The Alan Turing Institute, Edinburgh, Newcastle, Cambridge and UCL Universities are organising a series of workshops to discuss Educating Engineers for Safe AI.

We are seeking participants in this workshop series who are:

AI Engineers, Data Scientists, Systems Engineers, ML-Ops, Research Software Engineers, Site Reliability Engineers, AI UI/UX designers, and more, working in the implementation of AI systems OR
Academics and other experts working in areas related to Safe, Ethical, Reliable and Trustworthy Machine Learning and Artificial Intelligence OR
Academics and other experts working in professional education, CPD, learning design, and related areas, interested in developing materials related to safe AI for professional audiences.

The workshops consist of two regional nonresidential satellite workshops in Cambridge (4th July) and in Edinburgh (29th June), and a final residential workshop in Newcastle on the 15th and 16th August.

The purpose of the workshop series is to develop a road map for the creation of a syllabus and set of professional education materials, targeted at software and systems engineers, so that they can be empowered to champion the creation of safe, ethical and trustworthy AI in their workplaces. Developers and engineers, appropriately empowered and skilled, are uniquely placed to ensure that the systems they build are done so according to emerging ethical best practices. These materials will become part of The Turing Way project.

To create these materials, we believe we need to bring together researchers in safe, ethical and trustworthy AI, and experts in professional education, together with the engineering communities, in companies and research institutes around the UK, to co-create this content.

By the end of the workshop, participants will:

Be better informed about the current discussions on and practical approaches to on ethics and reliability of AI s and reliability of AI/ML
Have identified the their community's biggest key challenges relating to the ethical and trustworthy use of AI/ML in the specific contexts of their applications
Have developed a vocabulary and toolkit related to AI and ML that is applicable across different fields and across communities

The Edinburgh workshop will start with a panel discussion on responsible and trustworthy AI featuring speakers including Steph Wright (Scottish AI Alliance) and Arfon Smith (GitHub). Following this participants will take part in sessions to identify and discuss key challenges, engage in knowledge exchange around useful resources, and provide input for recommendations for training in this area. This workshop is being organised by EPCC and the Bayes Centre at the University of Edinburgh.

Lunch will be provided and the day will finish with a drinks reception. This workshop is being organised by EPCC and the Bayes Centre at the University of Edinburgh.

There is some travel/accommodation assistance available to help travelers with the costs associated with this event. Please fill in the section in the event order form with details of costs and we will be in touch if you are eligible for funding. Please note: this is only available to those with no other funding options available.

Applications for travel/accommodation assistance received after Friday 23rd June will not be accepted. This is due to applications being reviewed and awards being sent at the beginning of the week. All successful applications will be contacted directly with confirmation and instruction.

To apply to join any of the other workshops in this series, please register through their Eventbrite pages.

All participants are welcome to register for the workshop. The Bayes Centre venue is fully accessible, further information on Bayes Centre’s accessibility can be found here (https://www.accessable.co.uk/venues/bayes-centre). If any additional support is needed, please kindly let us know on the registration form and we will do our best to accommodate them.

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This event is supported by The Alan Turing Institute. The Turing is not involved in the agenda or content planning.