AI technologies provide computers with the ability to make decisions and learn without explicit programming. AI has already been observed with respect to intelligent personal assistants, and autonomous vehicles. Concerning public services, AI technologies are envisioned in many areas such as, comprehensive digital government services, providing intelligent virtual assistants, automating payments from and to citizens and gathering public opinion to drive policy.


The technological elements of Blockchain, originally conceived for Bitcoin, are recognised as having far-reaching potential for government. Core Technologies are: i. Distributed Ledger Technology (DLT) — a decentralized database of transactions secured by cryptographic sealing. And, ii. Smart Contracts — rules, which attempt to codify transactions such that the records managed by the distributed ledger are authoritative with respect to the underlying legal agreements they represent.


The IoT provides a unique opportunity to interconnect and dynamically manage public infrastructure. Any device with an on/off switch will have an identifier, communicate and be managed by ‘intelligent’ software. ‘Smart Cities’ are envisioned, where informatics and technologies are used to improve the efficiency of services. ICT will enable officials to interact directly with the community and city infrastructure, monitoring how the city is evolving in real time.


Government collects huge volumes of data and thus has major opportunities for so-called big data (analytics). In general, big data provides the opportunity of examining large and varied data sets to uncover hidden patterns, unknown correlations, customer preferences, etc. Big data encompass a mix of structured, semi-structured and unstructured data gathered formally through interactions with citizens, social media content, phone call data and records, data captured by sensors connected to the Internet-of-things and so on.


A subset of Big Data is Behavioural/Predictive analytics. These focus on providing insight into the actions of people, uncovering hidden patterns and unknown correlations, helping to make informed decisions. Behavioural Analytics centres on understanding how consumers act, and are likely to act in the future. Predictive Analytics extracts information from historical and real-time datasets to determine patterns and predict future outcomes.


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