Awkward Silences

#103 - Ethical Design and Respectful UX Research with Kat Zhou of Epidemic Sound


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‘Ethical design’ is a term that encompasses a process of designing useful, empowering, and accessible products that do not harm, manipulate, or deceive people. It is, in essence, about treating people you design for with respect and consideration.

That’s a deceptively simple goal, and many companies miss the mark. Kat Zhou joins us today to talk about the challenges, opportunities, and urgent need for ethical design and research.


In this episode:

  • Why is ethical design so critical for both users and companies?
  • How to integrate ethics and respect in your UX research
  • How ethical design empowers inclusive and equitable representation


Highlights:

  • [0:51] What is ethical design in UX?
  • [2:35] Where can you learn about ethical design for UX?
  • [4:38] Ethical design resources for researchers
  • [5:29] What does it mean to treat people with respect?
  • [8:33] Could we balance business goals with respect?
  • [12:40] Pragmatism versus idealism
  • [15:52] What does deceptive design imply?
  • [17:40] Ethical design practices for UX researchers
  • [24:28] Boosting inclusive representation
  • [29:44] Changing the world for the better
  • [34:11] UX regulations
  • [43:00] Kat’s key takeaways on ethical design and research


Sources mentioned in the episode:

  • < Design Ethically >
  • Race After Technology by Ruha Benjamin
  • Algorithms of Oppression by Safiya Umoja Noble
  • This Changes Everything: Capitalism vs. The Climate by Naomi Klein
  • The UX Designer's Guide to User Research


About our guest

Kat Zhou is a product developer and designer who focuses on integrating ethics into the design of AI systems. Currently, she is the Senior Product Designer at Epidemic Sound. Before that, Kat was the Creator of the < Design Ethically > project, a Member Of The Board Of Advisors at The YX Foundation, and a Product Designer at Spotify and IBM. Kat is also a strong advocate for more inclusive and privacy-friendly approaches to AI.

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