Self-disclosure 101. Building trust with users of autonomous systems

Course description

This session targets developers, data labelers, product owners of autonomous systems and is intended to spot and mitigate potential ethical risks that the end-users are facing. The course will overview the current landscape of AI regulation and will explain how to build trust using instruments of self-disclosure for the three key systemic boundaries: training data, algorithms, decision space. Open Ethics is the not-for-profit initiative that aims to bring transparency standards to AI. As humans and machines start to work together increasingly more, the question of regulation becomes a cornerstone. The initiative aims to promote self-disclosure and improve the algorithmic accountability for AI solutions using bottom-up and crowd-sourced approaches. Prerequisites

• Critical thinking
• Basic programming experience in any language

Level of complexity of course Intermediate

Lecturer

Mr. Nikita Lukianets Nikita is a founder and CTO at PocketConfidant AI (artificial intelligence coaching service) and a founder of the Open Ethics initiative (regulatory standards for AI). Nikita holds a Master’s degree in Applied Physics from the Kyiv Polytechnic Institute and an MBA in Design and Innovation Management from the Politecnico di Milano School of Management. Nikita is Continuum Innovation and Microsoft alum and has more than 10 years of experience in Human-Computer interaction. Fields of interests: AI Ethics and Privacy, HITL, User Experience design, Impact assessment for emerging technologies Contacts: n.lukianets@openethics.ai https://www.linkedin.com/in/nikiluk/