Intermediation platforms connect people, services and even things in ways that have been unthinkable until now. Search engines provide relevant references for people searching for information. Social networks connect users in their environment. Car pooling systems link drivers and passengers using the same routes. Intermediation platforms use big data to fuel the services they offer and these services are evolving extremely quickly but almost unnoticed. They are already competing with the oil industry as the world’s top market capitalisations and are on the verge of revolutionising the world in which we live.

Over the past two and a half centuries, there have been several technological revolutions: the industrial revolution in around 1770, the introduction of steam engines and railways in the 1830s, the introduction of steel and electricity in the 1870s, the use of mass production from 1910 onwards and finally, the current Information Technology (IT) revolution that began in the 1970s. This modern day revolution is unique: not only has it brought us incredible achievements but it also poses some real threats to our traditional concept of employment.

The on-going transition to more sustainable energy production methods means that we are moving away from a monolithic, centrally controlled model to one in which both production and consumption are progressively decentralised and localised. This in turn gives rise to complex interacting networks. ICT and mathematics will be instrumental in making these networks more efficient and resilient. This article highlights two research areas that we expect will play an important role in these developments.

Big data research in Life Sciences typically focuses on big molecular datasets of protein structures, DNA sequences, gene expression, proteomics and metabolomics. Now, however, new developments in three-dimensional imaging and microscopy have started to deliver big datasets of cell behaviours during embryonic development including cell trajectories and shapes and patterns of gene activity from every position in the embryo. This surge of multicellular and multi-scale biological data poses exciting new challenges for the application of ICT and applied mathematics in this field.

Nowadays, software has a ubiquitous presence in everyday life and this phenomenon gives rise to a range of challenges that affect both individuals and society as a whole. In this article we argue that in the future, the domain of software should no longer belong to technical experts and system integrators alone. Instead it should transition to a firmly engaged public domain, similar to city planning, social welfare and security. The challenge that lies at the heart of this problem is the ability to understand, on a technical level, what all the different software actually is and what it does with our information.

Existing software cannot benefit from the revolutionary potential increases in computational power provided by manycore chips unless their design and code are polluted by an unprecedented amount of low-level, fine-grained concurrency detail. As a consequence, the advent of manycore chips threatens to make current main-stream programming approaches obsolete, and thereby, jeopardizes the benefits gained from the last 20 years of development in industrial software engineering. In this article we put forward an argument for a fundamental breakthrough in how parallelism and concurrency are integrated into the software of the future.