Artificial Intelligence & Machine Learning – What Will They Look Like in Five Years?
If you use a smartphone you’re already holding a more powerful computer than the guidance system NASA used to land Apollo 11 on the moon. Even at the turn of this century few people could have predicted the advances in computing technology that have made things such as Artificial Intelligence and Machine learning possible.
At the moment there are a range of advanced technologies used in private sector organisations which may be utilised in public sector and not-for-profits such as:
The Internet of Behaviours (IoB) – developing the Internet of Things (IoT) into a data-collecting form of technology which acquires information from devices connected to the internet to track, analyse and predict behaviour. At the moment the IoB is raising interest from advertising and marketing functions, but it also has applications for not-for-profits and the public sector, and may be able to assist in more targeted fundraising campaigns or health care monitoring.
Document data extraction – software which allows more efficient data extraction and exports it to a usable format. Data extraction processes like this can assist in scanning information more effectively, and when combined with machine learning will be able to improve its own capabilities in the future. Applications in the public sector could include pensions and benefits processing as well as departments such as the DVLA.
Predictive analytics – using data to predict future events and trends by using historical data to forecast what could potentially happen. Already in use in sectors such as risk management and marketing, predictive analysis could potentially be used in public health to predict future potential pandemics, for example, or in planning to ascertain the effect of housebuilding in certain areas.
Looking to the future
Let’s cast our minds forward five years into the future and imagine that not-for-profits and public services have branched out of Data and Tech, embraced AI/ML and are now led by a Chief AI Officer (CAIO). What will we notice?
In healthcare personalised medicine is advancing, creating personalised treatments for individuals suffering from a range of illnesses and diseases. By using a patient’s medical history any deviations from the ‘norm’ can be flagged as requiring further investigation, and possible treatment.
In Government AI is being used to design policies that benefit people, more equitable decisions are being made, the Government communicates better with its citizens, and the quality of public services are enhanced.
In the not-for-profit sector web pages are now enhanced to be easier to navigate. This allows more interaction between the not-for-profit and its service users and, in the case of someone needing direct intervention, support is more immediately available.
The CAIOs overseeing this have already aligned the public sector or not-for-profit’s AI strategy to their end-goals, and have identified opportunities to roll out an AI expansion within day-to-day tasks, allowing automation to improve efficiency and reduce waste. They have also found ways to drive fundraising (in the case of not-for-profits), and reducing costs (in the public sector). They have identified which processes can be automated, and conversely which need to be reimagined in order to go through the automation process. They have overseen the upskilling of existing staff and identified the talent necessary to ensure that the AI strategy can be implemented effectively, and ensured that everyone understands exactly why AI is crucial to the organisation’s future success and how it will affect everyone. And finally they have overseen the implementation of any ethical considerations, as well as the regulation of AI and how organisations will comply with that.
It's difficult to accurately predict the future but as AI and ML are more tightly integrated into systems and processes not-for-profits and the public sector will see themselves transformed into more efficient and more effective entities. The role of Chief AI Officer, while still an emerging one today, will become more widespread, and will bear the responsibility for changes that we can only guess at.
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