Government & Public Sector
Use Cases
Newsfor Government & Public Sector
Allocate access to public goods such as healthcare for individuals
Using algorithms to allocate access to public goods. This may be to distribute access fairly, efficiently, effectively - or for more broad political goals (minimise dissent and reward behaviour).
Analyse social media data to evaluate architectural or planning impact of new developments
Analyse social, traffic data to measure potential impact of new building developments. Modeled outcomes might indicate hazards (e.g. fire evacuation risks) or design features for consideration (e.g. siting of facilities etc)
Assess environmental health status and bio-diversity of natural sites
Using cameras to take photos of environmentally sensitive sites - whether above or below the waves - which can then be analysed, and the contents of pictures classified, to estimate their overall health status. Issues that might be included would be bio-diversity of flora and health status of things like coral. Future iterations might assess small creatures - fish or insects - to add depth to the calculations.
Automate customer service disruption alerts
Using social media to compile information to identify service disruptions. Angry or worried tweeting (or similar) by customers or announcements by operators will trigger consolidated public service alerts on service disruptions. This is most advanced in transport networks but could be applied to other services.
Automate decision processes for applications or permitting
Replicate (often back-office decision) processes for applications, permitting, tax auditing, etc
Codify legal expertise for automated deployment
Codifying legal expertise so that it is more widely available and understandable - potentially deployed through the medium of a text chatbot. Examples might be quick advice on potential bribery and corruption (e.g. what gifts are acceptable), employment law questions or generating NDAs.
Create maps from satellite and other remote imagery
Global distribution and connectivity relieson increasingly accurate mapping to optimise supply chains, distribution and access. Using satellite and other remotely captured images it is increasingly possible to build accurate maps at scale and provide addressing schemes in underserved areas.
Create questionable social media content to influence public opinion
Deployment of falsified media content with the aim of influencing public opinion - either by setting up new narratives or undermining existing narratives. "Memes" are typically deployed.
Detect potentially fraudulent or nefarious users
Detect potentially fraudulent or nefarious users (e.g. individuals under sanctions, investigation etc) through pattern matching of structured and unstructured data on transactions from different sources, such as phone numbers, addresses, company directors and news reports (HSBC, Quantexa, Silent Eight)
Discover anomalies in data scanned from space
Vast amounts of data has been generated by an array of human sensors like telescopes or exploratory spacecraft examining the mysteries of space. Analysing data at this scale is beyond human abilities - especially when part of the challenge is to find things that we did not know existed - so machine learning plays a vital role. Ultimately this may lead to the discovery of something as exciting as extra-terrestrial beings - but that is probably at least as distant as the creation of Artificial General Intelligence....
Forecast macroeconomic variables based on government, proprietary and public data
Forecast macroeconomic variables based on huge volumes of government proprietary and public data - often combined with other data sources to optimise forecasting.
Identify creature characteristics to assist in disease control
Sorting insects by sex enables aggressive intervention (e.g. sterilisation or culling) to minimise their ability to procreate and therefore spread disease. Machine vision enables this to happen at greater scale and pace therefore enabling more significant interventions. This also has research benefits.
Identify illicit use of natural resources, including land and forest
Monitoring and identifying the illicit use of natural resources for activities such as illegal farming, logging, deforestation, etc.
Identify the right match between foster child and foster family
Foster Care Technologies use AI to find better matches for children placed in foster care increasing stability in their lives and chances of permanent adoption
Identify with satellite imagery areas of need for targeted support
Use satellite imagery to identify areas that need the most support and assistance due to lower levels of development or emerging agricultural issues (e.g. poor harvests)
Improve weather forecasting accuracy
Improve weather forecasting accuracy using machine learning applied to multiple data sources. The aim is to improve an existing process that is typically already a sophisticated user of computer modelling.
Manage electronic patient health records
E-records in health systems are a growing set of critically important documents. Machien learning enables them to be created more efficiently and then updated and (where necessary) consolidated more effectively and cheaply.
Manage street cleaning using on-demand approach
Sending out street cleaning teams in response to grafitti or rubbish that has been identified using street and mobile cameras rather than simply deploying in regular sweeps. This ensures that teams respond more swiftly to emerging problems. A similar approach can be applied to tending street vegetation, especially trees.
Model city-wide process flows and cross-departmental outcomes
Merge data flows from multiple sources - visual (satellite, drone, CCTV, Google Street Map etc), demographic and socio-economic, sensors (e.g. traffic flow), social media and other - to build models for prediction and flow modelling and analytics of the city as a system. can be used for short term tactical decisions - traffic stoppages for example - or long term strategic - planning decisions for example. AI co-ordinates, calculates and potentially delivers visualisation.
Model public health outcomes based on multiple social and economic indicators
Using a full spectrum of economic, social, demographic, physical, health and other data to model and predict likely health outcomes in a given population with a focus on emerging chronic and mental health issues. This can help with scenario and investment planning - e..g the impact of housing investment or employment losses on likely mental issues.
Monitor animal populations
Detecting, identifying and monitoring animal populations is especially useful when they are in the wild and potentially at risk. Typically it requires a network of static camera traps or acoustic recorders but can also be extended to include mobile sensors.
Optimise and target labour allocation for publicly provided services
Optimise and target labour allocation for publicly provided services to match demand, especially in areas of constrained supply (e.g. specialist skills)
Optimise pricing for government provided goods and services e.g. tolls or park entrance fees
Optimise pricing for government provided goods and services (e.g. road pricing, park or museum entrance fees)
Optimise procurement strategy to reduce costs for large government agencies
Optimise procurement strategy to reduce costs for large government agencies (e.g., Defence). This is especially viable when used to repeat purchase lower value, commoditised goods - e.g. food or ammunition rather than aircraft carriers.
Optimise public policy decisions to take into account a greater set of complex interactions
Optimise public policy decisions (e.g., housing) to take into account greater set of complex interactions. AI can be especially useful in modelling some of the potential second or third order effects of decisions but clear analyst question formulation will be key. This requires manipulating multiple data sources to help define decision-making options, and recommend preferential outcomes. This is an area increasingly being investigated by defence and security state-level actors and is therefore often relatively opaque in terms of detailed information.