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ARTIFICIAL INTELLIGENCE & MACHINE LEARNING
AI AND ML MAY TURN OUT TO BE MORE PROFOUND THAN FIRE AND ELECTRICITY.
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* The John E. ("Johnny") Miller Law Office-WebMaster at GoodUSAi.com 512 619 7512 Johnny@JohnnyAttorney.com
INTENDED AND UNINTENDED
CONSEQUENCES
of
ARTIFICIAL INTELLIGENCE (AI)
and
MACHINE LANGUAGE (ML)
by
The Good United States Artificial Intelligence Group
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GoodUSAi.com
The below three named individuals are concurrently Co-Founders and Officers
of
The "Good United States Intelligence Group."
Qin ("Tim") Sheng, Russ Peterman, John E. ("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.
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2. Russ Peterman
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.
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-
* 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
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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 Texas
McDonald 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
i
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 aircraft 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.
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3. John ("Johnny") E. Miller
Attorney Emeritus
State Bar of Texas
The John E. Miller Law Office
EDUCATION
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.
LEGAL FOCUS, PUBLICATIONS, AND CIVILIAN AWARDS
Mr. Miller's legal focus is in contracts, procurement, business law, software, IP, licensing, and technology. In the last 20 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 1980 he was awarded the Annual Midwest Research Institute (MRI) Contract Department Improvement Award for his creation of the "Proactive Contracts Administration Program (PCAP). " Johnny was working for MRI at that time. PCAP is a system to be used by each contract administrator to proactively observe, discover, identify, analyze and correct contractual, legal. technical, financial, schedule, and other issues in contracts before they ripen into problems.
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.
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.
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/file/Articles/B50B6_CM_Apr06_p62.pd
MILITARY EXPERIENCE, DUTY, AND HONORS
,
During the first semester of the second year of Law School, Johnny was drafted into the US ARMY on October 31, 1968 (Halloween). In those days military draft educational deferments were not granted to law students.
After completion of US Army Basic Combat Training on January 11, 1969 Colonel Irvine G. Hughes, Infantry (Commanding) selected Johnny as the "TOP MAN" in his US Army Basic Combat Training Company, Ft. Leonard Wood.
Mr. Miller received some additional main frame communications electronics training at Fort Gordon, Georgia and Fort Ord - Oakland, California and then served in the US Army in Southeast Asia from 1969 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. Lieutenant Colonel Jones was an outstanding leader and an excellent mentor for his troops.
Mr. Miller was assigned to provide US Army S-2 Support to most the US Army Signal Corp in Thailand (except the Bangkok, Chang Mai and Pattaya Regions) as well as on Monkey (Son Tra) Mountain. Vietnam (about 30 miles from the USA Da-Nang Air Base , Vietnam). Monkey Mountain was called Monkey Mountain for good reason!
Mr. Miller also supported various US Army S-2 security and intelligence activities in Laos and Cambodia, as required. The Ho Chi Minh Trail was the elaborate logistical network of about 10,000 miles of roads and trails that ran from North Vietnam through parts of Laos and Cambodia and then into South Vietnam. It provided North Vietnam with troops (Viet Cong and North Vietnamese Army ), supplies, ammo, weapons, and equipment.
Johnny was permanently stationed in Korat, Thailand. He and his wife Nancy (a US Citizen) lived off post on the local Korat economy. Nancy got a job as a full time kinder-garden teacher (independent contractor) on the Korat, Thailand US Army base - Camp Friendship.
Thailand is a very beautiful country and the Thai people are outstanding. Thailand is best described as "The Land of Smiles."
After completing two back-to-back deployments to Thailand, Johnny 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.
EMPLOYMENT HISTORY
After his 1 year Mrs. Lamb's kinder- garden hibernation, an 8 year Sedalia grade school/middle school illumination, a 4 year Smith Cotton high school college preparation, a 4 year Baylor University education, a 3 year University of Memphis law school graduation, a 3 year US Army obligation, a 2 year UMKC LLM celebration, and a 5 year home town general law practice operation.
At that point forward -- .he then started working for high,-
tech corporations.
Mr. Miller has continuously worked with ... "his boots on the ground"... for 45+ years at numerous high-tech corporate and US Government client locations and remotely/online or in-person as a regular employee/contractor/attorney/out-source provider/subcontractor / prime contractor/consultant
for many classified/unclassified /military/civil/commercial
/federal/state /local governmental/academic, medical/health, professional, international, and non-profit entities , in many business/technology domains in various cities including but not limited to , St. Louis, Chicago, Detroit, Memphis, Atlanta, Cleveland, North Carolina, New York, Boston, Austin, Denver, Dallas, LA, San Francisco San Diego, Sacramento, El Paso, Philly, Bangkok, Sydney, Melborne, Hong Kong, Mexico City, UK, and others with increasing levels of responsibility.
A list of his numerous specific high tech clients and employers is available upon request.
BASEBALL: In the 1960s, he played baseball for Baylor University during 1963-1964 and then he played Semi-Pro Baseball the Waco Braves in 1964-1967.
TENNIS: Johnny played a lot of competitive singles & doubles tennis
tournaments in the 1970's. He was the First Place 1978 Outdoor Overland Park Summer Singles Tournament Winner, in Overland Park, Kansas on a very hot weekend in Overland Park. Johnny vividly remembers that he took a long time-out before starting that 3rd set of the singles finals. He went to the Men's locker room and flopped flat on the large shower room floor and turned the cold water on his body - full blast for about 15 minutes just to cool off. He then went on to win the Men's Singles Finals.
GOLF Johnny played golf in the Sedalia , Missouri Country Club Lawyers Annual Best Ball Tournament in the Summer of 1975. Johnny's doubles partner in the best-ball scramble tournament was Bill T, an excellent attorney and a very good golfer. The Bill T-Johnny Miller Team won first place
in that golf tournament.
Johnny's Web Sites:
www.Con-tracts.com
www.JohnnyAttorney.com
www.GoodUSAi.com
www.JohnnyPickleball.com
Johnny's Cell & Text
512 619 7512
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BIOS
More comprehensive Bios are available for each of the above three Co-Founders upon request.
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THREE CO-FOUNDERS
The above three individuals are the Co-Founders and Officers 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.
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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.
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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 THE SIMULATION OF ANY INTELLIGENT TASK.
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?
JUST REMEMBER ...
AI IS THE SIMULATION OF ANY INTELLIGENT TASK.
-------------------------------------
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.
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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.
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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?
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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.
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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.
ML IS THE MOST IMPORTANT ASPECT OF AI .
ML IS THE MOST ESSENTIAL PART OF AI.
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 the appropriate 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 sensors/ 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.
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"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 Vision (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;
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 creating or using 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;
37. Eventuality of AI hacking and subversive activities involving rules, algorithms, data, and other and/or other components.;
38. Potential autonomous killing machines (except in very rare US military cases);
39. 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.;
40. Danger of manipulation of data. Data is a huge AI issue.
See:
I
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 !
41. 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).
42. 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
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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
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"SEVEN PATTERNS OF AI. "
SEE: 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:"
"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
It is highly recommended that the outstanding ..."COGNILYTICA WEB SITE"... be reviewed to see the interesting AI/ML Use Cases decribed there.
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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)
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THE GOOD UNITED STATES ARTIFICIAL INTELLIGENCE GROUP
(GoodUSAi.com)
A FREE 2020 CURATED LIST OF Ai / ML RELATED LINKS REGARDING FREE ON-LINE
WEB SITES, NEWSLETTERS, BLOGS, PODCASTS, WEBINARS, COURSES, EDUCATION, TRAINING, AND OTHER HERE ARE SOME GOOD AI AND ML RELATED LINKS -
1. IMPROVED MEDICAL DIAGNOSIS CASES WITH AI / ML https://www.youtube.com/watch?v=HrKzXLgGohA
2. TOP 25 MACHINE LEARNING START-UPS
https://www.forbes.com/sites/louiscolumbus/2020/04/26/top-25-machine-learning-startups-to-watch-in-2020/#a046b61f5214
3. AI AND ML TRENDS TO LOOK FOR IN 2020
https://medium.com/@quosphere/ai-and-ml-trends-to-look-for-in-2020-d76cdcceb302
ALSO SEE:
https://www.forbes.com/sites/gilpress/2019/12/09/120-ai-predictions-for-2020/#676708c50cf9
4. TEN BEST 2020 FREE ON LINE AL AND ML CLASSES
https://www.forbes.com/sites/bernardmarr/2020/03/16/the-10-best-free-artificial-intelligence-and-machine-learning-courses-for-2020/#350f41cf6f66
5. THE FUTURE OF ARTIFICIAL INTELLIGENCE
https://builtin.com/artificial-intelligence/artificial-intelligence-future
6. THE TOP 20 WORK FROM HOME OR REMOTE JOBS
https://www.forbes.com/sites/laurabegleybloom/2020/02/11/work-from-home-top-20-companies-remote-jobs/#4add
7. WHAT IS THE DIFFERENCE BETWEEN AI, ML AND DEEP LEARNING?
https://www.guru99.com/machine-learning-vs-deep-ng.html
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8. WHAT ARE THE AI AND ML TRENDS IN 2020?
https://www.forbes.com/sites/mariyayao/2020/01/22/what-are--important-ai--machine-learning-trends-for-2020/#1b7e436e2323
ALSO SEE:
https://www.forbes.com/sites/gilpress/2019/12/09/120-ai-predictions-for-2020/#676708c50cf9
9. HERE ARE THE TOP 10 AI AND ML USE CASES THAT EVERYONE NEEDS TO KNOW ABOUT
https://www.forbes.com/sites/bernardmarr/2016/09/30/what-are-the-top-10-use-cases-for-machine-learning-and-ai/#5d1c36b
10. LOOK AT THESE 10 BEST AI AND ML USE CASES FOR GOOD
https://www.forbes.com/sites/bernardmarr/2020/06/22/10-wonderful-examples-of-using-artificial-intelligence-ai-for-good/#2a82c97a2f95
11. NEED FOR GDPR COMPLIANCE
https://www.forbes.com/sites/ajdellinger/2019/05/31/a-year-later-many-sites-are-still-failing-to-meet-basic-gdpr-requirements/#4e0913501eb9
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-AI HUMOR -
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Question: "What do you call a blonde who has dyed her hair to brown?"
Answer: "Artificial Intelligence."
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