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Can AI Effectively Tag for Empathy: A Discussion on Artificial Intelligence and the Perception of Empathy

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Empathy helps us create appealing content interactions and encourage user engagement. Digital assets tagged to empathy concepts increases user interaction with brands throughout the customer journey. But how can we tag at scale for these types of concepts? Is artificial intelligence (AI) the solution, or an impractical approach? Can AI provide appropriate empathy-based tags without bias and with the appropriate context? Rebecca Schneider explored all of these questions at the DAM Practitioners Summit 2020.

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Can AI Effectively Tag for Empathy: A Discussion on Artificial Intelligence and the Perception of Empathy

  1. 1. CAN AI EFFECTIVELY TAG FOR EMPATHY? DAM Practitioners’ Summit January, 2020 Rebecca Schneider Director, Content Experience A Discussion on Artificial Intelligence and the Perception of Empathy.
  2. 2. TOPICS FOR TODAY • Introductions • Why Empathy? • Tagging for Empathy: Is This Practical at Scale? • Some Final Thoughts 1/30/2020 | @RebeccaDeclares | © 2019 AvenueCX, LLC. All rights reserved. 2
  3. 3. 1/30/2020 | @RebeccaDeclares | © 2019 AvenueCX, LLC. All rights reserved. 3 Rebecca Schneider, Executive Director, Content Organizer. Librarian. Gadget Lover. Owner of many, many pairs of black shoes. • Expert in taxonomies, metadata, and enterprise content strategy. • Thought leader in taxonomy development and metadata. • Key Clients: Total Wine & More, Verizon Wireless, Bank of New York Mellon, Analog Devices About Myself Helping you shape your content experience
  4. 4. 1/30/2020 | @RebeccaDeclares | © 2019 AvenueCX, LLC. All rights reserved. 4 • I’d like to see empathy represented in tagging.  Rebecca Schneider, DAM Summit 2018 • Presentation: Tagging & Empathy  Rebecca Schneider, DAM Summit 2019 • OK, but how can we practically tag to scale? Is AI the solution?  Rebecca Schneider, October(ish) 2019 • This is a conversation, please contribute! Why This Topic? I’m a bit curious!
  5. 5. Why Empathy?
  6. 6. 1/30/2020 | @RebeccaDeclares | © 2019 AvenueCX, LLC. All rights reserved. 6 • Cognitive  Recognize what the other person is feeling. • Emotional  Feel what the other person is feeling. • Compassionate  We want to help the other person deal with his/her situation and emotions. Empathy Defined
  7. 7. 1/30/2020 | @RebeccaDeclares | © 2019 AvenueCX, LLC. All rights reserved. 7 Being able to walk in another person’s shoes . . . No matter how much those four-inch heels hurt you. — Margaret Magnarelli In Short . . . Empathy is a skill that can be taught and learned.
  8. 8. 1/30/2020 | @RebeccaDeclares | © 2019 AvenueCX, LLC. All rights reserved. 8 • Creates distinctive “in the moment” experiences by providing highly relevant content • Increases brand loyalty, increasing customer lifetime engagement • Amplifies interest in the brand, beyond initial customer base Why is empathy important? Brand and marketing perspective I miss the personalization that Vegas was - there were showroom captains and all the dealers knew the gamblers by their first names. — Wayne Newton
  9. 9. The Need for Context.
  10. 10. 9/25/2019 | @RebeccaDeclares | © 2019 AvenueCX, LLC. All rights reserved. 10 • Culture  What is your way of life? • Education  Where did you go to school? • Income  What’s your rough level of income? • Ethnicity  How do you identify with others? • Social Norms  What is acceptable in your world? Context The Veldt by Ray Bradbury. a mother and father struggle with their technologically advanced home taking over their role as parents, and their children becoming uncooperative as a result of their lack of discipline.
  11. 11. 9/25/2019 | @RebeccaDeclares | © 2019 AvenueCX, LLC. All rights reserved. 11 • Think in terms of an empathy map  Who is the user and their context? • Audience (and context)  Segment  Persona • Communication Goal  Empowerment, Understanding, etc. • Emotional Mindset  Needs Validation, Got to Be First, Buy and Be Done, etc. Representing Content Empathy Metadata
  12. 12. 9/25/2019 | @RebeccaDeclares | © 2019 AvenueCX, LLC. All rights reserved. 12 Empathy: Metadata Example What would an empathy metadata structure look like? • Context (and descriptive metadata)  Train, Travel, Snow  Young  Female  Friend  Cat, Pet • Audience (and context)  Segments – Pre-Teens, Parents  Persona – Sally the Searcher • Communication Goal  Understanding • Emotional Mindset  Wants Inspiration
  13. 13. 1/30/2020 | @RebeccaDeclares | © 2019 AvenueCX, LLC. All rights reserved. 13 • Walking the customer journey. • Relaying customer stories. • Using qualitative success measures.  Sentiment, focus groups, in-depth interviews, etc. • Gathering customer support feedback. • Leveraging sales team input (point of sale – B2C; direct sales – B2B). Empathy Inputs
  14. 14. Is This Practical at Scale?
  15. 15. 1/30/2020 | @RebeccaDeclares | © 2019 AvenueCX, LLC. All rights reserved. 15 • AI and machine learning is already used for tagging assets. • Many focus on particular verticals and associated objects (including people).  Security  Healthcare  Retail • Affective AI creates intelligence that responds to our facial expressions, vocal undertones and other nonverbal cues.  But how does this help us tag assets using empathy? AI & Metadata
  16. 16. 1/30/2020 | @RebeccaDeclares | © 2019 AvenueCX, LLC. All rights reserved. 16 Interpreting Images is Complex
  17. 17. 1/30/2020 | @RebeccaDeclares | © 2019 AvenueCX, LLC. All rights reserved. 17 • Reference datasets can vary • Breadth vs. depth affects quality depending on coverage • “Training” and review is paramount Importance of Datasets
  18. 18. 1/30/2020 | @RebeccaDeclares | © 2019 AvenueCX, LLC. All rights reserved. 18 • A ‘canonical’ training set, launched in 2009. • Grew to 14 million images (including those harvested from Google Images). • Images were organized into over 20k categories. • Used for computer vision research. • Exposed bias, issues with judgement.  Machines are only as unbiased as the training sets they work with. ImageNet Lessons Learned Datasets aren’t simply raw materials to feed algorithms, but are political interventions. As such, much of the discussion around ‘bias’ in AI systems misses the mark: there is no ‘neutral,’ ‘natural,’ or ‘apolitical’ vantage point that training data can be built upon. — Kate Crawford and Trevor Paglen
  19. 19. Multiple Opportunities for Bias
  20. 20. 9/25/2019 | @RebeccaDeclares | © 2019 AvenueCX, LLC. All rights reserved. 20 Remember Our Girls on the Train?
  21. 21. Some Final Thoughts
  22. 22. 1/30/2020 | @RebeccaDeclares | © 2019 AvenueCX, LLC. All rights reserved. 22 • Now? No • Future? Maybe • It will require well-defined datasets. • What if we consider bias as part of the context?  Mitigates risk (we know it is there)  Creates more data (potentially a bad or good thing)  Could provide more relevant experiences Tagging for Empathy at Scale?
  23. 23. THANK YOU! Rebecca Schneider Email LinkedIn Twitter rschneider@avenuecx.com linkedin.com/in/rebeccaschneider @RebeccaDeclares

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