Dave Edwards

In today’s digital workplace, decisions are made with data. But modern, high-dimensional data can confound our evolved intuitions and, paradoxically, make decisions harder.

Join us to learn the art and science of data-driven decision making in the age of Generative AI. Our Decision Making workshop is an interactive, practical introduction to the key skills of understanding meaning in data and how humans make decisions in partnership with machines.

“Organizations are decision factories,” says Nobel Laureate, Danny Kahneman. But with organizations increasingly being staffed not only by people and teams but also by data and machine learning models, how do human employees work best with machine employees? We explore the nuances of human decision making when workflow includes intelligent machines.

How do we know that machines are learning what we want them to learn? This is a central problem in machine learning and is known as the problem of alignment. Aligning machines to human intent is no trivial thing. While most people don’t worry about a superintelligence running amok, most of us do worry about the impact of intelligent machines on our experience of the world—are we eroding our own decision making capabilities and choices as we outsource more of our thinking and knowledge to machines?

In this session, we disrupt the traditional view the audience has of privacy. We describe how a new type of intelligence is interacting with us, forcing us to think differently about privacy. We detail how, instead of the inputs — what information we volunteer — we have to think of the outputs — what inferences are made about us. We explain how AI is alien in its knowledge about us, and how passive and unavoidable data collection can be used to track and infer our inner states, giving away our doubts and hesitations. We explore where these are used to budget us to alternate ends. We thread many privacy-related themes together to end with audience insights into AI’s role in denying us the right to explore, change, make mistakes and grow.

In an era where artificial intelligence is evolving beyond mere predictive tools to become creative partners and generative entities, our relationship with machines has never been more crucial. This talk will explore how trust between humans and machines can either support or disrupt the trust we place in one another. Each of us is preparing for a future where our lives constantly interact with machine intelligence. What does this mean for how we trust each other and our institutions? How do develop “machine intuition,” a reliable mental model for how our robot partners think? Trust relies on collective intelligence but there’s no guarantee that AI won’t make us collectively stupid instead. So we will delve into the concept of designing AI systems that not only enhance our individual capabilities but also amplify how we can be better together.