How I'm using biological data to tell better stories -- and spark social change
-
0:02 - 0:05For the past 15 years I've been trying
to change your mind. -
0:06 - 0:10In my work I harness pop culture
and emerging technology -
0:10 - 0:11to shift cultural norms.
-
0:12 - 0:16I've made video games
to promote human rights, -
0:16 - 0:21I've made animations to raise
awareness about unfair immigration laws -
0:21 - 0:25and I've even made location-based
augmented reality apps -
0:25 - 0:28to change perceptions around homelessness
-
0:28 - 0:29well before Pokémon Go.
-
0:29 - 0:30(Laughter)
-
0:31 - 0:35But then I began to wonder
whether a game or an app -
0:35 - 0:38can really change attitudes and behaviors,
-
0:38 - 0:40and if so, can I measure that change?
-
0:41 - 0:43What's the science behind that process?
-
0:43 - 0:47So I shifted my focus
from making media and technology -
0:47 - 0:50to measuring their
neurobiological effects. -
0:51 - 0:53Here's what I discovered.
-
0:53 - 0:57The web, mobile devices,
virtual and augmented reality -
0:57 - 1:00were rescripting our nervous systems.
-
1:00 - 1:03And they were literally changing
the structure of our brain. -
1:04 - 1:09The very technologies I had been using
to positively influence hearts and minds -
1:09 - 1:13were actually eroding functions
in the brain necessary for empathy -
1:13 - 1:15and decision-making.
-
1:15 - 1:19In fact, our dependence
upon the web and mobile devices -
1:19 - 1:24might be taking over our cognitive
and affective faculties, -
1:24 - 1:27rendering us socially
and emotionally incompetent, -
1:27 - 1:30and I felt complicit
in this dehumanization. -
1:31 - 1:36I realized that before I could continue
making media about social issues, -
1:36 - 1:40I needed to reverse engineer
the harmful effects of technology. -
1:41 - 1:44To tackle this I asked myself,
-
1:44 - 1:47"How can I translate
the mechanisms of empathy, -
1:47 - 1:51the cognitive, affective
and motivational aspects, -
1:51 - 1:54into an engine that simulates
the narrative ingredients -
1:54 - 1:56that move us to act?"
-
1:57 - 2:00To answer this I had to build a machine.
-
2:01 - 2:02(Laughter)
-
2:02 - 2:05I've been developing
an open-source biometric lab, -
2:05 - 2:09an AI system which I call
the Limbic Lab. -
2:09 - 2:11The lab not only captures
-
2:11 - 2:14the brain and body's unconscious response
to media and technology, -
2:14 - 2:18but also uses machine learning
to adapt content -
2:18 - 2:20based on these biological responses.
-
2:21 - 2:24My goal is to find out what combination
of narrative ingedients -
2:24 - 2:27are the most appealing and galvanizing
-
2:27 - 2:28to specific target audiences
-
2:28 - 2:33to enable social justice, cultural
and educational organizations -
2:33 - 2:36to create more effective media.
-
2:36 - 2:40The Limbic Lab consists
of two components: -
2:40 - 2:42narrative engine and a media machine.
-
2:43 - 2:47While a subject is viewing
or interacting with media content, -
2:47 - 2:50the narrative engine takes in
and syncs real-time data -
2:50 - 2:51from brain waves,
-
2:51 - 2:55biophysical data like heart rate,
blood flow, body temperature -
2:55 - 2:56and muscle contraction
-
2:56 - 2:59as well as eye-tracking
and facial expressions. -
3:00 - 3:04Data is captured at key places
where critical plot points, -
3:04 - 3:05character interaction
-
3:05 - 3:07or unusual camera angles occur.
-
3:09 - 3:12Like the final scene
in "Game of Thrones" "Red Wedding," -
3:12 - 3:15when shockingly, everybody dies.
-
3:16 - 3:17(Laughter)
-
3:17 - 3:21Survey data on that
person's political beliefs, -
3:21 - 3:24along with their psychographic
and demographic data, -
3:24 - 3:25are integrated into the system
-
3:25 - 3:28to gain a deeper understanding
of the individual. -
3:29 - 3:31Let me give you an example.
-
3:32 - 3:38Matching people's TV preferences
with their views on social justice issues -
3:38 - 3:41reveal that Americans who rank
immigration among their top three concerns -
3:41 - 3:45are more likely to be fans
of "The Walking Dead," -
3:45 - 3:48and they often watch
for the adrenaline boost, -
3:48 - 3:50which is measureable.
-
3:50 - 3:55A person's biological signature
and their survey response combines -
3:55 - 3:58into a database to create
their unique media imprint. -
3:59 - 4:03Then our predictive model
finds patterns between media imprints -
4:03 - 4:05and tells me which narrative ingredients
-
4:05 - 4:09are more likely to lead to engagement
in altruistic behavior -
4:09 - 4:11rather than distress and apathy.
-
4:12 - 4:16The more imprints added to the database
across mediums from episodic television -
4:16 - 4:17to games,
-
4:17 - 4:19the better the predictive models become.
-
4:21 - 4:24In short, I am mapping
the first media genome. -
4:25 - 4:29(Applause and cheers)
-
4:32 - 4:35Whereas the huiman genome
identifies all genes -
4:35 - 4:38in sequencing human DNA,
-
4:38 - 4:41the growing database of media imprints
will eventually allow me -
4:41 - 4:45to determine the media DNA
for a specific person. -
4:47 - 4:49Already the Limbic Lab's
narrative engine -
4:49 - 4:54helps content creators refine
their storytelling -
4:54 - 4:57so that it resonates with their target
audiences on an individual level. -
4:59 - 5:01The Limbic Lab's other component,
-
5:01 - 5:04the media machine,
-
5:04 - 5:08will assess how media elicits
an emotional and physiological response, -
5:08 - 5:10then pulls scenes from a content library
-
5:10 - 5:13targeted to person-specific media DNA.
-
5:14 - 5:18Applying articial intelligence
to biometric data -
5:18 - 5:21creates a truly personalized experience.
-
5:21 - 5:26One that adapts content based
on real-time unconscious responses. -
5:27 - 5:33Imagine it non-profits and mediamakers
were able to measure how audiences feel -
5:33 - 5:35as they experience it
-
5:35 - 5:37and alter content on the fly.
-
5:37 - 5:40I believe this is the future of media.
-
5:42 - 5:44To date, most media
and social-change strategies -
5:44 - 5:47have attempted to appeal
to mass audiences, -
5:47 - 5:51but the future is media customized
for each person. -
5:52 - 5:55As real-time measurement
of media consumption -
5:55 - 5:57and automated media production
becomes the norm, -
5:57 - 6:01we will soon be consuming media
tailored directly to our cravings -
6:01 - 6:05using a blend of psychographics,
biometircs and AI. -
6:07 - 6:10It's like personalized medicine
based on our DNA. -
6:10 - 6:12I call it "Biomedia."
-
6:13 - 6:17I am currently testing
the Limbic Lab in a pilot study -
6:17 - 6:18with the Norman Lear Center,
-
6:18 - 6:21which looks at the top 50
episodic television shows. -
6:22 - 6:25But I am grappling with
an ethical dilemna. -
6:26 - 6:29If I design a tool that can be
turned into a weapon, -
6:29 - 6:31should I build it?
-
6:32 - 6:36By open-sourcing the lab
to encourage access and inclusivity, -
6:36 - 6:39I also include the risk of enabling
powerful governments -
6:39 - 6:42and profit-driven companies
to appropriate the platform -
6:42 - 6:46for fake news, marketing
or other forms of mass persuasion. -
6:48 - 6:51For me therefore it is critical
to make my research -
6:51 - 6:54as transparent to lay
audiences as GMO labels. -
6:56 - 6:58However, this is not enough.
-
6:59 - 7:01As creative technologists,
-
7:01 - 7:03we have a responsibility
-
7:03 - 7:08not only to reflect upon how present
technology shapes our values -
7:08 - 7:10and social behavior,
-
7:10 - 7:14but also to actively challenge
the trajectory of future technology. -
7:15 - 7:19It is my hope that we make
an ethical commitment -
7:19 - 7:22to harvesting the body's intelligence
-
7:22 - 7:25for the creation of authentic
and just stories -
7:25 - 7:27that transform media and technology
-
7:27 - 7:31from harmful weapons
into narrative medicine. -
7:31 - 7:32Thank you.
-
7:32 - 7:35(Applause and cheers)
- Title:
- How I'm using biological data to tell better stories -- and spark social change
- Speaker:
- Heidi Boisvert
- Description:
-
- Video Language:
- English
- Team:
- closed TED
- Project:
- TEDTalks
- Duration:
- 07:49
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