Machine Learning: Formulating an Innovation Policy for the 4th Industrial Revolution
10:30am - 4:15pm /
Monday 11th July 2016
/ Venue: The Chapel Foresight Centre (Block J)
Type: Seminar /
Category: Department
- Joseph Savirimuthu
- Admission: Free event but places are limited. Please register
- Book now
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What if we could design machines that learn, adapt and create new knowledge in a way that could be used to address many pressing and future health, transport and energy concerns? Machine learning, big data and artificial intelligence hold out the prospect for innovation and help realise social and welfare goals. The implications for policy, investment and regulations are complex and at present uncertain. If the potential of machine learning is to be realised, we need to engage with the benefits, risks and unintended consequences. Three areas can be identified where there is a pressing need to increase greater awareness and understanding of machine learning algorithms, autonomous systems and artificial intelligence:
A. As volumes of data are collected to address health, transport, energy and public services issues, we may need to reassess the role of privacy and data protection law.
B. The design of autonomous systems and intelligent machines will enable machines to develop new knowledge and prediction capabilities, and as a consequence, may require a re-assessment of how we think about rules, laws and regulations.
C. More broadly, at a societal level, as algorithms and smart communication platforms make available to industry, governments and local authorities considerable resources to create a “good society”, its implications for local and national democracy are unclear and not fully understood.
In a period of rapid technological developments, reactive policy prescriptions merely serve to reinforce the status quo of the immediate past rather than anticipate the challenges likely to be encountered in the future. The need for an interdisciplinary event to facilitate an exchange of views is timely. The Royal Society has recently commenced a Machine Learning Project. It is imperative that as we contribute to the process of engagement and deliberation we are also mindful of public anxiety and uncertainty regarding the impact of autonomous systems, artificial intelligence and Big Data on present and future generations.
This Symposium is intended to help inform public opinion, generate discussion on relevant issues posed by machine learning, and identify aspects critical to formulating an innovation policy that is not only fair and sustainable but is alert to the realities of national, regional and global commerce. To achieve these goals, the Panellists will engage with Machine Learning from various perspectives.
10:30 – 11:00 Coffee
11:00 – 11:15 Welcome And Opening Address:
11:15 – 12:30 Session 1 Framing the Discussion: What is Machine Learning and why has it become an area of industry and policy interest? What are its technological capabilities? Where do human operators fit in a Machine Learning environment?
Reflection: Mr Christopher Graham, Information Commissioners Office (UK)
This session will also discuss the question of how precisely we can or should define Machine Learning. The discussion will also involve a consideration of examples of Machine Learning applications.
12:30 – 13:15 Lunch (Sandwiches)
13:15 – 14:30 Session 2 will involve a group Break Out and Reporting Session: Can you create a Machine that is Ethical? How and When should Machine Learning be Used?
Reflection: Professor Ronald Leenes Tilburg Institute for Law, Technology, and Society, Tilburg University
Topics considered will include the issue of whether Machine Learning systems raise unique ethical challenges within the context of autonomous systems, Health care and Smart Cities.
14:30 – 14:45 Coffee
14:45 – 1545 Session 3 ‘Machine Learning: challenges for innovation and regulation’
15:45 – 1615 Wrap Up and Next Steps: Building a Liverpool Hub
Reflections: Representatives from Liverpool Geek Girls (Merseyside), and NESTA Innovation Charity
A. As volumes of data are collected to address health, transport, energy and public services issues, we may need to reassess the role of privacy and data protection law.
B. The design of autonomous systems and intelligent machines will enable machines to develop new knowledge and prediction capabilities, and as a consequence, may require a re-assessment of how we think about rules, laws and regulations.
C. More broadly, at a societal level, as algorithms and smart communication platforms make available to industry, governments and local authorities considerable resources to create a “good society”, its implications for local and national democracy are unclear and not fully understood.
In a period of rapid technological developments, reactive policy prescriptions merely serve to reinforce the status quo of the immediate past rather than anticipate the challenges likely to be encountered in the future. The need for an interdisciplinary event to facilitate an exchange of views is timely. The Royal Society has recently commenced a Machine Learning Project. It is imperative that as we contribute to the process of engagement and deliberation we are also mindful of public anxiety and uncertainty regarding the impact of autonomous systems, artificial intelligence and Big Data on present and future generations.
This Symposium is intended to help inform public opinion, generate discussion on relevant issues posed by machine learning, and identify aspects critical to formulating an innovation policy that is not only fair and sustainable but is alert to the realities of national, regional and global commerce. To achieve these goals, the Panellists will engage with Machine Learning from various perspectives.
10:30 – 11:00 Coffee
11:00 – 11:15 Welcome And Opening Address:
11:15 – 12:30 Session 1 Framing the Discussion: What is Machine Learning and why has it become an area of industry and policy interest? What are its technological capabilities? Where do human operators fit in a Machine Learning environment?
Reflection: Mr Christopher Graham, Information Commissioners Office (UK)
This session will also discuss the question of how precisely we can or should define Machine Learning. The discussion will also involve a consideration of examples of Machine Learning applications.
12:30 – 13:15 Lunch (Sandwiches)
13:15 – 14:30 Session 2 will involve a group Break Out and Reporting Session: Can you create a Machine that is Ethical? How and When should Machine Learning be Used?
Reflection: Professor Ronald Leenes Tilburg Institute for Law, Technology, and Society, Tilburg University
Topics considered will include the issue of whether Machine Learning systems raise unique ethical challenges within the context of autonomous systems, Health care and Smart Cities.
14:30 – 14:45 Coffee
14:45 – 1545 Session 3 ‘Machine Learning: challenges for innovation and regulation’
15:45 – 1615 Wrap Up and Next Steps: Building a Liverpool Hub
Reflections: Representatives from Liverpool Geek Girls (Merseyside), and NESTA Innovation Charity