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Techtopia

Scenario A

Scenario A | Techtopia

The world is technologically advanced, with fewer people in employment as machines and technology have taken over many roles that were previously carried out by humans. There are a few key private technology corporations dominating all elements of medical research, owning most of the data and choosing where to invest. There is a smaller, private ecosphere driven by philanthropic entrepreneurs who are paying for research to be undertaken in neglected areas. All medicine is personalised and mapped against the genetic predisposition of individuals. Disease interception and genetic modification is the norm.

This is a world shaped by transformational technology, and the private technology corporations who control it. Many jobs are now performed by artificial intelligence and robots. Empathy and imagination are highly valued employee attributes, and those who work for the private corporations are rewarded well. The unemployed masses receive a universal basic income.

Research is entirely funded by private individuals or corporations as public taxation revenues are depleted. Corporations require economic returns: intellectual property from which they develop new products and services, or data that they can use to drive more research.

Research is conducted in cloud labs and is mainly an automated process using predictive and big data technologies. Where data doesn’t provide an immediate answer, computers generate new hypotheses and interrogate vast databases. Human researchers and engineers correct data and software errors. They also judge the morality of research programmes.

Networks of researchers have shrunk as concerns about IP and industrial spying reduce sharing and collaboration. Researchers are more insular, pursuing “moonshot” type research for corporations. Down-to-earth and curiosity led research is neglected, unless it yields financial returns. Philanthropic entrepreneurs fund research into problems affecting poorer populations based on their personal hopes for change.

The rise of developmental and evolutionary robotics has rid the need for entire medical disciplines. Robots perform surgery and take images, and machines interpret the results. The skill in these disciplines is now in programming, engineering, and keeping machines and software healthy.

All humans have their DNA mapped and analysed to predict disease and reduce risk. Technology alters gene expression and “designer” babies are commonplace. Wearable and implanted data chips are the norm and individuals – particularly those who cannot afford personalised medicine – are constantly monitored, providing data of great value to technology companies.

Medical advances keep people well for longer. Life expectancy continues to rise, while the global population is shrinking. Machines have replaced human carers. Patients are triaged in the cloud when data flags up worrying trends. Medical facilities are small and are owned and run by the technology corporations, directly assisting their research programmes. Virtual reality is replacing many real social interactions, and loneliness no longer exists as a health problem.

Insights from leading figures

“At the moment … an awful lot of time is spent [working on] alliances and programmes, and doing all that scholarly research work that needs to be done to set up research trials. A lot of that is going to be swept away and much of the research can and will be automated and done in real time … This is a very different way of conducting research than conventional research. It will be data driven and the people who can master the technocratic arrangement of both the technology and the commercial underpinnings of that will win… Many people conducting research in a conventional way will look like dinosaurs.”

“In 20 years we will all have extremely capable, remarkably autonomous freeform digital assistants. There will be a lot of shake up in roles done by people. A lot of what’s happening now in AI, is taking things that were previously the purview of human intellectual capability and turning that into things that will be done by machines, in other words important thinking jobs.”

“AI technologies will be game-changing for the analysis and publishing of research – taking large datasets and creating learning and patterns of behaviour. It will be common within 10 years to be able to check up for things that are likely to happen in the future rather than check up on things that have happened.”

Weak signal: Genetic re-engineering

CRISPR/Cas9 is a gene-editing technique that can target and modify DNA with groundbreaking accuracy. It is possible to snip out a section of DNA sequence from a gene and put a different one in very quickly and accurately. There is an international moratorium on all therapies for making heritable changes in human genes until they are proved safe and effective, however, in February 2016 UK’s independent fertility regulator gave a research team permission to use CRISPR to explore the mechanisms of miscarriage with human embryos.

Weak signal: Wearable technologies are on the rise

Manufacturers are looking at ways of assisting patients with particular medical needs through wearable technologies. For example, Novartis and Google teamed up to investigate the possibility of building a smart contact lens that can measure glucose levels of diabetes patients through their tears.

Scroll down to view our three other scenarios or go back to the Future of Global Research overview.