The advent of online learning and Massive Open Online Courses (MOOCs) in recent years has provided a new platform for education, but it’s still early days.

“The future of education is about increasing access to higher education for people who would not otherwise have it,” says Seth Berkley, CEO of the Global Alliance for Vaccines and Immunisation (GAVI).

“That means developing new approaches to teaching that are affordable and sustainable. It means creating new learning tools that allow people to take courses at their own pace. And it means using data to measure how people learn and adjust our courses accordingly.”

3D printing: The next big thing?

While 3D printing may not be a household name yet, the technology is poised to revolutionise manufacturing processes across a wide range of industries – from healthcare to architecture – by making it possible to print objects on demand instead of producing them in bulk.

The next step is embedding electronics into these printed objects so they can become intelligent devices with functionalities such as sensors, GPS, lighting or even wireless charging capabilities. This will make 3D printing even more powerful and enable even more industries to adopt the technology.

According to the Gartner Hype Cycle, 3D printing is still in the “Peak of Inflated Expectations”, with many of the real-world challenges still to be addressed.

Making technology ‘human’

In the last year, there has been a huge amount of excitement around Artificial Intelligence (AI) and its potential to transform every aspect of our lives. It’s also becoming clear that AI will only be truly successful if it becomes a lot more human.

That means making sure that AI works for people, not just for itself. The technology will need to be transparent and explainable, rather than opaque and inscrutable. It will need to make sure that it understands what it is doing and why it is doing it. And it will need to do all this without sacrificing its own core strengths: speed, efficiency and accuracy.

To get there, AI must have better data on which to learn from and teach with – such as personal health data or public transport data – as well as understanding what humans actually want or need in order to make informed decisions about how they want their information processed or analysed.

In concusion, artificial intelligence and its applications in medicine, energy, education and other sectors will drive significant growth in the global economy over the next 10 years. In fact, McKinsey estimates that AI will contribute $13 trillion to the global economy by 2030.

Yet AI is not a ‘silver bullet’ for solving all of our problems. It will have to work with human decision-makers to reach its full potential – and that means understanding how humans think and act. Only then can we begin to harness the power of AI for the good of society as a whole.