INTENDED & UNINTENDED 

CONSEQUENCES

of 

ARTIFICIAL INTELLIGENCE (AI)

by

The Good US Artificial Intelligence Group

--------------------------------------------------

GoodUSAi.com  

The below three individuals are the Co-Founders and 

Members of  

"The Good US Artificial Intelligence Group."

Qin ("Tim") Sheng, Russ Peterman, John ("Johnny") Miller

1.  Dr. Qin ("Tim") Sheng

* Baylor University, Math Professor and Math Researcher

* Baylor University Center for Astrophysics, Space and Engineering

* Research Editor in Chief at Taylor and Francis`

* Ph.D. in Mathematics at University of Cambridge

Dr. Sheng joined the Baylor faculty in August 2005. Prior to coming to Baylor he held  a research position in University of London (1989-1990), a visiting professor position  in Baylor University (2003) and faculty positions in National University of Singapore  (1990-1995), University of Louisiana (1996-2001) and University of Dayton (2001-2005).  He was a recipient of the J. T. Knight Prize in Mathematics (1987) and  Lundgren Research Award (1989). 

Dr. Sheng was an invited research participant of the  Isaac Newton Institute for Mathematical Sciences, Cambridge, England (2007). He was a  U.S. Air Force SFFP Research Fellow (2005-2007). Dr. Sheng directed two doctoral dissertations, 8 Master of Science theses and a number of undergraduate research theses. 

Dr. Sheng's research is in computational and applied mathematics. In particular, he is interested  in splitting and adaptive methods for solving singular partial differential equations. He has been involved in cross-disciplinary projects in scientific and engineering  computations. Dr. Sheng has been active in his research fields and community. He is on editorial boards of  several scholarly journals and special research issues. His  projects have been supported by the United States Air Force Research Laboratory and Department of Defense.

Dr. Sheng’s focus is computational and applied mathematics. His studies have been continuously supported by the University, USAF,  DoD, and others. He is married to Helen. They have sons Andy and Dan. He enjoys reading, painting, traveling and spending time with the family.    

  https://www.baylor.edu/math/index.php?id=54497h

https://www.baylor.edu/math/index.php?id=54019

https://sites.baylor.edu/qin_sheng/

EMAIL;   Qin_Sheng@Baylor.edu

------------------------------------------

2.  Russ Peterman

President of Peterman Consulting Associates, 

Round Rock, Tx 

2005 - Present

 russ.peterman@yahoo.com

 Russ is active in the Austin Metro entrepreneurial space, focused on life sciences, nanotechnology, aviation tech, and general and  specific challenges with underlying physics components. Russ has served on numerous state and local boards and commissions focused on technology and economic development. He holds five technical USPTO patents, has started numerous technical and non-profit companies,  mentored over twenty successful technical and administrative interns, and is currently available for ..mentoring, consulting and new company formation and funding, among other consulting areas.

----------------------------------------------

* BS -The University of Texas at AustIn

1974

* MS - The University of Texas at Austin -  

 Russ completed his  undergraduate work in physics at UT-Austin. After serving as the Station  Science Leader for Applied Research Laboratories/NSF at McMurdo  Station, Antarctica he completed his Masters in Physics at UT Austin and  then transitioned to the Ph.D program in Electrical and Integrated  Circuit Engineering at UT Austin. 

* 1978

 - University of Colorado (Boulder)

Business Management

* 1995

--------------------------------------

RUSS PETERMAN - EMPLOYMENT

Research Scientist

Applied Research Labs

The University of Texas at Austin

1970 - 1978

- Radian International LLC- 

(Principle Scientist)

1978-2001

-Vaisala -

(Interim Vice President)

2001-2002

- Peak Weather Resources-

NCAR

(President)2002-2004-The University of Te

 McDoald Observatory- 

(Supervisor of Observatory)

2004-2006

-Texas Life Sciences Collaboration Center-

(Executive Director) 

2007- 2012

- Frame Switch Energy , Inc.- 

(President and Founder)

2012-2013

Texas Bio Corridor Allowance

(President and Founder)

2012 - 2014

Tango Flight

(Director of Business Development)

2016--2018

Tango Flight is a non-profit organization created to support GISD's  Project Lead the Way in building a Van's RV-12 Light Sport Aircraft .  The aircraf has been built entirely by high school students and  experienced mentors, as part of a class with award-winning engineering  teacher Dan Weyant at Eastview High School  in Georgetown, Texas. In  what is envisioned as a ten-year project to build one aircraft per  school year for the next ten years.

---------------------------------------------------

3. John ("Johnny") E. Miller

 Attorney  Emeritus

State Bar of Texas

The John E. Miller Law Office

Bryan, Texas 

Mr. Miller received a BA in Political Science (with a minor in Oral Communication) from Baylor University in 1967, a JD in Law from University of Memphis in 1973, a LLM in Urban (Legal) Affairs from University of Missouri - KC in 1980, and a CPCM from NCMA in 2015.

Mr. Miller's legal focus is in contracts,  procurement, business law, software, IP, licensing, and technology . In the last 10 years he has published more than 20 articles in the  National Contract Management Association (NCMA) "Contract Management  (CM) Magazine" and other national magazines. Links to each of these  profession publications can be found at www.con-tracts.com. 

In 2007 he was the co-winner of the Annual National Contracts Management Association - Charles J. Delaney Memorial Award for the most outstanding national article published in the National Contract Management  Association Magazine.

In 1990 he was one of ten Radian Corporation's 2,000 employees to win a "Corporate Achievement Award."This award was granted to him primarily for his work in safeguarding Radian's intellectual property.

Early 2013 he was involved  in the following Colorado CLE presentation: *Advising Small Companies -  Responding to Your Clients' Needs with Practical Advice – February 27,  2013 – Colorado Bar Association CLE - Basics of Contract Drafting and  Negotiations: - Analysis of common contract provisions; Strategy in  contract drafting; and Negotiating Tips - Presented by Colleen Belak,  Esq. -  http://cle.cobar.org/Seminars/EventInfo/sessionaltcd/BL022713L.aspx -  with Johnny Miller’s Sixty Practical Contract Drafting Tips – NCMA CM  Magazine in April 2006  -http://www.ncmahq.org/files/Articles/B50B6_CM_Apr06_p62.pdf.

Earlier in his career, he played baseball for Baylor University in 1963-1964 and played Semi-Pro Baseball for the Waco Braves in 1964-1967. 

During the second year of Law School, he was drafted into the US ARMY in 1968 and on January 11, 1969  Colonel Irvine  G. Hughes, Infantry (Commanding)  selected him as "TOP MAN" in his Basic Combat Training Company. In those days draft deferments were not available to law students.

 Mr. Miller received some additional electronics training at Fort Gordon, Georgia and Fort Ord - Oakland, California and then served in the US Army in Southeast Asia  from 1968 to 1971 working in S-2 Security and Intelligence (Battalion Level)  for the US Army Signal Corp. He was awarded the US Army Commendation Medal  for his work in Southeast Asia by  his Commanding Officer  Lieutenant Colonel Ed Jones. Mr. Miller was assigned to support  the US Army Signal Corp and (as part of his security and intelligence duties) he supported Thailand as well as Monkey  (Son Tra) Mountain. Vietnam  about 30 miles from  Da Nang Air Base , Vietnam, Mr. Miller also supported various activities in Laos and Cambodia. He was, however, permanently stationed in Korat, Thailand. He and his wife Nancy lived off post on the local Korat economy.

Thailand is a very beautiful country and the Thai  people are outstanding. Thailand is best described as "The Land of Smiles."

He also received the Vietnam  Service Medal W/2 Stars and the Vietnam Campaign Medal W/60 Device. Additionally, his name ("JOHN EDDIE MILLER") and branch of service (US ARMY) have been inscribed on the Brazos Valley Veterans Memorial Wall in Veterans Park, College Station, Texas.

After his military service and law school , over the years Mr. Miller has worked with "his boots on the ground" at client locations and remotely as a regular employee/contractor/attorney  for many classified/unclassified military/civilian/commercial, federal/state /local governmental, academic, medical/health, professional, international, and non-profit entities in many business/technology domains in various geographical regions (Asia, Europe, Australia, Mexico, Space) with increasing levels of responsibility. 

See: www.JohnnyAttorney.com 

Johnny's Email:

Johnny@Con-tracts.com

Johnny@JohnnyAttorney.com

  TTJohnEMiller@hotmail.com

Johnny's Web Sites:

www.Con-tracts.com

www.JohnnyAttorney.com

www.GoodUSAi.com

www.JohnnyPickleball.com

Johnny's Cell & Text 

512 619 7512 

-------------------------------------------------

BIOS

Bios are available for each of the above three Co-Founders upon request.

----------------------------------------------

THREE  CO-FOUNDERS

The above three individuals are the Co-Founders of  

"The Good US Artificial Intelligence Group."

This Group is not a legal, business, enterprise, not-profit, foundation, governmental or academic entity of any type but rather merely an independent,  informal, unstructured. unbiased group of experienced and well-regarded professionals (in their respective fields) who share a strong common interest of doing and promoting what is "Good" (not bad) for the USA in the areas of Artificial Intelligence (AI), including but not limited to Machine Learning (ML).  

The word "Good" generally means morally right, virtuous, beneficial, advantageous, positive, 

high quality, excellent, cool, outstanding, super, empathy, ethics, integrity, honesty, social benefit

and so-forth. 

The word "Bad" generally means detrimental, harmful, poor quality, inferior, evil, detrimental, immoral, malicious, and so forth.

---------------------------------------------------------

THE MAIN THRUST OF THIS WEB SITE

THE MAIN THRUST OF THIS WEB SITE IS NOT THE DARK / EVIL SIDE OF AI BUT RATHER  RESEARCHING, EDUCATING, TEACHING, PROMOTING, AND APPLYING: (1)  SAFETY; (2) INTEGRITY; (3) HONESTY; (4) ETHICS; (5) ZERO BIAS; (6) EMPATHY; (7) RESPONSIBILITY; AND (8) SOCIAL BENEFIT WITH REGARD TO ALL ASPECTS OF GOOD UNITED STATES ARTIFICIAL INTELLIGENCE  INCLUDING  (BUT NOT LIMITED TO) MACHINE LEARNING, DEEP LEARNING, ROBOTICS, ROBOTIC VISION, NATURAL LANGUAGE PROCESSING, VOICE RECOGNITION,  SPEECH RECOGNITION,  FACIAL RECOGNITION, DRONES, ARTIFICIAL NEURAL NETWORKS, INTERNET OF THINGS, AND OTHER ASPECTS OF AI.

-----------------------------------------------------

DEFINITION OF AI

The definition of Artificial Intelligence (AI) can be a little confusing. However let's give it a shot and try to make it easier understood. 

AI is a subset of Data Science.  Data Science is a subset of Computer Science. AI (as a subset of Data Science) is the ability of  a machine  and/or of computer software/firmware programs  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 (ML), 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 (FR) is Machine Learning. Applications of Machine Learning normally use a Neural Network (NN).  A Neural Network is a computer system mimicking the human  brain. An example of Deep Learning is Speech Recognition (SR). Included in the AI definition is the difference between weak/narrow AI and strong/broad 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." There - that AI definition wasn't so bad - was it?

-------------------------------------

PROFESSOR McCARTHY

The term "Artificial intelligence"  dates back to about the mid-1950's. About  1956. AI was first named and identified in 1956 by the  Sanford professor / researcher John McCarthy as a sub-field of the larger academic study of computer science.  

----------------------------------------------

ROCK & ROLL

(The mid 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? (FYI - Little Richard was the King of Rock & Roll). 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. 

----------------------------------------------

IMPORTANCE OF ARTIFICIAL INTELLIGENCE (AI)

Artificial Intelligence (AI) systems will play a major role in every aspect of life on earth.  It will change the world in which we live.  AI  will improve the speed, accuracy, efficiency, and safety of human decision making. However,  it will carry the risks of some unintended or unplanned results. 

In fact, AI may turn out to be a greater world problem than any of the future concerns, such as: nuclear security, radiation, climate change, civil unrest, chemical - biological warfare, terrorism, cyber-security, asteroid impact, loss of coral and plankton,  alien visitors, locus invasion. destroyed food supply, bacteria and virus threats, power grid  destruction, ozone depletion,  loss of internet, deforestation,  poverty, hunger, lowering  water supply, air pollution, sanitation, water shortage, water pollution, nuclear waste, de-forestation, lack of education, loss of rain forests, Disclosure (in the ET meaning) , failure of monetary system, world-wide bankruptcy, and so forth. 

Is it possible that AI will be an "existential" event once AI reaches the human /general / conscious / super level and beyond?

----------------------------------------------------------

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 social ills.

 The benefits brought by the internet are too many to mention, however, misinformation, false-truth, erosion of privacy, scams, election interference, hackers, pornography, dark web, terrorists, human traffic facilitation, and others are all unintended consequences. Not even medicine is free from side effects. 

Rarely at the time of creation / implementation is the designer /  inventor / creator / implementer / integrator / reseller the best judge of how the system will be used, or truly knows what good or harm will come of it. Understanding this, we ought to analyze  the issues deeply before taking on an unintended bad consequence type project.

---------------------------------------------

WHY NOW?   BECAUSE THE TIME IS RIGHT

Unlike the past "AI Winter", AI / ML 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 to be addressed;  (4) being able to timely  convert those unique issues / problems into  targeted knowledge engineering rules (algorithms) so that AI systems can learn; (5) efficiently plugging the resulting  rules into appropriate AI systems; and (6) allowing AI systems to learn the rules automatically.

-----------------------------------------------

MAJOR  AI COMPONENTS

The following items are some of the  major components that make up Ai and help to better define AI:

1. Machine Learning (ML)- Machine Learning (ML) is an application of AI that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it to learn for themselves. It allows systems to learn from data, identify repeating patterns and making decisions without explicit instructions or human intervention. It enables entities/humans to save time and resources. 

2. Big Data -   In the article:   "Data, Data, Everywhere",  Baylor Arts and Sciences, Special Issue, Research in Arts & Sciences, Fall 2018  (by Julie Engebretson) it states: "It is estimated that about 16.3 Zettabyes of data - the equivalent of 16.3 trillion  Gigabytes  - is produced in the world each year." Wow !  Now that's big data !

 Dark  Data (DD) is sometimes  data that  is obtained through numerous computer network operations but because it is so disorganized  it is generally not used  to obtain insights or for decision making.

According to Oracle: "Put simply, Big Data is larger, more complex data sets, especially from new data sources. These data sets are so voluminous that traditional data processing software just can't manage them." It includes structured and unstructured data.  There is a growing belief that data is more valuable than oil.  

Before data can be used in an AI use case it must be cleaned, prepared, and labeled. 

Data is the heart of AI. Data is the new electricity. Cleaning data involves eliminating duplicates, deleting extraneous data, and working with data by humans to get it ready for use with thappropriate AI algorithm for  a use case. 

3. Artificial Neural Networks - Artificial Neural Networks are one of the main tools used in Machine Learning. As the “neural” part of their name suggests, they are brain-inspired systems which are intended to replicate the way that we humans learn. Neural Networks consist of input and output layers, as well as (in most cases) a hidden layer consisting of units that transform the input into something that the output layer can use. They are excellent tools for finding patterns which are far too complex or numerous for a human programmer to extract and teach the machine to recognize.

4.   Robotics (including Robotic Vision) - From Wikipedia, the free encyclopedia, it states: “Robotics is an interdisciplinary branch of engineering and science that includes mechanical engineering, electronic engineering, information engineering, computer science, and others. Robotics deals with the design, construction, operation, and use of robots, as well as computer systems for their control, sensory feedback, and information processing. These technologies are used to develop machines that can substitute for humans and replicate human actions. Robots can be used in many situations and for lots of purposes, but today many are used in dangerous environments (including bomb detection and deactivation), manufacturing processes, or where humans cannot survive (e.g. in space). Robots can take on any form but some are made to resemble humans in appearance. This is said to help in the acceptance of a robot in certain repiutation type  behaviors usually performed by people. Such robots attempt to replicate walking, lifting, speech, cognition, and basically anything a human can do. Many of today's robots are inspired by nature, contributing to the field of bio-inspired robotics.”  From Wikipedia, the free encyclopedia it states:   "Robot vision or a Vision Guided Robot (VGR) System is basically a robot fitted with one or more cameras used as sensors to provide a secondary feedback signal to the robot controller to more accurately move to a variable target position. VGR is rapidly transforming production processes by enabling robots to be highly adaptable and more easily implemented, while dramatically reducing the cost and complexity of fixed tooling previously associated with the design and set up of robotic cells, whether for material handling, automated assembly, agricultural applications, life sciences, and more.

5.   Facial Recognition- Now here is a controversial topic. A Facial Recognition (FR) system is a technology capable of identifying or verifying a person from a digital image or a video frame from a video source. There are multiple methods in which Facial Recognition systems work, but in general, they work by comparing selected facial features from given image with faces within a database. It is also described as a Biometric AI (BAI). It is an  application that can uniquely identify a person by analyzing patterns based on the person's facial textures and face shape. 

6.  Speech Recognition - Speech Recognition (SR) is the ability of a machine or program to identify words and phrases in a spoken language and convert them to a machine-readable format. Rudimentary speech recognition software has a limited vocabulary of words and phrases, and it may only identify these if they are spoken very clearly.

7. Voice Recognition - The ability of hardware and software to recognize the voice of a person (as unique as a fingerprint). It differs from Speech Recognition 's ability to understand words - not the identity of a person.  

8. Deep Learning -  Networks  capable of learning from unstructured data  when the network is unsupervised.

9.  Internet of Things  (IoT) -  This is computer components embedded in many every day objects with capabilities of sending and receiving data and performing other activities.  The oil & gas industry is especially ripe for the application of IoT with potential benefits in safety, the environment, reduced spills, reduced carbon emissions,  improved monitoring, improved drilling strategy, cost reduction, time savings, and increased revenue.  

Here, just  below, is a good high level description of how IoT works, as so stated in the LEVERAGE'S E-Book

"An Introduction to Internet of Things:"  “An IoT system consists of sensors/devices which “talk” to the cloud through some kind of connectivity. Once the data gets to the cloud, software processes it and then might decide to perform an action, such as sending an alert or automatically adjusting the sensors/devices without the need for the human user . But if user input is needed or if the user simply wants to check in on the system, a user interface allows them to do so . Any adjustments or actions that the user makes are then sent in the opposite direction through the system: from the user interface, to the cloud, and back to the sensoIrs/ devices to make some kind of change."

10.  Drones - An Unmanned Aerial Vehicle (UAV), commonly known as a drone, is an aircraft without a human pilot aboard. UAVs are a component of an Unmanned Aircraft System (UAS); which include a UAV, a ground-based controller, and a system of communications between the two. The flight of UAVs may operate with various degrees of autonomy: either under remote control by a human operator or autonomously by onboard computers. Compared to manned aircraft, UAVs were originally used for missions too "dull, dirty or dangerous” for humans. While they originated mostly in military applications, their use is rapidly expanding to commercial, scientific, recreational, agricultural, and other applications, such as policing, peacekeeping,   surveillance, product deliveries, aerial photography, agriculture, smuggling, and drone racing. Civilian UAVs now vastly outnumber military UAVs, with estimates of over a million sold by 2017, so they can be seen as an early commercial application of autonomous things, to be followed by the autonomous car and home robot.

11. AI Algorithms - are  mathematical  instructions  that provide  step by step procedures  for calculations. It is kind-of like a set of step-by-step instructions.

12. Augmented AI -  At this point (all things considered), it seems as though one of the most promising methods of beneficially, expeditiously, and effectively making the best use of Artificial Intelligence (AI) is to use it to augment the efforts of the AI user. 

AI should, on most cases only be used to assist the human worker. It should not be used to replicate and replace him/her. 

 Augmented Artificial Intelligence (AAI) is the best way to use AI.  Augmented Artificial  Intelligence refers to the result of skillfully blending human and machine intelligence. With the the proper use of Augmented Artificial  Intelligence, Humans will be safer during disasters, better cared for as they get older, and more independent for they get older.

------------------------------------------------------------- 

"SOME OF THE POTENTIAL BENEFITS OF AI  

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 brain; 

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, smell, touch, 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; 

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

21. Improves ability to help customer;

22. Improves  e-commerce;

23. Chat boxes.; 

24. Better decisions and fewer mistakes;

25. Assisting humans with Augmented Artificial Intelligence;

26. Help compose music.

27. Improved gaming and media;

28. Help in the hospitality and restaurant business;

29. Improve the back office;

30. Bank loan determination;

31. Fraud determination;

32. Assisting in ancestry research; 

33. AI serving as an enabler;

34. Potential wide-spread access and use of open-source AI world-wide;

35.  Airlines can save money annually on fuel savings in-flight and during take-off and landing (such as Quantas Airlines saving $40M in 2018) due to AI);

36. Assisting air traffic control to improve safety, efficiency, and decision making;

37. Use of AI and ML in the oil and gas business to address safety, exploration, discovery, drilling, production, analysis, and distribution.

SOME OF THE POTENTIAL 

RISKS AND THREATS TO AI

Here are  numerous  risks and threats that arise out of the use of AI including Machine Learning ("ML"), Deep Learning (DL), robotics, Robot vVsion (RV), Internet of Things (IoT), Signal Processing (SP), Neural Networks (NN), Natural Language (NL) and Unstructured Data (UD) or Dark Data (DD)  that need to be anticipated and analyzed:

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. This is also often called: Super A or General AI;

4. Robots utilizing AI may sometime be seeking certain civil rights;

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

6. Privacy rights of people are potentially being eroded with AI;

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

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

9.  Mass unemployment;

10. Wars;

11. Autonomous weapons;

12. Mass surveillance; 

13 Discrimination;  

14. Improper actions of robo doctors;

15. Wrongful financial services actions;

16. Constructing algorithms improperly;

17. Improper healthcare issues;1

18. Improper insurance issues;

19. Ineffectively regulatory issues; 

20. "Reasonable man" and "proximately caused"  issues in tort law;

21.  Non competitive antitrust AI issues .     

22  In addition to the potential benefits of the quantum  issues, we also need to keep an eye on the soon to be emerging  potentially harmful uses of quantum physics (QP), quantum computers (QC), quantum gravity (QG), quantum  mechanics (QM) and other quantum issues

23. Eventuality of AI hacking and subversive activities involving rules, algorithms, data, and other and/or other components;

24.  Potential autonomous killing machines (except in very rare US military cases for cause);

25. In the event of consciousness in AI, seek the embedding of ethics, clean data, bias, responsibility, error prevention, legal compliance, integrity, moral values, ethics, continuous human feedback, and proper social manners;

26. Danger of manipulation of data a motor vehicle accident involves AI, trying to find the liable party is difficult and confusing. (i.e. a autonomous car hits another vehicle);

27.    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 on be used in court? Autonomous weapons; 

28. Mass surveillance;

29.. Discrimination;  

30. Improper actions of robo doctors algorithms improperly; 

31. Improper healthcare issues;  

32. Improper insurance issues;

33. Ineffectively regulatory issues; 

34. "Reasonable man" and "proximately caused"  issues in tort law; 

35. Non competitive antitrust AI issues; 

36. In addition to the potential benefits of the quantum issues, we also need to keep an eye on the soon to be emerging  potentially harmful uses of quantum physics (QP), quantum computers (QC), quantum  mechanics (QM) and other quantum issues.Eentuality of AI hacking and subversive activities involving rules, algorithms, data, and other and/or other components. 37.  Potential autonomous killing machines (except in very rare US military cases); 

38. In the event of consciousness in AI, seek the embedding of ethics, clean data, bias, responsibility, error prevention, legal compliance, integrity, moral values, ethics, continuous human feedback, and proper social manners.; 

39. Danger of manipulation of data. Data is a huge AI issue. 

See:

 In "Data, Data, Everywhere",  Baylor Arts and Sciences, Special Issue, Research in Arts & Sciences, Fall 2018  (by Julie Engebretson) It states: "It is estimated that about 16.3 Zettabyes of data - the equivalent of 16.3 trillion  Gigabytes  - is produced in the world each year."  Wow !  Now that's Big Data !

-----------------------------------------

  40.  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).

-------------------------------------------------

41.  Below is a great link to a very thought-provoking article on the AI dangers to democracy and privacy in the US:    "Artificial Intelligence: Risks to Privacy and Democracy - Karl Manheim* and Lyric Kaplan" 21 Yale J.L. & Tech. 106 (201

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=327301

-----------------------------------------------------------

  HOW TO POTENTIALLY  MITIGATE AI/ML RISKS, DANGER, AND THREATS

1. Understand the vast complexities of AI / ML;

2.  Track AI / ML reasoning;

3. Participate in rule making, algorithms development, and data gathering;

4. Use good clean structured data;

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

6. Start soon with Augmented AI applications,

7. Protect AI with IP such as patents and trade secrets;

8. Establish an AI team;

9. Recruit and retain AI talent;

 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 ; 

12. Participate in government regulation of AI;

13. Make AI / ML  secure;

14. Develop strong AI / ML testing prior to deployment; and 

15.  Think like a robot.

Certain portions of the next-above section (on potential mitigation of AI/ML risks, threats, and dangers)  have been summariized and/or derived from:  "Understanding the Legal Implications of Artificial Intelligence", Perkins Coie, News – Insights 5/12/2018

-[and]

       Two-Minute Guide To Artificial Intelligence, Parmy Olson, Forbes – 10/3/2018

--------------------------------------------------------

"SEVEN  PATTERNS OF AI. "     

SE:  https://www.cognilytica.com/2019/04/04/the-seven-patterns-of-ai 

CHECK OUT THE COGNILYTICA WEB SITE LINK JUST BELOW DESCRIBING THE ...  "SEVEN PATTERNS OF Ai:"

 https://www.cognilytica.com/2019/04/04/the-seven-patterns-of-ai 

"THE COGNILYTICA WEB SITE DECRIBES HOW AI APPARENTLY SEEMS TO REPEAT THEMSELVES IN DIFFERENT COMBINATIONS IN ALL OF THE AI  USE CASES THAT VARIOUS ENTITIES HAVE CREATED."  https://www.cognilytica.com/2019/04/04/the-seven-patterns-of-ai 

COGNILYICA STATES THE FOLLOWING IN THEIR WEB SITE -

 https://www.cognilytica.com/2019/04/04/the-seven-patterns-of-ai  

1.  "Autonomous Systems (AS) are systems that are able to  perform a task, goal, or interaction with minimal to no human  involvement or labor. The primary objective of the  autonomous systems type is to minimize human labor.  Autonomous Vehicles and Drones are 

examples of this AI type."    https://www.cognilytica.com/2019/04/04/the-seven-patterns-of-ai 

2.  "Hyper-Personalization (HP) is defined as using machine learning (ML) to develop a very unique profile of each individual human, and having that special profile learn and adapt for a wide variety of purposes, including content, products, personalized recommendations,  personalized healthcare, finance, and other specific one-to-one activities.  Advertising, finance, medical/health care, and fitness are some of the AI uses of HP."  https://www.cognilytica.com/2019/04/04/the-seven-patterns-of-ai 

3.  "Predictive Analytics & Decision Support  is using ML to   understand  how learned patterns of data can assist in          predicting the future.  It also assists humans in making  decisions about the future using what it learned from data and other information. It is all about helping humans make better  decisions. This application of AI is primarily intended to assist humans to figure out an answer to a problem. The human is still making the decision but it is ML helping the humans make the better decision."   https://www.cognilytica.com/2019/04/04/the-seven-patterns-of-ai 

  4. "Conversational / Human Interaction is the use of machines in communicating with humans through natural conversation and including voice, text, images, and other forms. The goal is to create communication between machines and humans. This is enabling machines to interact with humans the way that humans interact with each other. "  

https://www.cognilytica.com/2019/04/04/the-seven-patterns-of-ai 

5.  "Pattern & Anomaly Detection is the AI type that has the ability to find which one of the things is like the other and which is not. The goal is to find anomalies in data and indicate what looks out of the ordinary such as fraud detection and risk analysis."  https://www.cognilytica.com/2019/04/04/the-seven-patterns-of-ai 

6.  "Recognition is the AI type using machine learning to identify objects or other things within some form of unstructured content.  Use cases include image recognition, facial recognition, sound recognition, audio recognition, item detection, handwriting detection, text recognition, and gesture detection. The recognition AI type is one of the most widely used and adopted of all AI use types"

https://www.cognilytica.com/2019/04/04/the-seven-patterns-of-ai 

7.  "Goal Driven Systems is the final pattern of AI that we’ve identified. We define this as using machine learning and other cognitive  approaches to give your agents the ability to learn through trial and  error. The primary objective of this pattern is to find the optimal solution to a problem. "

https://www.cognilytica.com/2019/04/04/the-seven-patterns-of-ai 

"Examples  of this pattern include scenario simulation, game playing, resource  optimization, iterative problem solving, bidding and real time auctions.  Some of the most famous use cases and examples of this pattern are  dominated by reinforcement learning approaches to machine learning. In  particular, DeepMind’s approach with AlphaZero is goal-driven systems  pushed as far as they can go. DeepMind’s theory is that if a computer  can learn through trial and error, just trying a whole bunch of things,  then a system could theoretically learn anything. "  https://www.cognilytica.com/2019/04/04/the-seven-patterns-of-ai 

It is highly recommended that the outstanding  ..."COGNILYTICA WEB SITE"...  be reviewed to see the AI/ML Use Cases outlined there.  

-------------------------------------------------------

WATCH THIS GREAT  COLD FUSION AI / ML VIDEO  !

Don't Miss ThIs Great Video About  "General AI / ML. " This may be the first time a computer achieved the General (Human Level) AI/ML." 

Deep Mind - World's First General AI ? 

https://www.youtube.com/watch?v=T//nUYcTuZJ

(Back-Up Link)

-----------------------------------------------------

THE GOOD UNITED STATES ARTIFICIAL INTELLIGENCE 

GROUP 

(GoodUSAi.com)

FREE 2020 CURRATED  LIST OF Ai / ML RELATED LINKS REGARDING FREE ON-LINE

WEB SITES, NEWSLETTERS, BLOGS, PODCASTS,  WEBNARS, COURSES, EDUCATION, TRAINING, AND OTHER RESOURCES:

THE JUNE 2020 ISSUE OF THIS LIST OF AI/ML RESOURCES IS A WORK-IN-PROGRESS.  

STAY TUNED!

--------------------------------------------------

GoodUSAi.com  SUBSCRIBER - 

MONTHLY NEWSLETTER !

IF YOU SIGN-UP AS A SUBSCRIBER TO RECEIVE THE GoodUSAi.com SUBSCRIBER MONTHLY  NEWSLETTER, YOUR FREE EMAIL COPY OF OUR  NEWSLETTER WILL INCLUDE INTERESTING AND USEFUL AI/ML  INFORMATION THAT YOU CAN USE.

In the alternative, you may email Johnny Miller directly at Johnny@JohnnyAttorney.com  or Johnny@Con-tracts.com and request to be a Subscriber and to receive our Newsletter.

------------------------------------------------------

CHECK OUT OUR BLOG: 

Good United States Artificial Intelligence Group BLOG !

Johnny Miller WebMaster  Johnny@JohnnyAttorney.com

------------------------------------

THREE FOUNDERS' FAVORITE QUOTES 

" We need to let  people know more about our interests, expertise, and endeavors. Let's do the best  to support this wonderful  country."

Dr. Qin (Tim) Sheng

Co-Founder of www.GoodUSAi.com 

"Never give in, never give in, never, never, never"

Winston Churchill

Russ Peterman

Co-Founder of www.GoodUSAi.com 

"Bloom where planted;

Do the right thing; 

Do the thing right;

Finish strong."

John ("Johnny") Miller

Co-Founder of www.GoodUSAi.com

-----------------------------------

COPYRIGHT (C) 2019 -- 2020

The 

Good United States Artificial Intelligence Group 

ALL RIGHTS RESERVED 

---------------------------------------------

"Johnny Pickleball" is a USPTO Registered Trademark of John ("Johnny") E. Miller

-----------------------------------------------------------

----------------------------------

Web Master

Johnny Miller

 Johnny@JohnnyAttorney.com

-------------------------------

-AI HUMOR -

-Just Kidding -

Question: "What do you call a blonde who has dyed her hair to brown?"

Answer: "Artificial  Intelligence." 

----------------------------------------

Note:   Any humor in the above "Just Kidding" section of this web site about "blondes" or others is clearly not intended by the  "GoodUSAi.com" web site , the Good United States Artificial Intelligence Group, its Founders, its Members, its  Advisors or others (in any manner whatsoever) to make fun of, discriminate against , ridicule, belittle or devalue others. It is just a joke used to drive home the definition, proper usage, value and importance of the  Artificial  Intelligence. By  the way, hair color and hair style have nothing to do with intelligence.

--------------------------------