“As artificial intelligence (AI) adoption continues to grow across the Federal government, officials said on July 15 it’s important to share lessons learned across the government, and spoke about the importance of operational and organization efficiencies in the AI adoption process…”
“Bryan Lane, Director of Data and AI at GSA, said the agency made sure to take an honest account of its own organizational and operational maturity, and along those lines said it’s also important to determine whether a strategy or roadmap and requirements to drive the AI journey are in place.
‘Do you have the right development programs to train and educate people on artificial intelligence?’ posited Lane. ‘As we move through the layers of operational maturity for AI, we get into things like DevSecOps cloud and infrastructure data operations, machine learning operations, and you can have different levels of maturity across those operational areas. You can have a very mature cloud DevSecOps environment, but you may have data scientists that are still operating on local machines and testing one-shot models.’…”
“A key part of the AI journey is data, and accounting for the data that the agency will be utilizing. Elanchezhain Sivagnanam, Chief Enterprise Architect at NSF, said that a mature deployment of AI requires establishing training data and building an efficient feedback loop.
‘I think the bottom-most layer – the foundational layer— would be the trustworthy training data,’ said Sivagnanam. ‘How do we develop a trustworthy training data that the parent automation needs to publish good documentation … and needs to be automated and all that stuff? It needs to have good inventory definitions, lineage, and also associated legal policies and that’s very important to how we use the data.’…” Read the full article here.
Source: Feds Call Operational, Organizational Maturity Keys for AI Deployment – By Jordan Smith, July 16, 2021. MeriTalk.