How Human Centered Design Can Create Inclusive Systems with Chris Butler


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Chris Butler is a product manager, writer, and speaker. He facilitates critical decision making for teams that build new and innovative products. Chris focuses on bias, uncertainty, and randomization to help build more robust and resilient teams.

He has been a product leader at Microsoft, Facebook, KAYAK, and Waze. He created techniques like Empathy Mapping for the Machine and Confusion Mapping to create cross-team alignment while building AI products. Most recently he has been working through the application of adversarial mindsets to product development.  

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Here’s the timestamps for the episode: 

(00:00) – Introduction

(03:04) –Text to speech and speech to text will be more commoditized than the actual semantic understanding of things

(03:41) – Design principles and their integration with systems that have been around for 10 or 20 years in some cases

(05:52) – A conversational agent is really meant to help that employee, or that customer be able to make a request that makes sense to this huge set of machinery that’s on the backend

(06:31) – Design thinking is how we get better at being human-centered for the things that we’re building. You harness what is the best state-of-the-art technology that’s available today to do a particular task, but then how you make it understandable to a human being

(07:47) – The thing that’s really important when it comes to conversational agents is that we’re including the actual people that will use the system in the design of it

(10:59) – Bias and data. A lot of the time people are underrepresented 

(15:48) –  Common ethical code when it comes to artificial intelligence

(17:22) –  Human beings operate on a timeframe that is very different. And so it’s up to us to give that type of purposeful understanding when we talk about hacking AIs

(21:50) –  Talking about AI and machine learning, being in our world, we try to humanize them as much as possible.

(24:30) – Human-centered design for AI, or Google, Facebook comes down to how do these machines actually fit into the world of humanity rather than humans fit into the world of machines. That really is the key aspect of it

(28:28) –  IoT is the way that people tend to understand, or they’ve always fantasized about what the future of this is. That’s true about personal computers as well

(38:08) – Trust in automation

(41:51) – Under-representation of data: Most common bias