Slides from talk given to the Adelaide Chapter of Reasonable Faith. The video is available at https://www.youtube.com/watch?v=SQYPaLR_NbE

1. AI Implications and Ethics Today
(Tom Daly 2018)
A brief introduction to the status of AI
and consideration of some of the
current ethical questions.

2. GOALS
Start conversations
• within the “C”hurch to raise
awareness.
• (in part) use AI to highlight that
we would all benefit if science
and technology would embrace
rather than exclude theological
considerations

3. Agenda
1. Introduction to AI
2. Implications of AI
– Economic / societal
– Direct Ethical considerations
– Risks
3. Implications from the future “today”
4. Initial thoughts on how to respond

4. AI Introduction

5. AI Introduction
Definition
Artificial Intelligence
is intelligence displayed by machines, in contrast
with the natural intelligence (NI) displayed by
humans and other animals.
Machine Learning
gives computers the ability to learn without being
explicitly programmed. (Arthur Samuel 1957)

6. • Image recognition & processing (c.f. human sight)
• Speech recognition
– natural language processing
• speech to text <-> text to speech
• language translation
• Rudimentary Spatial awareness
– via imaging and radar etc
– Boston Dynamics robot arms for examples.
• Rudimentary modeling
– prediction
AI Introduction
some important components – that are part of overall AI “progress”

7. AI is today
Far broader than just (ro)bots
• Junk mail filtering
• Credit Card companies : fraud detection
• Hiring/recruiting
• Driverless cars
• Electronic assistants : Siri, Alexa Cortana etc
• Google search
• Facebook,Google, advertising, marketing etc
• Medical (reading scans, images, diagnostics,
surgery and more ... )
• Boston Dynamics,
• Amazon Go : cashless supermarkets
• Cloud (early) : AI used to spot and fix/manage
operational errors
• Face recognition
– fun e.g. photos on your laptop/facebook
– anti-terror and policing uses, for tracking people.
– major crimes ?
• Uber/Lyft – ML for pricing
• Navigation (maps)
• Financial modeling / stock market trading
• Loan approving / credit risk
• Speech recognition
• Language translation
• Text to Speech
• Battlefield and Warfare (LAWs)
• Image recognition
• Game playing
– Watson – chess , AlphaGo and AlphaGo Zero => watershed
moment!
• Legal/Paralegal
• Crime fighting
– modeling / prediction
And so much more !
customer
service BOTS ?

8. AI is already causing changes

9. AI Today – Examples
Amazon Go , Bingo Box
https://technode.com/2017/09/28/bingobox-unveils-new-ai-tech-for-
its-unmanned-stores
BingoBox
• fast moving consumer
goods
• cheaper (?)
• like automated OTR

10. AI Today – Example
Medical Imaging
• IBM Deep learning => identifying tuberculosis with 96 percent
accuracy
• IBM Deep Patient => predict disease given a patient's medical
records. The application proved to be considerably better at
forecasting disease than physicians—even for schizophrenia.
https://www.ibm.com/developerworks/library/cc-beginner-guide-machine-learning-ai-
cognitive/index.html
Smart Phone apps https://iq.intel.com/skin-cancer-detection-using-artificial-
intelligence/?sf181438035=1
• initially 10,000 photos
• looking for 100 of thousands more
How many images/patients could a dermatologist view in their lifetime ?
How does the medical professionals role change in light of this “type” of application?

11. AI Today – Example
Mortality prediction
• for end of life (so can die at home)
• predict sudden death => intervention
https://spectrum.ieee.org/the-human-
os/biomedical/diagnostics/stanfords-ai-predicts-death-for-better-end-
of-life-care
University of Adelaide have developed an AI that can
analyze CT scans to predict if a patient will die within five
years with 69 percent accuracy.

12. • Computing power (enables Deep Neural Networks)
• Moore’s law , GPUs , (soon Quantum)
• Large Super Computers -> PC -> Cloud
• Democratization of Tools and Techniques
• Availability of large data sets (many for free)
• IOT (cameras , sensors, cars , phones … )
• facebook, google …
• scientific: SKA to capture 1ZB data/6 hrs
AI Today – why now
Computing power and big data
computing power increasing
exponentially

13. AI Today – why now
Collaboration / neuroscience advances
Internet and globalisation
 sharing of information , building on progress
 C.F. Human gnome project where collaboration was key
Advances in neuroscience
• advances in imaging
• AI adopting discoveries and models from neuro and cognitive sciences
https://www.technologyreview.com/video/609389/understanding-intelligence/

14. AI Today – why now
M-O-N-E-Y !
Follow the Money
 China
 US Tech Companies
 Facebook, AWS, Google , Oracle, IBM
Microsoft and many many more
 huge venture capital => drives innovation
 Defence and Govt agencies
https://www.forbes.com/sites/louiscolumbu
s/2018/02/18/roundup-of-machine-
learning-forecasts-and-market-estimates-
2018/#13c9280d2225
ML patents grew at a 34% (CAGR)
between 2013 and 2017, the third-
fastest growing category of all
patents granted.
IDC: spending on AI and ML will
grow from $12B in 2017 to $57.6B
by 2021.
Deloitte Global: #of machine
learning pilots and implementations
will double in 2018 compared to
2017, and double again by 2020

15. Existing
Technology
AI Continuum
Automation
/Robotics
AI , Deep
Learning
DNN
time
Human
level AGI
Super
Intelligence
Intelligence
unknown
time assumed to
happen
quickly
we are here
Still a huge gap

16. AI Implications

17. Areas of Implications of AI
Economic/social Ethics
Use of AI
• Significant job loss and
structural change
• UBI
• impact on developing
countries
• Who owns assets E.g.
Uber
• Meaning / Purpose
without employment Good Bad
Intrinsic
Risks
• legal responsibility for AI
• AI goals/value encoding
• Biases (e.g. racial)
• black box problem
• Augmentation
• Cure diseases
• climate and ecology
• solve energy issues
• reduce road toll
• ease poverty(?)
• assisted living
• AI assisted research
• autonomous
weapons
• Replacement
for “beating
heart”?
• Sex
robots/Deep
fakes
• catastrophic failure
• AI arms race
• govenment misuse
• new security threats
• SuperIntelligence
Alignment problem /
loss of control
• investment in AI
power not risk
mitigation
Theological/Philosop
hical
(Super Intelligence)
• create god(s)
• become god(s)
• alignment issues
• justice
• freewill
• mercy
• morality
• agency
• what does it mean to be
human?
• mind or matter first
• machine rights
• charity/empathy/compa
ssion
• moral to stop it / kill it ?
• consciousness
• Implications for
Christianity

18. Employment / Economic implications
Job losses just from transport are potentially signifcant !
http://www.abc.net.au/news/2017-03-11/everything-you-need-
to-know-about-driverless-cars/8336322
Highly automated 2020
Fully automated next decade
(i.e. 2020’s)
Society of Automotive Engineers/VicRoads
Robotaxi permit gets
Arizona’s OK; Waymo will
start service in 2018
Insurance industry is “very aware” and preparing for massive change

19. Employment / Economic implications
significant loss of employment over broad range – looking likely
From MIT where there is a HUGE investment
into AI research and robotics
http://www.abc.net.au/news/2017-08-08/could-a-
robot-do-your-job-artificial-intelligence/8782174
Feb 2018 NAB
announced 6000 job
losses due entirely to
automation
ABC Website has
some good analysis
on AI and jobs

20. World Economic Forum
• USA Med students start with $300K debt , but if AI is doing better diagnostics than
doctors, then try paying that off as a yoga teacher.
• In Germany robots have effectively blocked many from entering the manufacturing field,
instead higher numbers go straight into service jobs.
• global management consultants McKinsey “More than a fifth of the global labour force -
800 million workers - might lose their jobs because of automation.”
Oxford University academics Carl Frey and Michael Osborne,
• 47 percent of jobs in the US were at high risk of being automated
OECD :
• 10% job loss but significant structural change in many jobs .
World Bank :
• World Bank Group President Jim Yong Kim says the world is a on a "crash
course"
Employment / Economic implications
Number of jobs lost to AI is debated, the fact of Job loss and change in not.

21. Offshoring took jobs and placed them in
developing countries
What happens now that workers in developing
countries are competing with AI and robots in
richer countries ?
E.g. Call centres
• jobs reduced by AI bots (text and voice)
• potential for cost savings is large i.e. $/day
is starting to look expensive
Employment / Economic implications
Developing Countries
BOTS
• don’t need a break
• can work 24*7
• get sick or need health care
• scale cheaply
• get cheaper with more work
• are owned by the rich
• can have the right “voice”

22. • Once heard a sermon from Tim Costello where he referred to work as
“occupational therapy” as it is closely tied to identity and often personal value
• Universal basic wage or universal basic income is appearing in the mainstream
media.
• Who owns assets ?
– e.g. Uber for instance
– Robot Tax c.f. land tax
Employment / Economic implications
Compare Industrial revolution => societal change
Job losses and displacement from AI and automation are already happening, perhaps
it is just change but what if it is more than that ?
What is the meaning of work ?

23. Ethics

24. Ethics in use of AI
beneficial uses of AI : some examples
• reduce road toll
– approx 36,000 deaths in the US , 1200 in Australia in
2017
• enable discovery of cures for diseases
– Cancer and disease screening set to be vastly more
reliable
– AI may discover answers to medical questions we
haven’t yet asked
• Assisted living (disabled, elderly)
• Assist developing world
– AI and chatbots gathering data, directly assisting people
Is there a “moral obligation” to pursue AI because of the suffering it could alleviate ?
Stanford research
IBM
investment
World Bank Blog

25. Note the personalisation and the use of “I” and “we” pronouns
Are we fooling ourselves ? Do people in need … need a machine ?
Ethics in use of AI
bad (or at least questionable) uses of AI : woebot on FB messenger

26. Ethics in use of AI
Bad uses of AI
• AI arms race
– Intelligence itself can yeild power => AI arms race to AGI
https://motherboard.vice.com/en_us/article/xywmyk/a-global-
arms-race-to-create-a-superintelligent-ai-is-looming
• Lethal Autonomous Weapons (LAWs)
– Imagine a “drone” which learns who, what, when to
attack with no human control.
– What about swarms of autonomous drones
– Many countries are developing LAWs
http://time.com/4948633/robots-artificial-intelligence-war/
Remember a LAW is likely “writing or modifying its own code or
data ”
Boston Dynamics
have a range of ever
more capable AI robots

27. • AI powered sex robots
• Deepfakes Porn / Child Porn
Ethics in use of AI
bad uses of AI : impact on human sexuality
WikiPedia : Deepfake, a portmanteau of "deep learning"
and "fake",[1] is an artificial technique. It is used to combine
and superimpose existing images and videos onto source
images or videos.
Deepfakes may be used to create fake celebrity pornographic
videos or revenge porn.[2] Deepfake pornography surfaced
on the Internet in 2017, particularly on Reddit,[3] and has
been banned by sites including Reddit, Twitter, and
Pornhub.[4][5][6] Deepfakes can be used to create fake news
and malicious hoaxes.[7][8]

28. Moral/Ethical implication #3
• Today AI used (increasingly) for hiring decisions
– What if the AI has indeed learned who is the “best
person for the job” , do we need to re-examine our
definition of best?
• Another example: credit rating in the US
– racial bias built into the data, but it is data !
Ethics : Intrinsic
Example : decision making HR
Great example of challenges of goal alignment => we had better be honest, but
also who chooses ?

29. Moral/Ethical implication #3
• Example : AI used to determine/assist recidivism risk i.e parole / bail
 Good, because it is well known that human factors can negatively influence outcomes (e.g.
prior to lunch, after lunch variation)
 Challenging because how do we know the basis of a decision
?https://www.nytimes.com/2017/05/01/us/politics/sent-to-prison-by-a-software-
programs-secret-algorithms.html
• Example: a particular classifier engine classifies “husky dog” as wolf but never
actually gave weight to the part of the image that was the dog.
Ethics : Intrinsic
decision making , black box problem
Black-Box problem: not possible to understand the AI’s
decisions/results
Is there some human “uniqueness” needed ?

30. Risks

31. • Catastrophic failure
– c.f. nuclear weapons
• New AI based cyber attacks
– MicroSoft using VR to “test” advanced AI’s against “attack”
– “indeed, the big takeaway of the report is that AI is now on the cusp of
being a tremendously negative disruptive force as rival states, criminals,
and terrorists use the scale and efficiency of AI to launch finely-targeted
and highly efficient attacks”
Risks
https://www.gizmodo.com.au/2018/02/new-
report-on-ai-risks-paints-a-grim-future
• Oxford “Future of humanity institute”
• Cambridge “Centre for study of existential risk”
• EFF (electronic frontiers foundation)
• OpenAI
Stuxnet

32. • Investment
– Money going into AI power not risk mitigation both
• Human influences
– Microsoft Tay chatbot
• Courts and evidence
– fake audio, fake video
Risks
ABC Website 4th March 2018
Scientific American

33. Nudge Theory / pursasion
– AI chatbots already suspected of influencing political
opinions via social media (c.f. subliminal adverstising
on steroids)
– 2017 Veritas Forum at Brown : “ Can Robots Become
Human”
https://www.youtube.com/watch?v=tbUnMhod_A0
– Guardian Science Weekly podcast on AI from 2017
Risks

34. Risks
"We've deployed new AI tools
that do a better job of
identifying fake accounts that
may be trying to interfere in
elections or spread
misinformation," he said.
"There are people in Russia
whose job it is to try to exploit
our systems and other internet
systems … so this is an arms
race.
Example of “AI and power being connected”

35. • Surveilence
– Video
• facial recognition
• tracking
• top of head / shoulders recognition / tracking
– drone(s)
– USA seriously considering requiring “social media account access” as visa /
immigration requirement
• E.g. China “citizen number”
Risks

36. Implications from the future
prelude to part #2

37. Theological implications
What our culture is being told : why it matters now, not tomorrow.
“I am absolutely convinced that the gas chambers of Auschwitz,
Treblinka, and Maidanek were ultimately prepared not in some
ministry or other in Berlin, but rather at the desks and in the lecture
halls of nihilistic scientists and philosophers.”
Viktor E Frankl (2012).
“The Doctor and the Soul: From Psychotherapy to Logotherapy”
Suggests :
academic, scientific statements/beliefs about AI made today => effect tomorrow
Implies:
important to understand and critically examine these statements/beliefs today

38. https://www.wired.com/2017/04/the-myth-of-a-superhuman-ai/
Excerpt: Many proponents of an explosion of intelligence expect it will produce an explosion of
progress. I call this mythical belief “thinkism.” It’s the fallacy that future levels of progress are only
hindered by a lack of thinking power, or intelligence. (I might also note that the belief that thinking is
the magic super ingredient to a cure-all is held by a lot of guys who like to think.)
Theological implications
Also interestingly this.
But what about the (broken) state
of the human heart
lust for power
love of money
devotion to sex
Will more available intelligence solve or amplify the issues of the heart ?
How do we avoid tainting an AI with these human characteristics
nationalism
pride
fear
hatred
indifference
…

39. Areas of Implications of AI
Economic/social Ethics
Use of AI
• Significant job loss and
structural change
• UBI
• impact on developing
countries
• Who owns assets E.g.
Uber
• Meaning / Purpose
without employment Good Bad
Intrinsic
Risks
• legal responsibility for AI
• AI goals/value encoding
• Biases (e.g. racial)
• black box problem
• Augmentation
• Cure diseases
• climate and ecology
• solve energy issues
• reduce road toll
• ease poverty(?)
• assisted living
• AI assisted research
• autonomous
weapons
• Replacement
for “beating
heart”
• Sex robots
• Deep fakes
• catastrophic failure
• AI arms race
• govenment misuse
• new security threats
• SuperIntelligence
Alignment problem /
loss of control
• investment in AI
power not risk
mitigation
Theological/Philosop
hical
(Super Intelligence)
• create god(s)
• become god(s)
• alignment issues
• justice
• freewill
• mercy
• morality
• agency
• what does it mean to be
human?
• mind or matter first
• machine rights
• charity/empathy/compa
ssion
• moral to stop it / kill it ?
• consciousness
• Implications for
Christianity

40. Thoughts on how to respond

41. General Responses “Today”
1. Recognise the increasing rate of “change” due in
part to technology
2. Question how and where AI is being relied upon
3. Start to foster dialogue in workplace
4. Take charge of “tech in our families”

42. Christian Responses
Identify / investigate / raise discussions about
resources that Christian faith (should) provide: -
 demonstrate the resources that faith in Christ offers
such as peace and hope in an uncertain world
 basis for human value in a world of less or drastically
different and more segregated work
 thoughtful discussion of need of “human uniqueness”

43. Christian Responses
 challenge and investigate the cultural assumption
that AI/science/tech can solve all of mankind’s
problems.
 Given the corresponding fears of
AGI/SuperIntelligence we have a moment in time
in which to do so!