{"id":6804,"date":"2023-10-26T19:21:21","date_gmt":"2023-10-26T19:21:21","guid":{"rendered":"https:\/\/dailyai.com\/?p=6804"},"modified":"2023-10-26T21:16:11","modified_gmt":"2023-10-26T21:16:11","slug":"new-research-into-datasets-reveals-systemic-ethical-and-legal-issues","status":"publish","type":"post","link":"https:\/\/dailyai.com\/da\/2023\/10\/new-research-into-datasets-reveals-systemic-ethical-and-legal-issues\/","title":{"rendered":"Ny forskning i datas\u00e6t afsl\u00f8rer systemiske etiske og juridiske problemer"},"content":{"rendered":"

AI drejer sig om data, men hvor kommer de fra? Er datas\u00e6t lovlige og etiske? Hvordan finder udviklere ud af det med sikkerhed?\u00a0<\/b><\/p>\n

Tr\u00e6ning af maskinl\u00e6ringsmodeller som f.eks. store sprogmodeller (LLM) kr\u00e6ver store m\u00e6ngder tekstdata.\u00a0<\/span><\/p>\n

Der er stakkevis af datas\u00e6t tilg\u00e6ngelige p\u00e5 platforme som Kaggle, GitHub og Hugging Face, men de befinder sig i en juridisk og etisk gr\u00e5zone, prim\u00e6rt p\u00e5 grund af problemer med licenser og fair use.\u00a0<\/span><\/p>\n

Den Initiativ til data-proveniens<\/a>et samarbejde mellem AI-forskere og jurister, har gennemg\u00e5et tusindvis af datas\u00e6t for at kaste lys over deres sande oprindelse. <\/span><\/p>\n

Den <\/span>fokuserede p\u00e5 over 1.800 datas\u00e6t, der var tilg\u00e6ngelige p\u00e5 platforme som Hugging Face, GitHub og Papers With Code. <\/span>Datas\u00e6ttene er hovedsageligt designet til at finjustere open source-modeller som Llama-2.\u00a0<\/span><\/p>\n

Unders\u00f8gelsen viste, at ca. 70% af disse datas\u00e6t enten manglede klare licensoplysninger eller var m\u00e6rket med alt for tilladte licenser.\u00a0<\/span><\/p>\n

Med en \u00e5benlys mangel p\u00e5 klarhed om copyright og begr\u00e6nsninger for kommerciel brug risikerer AI-udviklere ved et uheld at bryde loven eller overtr\u00e6de copyright.<\/span><\/p>\n

Shayne Longpre, en ph.d.-kandidat ved MIT Media Lab, som stod i spidsen for revisionen, understregede, at problemet ikke er hostingplatformenes skyld, men snarere et systemisk problem inden for maskinl\u00e6ringssamfundet.<\/span><\/p>\n

2023 har v\u00e6ret vidne til en B\u00f8lge af retssager<\/a> rettet mod store AI-udviklere som Meta, Anthropic og OpenAI, som er under ekstremt pres for at indf\u00f8re en mere gennemsigtig dataindsamlingspraksis. Forordninger som f.eks. EU's lov om kunstig intelligens<\/a>er indstillet til at h\u00e5ndh\u00e6ve netop det.\u00a0<\/span><\/p>\n

Data Provenance Initiative g\u00f8r det muligt for maskinl\u00e6ringsudviklere at <\/span>Udforsk de reviderede datas\u00e6t her<\/span><\/a>. Initiativet analyserer ogs\u00e5 m\u00f8nstre i datas\u00e6ttene og kaster lys over deres geografiske og institutionelle oprindelse.\u00a0<\/span><\/p>\n

De fleste datas\u00e6t er konstrueret i det engelsktalende globale nord, hvilket fremh\u00e6ver sociokulturelle ubalancer.\u00a0<\/span><\/p>\n

\"Data-proveniens
Data Provenance Initiative fandt ud af, at datas\u00e6t overvejende repr\u00e6senterer engelsktalende lande og det globale nord. Kilde: Data Provenance.org<\/a>.<\/figcaption><\/figure>\n

Mere om unders\u00f8gelsen<\/span><\/h2>\n

Denne omfattende analyse af datas\u00e6t afsl\u00f8rede systematiske problemer med, hvordan data indsamles og distribueres. Initiativet har ogs\u00e5 udarbejdet et dokument, der forklarer deres resultater, <\/span>udgivet her<\/span><\/a>.<\/span><\/p>\n

Her er flere oplysninger om unders\u00f8gelsens metoder og resultater:<\/span><\/p>\n

    \n
  1. Analyse af datas\u00e6t for oprindelse og m\u00e6rkning<\/b>: Denne unders\u00f8gelse reviderede systematisk over 1800 finjusteringsdatas\u00e6t for at granske deres datafrembringelse, licensering og dokumentation.\u00a0<\/span><\/li>\n
  2. Bevis for forkert m\u00e6rkning<\/b>: Resultaterne fremh\u00e6vede kl\u00f8ften i datatyper, der er tilg\u00e6ngelige under forskellige licenser, og konsekvenserne for juridiske fortolkninger af copyright og fair use. Det afsl\u00f8rede en h\u00f8j grad af fejlkategorisering af licenser, hvor over 72% af datas\u00e6ttene ikke specificerede en licens og en fejlprocent p\u00e5 50% i dem, der gjorde.<\/span><\/li>\n
  3. Up\u00e5lidelig data-proveniens<\/b>: Forskningen henleder opm\u00e6rksomheden p\u00e5 sp\u00f8rgsm\u00e5let om up\u00e5lidelig dataherkendelse og understreger behovet for standarder til at spore dataherkendelse, sikre korrekt tilskrivning og tilskynde til ansvarlig brug af data.\u00a0<\/span><\/li>\n
  4. Geografisk udbredelse: <\/b>Unders\u00f8gelsen fremh\u00e6ver en alvorlig mangel p\u00e5 repr\u00e6sentation og tilskrivning af datas\u00e6t, der stammer fra det globale syd. De fleste datas\u00e6t drejer sig om det engelske sprog og er kulturelt bundet til Europa, Nordamerika og det engelsktalende Oceanien.\u00a0<\/span><\/li>\n<\/ol>\n

    Denne unders\u00f8gelse fremh\u00e6ver systemiske og strukturelle problemer i, hvordan data skabes, distribueres og bruges. Data er en kritisk ressource for AI, og ligesom naturressourcer er de begr\u00e6nsede.\u00a0<\/span><\/p>\n

    Der er bekymring for, at AI-teknologien med tiden vil vokse sig st\u00f8rre end de nuv\u00e6rende datas\u00e6t og m\u00e5ske endda <\/span>begynder at forbruge sit eget output<\/span><\/a>Det betyder, at AI-modeller vil l\u00e6re af AI-genereret tekst.\u00a0<\/span><\/p>\n

    Det kan forringe kvaliteten af modellerne, hvilket betyder, at etiske og lovlige data af h\u00f8j kvalitet kan blive meget v\u00e6rdifulde. <\/span><\/p>","protected":false},"excerpt":{"rendered":"

    AI drejer sig om data, men hvor kommer de fra? Er datas\u00e6t lovlige og etiske? Hvordan kan udviklere afg\u00f8re det med sikkerhed? Tr\u00e6ning af maskinl\u00e6ringsmodeller som f.eks. store sprogmodeller (LLM) kr\u00e6ver store m\u00e6ngder tekstdata. Der er stakkevis af datas\u00e6t tilg\u00e6ngelige p\u00e5 platforme som Kaggle, GitHub og Hugging Face, men de befinder sig i en juridisk og etisk gr\u00e5zone, prim\u00e6rt p\u00e5 grund af licens- og fair use-problemer. Data Provenance Initiative, som er et samarbejde mellem AI-forskere og jurister, har gennemg\u00e5et tusindvis af datas\u00e6t for at kaste lys over deres sande oprindelse. Det fokuserede p\u00e5 over 1.800<\/p>","protected":false},"author":2,"featured_media":6806,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[84],"tags":[454,453,105],"class_list":["post-6804","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-industry","tag-data","tag-datasets","tag-machine-learning"],"yoast_head":"\nNew research into datasets reveals systemic ethical and legal issues | DailyAI<\/title>\n<meta name=\"description\" content=\"AI revolves around data, but where does it come from? Is it legal to use? 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