SUMMARY
As AI becomes increasingly ingrained in our systems, its impact on individuals and society is undeniable.
However, the unchecked design and deployment of AI can lead to serious ethical and societal issues. This includes concerns such as underpaying workers, data appropriation without compensation, and the threat to content creators through mimicry of creative styles. Also, algorithmic bias in decision-making and automated processes without human intervention raise questions of fairness and societal inequality.
In this session I will outline crucial ethical considerations teams need to be aware of when designing AI driven systems, and will reference industry best practices that address these issues. I will make this tangible by sharing details about an AI innovation initiative from my own experience, and how my team implemented an AI ethics framework.
DESCRIPTION
The talk will kick off with an exploration of the current AI landscape, highlighting the pervasive ethical dilemmas faced by IT professionals.
I'll navigate through real-world examples, emphasising the repercussions of inconsiderate design and implementation with focus on aspects such as social justice, inclusion and diversity, equality and democracy.
We'll then transition into an in-depth analysis of various ethical considerations in AI, addressing issues such as data appropriation, underpaid workers, content creation threats, and algorithmic bias, in light of the systems design lifecycle of an AI driven system.
To ground these concepts in reality, I'll share insights from an ongoing AI innovation project. By dissecting the implementation of our AI ethics framework, attendees will gain practical knowledge on incorporating ethical considerations into their own projects. The talk will conclude with a discussion of industry best practice frameworks, providing a roadmap for attendees to navigate the ethical challenges in their AI endeavours.
TAKE AWAY
Participants in my talk will leave with
A heightened awareness of the ethical complexities surrounding AI.
Practical insights and real-world examples for integrating ethics into AI projects
Exposure to a framework that applies ethical actions to the various stages of the AI system development lifecycle
Actionable strategies to recognize and address bias, along with industry best practices for responsible AI innovation.