In our AI augmented society attention becomes the most traded commodity. We see it in voice applications (Google Assistant, Alexa etc), trending audio consumed information (podcasts, audio books etc), automotive applications using attention as a safety feature, retail optimizing their inventory or further monetizing and why not soon Netflix automatically pausing our film if our attention switches to something else nearby. But where do the attention and AI intersect and how we can all benefit? Eye tracking, auditing algorithms and trading our attention.

1. Human Attention (HA)
for an AI augmented world

3. Voice Applications
Applications
Automotive
ApplicationsApplications
Retail
Applications
Applications
Audio/Video
Google Assistant
Alexa
Dubbing voices
Podcasts
Audio Books
Netflix
Attention as a safety feature Optimizing inventory for further
monetizing

4. Why is Human Attention a metric?
Applications
NPR Podcast, May ‘19 - “How Tech Hijacks Our Brains, Corrupts Culture, And What To Do Now”
Applications

5. It takes 9 months to grow attention.

6. About every 40 seconds we switch out attention.
Applications

7. Voice Applications
Applications

8. Voice Applications
Applications

9. Voice Applications - THE metric

10. Voice Applications - e.g. Google Assistant
.tell(‘
<speak>
Engage users through the Google Assistant.
</speak>
‘);

11. Voice Applications
Applications

12. Voice Applications - DubbingApplications
Credits: Synthesia ENACT

13. Audio/Video
Recommender
systems for
Personalization
Artwork
personalization,
content
distribution.
Netflix,
Podcasts, Audio
books
Audio-first,
the new wave.
Optimization
Post-production: Optimize
video & audio encoding;
adaptive bitrate selection.
Pre-production: location
scouting.

14. Netflix

15. Automotive Applications
Interface between Humans and AI
Driver Monitoring System (DMS)
● cabin monitoring via 3D head and eye tracking
systems
● Eye tracking combined with speech technologies

16. Automotive Applications - Eye tracking
Image credits: eyeware.tech

17. Automotive Applications - Eye tracking
Computer Vision
All methods that use computer algorithms in order to
decide what an image or video contains.
Machine Learning
System’s ability to be trained by being exposed to
datasets.
Deep Learning
Many-layered neural networks. Highly modern
types of machine learning methods, based on
AI-technology.
Image credits: eyeware.tech

18. Retail ApplicationsApplications

19. Image credits: Advertima’s attention tracking

20. Retail Applications - consumer behaviour observed
Consumers want
experiences not
products.
Experiential
Marketing
72% of millennials
prefer to spend money
on experiences rather
than material things
(Harris Group study).
Millennials
Reconcile the difference
between shoppers’
words and their actions
Eye tracking insights
for personalization &
experimentation

21. Auditing
Algorithms

22. Current AI’s Hierarchy of needs
1 Self-actualization
3
Love & belonging
5
Psychological
needs
2
Esteem
4Safety needs
Datasets, people
Models, algos
XAI Conclusions
Sentient AI
Child AIs

23. Explainable AI - by DARPA

24. How are YOU trading YOUR attention?