the ethics of machine learning/ai - brent m. eastwood

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

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Page 1: The Ethics of Machine Learning/AI - Brent M. Eastwood

The ETHICS of machine learning/AI

Brent M. Eastwood, PhD

Page 2: The Ethics of Machine Learning/AI - Brent M. Eastwood

How do we maintain control over the

machine?

Page 3: The Ethics of Machine Learning/AI - Brent M. Eastwood

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 codeTheoretical Computer Science - you have

parsimonious reductions (counting problem of solutions for Search)

High R²

Page 4: The Ethics of Machine Learning/AI - Brent M. Eastwood

Control is easier when the machine is a 12-Year-Old It can do a repetitive simple chore very wellFor 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

Page 5: The Ethics of Machine Learning/AI - Brent M. Eastwood

ExplanatoryVariables

The Machine as a 12-Year-old Parsimony and Elegance in

Machine Learning• Spark MLLib (code provided by

Apache Spark)

Occam’s RazorParsimonyElegance

Page 6: The Ethics of Machine Learning/AI - Brent M. Eastwood

Controlling a complex machineThis is where human morality, ethics and virtue come in

The ethical human is more likely to train the machine ethically

Page 7: The Ethics of Machine Learning/AI - Brent M. Eastwood

Elon MuskARTIFICIAL INTELLIGENCEIS OUR BIGGEST EXISTENTIAL THREAT

Page 8: The Ethics of Machine Learning/AI - Brent M. Eastwood
Page 9: The Ethics of Machine Learning/AI - Brent M. Eastwood

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

Page 10: The Ethics of Machine Learning/AI - Brent M. Eastwood

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

Page 11: The Ethics of Machine Learning/AI - Brent M. Eastwood

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

Page 12: The Ethics of Machine Learning/AI - Brent M. Eastwood

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 HybridAugmented Intelligence

What if we just make the machine collegial?

Page 13: The Ethics of Machine Learning/AI - Brent M. Eastwood

RoboEthics: The TARS Humor Setting

“Hey TARS, bring the humor setting down to 75”

Page 14: The Ethics of Machine Learning/AI - Brent M. Eastwood

TARS Is a Bad BoyTARS: “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

Page 15: The Ethics of Machine Learning/AI - Brent M. Eastwood

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

Page 16: The Ethics of Machine Learning/AI - Brent M. Eastwood

The Ethics of The 'Singularity‘Commentary-January 23, 2015

Alva Noe

Page 17: The Ethics of Machine Learning/AI - Brent M. Eastwood

Keep it simple and elegant

Train the 12-year-old

Human is the “Hero” (ethical and virtuous training)

Is it our “biggest existential threat?”

Conclusion

Page 18: The Ethics of Machine Learning/AI - Brent M. Eastwood

Thank you! Brent M. Eastwood, PhD

@BMEastwood BrentEastwood.com

@GovBrain Washington, DC