Hey There, It's Borhan here! I'm a huge fan of your "Learners" KZfaq channel. Your content is always top-notch, and I can see the passion and effort you pour into each video. I believe you have incredible potential to reach an even wider audience with a solid KZfaq strategy. I would love to schedule a short meeting with you to discuss how I can help you grow your channel faster. This is not a sales call, but an opportunity to share ideas and offer assistance. Let me know if you're interested, and we can find a convenient time to chat. Thanks for your time and for creating such amazing content.

Is it possible to get links to the list of resources mentioned in this video? Not sure where it would be but it seems great :-) (mentioned around 28 minutes ins). thank you!

The audio isn't working

It's so funny how u speak about AI and UX, and the sound is shit - like that is the poor UX :D

Hi from England

Nice talks and wonderful community work ❤

Well done. Nice talks and wonderful community work. I was wondering if some of the speakers had insights on how the current trends in focus and "reckoning" are connected to macro economic an ideological patterns, somehow to explain the "paradigm shift" a bit better. Keep it up, and looking forward to your future events!

This is a superb conversation!

holy 4hrs long. hard pass, bleh!

31:09 holy shit i almost blew my speakers and fell out of my seat...

Who are these speakers?

Insightful and informative. Thxs.

I think this series was great, but from the topics covered, I believe a startling fatal flaw for AI+UX development and research was surfaced but left unresolved or misunderstood? A lot of the discussed strategies or visions, esp. related to trust and user (researcher) interaction with AI mentioned principles like transparency and control and human oversight/supervision - like double checking, verifying, setting and adjusting mental models and expectations, etc.). These are all very great in general (for most kinds of tech historically), but I don't know how well they apply to "new" frameworks of AI (the kind that is "non-deterministic"). "A nondeterministic algorithm is an algorithm that, given a particular input, can produce different outputs. This is in contrast to a deterministic algorithm, which will always produce the same output for a given input. Nondeterministic algorithms are often used in artificial intelligence (AI) applications" - Autoblocks Glossary. So, if calibrated trust can't be built in the traditional human way of inferring causality (e.g. prior performance predicts future behavior), then the conventional principles for trust seem to be setting us up maybe for a trap towards an inherent uncanny valley like gap-snap (e.g., trust gained in drops, but lost in buckets)? The issue is the dropwise trust seems would actually be misplaced, rather than calibrated (e.g., blind faith) rather than logically appropriate for human interaction with non-deterministic AI systems - because we know by definition we shouldn't be predicting (e.g. setting up and adjusting mental models) for how they will behave in the future since they are (esp. very rapidly and supposed to be) changing and unpredictable to the extent they are non-deterministic. At best, outcomes from this misplaced trust might be amusing, but at worst seems could be really scary and catastrophic depending on the domain. If some of the leaders, change makers and top executioners in the field aren't seriously considering this fatal flaw (maybe even a fallacy), who else should be?

Any chance we could get just the audio for this? Even transcript

thanks a lot for sharing this video, it is so insightful

Gosh the audio is really rough. Makes it difficult to follow along. Pity, the content seems interesting!