AI Use Cases 

Protecting the privacy of individuals as part of mapping data generation is a growing regulatory and media imperative. Typically vehicles mounted with sensors drive the streets to be mapped capturing images that include faces and number plate data. Automatically obscuring this is a necessity for the huge processing scale at which digital mapping outfits operate.

Machine learning can be use to generate works of fiction - the algorithm will recreate common patterns of wording in a way that implies artistic output. However, the machine does not understand what it has created - and there remains significant scepticism as to the average quality of output. It may be argued that this is a broader issue of what constitutes art.

AI-enabled visual recognition through camera phone (e.g. Google Lens) enables a host of other consumer applications, as well as potentially creating new service support for differently abled consumers

Identifying the source language of text is crucial for both decrypting ancient languages that we cannot understand and for modern translation purposes. Symbols and ancient alphabets can be identifies through the use of machine vision.

Censor user generated content on social media and other platforms. or This may be used to reduce hate speech or incitements to violence similar negative issues - but can also be used for political censorship. The line between the two can become a matter of debate.

Prediction modelling typically used to support key decision-making steps in the judicial system - e.g. sentencing and early release. Historically rules and expert based systems there remains perceived risk of bias (e.g. on ethnic grounds) and lack of transparency and accountability.

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.

Widely deployed video technology, combined with passport databases, to enable instant, remote passenger recognition to potebntially autoamte the check-in, security and immgration processes. Other management benefits will include warning (and chasing) individuals who are about to miss their flights.

Mimicing animal behaviour in drones or robots has several potential uses: camouflage (for example in a security situtation), research or media support (allowing humans to better interact with creatures in their natural environment) or replicating (or even replacing) tasks currently performed by natural creatures (pollination for example).

Optimise and target labour allocation for publicly provided services to match demand, especially in areas of constrained supply (e.g. specialist skills)

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)

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).

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.

Forecast macroeconomic variables based on huge volumes of government proprietary and public data - often combined with other data sources to optimise forecasting.

Students expressions and movements are analysed to check that they are paying attention in class. The system will be able to tell if students are reading or listening – or napping at their desks. Students will get a real-time attentiveness score, which will be shown to their teacher on a screen.

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.

Replicate (often back-office decision) processes for applications, permitting, tax auditing, etc

Gathering evidence for criminal prosecution increasingly requries accessing suspect's phones or computers to seek out potential clues - including from photos. In the era of the selfie and cheap computer memory this can potentially involve thousands of images. Using machine learning to identify weapons, drugs or nudity in stored images can considerably speed up the process - although false positives remain an issue.

Optimise public resource allocation for urban development to improve quality of life (e.g., reduce traffic, minimise pollution). This may be based on multiple input models.

Analyse and grade school or college work. Using machine learning to analyse key elements this will give grades - potentially on a national or international scale compared to individual teacher's marks. This will tend to reward conformity over originality so will be better suited for some courses and topics than others. It could potentially support roll-out of education to areas with limited educational resources (e.g. lack of teaching staff).

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.

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.

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

Provide access to digital information to illiterate folk through conversational agent tools / chatbots. Voice interaction enables new forms of communication - for example low / free marginal cost access to healthcare advice or other information. Access to digital devices, Internet and electricity may be factors limiting deployment.

Identification of "persons of interest" for law enforcement to intercept or track through facial recognition is a high profile use case for AI. Inevitably the debate about the trade-off between individual liberty and security effectiveness plays out differently according to local political expectations. In addition, actual levels of accuracy are a concern both in terms of effective implementation but also civil liberties (algorithmic bias is especially concerning on different ethnic faces for example). In some countries such as China emphasising the supposed effectiveness of the algorithms is a key part of national security communications strategy.

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.

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.

Protect individual's privacy by changing key pixels in photos to confuse AI driven image recognition. Typically these will not be immediately discernible to the human eye if, for example, they are published. The photo might be put through an app to ensure that that is is subtly changed. Inevitably counter software (AI-driven) can be deployed.

Predict risk from natural causes such as wildfires, using data from a wide variety of sources such as satellites and environmental sensors and often building on other data models - for example likely weather patterns. Predicting likely wildfire movement for example can have huge impact on human safety and resource deployment.

Detect manipulated or falsified media to discover attempts to damage reputations or create unwarranted legal situations. The rise in concerns over `fake news` deployment - especially at such sensitive times as during an election - is a growing area of security and media concern. with potentially huge ramifications.