Education
Use Cases
Newsfor Education
Analyse large text datasets to uncover trends from documentary evidence
Across large text datasets - for example, historical archives - there will be trends or insights that can be analysed but which it would take a human observer too much time to process. Although still at a relatively rudimentary stage this will become an increasingly powerful tool for creating new insights and levels of knowledge.
Detect plagiarism in documents
In a world where information is at anyone''s fingertips plagiarism is a constant challenge, especially in academic circles. NLP can be used to match content and identify suspect material.
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....
Evaluate school or college work
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).
Generate synthetic datasets for deep learning
Synthetic datasets is a way for researchers to train machine learning programs when sufficient real-world data is unavailable, difficult to obtain, or raises ethical or privacy concerns. Certain use cases for AI lend themselves better to synthetic datasets than others.
Mimic creature or animal behaviour with drones or robotics
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).
Mininise need for sensors through generating likely input data from other sources
Sensors can be expensive, hard to maintain or simply unavailable for what can be important data. Using data from other sources can enable the predictive modelling of other data sets. Note that this can create a series of new risks, especially if historic patterns break down or feedback effects occur.
Monitor student''s attentiveness in class with facial recognition technology
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.
Personalise learning
Provide personalised learning programmes - with regular testing / feedback loops used to assess and deliver against topics that individual students find more challenging and a pace, and potentially style, of interaction tailored to the individual.
Predict individualised educational and career paths to advise on life decisions
Predict individualised educational and career paths to maximise engagement and success - both on an economy-wide basis but also for individuals. Ideally this will help inform better life decisions.
Real time high volume data management
Even with advances in computing power there will come a moment when too much data has been gathered to be economically stored - for example during high spec science experiments. At that stage, in real time, machine learning can be used to help decide which data should be stored for analysis and which deleted.