Slides for a lecture I gave at the Dawes Centre for Future Crime, UCL in Feb 2020

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

3. 3
And Why…?

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

6. AI for Good

7. Blockchain for good
7

8. VAR for Good

9. 9
Convergence: “Curing” Visual
Impairment?

10. A Changing Operating
Environment

11. Disintermediation & Decentralisation
Commercial
Platforms:
Social Good
Platforms:
Decentralised
movements:

12. Radical Transparency?

13. Digital Assets
Cryptocurrencies Unique Digital Objects

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

16. AI Philanthropy
Charity
recommender
algorithms
Social Impact
Robo-advisors
Collective
Intelligence
philanthropy
Philgorithms

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

21. Making Philanthropy Rational
21
Then… …And now

22. Immersive Tech & Empathy
22

23. 23
The Bad Stuff…

24. Weaponised AI

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.

27. Deepfakes
Crisis:
Response?Tech:
Law
Media:

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

34. 34
What Have We
Learned?

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?

43. 43
Positive Signs?
E.g.

44. 44
Positive Signs?

45. Where to find more
45