AI systems are more and more expected to take autonomous decisions, often well hidden from plain view. This is not necessarily without danger. In this talk I’ll give a high-level overview of some common pitfalls in AI-powered applications, that require more thought than many AI gurus would admit. On the menu: bias and fairness, confounding variables, adversarial attacks, ethics, explainability, … As this presentation was given at a security-focused event, special attention is given to security concerns for individuals and society, such as AI-augmented phishing and disinformation campaigns.
Talk Infosecurity 2019: Pitfalls in AI
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analytics annexe_category Artificial intelligence big data blockchain BPM chatbot cloud computing cost cutting cryptography data center data quality development EDA egov Event GIS Knowledge Graph Machine Learning methodology Mobile Natural Language Processing NLP Open Source PaaS Privacy Productivity quantum computing Security software design