KIN Winter workshop 2017 - Data-driven decision making. 6th December 2017
The world of data-driven intelligence is evolving. Big data is now moving from the sole care of data scientists and becoming accessible to employees throughout organisations. The mystique surrounding data analytics is falling away, with sophisticated data visualisation tools designed to let non-technically-minded people understand metrics. Information that supports “good” business or policy decisions is just a click away.
The benefits are much faster – and we are told - more accurate decision making. But this raises a number of issues:
- Are algorithms replacing intuition in terms of establishing “truth”?
- Can we trust machines to make decisions for us?
- Do we always need to have a human in the decision- making loop?
- In this age of ‘democratised data and technologies’, what is the future role of the “expert” or professional?
These and other questions will be answered at the workshop, drawing on the practical expertise and experience of several world-class speakers and reinforced by experiential learning.
Dr. Stephanie Mathisen, Campaigns and Policy Officer at 'Sense about Science' has made a compelling case to the The House of Commons Science and Technology Committee for greater oversight of algorithms that influence decisions about citizens' lives. She will explain why this field of Artificial Intelligence needs more scrutiny.
Juan Mateos-Garcia, Head of Innovation Mapping in Policy and Research at Nesta, will talk about Algorithmic Fallibility and whether we understand enough about the algorithms that make critical decisions for us.
Gareth Jones and Jeremy Hindle from Headstart, a recruitment platform, will be presenting a case study on how Machine Learning can help companies identify the best-suited candidates in the shortest amount of time.
Anton Fishman from the Association of Business Psychology, will talk about the impact of AI & Machine Learning on the professions, the trends that are leading to the ‘democratisation of access’ to professional advice, the loss of monopoly control of related domains of knowledge and the consequences for professional development due to the growing ubiquity of robo-advisers.