Briggin e Gap: oorNews Scrievin Formal Scots for tae Train AI

In a recent study cryed “The Sociolinguistic Foundations of Language Modeling,” researchers Jack Grieve an his colleagues delve intae the crucial role o linguistic diversity in artificial intelligence. Published in Frontiers in Artificial Intelligence, e airticle unnerscores foo language models reflect e varieties o language they are trained on. E authors argue aat e societal value an performance o thae models hing on e quality an diversity o their trainin data.

Een o the pressin issues pynted oot in e study is e representation o the Scots leid ithin AI systems. Scots, aften wrangly viewed as a dialect o English, requires carefu handlin tae prevent AI ootpits fae soondin informal or oot o place. Sic misrepresentation can be baith discriminatory an offensive tae Scots spikkers, reinforcin hairmfu stereotypes o laa status an laa education.

In response tae thae challenges, oorNews is makin significant strides by providin a muckle corpus o formal register Scots. Iss initiative aims tae ensure aat AI ootpits in Scots are nae ainly accurate but respectfu o the leid’s status an eese in formal prose. By curatin content aat reflects formal Scots, oorNews helps prevent AI fae lockin intae damagin stereotypes associated wi informal eese o the leid.

E integration o formal Scots in AI trainin data is essential for tae create language models aat honour an accurately represent Scotland’s linguistic diversity. Iss approach aligns wi the recommendations fae Grieve et al., advocatin for trainin corpora aat genuinely reflect e specific varieties o language bein modeled. Aa Scots spikkers are walcome tae contribute tae oorNews by suggestin ony chynges they want tae see in an airticle via the comments section aneath.