How I'm using biological data to tell better stories -- and spark social change
-
0:01 - 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.
-
0:30 - 0:31(Laughter)
-
0:31 - 0:35But then I began to wonder
whether a game or an app -
0:35 - 0:37can really change attitudes and behaviors,
-
0:37 - 0:40and if so, can I measure that change?
-
0:40 - 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 - 1:23might be taking over
our cognitive and affective faculties, -
1:23 - 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 - 1:55that move us to act?"
-
1:57 - 2:01To 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 - 2:10The lab not only captures
-
2:10 - 2:14the brain and body's unconscious response
to media and technology, -
2:14 - 2:17but also uses machine learning
to adapt content -
2:17 - 2:20based on these biological responses.
-
2:21 - 2:24My goal is to find out what combination
of narrative ingredients -
2:24 - 2:26are the most appealing and galvanizing
-
2:26 - 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 - 2:39The Limbic Lab consists of two components:
-
2:39 - 2:41a narrative engine and a media machine.
-
2:42 - 2:47While a subject is viewing
or interacting with media content, -
2:47 - 2:51the narrative engine takes in and syncs
real-time data from brain waves, -
2:51 - 2:54biophysical data like heart rate,
blood flow, body temperature -
2:54 - 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 - 3:07character interaction
or unusual camera angles occur. -
3:08 - 3:11Like the final scene
in "Game of Thrones, Red Wedding," -
3:11 - 3:13when shockingly,
-
3:13 - 3:15everybody dies.
-
3:15 - 3:16(Laughter)
-
3:17 - 3:20Survey data on that
person's political beliefs, -
3:20 - 3:23along with their psychographic
and demographic data, -
3:23 - 3:25are integrated into the system
-
3:25 - 3:28to gain a deeper understanding
of the individual. -
3:29 - 3:30Let me give you an example.
-
3:32 - 3:37Matching people's TV preferences
with their views on social justice issues -
3:37 - 3:41reveals that Americans who rank
immigration among their top three concerns -
3:41 - 3:44are more likely to be fans
of "The Walking Dead," -
3:45 - 3:48and they often watch
for the adrenaline boost, -
3:48 - 3:49which is measurable.
-
3:50 - 3:54A person's biological signature
and their survey response -
3:54 - 3:59combines into 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.
-
4:11 - 4:14The more imprints added to the database
-
4:14 - 4:17across mediums from episodic
television to games, -
4:17 - 4:19the better the predictive models become.
-
4:20 - 4:24In short, I am mapping
the first media genome. -
4:24 - 4:28(Applause and cheers)
-
4:32 - 4:35Whereas the human genome
identifies all genes involved -
4:35 - 4:37in 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. -
4:46 - 4:49Already the Limbic Lab's narrative engine
-
4:50 - 4:53helps content creators
refine their storytelling -
4:53 - 4:57so that it resonates with their target
audiences on an individual level. -
4:59 - 5:01The Limbic Lab's other component,
-
5:01 - 5:03the media machine,
-
5:03 - 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 artificial 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 if nonprofits and media makers
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.
-
5:41 - 5:44To date, most media
and social-change strategies -
5:44 - 5:47have attempted to appeal
to mass audiences, -
5:47 - 5:50but the future is media
customized for each person. -
5:51 - 5:54As real-time measurement
of media consumption -
5:54 - 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,
biometrics and AI. -
6:06 - 6:10It's like personalized medicine
based on our DNA. -
6:10 - 6:12I call it "biomedia."
-
6:13 - 6:16I am currently testing
the Limbic Lab in a pilot study -
6:16 - 6:18with the Norman Lear Center,
-
6:18 - 6:22which looks at the top 50
episodic television shows. -
6:22 - 6:25But I am grappling
with an ethical dilemma. -
6:25 - 6:29If I design a tool
that can be turned into a weapon, -
6:29 - 6:30should I build it?
-
6:32 - 6:35By open-sourcing the lab
to encourage access and inclusivity, -
6:35 - 6:39I also run 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. -
6:47 - 6:51For me, therefore,
it is critical to make my research -
6:51 - 6:54as transparent to
lay audiences as GMO labels. -
6:55 - 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 cultural values -
7:08 - 7:10and social behavior,
-
7:10 - 7:15but also to actively challenge
the trajectory of future technology. -
7:15 - 7:19It is my hope that we make
an ethical commitment -
7:19 - 7:21to harvesting the body's intelligence
-
7:21 - 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 - 7:34(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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