Artificial Intelligence and machine learning has the potential for greater good and danger itself. Eastwood questions the ethics behind machine learning and artificial intelligence. Brent M. Eastwood, PhD

1. The ETHICS
of machine
learning/AI
Brent M. Eastwood, PhD

2. How do we maintain
control over the
machine?

3. Occam’s Razor “Other things being equal,
simpler explanations are generally better
than more complex ones“
Parsimony – Computer Science – use
simple models with few rules and few
parameters; fewer lines of code
Theoretical Computer Science - you have
parsimonious reductions (counting
problem of solutions for Search)
High R²

4. Control is easier when the machine is a 12-Year-Old
It can do a repetitive simple chore very well
For AI – simple is a robot vacuuming the house
 But it can learn the types of dirt and stains the vacuum picks up
For ML – simple control is data science

5. Explanatory
Variables
 The Machine as a 12-Year-old
 Parsimony and Elegance in Machine
Learning
• Spark MLLib (code provided by Apache Spark)
Occam’s Razor
Parsimony
Elegance

6. Controlling a complex machine
This is where human morality, ethics and virtue come in
The ethical human is more likely to train the machine ethically

7. Elon Musk
ARTIFICIAL
INTELLIGENCE
IS OUR
BIGGEST
EXISTENTIAL
THREAT

9. The Turing Test: Can a machine
think?
“If the output of the
machine is
indistinguishable from
that of a human brain,
then we have no
meaningful reason to
insist that the machine is
not thinking.”
The Innovators by Walter Isaacson, pg. 124

10. The Imitation Game: SQL vs. No SQL
• NoSQL Cluster Data
Monster
• Spark
• MongoDB
• Kafka
• Cassandra
• Elasticsearch
• The 4 V’s of Big Data
• MLlib
• MySQL Kitty Cat
• Relational and Structured
Database
• Vertical scaling
• MySQL
• SparkSQL (“Dataframes”)
• RMySQL
• Various Cloud SQLs

11. Do you ignore certain types of data?
 Room A – The NoSQl Data Monster
 Room B – MySQL Kitty Cat
 Room C- The Human
Execute the “Big Data” Turing Test

12.  IBM Watson Health usually plays
nice with doctors
 Instead of basically saying “I’m
correct…do this”
 “There is a 40% probability
that you will like this
recommendation.”
 Take a look at what I say and
check for yourself
 Human – Computer Hybrid
Augmented Intelligence
What if we just make the machine collegial?

13. RoboEthics: The TARS Humor
Setting
“Hey TARS, bring the humor setting down to 75”

14. TARS Is a Bad Boy
TARS: “I have plenty of
slaves for my robot
colony.”
TARS: “You can use it to
make your way back to
the ship when I blow
you out of the airlock

15. TARS is a Good Boy - But is collegial AI the same as ethical AI?

16. The Ethics of The 'Singularity‘
Commentary-January 23, 2015
Alva Noe

17. Keep it simple and
elegant
Train the 12-year-old
Human is the “Hero”
(ethical and virtuous
training)
Is it our “biggest
existential threat?”
Conclusi
on

18. Thank you!
Brent M. Eastwood, PhD
@BMEastwood
BrentEastwood.com
@GovBrain
Washington, DC