This, the third in a series of four articles, is an excerpt from the Collegiate Forum at the Richard Nixon Presidential Library. This article is a bit different from the previous two as we will explore the Background and Ethics of Artificial Intelligence. The previous two articles focused on practical business applications of analytics utilizing Artificial Intelligence.
The information in the article and more will be covered at JPK Group’s 2019 Analytics Academy. Click here for more information.
The Collegiate Forum at the Richard Nixon Presidential Library
The Forum brings together bright students from top colleges across California to discuss current and pressing topics on public policy. The moderator at the Forum on April 9, 2018, Robert J Zwerling, is an expert in the AI space and a person I am happy to have founded the Finance Analytics Institute with. As the Moderator at the Forum he introduced the event with the following view of the background and ethics of Artificial Intelligence.
Artificial Intelligence or AI dates back over 75 years. Alan Turing, a mathematician explored the mathematical possibility of artificial intelligence, suggesting that “humans use available information as well as reason in order to solve problems and make decisions” and if this premise is true, then machines can do so too. This was basis of his 1950 paper, Computing Machinery and Intelligence, which he discussed “how to build intelligent machines and how to test their intelligence.”
So, what is Artificial Intelligence? Very broadly speaking it is the ability of a machine to make decisions that are done by humans. But what does that mean, what does AI look like, and how will it change our lives and society?
The most prevalent AI might be the manufacturing factory floor with robots that assemble cars. Or personal assistants like Siri on the iPhone. Think too of driverless cars as the next wave of AI.
However, little attention is given to AI in the white-collar workforce. After all, these are the college educated folk whose thinking we can’t imitate with a robot. However, this is not so. Lawyers who do patent searches, radiologists, accountants, and even judges can be replaced with AI. In fact, any rule-based process, is the first wave for white collar AI applications.
My company, Aurora Predictions, develops AI software to predict trends and forecast outcomes of sales and customer demand that are difficult for humans. A salesman sees that every deal will close, but AI can cull through many different types and large volumes of data to assemble a profile of deals that have a propensity to close and those that do not.
And, if we are successful with Aurora software, we can eliminate 50% to 75% of the manual-based spreadsheet work to free humans to higher level functions of data analysis that will drive better business performance.
An initial reaction is that AI will reduce headcount but, think for a moment of bank tellers and the ATM. While there are fewer tellers per branch there are more branches so, the whole number of tellers is actually larger.
Today’s AI while remarkable, is relatively simple. IBM’s Deep Blue supercomputer is the world’s chess champion. But, it does not reason nor is it sentient. A computer does not look into the sky and question why or become “inspired”. It cannot make discoveries from serendipitous events that trigger innovation. Humans have a combination of intellect and emotion. We empathize, reason, and have a sense of our being. We fear death. And what of all human intellect, that of “common sense”. None of this is relevant in today’s AI.
In fact, the everyday task we take for granted of visual recognition is highly advanced for current AI. The tragic death of a pedestrian in Arizona by a driverless car makes this point.
Now image the choice confronted by an AI car when a child runs into the street chasing his ball. Does the car (1) avoid hitting the child by swerving off the road and injuring the passenger in the car, or (2) avoid hitting the child and avoid hurting the passenger by causing a vehicle in the opposite direction to run into an oncoming truck behind the car? What is the choice, by what parameters is the choice made, and who decides the parameters of the choice?
You see, humans react to this situation, however, an AI car is expected to analyze the conditions and calculate an outcome. Morality is reduced to an equation to be solved.
Over time AI systems will get more and more complex and with complexity we will lose control. Sentient systems and morality can collide.
Even if we imbed, deep within the program of AI, a command never to harm a human, will a sentient android override his programming when confronted with self-preservation?
So how will society handle the disruptive technology of AI. Will people loose self-respect from lack of labor, or demand a universal basic wage for simply doing nothing? Will government devolve into those who rule and those who are ruled, or will elevated and enlightened humans no longer need government?
As for me, I ponder, if AI can free mankind from labor than:
- Will philosophers, priests, and physicists gather to contemplate the mind of the Creator
- Will standing armies be replaced with poets who battle to express the beauty of nature, and victory is the sounds of unbridled imagination?
- Will our mental resources be brought to bear to the enlightenment of art and science and what wonderous knowledge would we gain? And . . .
- Will we replace petty politics with the pursuit of wisdom and virtue?
These are the questions dreams are made of.
If you are interested in this topic, then join us at the Analytics Academy in San Diego from September 18-19th 2019.
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This article is a collaboration between Robert J Zwerling and Jesper H Sorensen from the organization Finance Analytics Institute (www.fainstitute.com) and is an excerpt from their book, Implementing an Analytics Culture for Data Driven Decisions – A Manifesto for Next Generation Finance. Robert and Jesper are the content creators behind the Analytics Academy and will teaching at the Academy in September!
Copyright 2019 Finance Analytics Institute, Robert J Zwerling & Jesper H Sorensen. All rights reserved. No part of this document may be reproduced without this copyright notice.