In-house expertise would help ease reticence about these technologies, crucial for public sector digitalisation.
Building up in-house data science and artificial intelligence expertise would help public sector organisations ease misgivings about these technologies, which are essential for making governments more efficient and responsive, say Hertie School researchers at the Centre for Digital Governance and Data Science Lab in a new policy brief.
In “Data science and AI in government,” Professor of Public and Financial Management and Director of the Centre for Digital Governance Gerhard Hammerschmid, Prof of Data Science and Director of the Hertie School Data Science Lab Slava Jankin and PhD Researcher Maximilian Kupi discuss how data science and artificial intelligence can expedite the much-needed digital transformation of the public sector.
These technologies are already helping to improve regulatory efforts, public services and engagement, law enforcement and adjudication, to name a few, the researchers say. But the reliance on outside expertise to make use of these technologies raises a number of governance questions like data privacy, security, compliance and accountability.
“Governments are reticent about using these applications, in no small part because they lack in-house data science and AI capacities,” the researchers write. They need to build up their own capabilities and reduce their dependence on outside expertise.
Drawing on international experience, they provide six recommendations for successfully building and technical capacities in government. Among these are: making jobs more attractive to technology experts, building communities of practice and centres of excellence, strengthening interdisciplinary networks, and holding collaborative hackathons and competitions.
Read the full policy brief here: