Despite the fact that the aviation industry has good mechanisms in place to protect its business processes, various security breaches do occur. Having a resilient organisation in place that can promptly respond and handle the event is key for continued trust in the business.

• Background and context
• Learning from the aviation industry – previous cases
• Responding to an event

AI will enable breakthrough advances in areas like healthcare, agriculture, education and transportation; it’s already happening in many ways. But new technology also inevitably raises complex questions and broad societal concerns. As we look to a future powered by a partnership between computers and humans, it’s important that we address these challenges head on. Technologists will need to work closely with government, academia, business, civil society and other stakeholders. And focus on ethical principles – fairness, reliability and safety, privacy and security, inclusivity, transparency, and accountability – to guide the cross-disciplinary development and use of artificial intelligence for business and cyber. In this talk we’ll share the principle ethics of AI & ML and have a discussion about how we can all work together to forward AI and ML use responsibly.

• How do we ensure that AI is designed and used responsibly?
• How do we establish ethical principles to protect people?
• How should we govern its use?
• And how will AI impact employment and jobs?

• Privacy regulations drive companies to ask the question: What am I allowed to do?
• With the possibilities that Big Data and AI offer today, probing the limitations of laws and regulations could turn out to be undesirable
• Companies have to move beyond compliance with applicable laws and regulations and have to start to embrace ethics: What is the right thing to do?

A big debate is ongoing since few years about the ethics of applying AI to several fields. But when it comes to cyber security, the scenario is different: It is time to take action now as the evolution of this debate and its (potential) outcome don’t apply to the dark world. But what are the challenges for the industry? In this talk I will walk through a list of assessments that need to be completed in order to reach the necessary level of maturity to start towards this direction and will present a list of practical applications of Deep Learning to cyber security.

• Ethics of AI in cyber security
• Explainable AI
• The technical debt of AI (and cyber security)
• Practical examples of Deep Learning in cyber security