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1
Horizon Scanning for
Charities & Civil Society
Rhodri Davies
Head of Policy & Programme Director, Giving Thought
What Are We Talking About?
2
Artificial Intelligence
Blockchain
Cryptocurrency
Big Data
3D Printing
Virtual & Augmented Reality
(VAR)
Internet of Things
(IoT)
Autonomous Vehicles &
Drones
CRISPR/ Biotech
Wearables
Robotics
Human
Augmentation
Quantum Computing
3
And Why…?
The case for charities caring about
horizon scanning
4
New ways of achieving
mission
1)
Change the way
organisations operate
2)
Create new problems to
address
3)
New Ways to Do Good
AI for Good
Blockchain for good
7
VAR for Good
9
Convergence: “Curing” Visual
Impairment?
A Changing Operating
Environment
Disintermediation & Decentralisation
Commercial
Platforms:
Social Good
Platforms:
Decentralised
movements:
Radical Transparency?
Digital Assets
Cryptocurrencies Unique Digital Objects
Direct Social Impact Recording
14
 Gartner predicts there will be 20bn IoT devices by 2020
 Many experts believe blockchain tech will provide
infrastructure for data collection and transaction
 Some data could provide proxies for social impact and
outcomes (e.g. health data, environmental data, data on from
smart homes).
Chatbots & Conversational AI
By 2020, the average
person will have more
conversations with
bots than with their
spouse. 30% of web
browsing will be done
by voice.
Chatbots will power
85% of all customer
service interactions
by the year 2020
Source: Gartner
Awareness
Info & Services
Donations
NONPROFIT APPLICATIONS
AI Philanthropy
Charity
recommender
algorithms
Social Impact
Robo-advisors
Collective
Intelligence
philanthropy
Philgorithms
Advice and Recommendations
We are increasingly accustomed
to algorithmic recommendations
Philanthropy Recommender
Algorithms?
Charity recommendations
based on past preferences
or peer group behaviour
“If you liked Cancer
Research UK, you’ll
love RNLI!”
Philgorithms
19
Algorithm which identifies
most pressing needs at any
given time + most effective
interventions for addressing
them & effects automated,
rational matching of
philanthropic supply and
demand
Are Philgorithms Feasible?
20
You can’t remove the element of heart from charitable
giving, so this will never happen!
A) We will become
accustomed to
algorithmic advice in all
areas of life, so why
not charity?
Objection:
But…
B) There has always
been a desire among
some to make giving
more rational
C) There will be
contexts in which
giving is only
feasible without
human oversight
Making Philanthropy Rational
21
Then… …And now
Immersive Tech & Empathy
22
23
The Bad Stuff…
Weaponised AI
Algorithmic Bias
When machine learning algorithms are taught using data sets that contain statistical biases
for e.g. race, gender, they exhibit and strengthen those biases over time
Filter Bubbles
• Technology such as social media
allows us to build ‘filter bubbles’
around our experience
• Likely to get worse as increasing
reliance on AI-based interfaces
tailors our experience of the world
to fit existing preferences and
biases.
Deepfakes
Crisis:
Response?Tech:
Law
Media:
The Attention Economy
“The only factor becoming scarce in a world of abundance is human attention.”
-Kevin Kelly
 Need to compete in this “attention economy” has led
to new problems:
How do charities compete for our attention without adopting techniques that
cause long-term harm?
Child Development
Current concerns:
Emerging concerns:
Future concerns?
Psychological Distance &
Desensitisation
Brundage, M. et al (2018) The Malicious Use of Artificial Intelligence:
Forecasting, Prevention and Mitigation
Is this the real life, or is this just
fantasy…?
Behaviour within virtual
environments
 Most virtual environments are designed
specifically to allow people to escape
from reality
 This may include transgressive
behaviour
 But how far should we allow this to go?
Impact of virtual
environments on reality
 ‘Gamer rage’
 Neglect of physical health
 Dissociative identity
disorder
Inequality
Inequality already a massive economic problem
Key question for development of tech: does it reduce or increase
inequality?
33
Gene Editing & Inequality
34
What Have We
Learned?
35
 Making the case for importance of
horizon scanning
 Need for intellectual freedom &
headspace
 Value of fiction & creative arts (as
source of ideas & medium for
conveying them)
 Developing knack for spotting
isomorphism
 Focus on affordances rather than
specifics of technologies
What Does Horizon Scanning Require?
Key Questions for Civil Society about
Disruptive Technologies
36
Will it offer new ways for
existing CSOs to run more
efficiently or effectively?
Could it give rise to new kinds
of donations?
Will it make it easier or
harder to identify potential
donors?
Could it give rise to entirely
new classes of donors?
Will it offer new ways of
engaging donors and
supporters?
Could the development of
this technology itself be
seen as a charitable cause?
Could it create new ways for
existing CSOs to solve social &
environmental problems?
Could it disrupt the
existing governance
structures of CSOs?
Could it create entirely new
problems that CSOs will have to
address?
Will it reduce or increase
inequality?
Could it create new challenges
for existing beneficiaries?
Will it lead to new
organisations emerging to
compete with existing CSOs?
37
Creative Ways of Presenting Issues:
CharityNamer AI
38
Creative Ways of Presenting Issues:
Washing Machine Philanthropy
39
Creative Ways of Presenting Issues:
Washing Machine Philanthropy
40
Most people in charities don’t have the time/space to think
about things in this way (e.g. short-term KPIs, need to keep
the lights on)
Barriers
“Ethics-washing”?
Power imbalance between charities and tech companies
Lack of required technical knowledge/skills
41
If they don’t take opportunity to embrace/challenge/shape tech, it will
end up being something that just happens to them (and those they serve)
- could end up being irrelevant in 5-10 years.
Why Does This Matter?
Many social problems antecedents/adjacent to criminal activities, so in
terms of “weak signals” for future crime, insight from charities could be
invaluable
Opportunity cost: charities exist to serve some of most marginalised
people and communities in society, who are likely to be hit earliest and
hardest by negative impacts of tech SO: failing to engage them in thinking
through impacts could be costly
FOR CSOs
FOR SOCIETY
FOR FUTURE
CRIME
42
Forums that enable charities to think bigger picture/longer-term
Funder support (foundations etc.)
Role of infrastructure bodies
Better links between academia and charities
Forums that bring CSOs and tech industry together whilst
overcoming power imbalances
Leadership (trustees & CEOs)
What Needs to Be Done?
43
Positive Signs?
E.g.
44
Positive Signs?
Where to find more
45

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Horizon scanning for charities and civil society

  • 1. 1 Horizon Scanning for Charities & Civil Society Rhodri Davies Head of Policy & Programme Director, Giving Thought
  • 2. What Are We Talking About? 2 Artificial Intelligence Blockchain Cryptocurrency Big Data 3D Printing Virtual & Augmented Reality (VAR) Internet of Things (IoT) Autonomous Vehicles & Drones CRISPR/ Biotech Wearables Robotics Human Augmentation Quantum Computing
  • 4. The case for charities caring about horizon scanning 4 New ways of achieving mission 1) Change the way organisations operate 2) Create new problems to address 3)
  • 5. New Ways to Do Good
  • 11. Disintermediation & Decentralisation Commercial Platforms: Social Good Platforms: Decentralised movements:
  • 14. Direct Social Impact Recording 14  Gartner predicts there will be 20bn IoT devices by 2020  Many experts believe blockchain tech will provide infrastructure for data collection and transaction  Some data could provide proxies for social impact and outcomes (e.g. health data, environmental data, data on from smart homes).
  • 15. Chatbots & Conversational AI By 2020, the average person will have more conversations with bots than with their spouse. 30% of web browsing will be done by voice. Chatbots will power 85% of all customer service interactions by the year 2020 Source: Gartner Awareness Info & Services Donations NONPROFIT APPLICATIONS
  • 17. Advice and Recommendations We are increasingly accustomed to algorithmic recommendations
  • 18. Philanthropy Recommender Algorithms? Charity recommendations based on past preferences or peer group behaviour “If you liked Cancer Research UK, you’ll love RNLI!”
  • 19. Philgorithms 19 Algorithm which identifies most pressing needs at any given time + most effective interventions for addressing them & effects automated, rational matching of philanthropic supply and demand
  • 20. Are Philgorithms Feasible? 20 You can’t remove the element of heart from charitable giving, so this will never happen! A) We will become accustomed to algorithmic advice in all areas of life, so why not charity? Objection: But… B) There has always been a desire among some to make giving more rational C) There will be contexts in which giving is only feasible without human oversight
  • 22. Immersive Tech & Empathy 22
  • 25. Algorithmic Bias When machine learning algorithms are taught using data sets that contain statistical biases for e.g. race, gender, they exhibit and strengthen those biases over time
  • 26. Filter Bubbles • Technology such as social media allows us to build ‘filter bubbles’ around our experience • Likely to get worse as increasing reliance on AI-based interfaces tailors our experience of the world to fit existing preferences and biases.
  • 28. The Attention Economy “The only factor becoming scarce in a world of abundance is human attention.” -Kevin Kelly  Need to compete in this “attention economy” has led to new problems: How do charities compete for our attention without adopting techniques that cause long-term harm?
  • 29. Child Development Current concerns: Emerging concerns: Future concerns?
  • 30. Psychological Distance & Desensitisation Brundage, M. et al (2018) The Malicious Use of Artificial Intelligence: Forecasting, Prevention and Mitigation
  • 31. Is this the real life, or is this just fantasy…? Behaviour within virtual environments  Most virtual environments are designed specifically to allow people to escape from reality  This may include transgressive behaviour  But how far should we allow this to go? Impact of virtual environments on reality  ‘Gamer rage’  Neglect of physical health  Dissociative identity disorder
  • 32. Inequality Inequality already a massive economic problem Key question for development of tech: does it reduce or increase inequality?
  • 33. 33 Gene Editing & Inequality
  • 35. 35  Making the case for importance of horizon scanning  Need for intellectual freedom & headspace  Value of fiction & creative arts (as source of ideas & medium for conveying them)  Developing knack for spotting isomorphism  Focus on affordances rather than specifics of technologies What Does Horizon Scanning Require?
  • 36. Key Questions for Civil Society about Disruptive Technologies 36 Will it offer new ways for existing CSOs to run more efficiently or effectively? Could it give rise to new kinds of donations? Will it make it easier or harder to identify potential donors? Could it give rise to entirely new classes of donors? Will it offer new ways of engaging donors and supporters? Could the development of this technology itself be seen as a charitable cause? Could it create new ways for existing CSOs to solve social & environmental problems? Could it disrupt the existing governance structures of CSOs? Could it create entirely new problems that CSOs will have to address? Will it reduce or increase inequality? Could it create new challenges for existing beneficiaries? Will it lead to new organisations emerging to compete with existing CSOs?
  • 37. 37 Creative Ways of Presenting Issues: CharityNamer AI
  • 38. 38 Creative Ways of Presenting Issues: Washing Machine Philanthropy
  • 39. 39 Creative Ways of Presenting Issues: Washing Machine Philanthropy
  • 40. 40 Most people in charities don’t have the time/space to think about things in this way (e.g. short-term KPIs, need to keep the lights on) Barriers “Ethics-washing”? Power imbalance between charities and tech companies Lack of required technical knowledge/skills
  • 41. 41 If they don’t take opportunity to embrace/challenge/shape tech, it will end up being something that just happens to them (and those they serve) - could end up being irrelevant in 5-10 years. Why Does This Matter? Many social problems antecedents/adjacent to criminal activities, so in terms of “weak signals” for future crime, insight from charities could be invaluable Opportunity cost: charities exist to serve some of most marginalised people and communities in society, who are likely to be hit earliest and hardest by negative impacts of tech SO: failing to engage them in thinking through impacts could be costly FOR CSOs FOR SOCIETY FOR FUTURE CRIME
  • 42. 42 Forums that enable charities to think bigger picture/longer-term Funder support (foundations etc.) Role of infrastructure bodies Better links between academia and charities Forums that bring CSOs and tech industry together whilst overcoming power imbalances Leadership (trustees & CEOs) What Needs to Be Done?
  • 45. Where to find more 45