalwar mai karɓa zai zama mataki na bincike mai ci gaba da daban sosai.

Irin waɗannan ƙoƙari suna buƙatar ƙwarewar neural, amincewar mahukunta, kariyar likitanci da tsauraran kulawar ɗabi'a.

Don haka ya kamata a ba da fifiko, a binciken matakin farko, ga tabbatar da ko artificial intelligence na iya inganta aikin sadarwa tsakanin mutane.

8. Ƙalubalen Kimiyya da Ƙuntatawa na Yanzu

Akwai ƙalubale da yawa masu muhimmanci a wannan bincike.

Na farko, ba dukkan kwakwalwar mutane ke wakiltar kalmomi da ra'ayoyi a cikin tsarin neural iri ɗaya ba.

Don haka kowane mutum na iya buƙatar horo daban ko daidaita samfurin.

Na biyu, siginolin da aka yi rikodi a hanyoyin da ba na tiyata ba kamar EEG na iya ɗauke da babban ƙazanta da rikici.

Idan aka kwatanta da electrodes da aka shuka a cikin kwakwalwa, ƙarfin gano wasu nau'o'in ayyukan neural a cikin ƙanƙanta na iya zama ƙarami.

Na uku, ƙoƙarin yin magana, tunanin magana a zuciya, niyyar bayyana ra'ayi da tunani a sirri ba nau'in ayyukan neural iri ɗaya ba ne.

Dole ne a yi nazarin waɗannan daban-daban.

Na huɗu, large language models wani lokaci na iya samar da jimloli waɗanda ba gaskiya ba ne amma suna bayyana da kyau, bisa bayanan da suke da su.

A fasahar musanya tunanin mutum, irin waɗannan kurakurai na iya zama matsala mai girma.

Saboda, gaya wa mutum cewa mutum ya yi tunanin abin da bai yi tunanin ba na iya ƙirƙirar babban rashin fahimta.

Na biyar, yana da muhimmanci sosai cewa wasu masu bincike za su iya sake samun sakamakon binciken kimiyya.

Binciken da aka buga a Journal of Neural Engineering a shekarar 2026 ya nuna cewa akwai matsaloli da yawa a sake samar da sakamakon binciken da ke gano magana da ake tunani.

Daga cikin bayanan speech-imagery da aka bincika a wannan bincike, kawai 36% na mahalarta ne suka samu daidaiton rarrabawa da ya wuce iyakar muhimmancin kididdiga da ya dace [10].

Wannan yana nuna yadda tabbatarwa mai zaman kanta, hanyoyin bincike na bayyanannu da gwaji mai tabbaci suke da muhimmanci a wannan fanni.

A ƙarshe, saurin canja wurin bayanai ba shine kaɗai ƙalubalen ba.

Hankalin mutum, ƙwaƙwalwa, ƙarfin fahimta da tsarin tunani ma suna da rawar da suke takawa a wannan.

Cire buƙatar yin magana ba ya goge lokacin da ake buƙata don ƙirƙirar ko fahimtar tunani mai wuya gaba ɗaya.

Bisa shaidar kimiyya ta yanzu, ba za mu iya cewa za a iya musanya dukkan nau'o'in tunanin mutum kai tsaye da saurin gigabit ba.

Ɗaukar saurin canja wurin bayanan dijital da saurin canja wurin tunanin mutum mai ma'ana a matsayin abu ɗaya hanya ce marar kyau a kimiyya.

9. Sirri, Tsaron Bayanai da Haƙƙin Mutum

Fasahohin da ke fassara siginolin neural na kwakwalwar mutum suna kuma ƙirƙirar manyan nauyayen ɗabi'a.

A cikin tsarin kwamfuta na yau da kullum, kawai bayanan da mutum ya bayar da son ransa ne ake sarrafawa.

Amma neural interface na iya kuma yin rikodin siginolin da ke da alaƙa da ayyukan zuciya na sirri na mutum, waɗanda baya son gaya wa wasu.

Don haka muhimmiyar ƙa'idar farko ta bincikenmu dole ne ta kasance kamar haka.

Kawai bayanan da mutum yana son raba da cikakken izininsa da gangan ne ya kamata a gano kuma a aika ga wasu.

Don aiwatar da wannan ƙa'ida, ana buƙatar matakai na kariya daban-daban.

Mai amfani dole ne ya sami sarrafa bayyananne don fara sadarwa.

A duk inda ya yiwu, dole ne a sarrafa bayanan neural a na'urar mai amfani kanta.

Dole ne a aika bayanan a cikin nau'i da aka ɓoye (encrypted).

Dole ne a ƙirƙira ƙarfafa tsarin tsaro don hana mutanen da ba a ba su izini ba samun damar siginolin kwakwalwa.

Dole ne a guji adana bayanan neural da ba a buƙata na dogon lokaci.

Mai amfani dole ne ya sami damar dakatar da canja wurin bayanai nan da nan a kowane lokaci.

Bugu da ƙari, dole ne a bayyana a sarari cewa tunanin da artificial intelligence ke samarwa ba rikodin daidai ɗari bisa ɗari na tunanin zuciyar mutum ba ne.

Ƙiyasa ne da aka ƙirƙira bisa siginolin neural.

A watan Nuwamba 2025 UNESCO ta amince da shawarwarin ƙasa da ƙasa game da amfani mai ɗabi'a na neurotechnology [11].

Wannan shawara tana jaddada sirrin zuciya, mutuncin mutum da amfani da neurotechnology cikin alhaki.

A bincikenmu ma, tare da ci gaban fasaha, dole ne a ci gaba da sirri da matakan kariya na ɗabi'a.

10. Aikace-aikacen Nan Gaba na Wannan Fasaha

Idan wannan bincike ya yi nasara, waɗanda za su fara amfana sune mutanen da ke da matsaloli masu tsanani a magana da motsin jiki.

Musamman, brain-computer interface na iya ƙirƙirar sababbin damammaki ga mutanen da ba za su iya sadarwa ba saboda ciwon ganye na motor da wasu cututtukan neural.

Haka kuma za a iya amfani da irin wannan fasaha a wasu yanayi na musamman inda sadarwa ke da wahala ta hanyar magana ko motsin jiki.

Bugu da ƙari, na iya kuma inganta sauƙin amfani da kwamfuta ga nakasassu.

A dogon lokaci, wannan bincike na iya kuma taimakawa wajen sa sadarwa tsakanin mutane da tsarin artificial intelligence ta zama mai inganci.

Amma dole ne a tabbatar da amfanin kowane irin wannan aikace-aikace a kimiyance ɗaya-ɗaya.

Ba za mu iya tunani a gaba cewa sadarwa kai tsaye ta neural mafi kyau ce fiye da tattaunawa ta yau da kullum a kowane yanayi ba.

Saboda harshen mutum ba kawai kayan aiki ne na bayar da bayanai a hankali ba.

Haka kuma yana yin ayyuka masu muhimmanci kamar tunani, yin hujja, bayyanar motsin rai, sa ra'ayoyi su bayyana da gina dangantakar mutane.

Don haka sabuwar fasaha ta kamata ta ƙara ƙarfin sadarwar mutum, ba tare da asarar waɗannan muhimman halaye na harshen mutum ba.

11. Haɗin Gwiwar Kimiyya ta Wannan Bincike da Hanyar Nan Gaba

Ba a gabatar da wannan bincike bisa ra'ayin cewa an riga an ƙirƙira fasahar da ke canja wurin dukkan tunanin mutum kai tsaye ba.

A maimakon haka, an gabatar da shi a matsayin tsarin bincike na kimiyya wanda ke haɗa gano siginolin kwakwalwa, fahimtar ma'anar tunani da taimakon artificial intelligence, aunin aikin canja wurin bayanai da kuma ƙimar tunanin mutum na gaske.

Babban tambayarta ba ita ba ce:

Shin za a iya ƙirƙirar cikakken ƙarfin canja wurin bayanai na cibiyar sadarwar lantarki a kwakwalwar mutum?

Babbar tambaya ita ce - shin za a iya rage lokacin da ke tsakanin lokacin da aka ƙirƙira tunani a zuciyar mutum da lokacin da wani mutum ya fahimci wannan tunani daidai?

Don haka, shin bayyanar bayanai da ta dogara da ma'ana wadda aka samar da taimakon artificial intelligence na iya ba da ƙarin aiki idan aka kwatanta da fasahar neural na gano magana ta yau da kullum? Dole ne a bincika hakan.

Cewa fasaha ɗaya ta yi nasara, ba isa ba ne cewa artificial intelligence tana samar da jimloli masu kyau.

Dole ne ta rage lokacin canja wurin bayanai.

Dole ne ta kiyaye ma'anar tunanin da aka aika.

Dole ne ta sarrafa kurakurai a matakin da za a iya karɓa.

Dole ne ta yi aiki cikin tabbaci a cikin mutane daban-daban da kuma a yanayi na aiki.

Dole ne a tabbatar da waɗannan sharuɗɗa ta gwajin kimiyya.

Dole ne bincike ya yarda cewa wasu hanyoyi na iya kasancewa ba su nuna aiki mafi kyau fiye da sadarwa ta yau da kullum ba.

Ƙimar gaske ta binciken kimiyya ba kawai tabbatar da sakamakon da aka riga aka yi tsammani ba ce.

Yana cikin yanke shawara, bisa shaida mai tabbaci, ko ƙaddamarwa ta dace ko kuma ba ta dace ba.

12. Kammalawa

A cikin 'yan shekaru goma da suka gabata, fasahar canja wurin bayanan kwamfuta ta samu babban ci gaba.

A yau, kwamfutoci a sassa daban-daban na duniya suna musanya manyan bayanai da babban sauri.

Amma sadarwa tsakanin mutane har yanzu tana dogara da magana, rubutu da sauran bayyanawar jiki.

Binciken neural na kwanan nan ya kawo ci gaba mai mahimmanci wajen sake gina magana daga siginolin kwakwalwa, gano magana da ake tunani a zuciya da kuma canja wurin takamaiman bayanai tsakanin kwakwalwa.

Duk da haka, fasahar da ke musanya dukkan nau'o'in tunanin mutum kai tsaye, daidai da kuma da babban sauri har yanzu ba a ƙirƙira ta ba.

Wannan ya ci gaba da kasancewa babban ƙalubale na kimiyya da ake buƙatar magancewa.

A nan gaba, haɗin artificial intelligence da neurotechnology na iya ƙirƙirar sababbin hanyoyi waɗanda ke rage lokacin da mutane ke ɗauka don bayyana tunaninsu.

Bincikensa na aiki dole ne ya fara daga siginolin neural da mutane suke son bayarwa da gangan.

Sai a ƙirƙira samfuran da ke gano su daidai.

Bayan haka, dole ne a ƙima yadda ake kiyaye ma'ana ta gaske ta bayanan daidai.

A ƙarshe, dole ne a tabbatar a kimiyance ko wannan fasaha da gaske tana inganta saurin da aikin sadarwa tsakanin mutane.

Sai kawai za mu iya ci gaba zuwa ga fasaha mafi ci gaba kamar cikakkiyar sadarwa kai tsaye ta brain-to-brain.

Manufar Ƙarshe ta Bincikena

Manufar ƙarshe ta bincikena ita ce rage, gwargwadon yiwuwa, rata da ke tsakanin saurin da ake ƙirƙirar tunani a zuciyar mutum da saurin da wani mutum ke fahimtar ma'ana ta gaske ta wannan tunani daidai.

Don hakan, hanyar da nake gabatarwa ita ce haɗa artificial intelligence, brain-computer interface, neuroscience, information theory da fasahar sadarwa mai aminci da sauri tare da bincika su.

Manufarmu ba kawai aika ƙarin bayanai da babban sauri ba ce.

Manufarmu ita ce ƙirƙirar tushen kimiyya na sabuwar hanyar sadarwa da za ta iya musanya tunani da ra'ayoyin mutane yayin da ake kiyaye ma'anarsu ta gaske, cikin aminci, daidai da kuma a cikin ƙarancin lokaci.

Mazaba

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8. Kunz, E. M., et al. (2025). Inner speech in motor cortex and implications for speech neuroprostheses. Cell, 188(17), 4658–4673.e17. https://doi.org/10.1016/j.cell.2025.06.015
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By Keshavan Thiagaraja

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