Abstract: "AI no longer belongs to the realm of science fiction. From voice recognition to self-driving cars and medical diagnosis, artificial intelligence is weaving its way into our lives at work and at home: so it’s safe to assume that AI, the product of decades of scientific research, will have an impact on the realm of scientific research itself. The maturation of AI technologies is the prelude to an unforeseen step change in humankind's ability to understand and innovate. Yet big data and search companies’ utilization of AI is helping to usher in what has been called the ""post-truth"" era. If AI is currently struggling to discern facts from fiction, could it be that human intelligence is still a necessary component for the continued successful integration of AI?
The Digital Age created a new class of citizen scientists: people from every walk of life with a passion for knowledge. In the coming Age of AI, we can give those citizen scientists unfettered access to relevant scientific research and powerful new machine learning tools. But AI is only as as accurate as the information on which it is trained: and information gleaned solely through data scraping algorithms isn’t necessarily accurate. Moreover, in the publishing industry, existing academic literature is our biggest and richest dataset for training scholarly recommendation algorithms, but also suffers from bias towards fields and populations that historically have had more academic interest. Weighing the veracity of different perspectives requires the kind of critical thinking that humans possess. Beyond tagging and user feedback, valuable human expertise is necessary to steer and sanity check AI - a technology still very much in the infancy stage of its development.
Leveraging human expertise to train AI can increase the pace of democratization of science by disrupting the way current research and development is performed and communicated. AI can - and should - be used to support the growing movements towards open data, open publishing, and open science. Only by blending AI's ability to quickly process vast quantities of data with the ability of humans to understand nuance and context can we ensure facts remain facts in this post-truth era."
Bio: Dr Sybil Wong is COO at Sparrho, an online platform used in 150+ countries that combines machine learning and human expertise to democratise scientific knowledge. Sybil completed her PhD in Biochemistry at the University of Nottingham and Barts Cancer Institute, QMUL. Prior to joining Sparrho, Sybil was SVP Business Development & Director of OneStart, the world’s largest biotech and healthcare startup accelerator, at the Oxbridge Biotech Roundtable. Through OneStart, Sybil supported 70 budding biotech and healthcare startups from across Europe, North America and Asia, and managed partnerships with top pharma and venture firms, including SR One/GSK, Roche, Johnson & Johnson, and AstraZeneca/MedImmune.