The third event in IFF’s seminar series, The Future is closer than you think – what technology means for research, took place last Thursday evening at Skills Matter, Moorgate, the UK’s largest venue dedicated to technology events. It was an appropriate setting for a gathering of professionals from across research to discuss the technological revolution we have all found ourselves a part of, and more importantly what impact it will have on our future.
IFF Director and Chair for the evening Rowan Foster started proceedings by introducing the concept of the next technological revolution (otherwise known as the “4th industrial revolution”). This movement is undeniably changing not only the way we live, with the invention of Artificial Intelligence (AI), 3D-printing and driverless vehicles, but also the jobs we do and how we do them. An interesting and exciting time to be alive no doubt – but Rowan raised the question of whether, professionally, technology should be something we should embrace or something we fear? And perhaps more importantly what impact it will have for us as researchers in 10, 20, 30 years’ time?
The seminar was a thought-provoking, sometimes funny, and more than occasionally sobering evening giving the audience a chance to gaze through the looking glass towards a dystopian future.
Two possible futures of the profession
Daniel Susskind, co-author of best-selling book, The Future of the Professions, and Fellow of Economics at Oxford University, spoke about two possible futures for society: one in which our existing approach to work become more streamlined and efficient through use of technology (though remains broadly similar), or alternatively, a rather more chilling future – at least for those of us who are not computer scientists – in which machines ultimately displace professionals.
He took us on a fascinating whistle-stop tour of the research covered in his book, from the birth of artificial intelligence to its implications for professional jobs.
Artificial Intelligence began with the idea of a human expert passing on their knowledge to a computer system, by writing down instructions for it to follow. Consequently, people initially thought that computer knowledge would be limited to what a human expert knew. Of course, this did not account for exponential growth in processing power, which sees machine learning now far surpassing that of humans. This ultimately has great repercussions for the world of work as we know it.
Daniel explained that the idea of professions (medicine, law, research) originated within a print-based industrial society, where individuals became guardians of the specialist knowledge of that profession (due to a natural limitation in the amount of knowledge a human can realistically learn). He went on to point out that a profession is not a homogenous thing, but can be broken down into a set of tasks which are often quite repetitive and could easily be learnt by a machine. He shared some brilliant, quick fire examples of industries, and individual companies, leading the way in harnessing technology to automate some of the more routine ‘tasks’ of that professional; one of which was the Catholic Church’s Confession app (worth a Google if you’ve not heard of it before!).
Applying this to research, he forecasts a move away from bespoke service and greater automation: perhaps we don’t need to start anew with every research question we face, but can use machines to our advantage by automating the routine tasks.
The keynote speech ended by giving us a rather stark choice: to either try to compete with computers, or to build them ourselves.
It’s not all doom and gloom
By contrast, the panel made up of Mark Carrigan (SRA trustee and Digital Fellow at The Sociological Review Foundation), Olivier Legris (Head of Strategy at Future Platforms) and Katie Metzler (Head of Research Methods Innovation at SAGE Publishing) were more optimistic about what technology might mean for the research profession.
They discussed several issues, from how we will upskill ourselves and whether social scientists need data science skillsets, to whether ‘big data’ may contradict traditional market research ‘small data’ findings. We will be sharing a guest blog from Mark Carrigan exploring some of these views and the implications of technology for research early next week!
Ultimately the audience were left considering the idea that machines could enable us to do things that were previously thought impossible, speed things up through automation and that there might in fact be more of a role for humans in the research process going forward, to ask the interesting questions.