Technology foresight through the collaboration with human expert and machine intelligence

We always make efforts to predict our future from the past and the present, since the prediction can make great changes in our life, especially in the fields of science and technology. Many organizations in the globe have surveys and announces emerging or disruptive technologies every year. Of course, they have developed their own processes to achieve the goal, but the insights of experts from related domains are usually absolute. In the era of Bigdata, due to the enormous amount of information, domain experts are struggling with timeliness and completeness in developing insights for the future. In KISTI, we introduced a methodology in which human experts are collaborating with machine intelligence to overcome the information flood. Data-intensive analysis methodology is applied to implement the machine intelligence to predict emerging technologies. The intelligent service platform, named InSciTe, includes data gathering, text mining, identity resolution, reasoning, complex event processing, and prescriptive analytics modules. InSciTe generates candidates of emerging technologies with the evidences why they are selected as candidates, and then domain experts make the final decision. In this talk, I will introduce our intelligent service platform based on the data-intensive analysis. Besides, I will show several case studies in the domains of ICT, internet security, and healthcare as joint works with NIPA, KISA, and KRIBB respectively. For the cases with KRIBB, human experts collaborated with machine intelligence interactively to derive the results. We named this approach as Chi(Computer Human Interacting)-Delphi method for technology foresight. As Web goes to connect machine intelligences in the era of Internet of Things, the collaboration between human intelligence and machine intelligence will be eventually the next great wave for predicting the future.