Other parts of this series:
- Avoid the storm: what Europe needs to know to enact a new public services model
- What public leaders need to know to make a decision for change
- Turning ambition into action: How to launch the future of public service
- Tax compliance in the age of Ultron
- Preparing for the possible: the public service transition to a post-digital era
- Why has the civil servant been forgotten?
- Is singularity the end of the world as we know it?
- Is ZMOC a dirty word? Not for a data scientist
- Why becoming a data-driven organisation is a process, not a project
In the 1940s, Alan Turing developed an algorithm demonstrating that a computer could play chess. In 1967, a computer program beat a human at chess for the first time. And, by 1997, a computer was able to defeat a reigning world champion in a classical chess match. The way this age-old game is played shows the evolution of machines as a source of “intelligence”.
Technology is moving so fast that what would have been considered mere science fiction just 10 years ago is now a reality. Who would have thought that a refrigerator could order food or let you see what’s inside it remotely? Or that a watch could track your sleep patterns? Or that cars could drive themselves?
This new world is what futurists are calling technological singularity – the hypothetical future creation of superintelligent machines. It’s the idea that technological progress, particularly predictive technologies such as artificial intelligence (AI), will reach a point where machines are smarter than humans.
Technology’s crystal ball
The question around singularity is not if it will happen, but when? For any organisation undergoing change, this is an important question. Humans are getting smarter about building algorithms. So why wouldn’t we expect our machines to get smarter? The chess example described above is a perfect example of this transformation. Success will depend on your ability to embrace technological advancement.
Singularity is not an isolated phenomenon. Organisations across sectors are discussing the future role of AI. Some embrace it enthusiastically, while others fear that it will replace humans. But perhaps the future is not so black and white. Instead of a reality where machines take over the world, it may be that there is greater human-machine collaboration.
Trust is key
Humans will accept algorithmic prescriptions if they can trust them. Thanks to explainable AI, humans are “dompting” machines. That is, they are keeping machines at bay by ensuring decisions are transparent, understandable and explainable. No more black box machine learning.
Take the fields of medicine and law, for example. By building in clinical expertise into the design process and ensuring the ability to retrace decisions, AI gives these professionals the control – and the trust – they need to make the interface between the world and humans work again.
Tax singularity is another example. Tax agencies have always been leaders in adopting new IT capabilities. One day there will likely be a tax algorithm that will know people’s income and expenses and collect the right amount of taxes without having to make extensive, tedious calculations. Assessments may be more objective than decision-making, which can reduce the potential for error. Tax enforcement will be built into the system, freeing people to live their lives.
The speed of evolution continues to increase. Futurists predict that we are only 20-30 years from the singularity. No matter what your business is, to be ready for change, you should embrace your singularity.
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