intended & unintended consequences of AI

1. Definition of AI, Benefits of AI, Legal Risks of AI, and Mitigation of AI Risks


AI systems will play a major role in every aspect of life on earth.  Ai  will improve human decision making, however,  it will carry the risk of some unintended circumstances.  Authman Apatira of Coding Dojo on June 1, 2018 stated the following in his article "Ethics and Unintended Consequences  of Technology:  "Progress always comes at a cost. Paper fundamentally changed the way information was stored and distributed, but its production contributes to deforestation. Industrialization increased our standard of living, but has led to much pollution and arguably, even some social ills. The benefits brought by the internet are too many to mention, yet viral misinformation, vast erosion of privacy, and the diminishing patience of society as a whole were all unintended consequences. Not even medicine is free from side effects. This should come as no surprise because hindsight is always twenty-twenty. Rarely at the time of invention is a creator the best judge of how their system will be used, or truly knows what good or harm will come of it. Understanding this, as technologists, we ought to give pause and reflect deeply before taking on a project."



OK - first things first. We start first with data science. (DS)." According to Russ Rankin and Dr. Stephen Gardener  (Baylor 

Magazine - Fall Issue 2018 -  "Data Drive") "Data Science  is a broadly  interdisciplinary field that draws heavily on statistics  and computer science  and has applications in business, engineering, medicine, law, education, sociology, political science, and other disciplines.   Data science is the foundational field for development of AI, robotics, and other technologies that can mimic or transcend  many aspects of human intelligence." 



 The term "Artificial intelligence  (AI)  Ai dates back to about the mid-1950's. (The 1950's were famous for the development of creative  "Rock & Roll" music.  Remember Chuck Berry, Little Richard, Jerry Lee Lewis, Bo Diddley, Elvis,  Buddy Holly, Johnny Cash, Connie Francis, etc, etc?  They  also   were bursting in on the music scene in the mid-1950's.  So, it was only fitting for that time period to also be the time  of the start of development of creative ai). 

Ai was first named and identified

 in 1956 by Stanford professor / researcher John McCarthy as a sub-field of the larger academic study of computer science.  



Artificial intelligence (as a subset of data science) is the ability of  a machine  or of computer software programs (or both) to  find, assemble, process, calculate, translate, think, reason, learn, problem-solve, identify risks, create speech recognition, develop human-like speech generation, incorporate feedback,  remember,  reduce errors, exercise continuous improvement, and potentially act (to some extent). It could be performing in a manner that some people would consider it as ... "intelligent."  

AI is a field of science covering how computers can make decisions as well as (and sometimes better than) humans.  AI needs to be able to understand humans. Machine learning, a subset of AI, refers to the popular modern-day techniques for creating software that learns from data. It involves learning how to carry out a task from data without being programed to carry out the task. For example, facial recognition is machine learning. Applications of machine learning normally use a neural network.  Neural network is a computer system mimicking the human  brain.

An example of deep learning is speech recognition.



It is all about building machines or developing software / firmware capable of:  finding, assembling, processing, calculating, translating, thinking, reasoning, learning, problem-solving, identifying risks, creating speech-recognition, developing human-like speech generation,  exercising continuous improvement, remembering, reducing errors, incorporating feedback, and potentially acting / performing  (to some extent ) like people. The ai definition includes interdisciplinary scope as well as working in specific environments. It  duplicates the human thought process and behavior.  It should act in a person - like way that is intelligent, rational, reasonable, timely, and  (of course in my opinion) ethical with integrity.  



Ai is possible nowadays due to: 

(1) giant increases in computational capabilities; (2) huge growths in data (big data); (3) focusing on specific / unique problem issues;  (4) being able to timely  convert those unique issues / problems into  targeted knowledge engineering rules (algorithms) so that ai systems can learn; (5) allowing ai systems to learn the rules automatically, and (6) efficiently plugging the resulting  rules into appropriate ai systems.

There is also included in this ai definition the difference between Weak AI and Strong AI.  Strong AI genuinely simulates human reasoning while Weak AI  is just focusing on getting a system to work without simulating human cognitive behavior (thinking the way a human would think). Today most of the AI work falls somewhere between Weak Ai and Strong Ai.   Let's call that Mid-Range AI (Yep ... Miid-Range AiI s a term that is purely coined by me). Anyways ... we are not yet in the Robot Masters phase of AI !



Here is some LinkedIn information from Accenture in November 2018 about AI:

"AI has the potential to boost rates of profitability by an average of 38 percentage points and could lead to an economic boost of US$14 trillion in additional gross value added (GVA) by 2035.

Artificial Intelligence could double annual economic growth rates by 2035 by changing the nature of work and spawning a new relationship between human and machine.

The impact of AI technologies on business is projected to boost labor productivity by up to 40 percent by fundamentally changing the way work is done and reinforcing the role of people to drive growth in business.

 AI at its core combines intelligent technology with human ingenuity. Probably the most dramatic change that AI is driving for people is the nature of work.  And collaborative intelligence is very important because this is about how we take the best capabilities of a person and the best capabilities of software or machine or AI and put that together to create a new type of job. 

The idea is that there’s something missing from the discussion around AI today and it’s what’s happening in the middle between humans and machine. We tend to think about what humans are good at, which is communication, emotion, imagination, generalization, and so forth. And then you think about what machines are good at -- memorization, prediction, transaction, and more. There’s a lot of opportunity in that area in the middle and the discussion that has been missing is about how do you put humans and technology together to do new things and create new capability together. 

Human and AI technology are connected and will change the way we work and solve business problems. AI will also re-imagine society, in how we use it to solve social issues, and in how we apply it responsibly. Responsible AI is necessary for AI to come together across business, people and society and be successful.

There was no better place to talk about the last 25 years of technology, and the next 25 years when we will see epic change driven by AI. The Information Age has brought us to where we are today. The next period that will define our future and change the world.



1.  Humans will be safer during disasters;

2. Better care for the aging;

3. More independence for the elderly;

4. Reduction of traffic accidents;

5. Could become a tightly  coupled cognitive unit with humans;

6. AI can augment our brains;

7. AI can augment our bodies;

8. It can make humans better at everything;

9.  Great improvements to orthotics;

10. Wide applications to exoskeletons;

11. Improvement to human senses (vision, hearing, etc).

12. AI can help to solve climate change;

13. AI can quickly review millions of pages of documents;

14. AI can help to cure diseases;

15. Anticipated to greatly assist with space travel;

16. Improved internet access;

17. Use of robots powered by AI in homes;

18. Wide-spread embedding of AI;

19. Prevent environmental catastrophes; and

20. Creation of more free time for humans to be more creative.



The numerous legal risks that arise out of the use of artificial intelligence, (AI) including, machine learning ("ML"), deep learning (DL), robotics, robot vision (RV), internet of things (IoT), signal processing (SP), and neural networks (NN), needs to be anticipate. Here are some potential risks:

1  If a motor vehicle accident involves AI, trying to find the liable party is difficult and confusing. (i.e. a autonomous car hits another vehicle).

2    AI often has to identify vehicles, people, roads, sidewalks, traffic signals, buildings or other items. To do this, AI relies on robotic vision (cameras, radar, infrared, sonar, etc.), sensors, and recordings. Things may not look the same to AI as it does to humans. AI also can reflect the biases of the software/firmware designer/developer.

3   AI is getting getting closer to actual human-like consciousness. Robots utilizing AI may sometime be seeking certain civil rights.

4  If AI commits or is involved in a crime who is guilty? 

5  Privacy rights of people are potentially being eroded with AI.  

6  AI has been developing a very rapid rate. AI has outpaced applicable legislation.

7  How will AI generated information be used in court? (No right of cross-examination, etc.);

8. Financial services actions;

9. Constructing algorithms;

10. Healthcare issues;

11. Insurance issues;

12. Regulatory issues;

13. Reasonable man and proximately caused  issues in tort law; and

14.  Antitrust AI issues.     

15.        We also need to keep an eye on potentially harmful uses of quantum physics (QM), quantum computers (QC), quantum  mechanics (QM) and other quantum issues.



1. Understant AI;

2.  Track AI reasoning;

3. Participate in rule making;

4. Use good clean data;

5. Allocate AI risk amount applicable parties due to benefits received by the applicable parties;

6. Start early with AI;

7. Protect AI with patents and trade secrets;

8. Establish an AI team;

9. Recruit and retain AI talent; and

10. Humans will need to get smarter in order to deal with AI.

11. There needs to be a legal revolution with a focus on experiential  and  lifetime learning .

Certain portions of this section on AI legal risks and AI mitigation actions have been summarized, extracted from, and/or derived from:

 A. Understanding the Legal Implications of Artificial Intelligence,

Perkins Coie, News – Insites 5/12/2018 ... and ...

B.  A Two-Minute Guide To Artificial Intelligence

Parmy Olson, Forbes – 10/3/2018



512 619 7512











2. Current AI Applications




(To some extent, some of Johnny's Commentary below is summarized, derived from,  and/or extracted from an "AI Today" oral podcast - #057  "Is VC Funding for AI Over-rated?

Follow the money.  AI

iand its subset, machine learning, are both getting a huge amount of: (1) start-up ("non-Unicorn and Unicorn") VC funding,; (2) big company funding  (Amazon, MS, FaceBook, Google, Apple, Oracle, Accenture, Twitter, IBM, etc),  and  (3) government funding (US, China, UK, France, Germany, Japan, Russia, and South Korea ( in that order) today.  

For example (according to ABI Research) , in 2017  in the USA with  its 155  ai  VC companies there was  US$ 4.4 billion in just VC Unicorn-type funding (not including big company and government funding).  Chinese AI VC funding from its 19 companies for 2017 was US$  4.9 billion.  

AI  government funding and ai big company investments in   ai funding for 2017  is hard to calculate ... but consider this:  SenseTime is a Chinese big AI company. Its valued at US$ 4.5 billion. 


Even with all of this  AI  VC funding, it is possible that  the resulting ai solutions might not work out.   

Will ai prove itself out?  Is it the big wave promised and will the ai bubble remain inflated? AI has  tremendous promise.  I think that the US ROI will be met.  But there is a lot of competition.  

Having the right people in your labor force is important. For example, data engineers and data scientists are both urgently needed. Data scientists do the ai deep analysis. Data engineers do the management  and cleaning of big data for use by data scientists. Data scientists do the deep analysis of clean big data. You need more data engineers than data scientists. Obviously, a data scientist needs to have very high STEM skills.

The governments of the US and China. overwhelmingly dominate the AI  race. China has both its huge tech giants  and government collaborating and working closely.  The privacy issues do not hamper ai in China.  The Chinese are adding AI to the high school curriculum as a mandatory subject.    The US has a promising A labor force.  There are ai centers in the US  in  places like New York,  Boston (MIT, Harvard), Pittsburg,  Seattle ,(MS, Amazon)  Washington DC, Austin, northern and southern California. 

The global ai  race is on.  Japan is soaring in ai robotics but has an aging labor force. South Korea is pushing electronics, medical, and health ai and will soon have 5000 new data engineers. UK and France are leading the way in responsible and  ethical ai. Russia believes its future rests on ai and has sizable ai funding  but lacks  the creation of VC funding by companies."

10 Powerful AI Applications In Use Today


R.L. Adams


Author, blogger, software engineer and serial entrepreneur. Contributor to some of the biggest media platforms including Forbes, Entrepreneur Magazine, Huffington Post and Engadget. Founder and curator of, one of the most popular inspirational blogs. 

R.L. Adams is a software engineer, serial entrepreneur, and author. He runs a wildly-popular blog called Wanderlust Worker and contributes to Entrepreneur, Engadget and the Huffington.

© Copyright 2018 Forbes Media LLC. All Rights Reserved

"The machines haven't taken over. Not yet at least. However, they are seeping their way into our lives, affecting how we live, work and entertain ourselves. From voice-powered personal assistants like Siri and Alexa, to more underlying and fundamental technologies such as behavioral algorithms, suggestive searches and autonomously-powered self-driving vehicles boasting powerful predictive capabilities, there are several examples and applications of artificial intelligence in use today.

However, the technology is still in its infancy. What many companies are calling AI. today, aren't necessarily so. As a software engineer, I can claim that any piece of software has A.I. due to an algorithm that responds based on pre-defined multi-faceted input or user behavior. That isn't necessarily .I.

A true artificially-intelligent system is one that can learn on its own. We're talking about neural networks from the likes of Google's DeepMind, which can make connections and reach meanings without relying on pre-defined behavioral algorithms. True A.I. can improve on past iterations, getting smarter and more aware, allowing it to enhance its capabilities and its knowledge.

That type of A.I., the kind that we see in wonderful stories depicted on television through the likes of HBO's powerful and moving series, Westworld, or Alex Garland's, Ex Machina, are still way off. We're not talking about that. At least not yet. Today, we're talking about the pseudo-A.I. technologies that are driving much of our voice and non-voice based interactions with the machines -- the machine-learning phase of the Digital Age.

While companies like Apple, Facebook and Tesla rollout ground-breaking updates and revolutionary changes to how we interact with machine-learning technology, many of us are still clueless on just how A.I. is being used today by businesses both big and small. How much of an effect will this technology have on our future lives and what other ways will it seep into day-to-day life? When A.I. really blossoms, how much of an improvement will it have on the current iterations of this so-called technology?



Engage Employees And Spur Productivity With Workplace Flexibility Via The Cloud

Intuitive Surgical BRANDVOICE

A History Of Hard Work: Meaningful Innovation And A Systems Approach To Surgery


Enabling Your Employees To Become Change Makers

A.I. And Quantum Computing

The truth is that, whether or not true A.I. is out there or is actually a threat to our existence, there's no stopping its evolution and its rise. Humans have always fixated themselves on improving life across every spectrum, and the use of technology has become the vehicle for doing just that. And although the past 100 years have seen the most dramatic technological upheavals to life than in all of human history, the next 100 years is set to pave the way for a multi-generational leap forward.

This will be at the hands of artificial intelligence. A.I. will also become smarter, faster, more fluid and human-like thanks to the inevitable rise of quantum computing. Quantum computers will not only solve all of life's most complex problems and mysteries regarding the environment, aging, disease, war, poverty, famine, the origins of the universe and deep-space exploration, just to name a few, it'll soon power all of our A.I. systems, acting as the brains of these super-human machines.

However, quantum computers hold their own inherent risks. What happens after the first quantum computer goes online, making the rest of the world's computing obsolete? How will existing architecture be protected from the threat that these quantum computers pose? Considering that the world lacks any formidable quantum resistant cryptography (QRC), how will a country like the United States or Russia protect its assets from rogue nations or bad actors that are hellbent on using quantum computers to hack the world's most secretive and lucrative information?

In a conversation with Nigel Smart, founder of Dyadic Security and Vice President of the International Association of Cryptologic Research, a Professor of Cryptology at the University of Bristol and an ERC Advanced Grant holder, he tells me that quantum computers could still be about 5 years out. However, when the first quantum computer is built, Smart tells me that:

"...all of the world's digital security is essentially broken. The internet will not be secure, as we rely on algorithms which are broken by quantum computers to secure our connections to web sites, download emails and everything else. Even updates to phones, and downloading applications from App stores will be broken and unreliable. Banking transactions via chip-and-PIN could [also] be rendered insecure (depending on exactly how the system is implemented in each country)."

Clearly, there's no stopping a quantum computer led by a determined party without a solid QRC. While all of it is still what seems like a far way off, the future of this technology presents a Catch-22, able to solve the world's problems and likely to power all the A.I. systems on earth, but also incredibly dangerous in the wrong hands.

Applications of Artificial Intelligence In Use Today:

Beyond our quantum-computing conundrum, today's so-called A.I. systems are merely advanced machine learning software with extensive behavioral algorithms that adapt themselves to our likes and dislikes. While extremely useful, these machines aren't getting smarter in the existential sense, but they are improving their skills and usefulness based on a large dataset. These are some of the most popular examples of artificial intelligence that's being used today.

#1 -- Siri

Everyone is familiar with Apple's personal assistant, Siri. She's the friendly voice-activated computer that we interact with on a daily basis. She helps us find information, gives us directions, add events to our calendars, helps us send messages and so on. Siri is a pseudo-intelligent digital personal assistant. She uses machine-learning technology to get smarter and better able to predict and understand our natural-language questions and requests.

#2 -- Alexa

Alexa's rise to become the smart home's hub, has been somewhat meteoric. When Amazon first introduced Alexa, it took much of the world by storm. However, it's usefulness and its uncanny ability to decipher speech from anywhere in the room has made it a revolutionary product that can help us scour the web for information, shop, schedule appointments, set alarms and a million other things, but also help power our smart homes and be a conduit for those that might have limited mobility.

#3 -- Tesla

If you don't own a Tesla, you have no idea what you're missing. This is quite possibly one of the best cars ever made. Not only for the fact that it's received so many accolades, but because of its predictive capabilities, self-driving features and sheer technological "coolness." Anyone that's into technology and cars needs to own a Tesla, and these vehicles are only getting smarter and smarter thanks to their over-the-air updates.

#4 -- Cogito

Originally co-founded by CEO, Joshua Feast and, Dr. Sandy Pentland, Cogito is quite possibly one of the most powerful examples of behavioral adaptation to improve the emotional intelligence of customer support representatives that exists on the market today. The company is a fusion of machine learning and behavioral science to improve the customer interaction for phone professionals. This applies to millions upon millions of voice calls that are occurring on a daily basis.

#5 -- Boxever

Boxever, co-founded by CEO, Dave O’Flanagan, is a company that leans heavily on machine learning to improve the customer's experience in the travel industry and deliver 'micro-moments,' or experiences that delight the customers along the way. It's through machine learning and the usage of A.I. that the company has dominated the playing field, helping its customers to find new ways to engage their clients in their travel journeys.

#6 -- John Paul

John Paul, a highly-esteemed luxury travel concierge company helmed by its astute founder, David Amsellem, is another powerful example of potent AI in the predictive algorithms for existing-client interactions, able to understand and know their desires and needs on an acute level. The company powers the concierge services for millions of customers through the world's largest companies such as VISA, Orange and Air France, and was recently acquired by Accor Hotels.

#7 --

Amazon's transactional AI is something that's been in existence for quite some time, allowing it to make astronomical amounts of money online. With its algorithms refined more and more with each passing year, the company has gotten acutely smart at predicting just what we're interested in purchasing based on our online behavior. While Amazon plans to ship products to us before we even know we need them, it hasn't quite gotten there yet. But it's most certainly on its horizons.

#8 -- Netflix

Netflix provides highly accurate predictive technology based on customer's reactions to films. It analyzes billions of records to suggest films that you might like based on your previous reactions and choices of films. This tech is getting smarter and smarter by the year as the dataset grows. However, the tech's only drawback is that most small-labeled movies go unnoticed while big-named movies grow and balloon on the platform.

#9 -- Pandora

Pandora's A.I. is quite possibly one of the most revolutionary techs that exists out there today. They call it their musical DNA. Based on 400 musical characteristics, each song is first manually analyzed by a team of professional musicians based on this criteria, and the system has an incredible track record for recommending songs that would otherwise go unnoticed but that people inherently love.

#10 -- Nest

Most everyone is familiar with Nest, the learning thermostat that was acquired by Google in January of 2014 for $3.2 billion. The Nest learning thermostat, which, by the way, can now be voice-controlled by Alexa, uses behavioral algorithms to predictively learn from your heating and cooling needs, thus anticipating and adjusting the temperature in your home or office based on your own personal needs, and also now includes a suite of other products such as the Nest cameras."

R.L. Adams  ---- Above article ---

.Author, blogger, software engineer and serial entrepreneur. Contributor to some of the biggest media platforms including Forbes, Entrepreneur Magazine, Huffington Post and Engadget. Founder and curator of, one of the most popular inspirational blogs in t...

R.L. Adams is a software engineer, serial entrepreneur, and author. He runs a wildly-popular blog called Wanderlust Worker and contributes to Entrepreneur, Engadget and the Huffington 

Above article ` ©2018 Forbes Media LLC. All Rights Reserved



1. ARGOBOT - AI APPLICATION FOR  FARMING: Tracks the status and health of each individual strawberry to determine the best berry-specific management of each strawberry.

2. ROBORACE - AI APPLICATION FOR AUTO RACES: Race cars drive themselves in a race  tracking and managing  each vehicle in race with no human driver.

3. WILDBOOD -AI APPLICATION FOR MANAGING ZEBRAS AND ELEPHANTS:  AI enabled system identifies each animal and tracks the individual health, location, and status of each animal in an African country.

4. ICEBURG - AI APPLICATION FOR HOCKEY:  Manages the multitude of game statistics and analyzes   pros/cons of each player.

5. SMART DRONE - AI APPLICATION FOR CONTROLLING PHOTOGRAPHIC DRONES; Manages the control  and positioning  of the drone including multiple cameras in order to take the best desired photo..

MOTION PICTURE TRAILER DEVELOPMENT:  Motion picture companies are using AI to develop motion picture trailers based on the particular viewers of a trailer.

UNDERWATER ROBOTS: Underwater scientists are using AI in underwater robots to control the increasing number of harmful star fish.


Johnny's Creatives

Despite the vast capabilities of AI  there is also a lot of hype out there about Al. There is one general  area where  AiI may never fully cover ... or at least not any time soon.  I refer  to it as ... "the creatives"... human love, pride, humor, sarcasm, laughter, smiling, frowning, sadness, pain, joy, emotions, intuition, body language, gift of discernment, faith, trust, soul, fear, arts, and other similar


3. Future AI Applications


18 artificial intelligence researchers reveal the profound changes coming to our lives:

Read the original article on Tech Insider.

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Below Article (C) Copyright Tech Insider 2018.


"Artificial intelligence (AI) has been changing our lives for decades, but never has AI felt more ubiquitous than now.

It seems as though not a week passes without yet another AI system overcoming an unprecedented hurdle or outperforming humans.

But how the future of AI will pan out for humans remains to be seen. AI could either make all our dreams come true, or destroy society and the world as we know it.

To get an a realistic handle on what that future might look like, Tech Insider spoke to 18 artificial intelligence researchers, roboticists, and computer scientists about the single most profound change artificial intelligence could bring.

Scroll down to see their lightly edited responses.

Pieter Abbeel says robots will keep us safer, especially from disasters.

Japanese officials inspect the damaged Fukushima Daiichi nuclear power plant. 


AI for robotics will allow us to address the challenges in taking care of an aging population and allow much longer independence.

It'll enable drastically reducing, maybe even bringing to zero, traffic accidents and deaths. And enable disaster response for dangerous situations, for example, the nuclear meltdown at the Fukushima power plant.

Commentary from Pieter Abbeel, a computer scientist at the University of California, Berkeley.

Shimon Whiteson says we will all become cyborgs.

Ints Kalnins/Reuters

I really think in the future we are all going to be cyborgs. I think this is something that people really underestimate about AI. They have a tendency to think, there's us and then there's computers. Maybe the computers will be our friends and maybe they'll be our enemies, but we'll be separate from them.

I think that's not true at all, I think the human and the computer are really, really quickly becoming one tightly-coupled cognitive unit.

Imagine how much more productive we would be if we could augment our brains with infallible memories and infallible calculators.

Society is already wrestling with difficult questions about privacy and security that have been raised by the internet. Imagine when the internet is in your brain, if the NSA can see into your brain, if hackers can hack into your brain.

Imagine if skills could just be downloaded — what's going to happen when we have this kind of AI but only the rich can afford to become cyborgs, what's that going to do to society?

Commentary from Shimon Whiteson, an associate professor at the Informatics Institute at the University of Amsterdam.

Yoky Matsuoka says these implants will make humans better at everything.

Yoky Matsuoka says these implants will make humans better at everything.

JHU Applied Physics Laboratory

I think the way I have been promoting AI as well as the next big space aspect for AI is to become really an assistant for humans. So making humans better, making what humans want to do and what humans want to be, easier to achieve with the help from AI.

What if I lost a limb and I can't swim as fast, what if an AI can actually know how to control this robotic limb that's now attached to me to quickly and efficiently let me swim?

Those are the ways, my brain is doing control but to an extent, things that I can't do anymore or things I want to be if that part can be intelligently handled that's really great. It's almost like a partnership.

Commentary from Yoky Matsuoka, former Vice President of Technology at Nest.

Thomas Dietterich doesn't stop there, he hopes AI will turn us into superhumans.

Thomas Dietterich doesn't stop there, he hopes AI will turn us into superhumans.

Yuriko Nakao

I think combinations of human and artificial intelligence are fascinating and have potential to create combined systems that are smarter than either alone. We already see this in many applications of AI — I'm smarter when I have access to Google.

Future systems may work via augmented reality or by giving us sensory abilities far beyond existing vision, hearing, and manipulation. For example, I hope that exoskeletons will allow me to walk when I am old and feeble. I hope that I can retain my sense of hearing and sight even as my eyes and ears fail.

Commentary from Thomas Dietterich, the President of the Association for the Advancement of Artificial Intelligence.

Stuart Russell says very smart computers could solve all our problems, including climate change.

Stuart Russell says very smart computers could solve all our problems, including climate change.

AP -

If you had a system that could read all the pages and understand the context instead of just throwing back 26 million pages to answer your query, that kind of program could actually answer the questions asked.

It'll be like if you asked a real question and got an answer from a person who had really read all those millions and millions and billions of pages and understood them and been able to synthesize all that information.

Everything we have of value as human beings, as a civilization, is the result of our intelligence and what AI could do is essentially be a power tool that magnifies human intelligence and gives us the ability to move our civilization forward in all kinds of ways.

It might be curing disease, it might eliminating poverty. I think it certainly should be preventing environmental catastrophe. AI could be instrumental to all those things.

Commentary from Stuart Russell, a computer scientist at the University of California, Berkeley.

Oren Etzioni says AI might even save the world.

NASA Johnson/YouTube -

When we're talking about something that is at least 50 to 100, maybe even a thousand years away, it's very speculative. But when and if we have that, I would say that the sky's the limit.

All these things that we've contemplated, whether it's space travel or solutions to diseases that plague us, Ebola virus, all of these things would be a lot more tractable if the machines are trying to solve these problems.

I view today's computers as souped-up pencils but nowhere near the potential that they could have if they were able to perform effectively, much more sophisticated.

Commentary from Oren Etzioni, the CEO of the Allen Institute for Artificial Intelligence.

Sabine Hauert says it will open up whole new worlds to explore.

Sabine Hauert says it will open up whole new worlds to explore.

Paramount Pictures

I really think that robotics is going to improve the way we work, the way we live, and the way we explore new frontiers — if you think of the ocean, if you think of space. I think this will be done incrementally, because it's a hard thing to do.

I think it's going to also be integrated in the sense that you might have a robot car, but you're not going to think of it as an AI or a robot, you're going to think of it as a car.

A lot of these things that we'll be introducing will be seen as helpful technologies, just like your cell phone is a helpful technology, but not as lots of robots entering our work or entering our homes. They'll just be seen as smarter tech.

Commentary from Sabine Hauert, a roboticist at Bristol University.

Joanna Bryson says some of these amazing applications are already here, and it's making people easier to predict.

Joanna Bryson says some of these amazing applications are already here, and it's making people easier to predict.

Garry Knight/Flickr

Basically what learning is about, including machine learning, is using the past to make predictions about the future.

You might be able to predict who will start dating or who will get divorced. You can figure out when people are going to have kids sometimes by just the stuff they buy and what neighborhoods they move into. You can figure out more and more intimate details and be able to predict what each other will do.

People are already getting really good at predicting what we are going to do and then manipulating that to get us to buy things, or to vote particular ways.

Joanna Bryson, computer scientist and visiting fellow at the Princeton University.

But these changes will happen so slowly we won't notice it at first, Peter Stone says.

But these changes will happen so slowly we won't notice it at first, Peter Stone says.

Justin Sullivan/Getty Images

There's not one most significant change it will make.

Artificial intelligence is really embedded in many of the devices we already use, from cars to search engines, everything, and I think all of these, every technology we use changes our lives in profound ways.

I don't think there's a single change that going to be black and white once we're on one side and now there's a change and we're on the other side. It's a cumulative effect of everything, AI is embedded in many of the technologies that have been changing our world over the last several decades and will continue to do so.

Commentary from Peter Stone, a computer scientist at the University of Texas, Austin.

As more sophisticated AI trickles into our lives, Hector Geffner says it will also change how we connect with other humans.

As more sophisticated AI trickles into our lives, Hector Geffner says it will also change how we connect with other humans.

Courtesy of Warner Bros. Picture

One significant change will be socialization. The movie "Her" goes in that direction.

We are social beings and need people around, but increasingly, in some societies, many people seem to be more comfortable dealing with people through machines — through mobile, messenger, etc — than in person.

As machines get more intelligent and can better adapt to its "users," people may end up preferring dealing with machines than with people. Of course, this says something about who we are.

Commentary from Hector Geffner, researcher at the Universitat Pompeu Fabra.

Carlos Guestrin says they might even become our best buddies.


Computers and humans are very different in terms of how they think about the world. I think what's going to be most profound is our impact, positive and negative but mostly positive, on the kind of almost symbiotic relationship between humans and technology.

We've already seen that. I'm sure you have a smartphone today and you can see a lot of people experiencing the world through their smartphones, in some negative ways.

But also in positive ways, it's helped us, made us more connected to people that we love, made it easier for us to maintain contact with information, keep track of what's happening in the world, figure out what restaurants go to next, where to watch movies. It's really augmented our understanding of what the world is.

Commentary from Carlos Guestrin, the CEO and co-founder of Dato, a company that builds artificially intelligent systems to analyze data.

These friendly robots could give the elderly live better lives, Matthew Taylor says.

 These friendly robots could give the elderly live better lives, Matthew Taylor says. 

YouTube Screenshot

As we have more of the population growing older, the better we can enable them to stay in their homes longer, the more happy they are, and the healthier they are, the better it is for the whole healthcare system.

We can have more home robots that can help people with these activities of daily living: Making sure people take their medicine, helping them prepare their food, making sure that if they don't get out of bed someone is notified.

I think all of that is pretty low hanging fruit — stuff that will be easy to develop in the next few years. It will really cause a big change to that population, allowing them higher quality of life and also letting them stay in their homes longer.

Commentary from Matthew Taylor, a computer scientist at Washington State University.

They'll also improve medical care, Murray Shanahan says.

 They'll also improve medical care, Murray Shanahan says. 

Nurse Health Practitioner Rachelle Quimpo (C) introduces patient Shreya Sasaki to Dr. Heidi Meyer, MD Family Medicine, who appears on a video screen remotely. Reuters

A very important implication of the kind of AI technology that's coming soon will be in the area of personalized medicine. A great application of machine learning technology applied to big data is in personalized medicine.

If everybody's genome is sequenced, and their medical records are in very fine detail, and you have access to an enormous quantity of clinical studies and so on, it's possible, thanks to machine learning, to match up very very carefully individual problems with very specialized treatments that are tailored for exactly that kind of person.

At the moment, medicine is very statistical and treatments are tailored for large populations and not for the individual so I think that will have a dramatic effect.

Commentary from Murray Shanahan, a computer scientist at Imperial College.

Super intelligent computers could also make internet access available to people who don't have it now, according to Yoshua Bengio.

Super intelligent computers could also make internet access available to people who don't have it now, according to Yoshua Bengio.

A boy sits among children using tablet computers given to them by the One Laptop Per Child project in the village of Wenchi, Ethiopia. Jason Straziuso/AP Photo

A computer that better understands what we want and does things for us could have a huge impact on the billions of people on the Earth who aren't even able to interact with a computer because they can't read or write.

There are lots and lots of people that don't have access to knowledge because they don't know how to read and write, and don't have access to a computer.

If computers are able to converse in natural language and really understand what people are asking and give sensible answers it might really have a big impact on all of these people that currently don't benefit from the kind of technology that we do.

Commentary from Yoshua Bengio, a computer scientist at University of Montreal.

AI could also give us more time to be creative, says Lynne Parker.

AI could also give us more time to be creative, says Lynne Parker.


AI could open us up to the ability to be creative and to really think broadly because it can relieve us of some meaningless jobs.

I think there's a potential there if we seize the opportunity to be relieved from everyday mundane things to do things that are more impactful and really more human, more intelligent, more creative.

Whether or not we will seize the day, as they say, is a question to be answered.

Commentary from Lynne Parker, the division director for the Information and Intelligent Systems Division at the National Science Foundation.

Toby Walsh says these impacts will completely revolutionize how we live and work.

Toby Walsh says these impacts will completely revolutionize how we live and work.

Adam Berry/Getty

I think we're going to see similar profound changes in the nature of work, as much as that work can be automated even further by computers. It's hard to think of a job that a computer ultimately won't be able to do as well if not better than we can do.

That's going to require profound changes within society in terms of are we going to work a shorter working week? How are we going to distribute the wealth that this generates?

This is a challenge not for scientists but one for society to address, of how are we going to work through these changes.

One of the great challenges is that computers and AI as a technology are very quickly adopted. The great thing about computers is that you can reproduce the software almost at no cost. So once we have the technology it gets very easy to reproduce the technology and disseminate it.

The changes that we see precipitated by changes in computing are ones that tend to happen very very quickly. The challenge there is that society tends to change rather slowly.

Commentary from Toby Walsh, a professor in AI at the National Information and Communications Technology Australia.

But there are some downsides. Bart Selman says robots will take over many of our jobs.

But there are some downsides. Bart Selman says robots will take over many of our jobs.

File photo of humanoid robots working side by side with employees in the assembly line at a factory of Glory Ltd. Thomson Reuters.

The US and I think most of the world has pushed hard on this idea of knowledge workers — you should get an education, you should educate yourself and stay ahead of the changing world. That may become actually become somewhat difficult.

It's a sudden switch, when something becomes cheaper, when the self-driving car becomes cheaper than the human driver, immediately the whole system will flip around, and say just sell self-driving cars.

When a AI-based medical doctor becomes cheaper, why not switch all medical doctors to smart computer programs and have a few remaining human specialists for very special cases.

That's sort of one of the risks that AI people are worried about. It's a societal risk. Society will have to adapt. How we will adapt is not fully clear yet. But I think it's something we'll have to think about.

Commentary from Bart Selman, a computer scientist at Cornell University.

Because of that, Michael Littman says we will have to rethink how we value people.

Because of that, Michael Littman says we will have to rethink how we value people.

The Library of Congress

What people have when people are born is this sort of ability, this is how economists think about us anyways, is that we have the ability to carry out labor.

So there's two kinds of wealth in the world, there's labor and there's capital. We aren't born with capital but we can start to amass it over time and that gives us economic power and so forth. But the only thing that we have at our disposal, at least from the beginning, is labor.

We can turn machines into workers — they can be labor, and that actually deeply undercuts human value. My biggest concern at the moment is that we as a society find a way of valuing people not just for the work they do.

We need to value each other first and foremost. Make it clear that the machines that we're talking about are machines to benefit everybody and not just the people that have them.

Commentary from Michael Littman, a computer scientist at Brown University.

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