Business
A compelling argument why human oversight and leadership is needed to manage the impact of artificial intelligence and machine learning on decision making and content consumption. BioTessa Sproule & Katie MacGuire joined our host Marc Binkley to share insights about their work in Artificial Intelligence and Machine Learning. As the co-founders of Vubble, a video recommendation platform, Katie and Tessa have built proprietary AI technology to “read” video and contextually tag it with descriptive metadata, analyze audiences of existing video content and then surface new video recommendations to people most likely to enjoy it based on the metadata. Timestamps1:37 – Introduction to Katie MacGuire and Tessa Sproule3:33- What Vubble does6:38 – How Katie and Tessa went from broadcasting to artificial intelligence11:00 – How recommendation engines change people’s consumption behaviour13:24 – An overview of artificial intelligence (AI) and machine learning (ML)14:29 – How Google uses people to train machines – ReCaptcha15:43 – Content and Collaborative Filtering: two subsets of machine learning18:13 – The pitfalls of AI predictions and where humans need to intervene21:05 - The opportunity for Vubble’s AI & ML platform29:16 – How KPIs influence interest graphs, rabbit holes and filter bubbles33:29 - Why we need humans to keep machine recommendations in check38:02 – How cultural influences can change AI recommendations42:15 - Why content nutrition labels are needed to create informed citizens48:15 – The importance of auditing data sets 50:44 - The link between emotional content and video views 54:03 – A global project to govern AI tech and why human diversity can help1:02:44 – Why business leaders need to understand AI / ML to avoid bad decisions1:10:00 – How to find out more about Tessa and KatieLinksKatie on LinkedInTessa on LinkedInExample of a content nutrition labelCanadian Diversity of Content projectVubblepop.com