Talks

FEEDBACK: THE BIGGEST BROKEN LOOP IN HIGHER EDUCATION – AND HOW TO FIX IT

Personalized, intensive, precise, detailed feedback is the single most powerful driver of learning. But it is missing, weakened, subverted, perverted and controverted in most educational programs. I show how feedback enables and facilitates learning of the most valuable skills in the machine intelligence age, and what organizations, and institutions can do about creating the environment and experiences that use feedback to optimize learning.

INTELLIGENT ARTIFICIALITY: WHAT WE CAN LEARN FROM MACHINES THAT LEARN

Artificial intelligence has undergone a well-documented resurgence. Designers of the neural nets – basic building blocks of deep learning – have inspired themselves from neuronal architectures and neurological signal flows. But designers of AI algorithms and the hardware on which they run have taken the field in new directions and created ingenious building blocks for the analysis and synthesis of information from which we can now ourselves – owners of brains – can learn. I introduce INTELLIGEN T ARTIFICIALITY - a new field that teaches us how to learn from machines that learn – and from the designers of the software that powers them.

How Not to be Useless

What are we good for? As we push past the 7Bn mark as inhabitants of the planet and algorithmic intelligence challenges us to think carefully about why we need human work, we are forcibly confronted by an age-old terror: how do we make ourselves useful in the age of human fungibility? I explore the question in detail and set forth 10 ways in which we can leverage and build on what us uniquely human to remain useful and relevant 10, 20, 50 years hence.