Author: Francesca Rossi EN
Policy Department C: Citizens' Rights and Constitutional Affairs
European Parliament
PE 571.380
Artificial Intelligence: Potential Benefits and
Ethical Considerations
KEY FINDINGS
The ability of AI systems to transform vast amounts of complex, ambiguous
information into insight has the potential to reveal long-held secrets and help solve
some of the world’s most enduring problems.
However, like all powerful technologies, great care must be taken in its development
and deployment. To reap the societal benefits of AI systems, we will first need to trust
them and make sure that they follow the same ethical principles, moral values,
professional codes, and social norms that we humans would follow in the same
scenario. Research and educational efforts, as well as carefully designed regulations,
must be put in place to achieve this goal.
International Business Machines Corporation (IBM) is actively engaged, both internally
as well as with its collaborators and competitors, in global discussions about how to
make AI ethical and as beneficial as possible for people as society.
1. WHAT IS ARTIFICIAL INTELLIGENCE?
The term “artificial intelligence” (AI) has been mentioned for the first time in 1956 by John
McCarthy during a conference where several scientists decided to meet to see if machines could
be made intelligent. Since then, AI is usually defined as the capability of a computer
program to perform tasks or reasoning processes that we usually associate to intelligence
in a human being. Often it has to do with the ability to make a good decision even when there
is uncertainty or vagueness, or too much information to handle.
As an example, playing chess well, or some complex card games, is believed to need some
form of intelligence in a human being, as well as choosing the best diagnosis in a difficult
medical case, or creating something new, such as a mathematical theorem or even some form
of art, or even driving a car in the middle of a crowded city.
It is clear that this is a strange definition, because it depends on what we consider being
intelligent in the behaviour of a human being at a certain point in time. If our belief about
human intelligence changes, and we don't believe any longer that a certain task requires
intelligence, then a computer program performing that task is no longer part of AI, it becomes
just another boring computer program.
The term “artificial intelligence” brings to mind to the notion of replacing human intelligence
with something synthetic. At IBM, we prefer the term “augmented intelligence”. This means
that we aim to build systems that enhance and scale human expertise and skills rather than
replacing them. We therefore focus on practical applications of discrete AI capabilities that
assist people in performing well-defined tasks, by exploiting a wide range of AI-based services.
We also use th ...
This technology is no longer a matter of science fiction. Instead, we see artificial intelligence in every part of our lives. Smart assistants are on our phones and speakers, helping us find information and complete everyday tasks. At work, chatbots are affiliated with the Customer Support Team, with estimates that they will be responsible for 85% of customer service by next year.
Artificial Intelligence Vs Machine Learning Vs Deep Learningvenkatvajradhar1
This technology is no longer a matter of science fiction. Instead, we see artificial intelligence in every part of our lives. Smart assistants are on our phones and speakers, helping us find information and complete everyday tasks. At work, chatbots are affiliated with the Customer Support Team, with estimates that they will be responsible for 85% of customer service by next year.
Running Head ARTIFICIAL INTELLIGENCE AND EXPERT SYSTEMSArtifici.docxhealdkathaleen
Running Head: ARTIFICIAL INTELLIGENCE AND EXPERT SYSTEMS
Artificial Intelligence and Expert System
Artificial Intelligence and Expert systems
ABSTRACT:
· What is artificial intelligence?
· Characteristics of AI
· The field of AI
· How the AI field evolved
· What is Expert System?
KEYWORDS:
· Artificial intelligence Technology
· International Technology Transfers
· Expert Systems
· Applied Artificial Intelligence Human Experts
INTRODUCTION:
· AI to Predict and Adapt
· Making Decisions
· Continuous Learning
· Capability of Motion and Perception
OVERVIEW OF APPLIED ARTIFICIAL INTELLIGENCE:
· Natural language processing
· Robotics
· Computer vision
· Speech Recognition
· Machine learning
EXPERIMENT:
APPLICATIONS OF EXPERT SYSTEMS:
· Troubleshooting and Diagnosis
· Financial decision making
· Knowledge Publishing
· Design and Manufacturing
EXPERT SYSTEMS IN ORGANISATION:
BENEFITS AND LIMITATIONS OF AI ALONG WITH EXPERT SYSTEMS:
NEURAL NETWORKING:
Artificial Intelligence and Expert Systems
Sapana Dahal
CSCI 303
Texas A& M University Commerce
Artificial Intelligence (AI) in the current technological crazed world has been on the center stage. AI has commendable gained notable popularity and visibility that is very string in the public domain, business community, Educations and various other special fields. Now the most successful business in the world have not hesitated to fully take advantage of AI to better their products, through presented AI to the consumer in a cheaper state. This is the example Amazon Alexa AI, Apples Siri AI and Microsoft’s Cortana (Kaplan & Haenlein 2019). These are aperfect example of the use of AI to make things easier for the consumer, all these considered to be “personal assistants. Expert Systems (ES) on the other hand are a dominant filed in AI, basically the largest field in AI currently, this is because it offers scientific, commercial and military application of AI. This paper is aimed at looking at and explaining the AI concepts and ES applications that have been able to make the life of every individual in different field easier. Like ROSS the Ai attorney, or the Dendral expert system in medicine. The Implementation of AI technology cannot be ignored in our daily lives cannot be ignored because of the impact that such a technology is bringing to our world. Never have machines been able to mimic the human brain and be able to tackles decision making or problem-solving instance as better or just as the human brain. These aspects have caused a major quagmire of mixed feelings. Mainly because the AI and ESs will make our lives easier bhut at the same time it will step in the place of human experts that will mean they will be replaced. The paper clearly discusses on this fact on how the ESs and Ai are not here to replace the Human experts, especially the white-collar jobs but only to make their task much easier.
KEYWORDS
Artificial Intelligence Technology, Internationa ...
Running Head ARTIFICIAL INTELLIGENCE AND EXPERT SYSTEMSArtificiMalikPinckney86
Running Head: ARTIFICIAL INTELLIGENCE AND EXPERT SYSTEMS
Artificial Intelligence and Expert System
Artificial Intelligence and Expert systems
ABSTRACT:
· What is artificial intelligence?
· Characteristics of AI
· The field of AI
· How the AI field evolved
· What is Expert System?
KEYWORDS:
· Artificial intelligence Technology
· International Technology Transfers
· Expert Systems
· Applied Artificial Intelligence Human Experts
INTRODUCTION:
· AI to Predict and Adapt
· Making Decisions
· Continuous Learning
· Capability of Motion and Perception
OVERVIEW OF APPLIED ARTIFICIAL INTELLIGENCE:
· Natural language processing
· Robotics
· Computer vision
· Speech Recognition
· Machine learning
EXPERIMENT:
APPLICATIONS OF EXPERT SYSTEMS:
· Troubleshooting and Diagnosis
· Financial decision making
· Knowledge Publishing
· Design and Manufacturing
EXPERT SYSTEMS IN ORGANISATION:
BENEFITS AND LIMITATIONS OF AI ALONG WITH EXPERT SYSTEMS:
LIMITATIONS OF EXPERT SYSTEMS:
NEURAL NETWORKING:
· Artificial neural networking
· Training Data
Artificial Intelligence and Expert Systems
Sapana Dahal
CSCI 303
Texas A& M University Commerce
Artificial Intelligence (AI) in the current technological crazed world has been on the center stage. AI has commendable gained notable popularity and visibility that is very string in the public domain, business community, Educations and various other special fields. Now the most successful business in the world have not hesitated to fully take advantage of AI to better their products, through presented AI to the consumer in a cheaper state. This is the example Amazon Alexa AI, Apples Siri AI and Microsoft’s Cortana (Kaplan & Haenlein 2019). These are aperfect example of the use of AI to make things easier for the consumer, all these considered to be “personal assistants. Expert Systems (ES) on the other hand are a dominant filed in AI, basically the largest field in AI currently, this is because it offers scientific, commercial and military application of AI. This paper is aimed at looking at and explaining the AI concepts and ES applications that have been able to make the life of every individual in different field easier. Like ROSS the Ai attorney, or the Dendral expert system in medicine. The Implementation of AI technology cannot be ignored in our daily lives cannot be ignored because of the impact that such a technology is bringing to our world. Never have machines been able to mimic the human brain and be able to tackles decision making or problem-solving instance as better or just as the human brain. These aspects have caused a major quagmire of mixed feelings. Mainly because the AI and ESs will make our lives easier bhut at the same time it will step in the place of human experts that will mean they will be replaced. The paper clearly discusses on this fact on how the ESs and Ai are not here to replace the Human experts, especially the white-collar jobs but only to make the ...
Running Head ARTIFICIAL INTELLIGENCE AND EXPERT SYSTEMSArtifici.docxtoddr4
Running Head: ARTIFICIAL INTELLIGENCE AND EXPERT SYSTEMS
Artificial Intelligence and Expert System
Artificial Intelligence and Expert systems
ABSTRACT:
· What is artificial intelligence?
· Characteristics of AI
· The field of AI
· How the AI field evolved
· What is Expert System?
KEYWORDS:
· Artificial intelligence Technology
· International Technology Transfers
· Expert Systems
· Applied Artificial Intelligence Human Experts
INTRODUCTION:
· AI to Predict and Adapt
· Making Decisions
· Continuous Learning
· Capability of Motion and Perception
OVERVIEW OF APPLIED ARTIFICIAL INTELLIGENCE:
· Natural language processing
· Robotics
· Computer vision
· Speech Recognition
· Machine learning
EXPERIMENT:
APPLICATIONS OF EXPERT SYSTEMS:
· Troubleshooting and Diagnosis
· Financial decision making
· Knowledge Publishing
· Design and Manufacturing
EXPERT SYSTEMS IN ORGANISATION:
BENEFITS AND LIMITATIONS OF AI ALONG WITH EXPERT SYSTEMS:
LIMITATIONS OF EXPERT SYSTEMS:
NEURAL NETWORKING:
· Artificial neural networking
· Training Data
Artificial Intelligence and Expert Systems
Sapana Dahal
CSCI 303
Texas A& M University Commerce
Artificial Intelligence (AI) in the current technological crazed world has been on the center stage. AI has commendable gained notable popularity and visibility that is very string in the public domain, business community, Educations and various other special fields. Now the most successful business in the world have not hesitated to fully take advantage of AI to better their products, through presented AI to the consumer in a cheaper state. This is the example Amazon Alexa AI, Apples Siri AI and Microsoft’s Cortana (Kaplan & Haenlein 2019). These are aperfect example of the use of AI to make things easier for the consumer, all these considered to be “personal assistants. Expert Systems (ES) on the other hand are a dominant filed in AI, basically the largest field in AI currently, this is because it offers scientific, commercial and military application of AI. This paper is aimed at looking at and explaining the AI concepts and ES applications that have been able to make the life of every individual in different field easier. Like ROSS the Ai attorney, or the Dendral expert system in medicine. The Implementation of AI technology cannot be ignored in our daily lives cannot be ignored because of the impact that such a technology is bringing to our world. Never have machines been able to mimic the human brain and be able to tackles decision making or problem-solving instance as better or just as the human brain. These aspects have caused a major quagmire of mixed feelings. Mainly because the AI and ESs will make our lives easier bhut at the same time it will step in the place of human experts that will mean they will be replaced. The paper clearly discusses on this fact on how the ESs and Ai are not here to replace the Human experts, especially the white-collar jobs but only to make the.
What Is Artificial Intelligence,How It Is Used and Its Future.pdfMaazUmar3
What Is Artificial Intelligence,How It Is Used in now days and what is Its Future that help the humans also contain full history of artificial intelligence.
This technology is no longer a matter of science fiction. Instead, we see artificial intelligence in every part of our lives. Smart assistants are on our phones and speakers, helping us find information and complete everyday tasks. At work, chatbots are affiliated with the Customer Support Team, with estimates that they will be responsible for 85% of customer service by next year.
Artificial Intelligence Vs Machine Learning Vs Deep Learningvenkatvajradhar1
This technology is no longer a matter of science fiction. Instead, we see artificial intelligence in every part of our lives. Smart assistants are on our phones and speakers, helping us find information and complete everyday tasks. At work, chatbots are affiliated with the Customer Support Team, with estimates that they will be responsible for 85% of customer service by next year.
Running Head ARTIFICIAL INTELLIGENCE AND EXPERT SYSTEMSArtifici.docxhealdkathaleen
Running Head: ARTIFICIAL INTELLIGENCE AND EXPERT SYSTEMS
Artificial Intelligence and Expert System
Artificial Intelligence and Expert systems
ABSTRACT:
· What is artificial intelligence?
· Characteristics of AI
· The field of AI
· How the AI field evolved
· What is Expert System?
KEYWORDS:
· Artificial intelligence Technology
· International Technology Transfers
· Expert Systems
· Applied Artificial Intelligence Human Experts
INTRODUCTION:
· AI to Predict and Adapt
· Making Decisions
· Continuous Learning
· Capability of Motion and Perception
OVERVIEW OF APPLIED ARTIFICIAL INTELLIGENCE:
· Natural language processing
· Robotics
· Computer vision
· Speech Recognition
· Machine learning
EXPERIMENT:
APPLICATIONS OF EXPERT SYSTEMS:
· Troubleshooting and Diagnosis
· Financial decision making
· Knowledge Publishing
· Design and Manufacturing
EXPERT SYSTEMS IN ORGANISATION:
BENEFITS AND LIMITATIONS OF AI ALONG WITH EXPERT SYSTEMS:
NEURAL NETWORKING:
Artificial Intelligence and Expert Systems
Sapana Dahal
CSCI 303
Texas A& M University Commerce
Artificial Intelligence (AI) in the current technological crazed world has been on the center stage. AI has commendable gained notable popularity and visibility that is very string in the public domain, business community, Educations and various other special fields. Now the most successful business in the world have not hesitated to fully take advantage of AI to better their products, through presented AI to the consumer in a cheaper state. This is the example Amazon Alexa AI, Apples Siri AI and Microsoft’s Cortana (Kaplan & Haenlein 2019). These are aperfect example of the use of AI to make things easier for the consumer, all these considered to be “personal assistants. Expert Systems (ES) on the other hand are a dominant filed in AI, basically the largest field in AI currently, this is because it offers scientific, commercial and military application of AI. This paper is aimed at looking at and explaining the AI concepts and ES applications that have been able to make the life of every individual in different field easier. Like ROSS the Ai attorney, or the Dendral expert system in medicine. The Implementation of AI technology cannot be ignored in our daily lives cannot be ignored because of the impact that such a technology is bringing to our world. Never have machines been able to mimic the human brain and be able to tackles decision making or problem-solving instance as better or just as the human brain. These aspects have caused a major quagmire of mixed feelings. Mainly because the AI and ESs will make our lives easier bhut at the same time it will step in the place of human experts that will mean they will be replaced. The paper clearly discusses on this fact on how the ESs and Ai are not here to replace the Human experts, especially the white-collar jobs but only to make their task much easier.
KEYWORDS
Artificial Intelligence Technology, Internationa ...
Running Head ARTIFICIAL INTELLIGENCE AND EXPERT SYSTEMSArtificiMalikPinckney86
Running Head: ARTIFICIAL INTELLIGENCE AND EXPERT SYSTEMS
Artificial Intelligence and Expert System
Artificial Intelligence and Expert systems
ABSTRACT:
· What is artificial intelligence?
· Characteristics of AI
· The field of AI
· How the AI field evolved
· What is Expert System?
KEYWORDS:
· Artificial intelligence Technology
· International Technology Transfers
· Expert Systems
· Applied Artificial Intelligence Human Experts
INTRODUCTION:
· AI to Predict and Adapt
· Making Decisions
· Continuous Learning
· Capability of Motion and Perception
OVERVIEW OF APPLIED ARTIFICIAL INTELLIGENCE:
· Natural language processing
· Robotics
· Computer vision
· Speech Recognition
· Machine learning
EXPERIMENT:
APPLICATIONS OF EXPERT SYSTEMS:
· Troubleshooting and Diagnosis
· Financial decision making
· Knowledge Publishing
· Design and Manufacturing
EXPERT SYSTEMS IN ORGANISATION:
BENEFITS AND LIMITATIONS OF AI ALONG WITH EXPERT SYSTEMS:
LIMITATIONS OF EXPERT SYSTEMS:
NEURAL NETWORKING:
· Artificial neural networking
· Training Data
Artificial Intelligence and Expert Systems
Sapana Dahal
CSCI 303
Texas A& M University Commerce
Artificial Intelligence (AI) in the current technological crazed world has been on the center stage. AI has commendable gained notable popularity and visibility that is very string in the public domain, business community, Educations and various other special fields. Now the most successful business in the world have not hesitated to fully take advantage of AI to better their products, through presented AI to the consumer in a cheaper state. This is the example Amazon Alexa AI, Apples Siri AI and Microsoft’s Cortana (Kaplan & Haenlein 2019). These are aperfect example of the use of AI to make things easier for the consumer, all these considered to be “personal assistants. Expert Systems (ES) on the other hand are a dominant filed in AI, basically the largest field in AI currently, this is because it offers scientific, commercial and military application of AI. This paper is aimed at looking at and explaining the AI concepts and ES applications that have been able to make the life of every individual in different field easier. Like ROSS the Ai attorney, or the Dendral expert system in medicine. The Implementation of AI technology cannot be ignored in our daily lives cannot be ignored because of the impact that such a technology is bringing to our world. Never have machines been able to mimic the human brain and be able to tackles decision making or problem-solving instance as better or just as the human brain. These aspects have caused a major quagmire of mixed feelings. Mainly because the AI and ESs will make our lives easier bhut at the same time it will step in the place of human experts that will mean they will be replaced. The paper clearly discusses on this fact on how the ESs and Ai are not here to replace the Human experts, especially the white-collar jobs but only to make the ...
Running Head ARTIFICIAL INTELLIGENCE AND EXPERT SYSTEMSArtifici.docxtoddr4
Running Head: ARTIFICIAL INTELLIGENCE AND EXPERT SYSTEMS
Artificial Intelligence and Expert System
Artificial Intelligence and Expert systems
ABSTRACT:
· What is artificial intelligence?
· Characteristics of AI
· The field of AI
· How the AI field evolved
· What is Expert System?
KEYWORDS:
· Artificial intelligence Technology
· International Technology Transfers
· Expert Systems
· Applied Artificial Intelligence Human Experts
INTRODUCTION:
· AI to Predict and Adapt
· Making Decisions
· Continuous Learning
· Capability of Motion and Perception
OVERVIEW OF APPLIED ARTIFICIAL INTELLIGENCE:
· Natural language processing
· Robotics
· Computer vision
· Speech Recognition
· Machine learning
EXPERIMENT:
APPLICATIONS OF EXPERT SYSTEMS:
· Troubleshooting and Diagnosis
· Financial decision making
· Knowledge Publishing
· Design and Manufacturing
EXPERT SYSTEMS IN ORGANISATION:
BENEFITS AND LIMITATIONS OF AI ALONG WITH EXPERT SYSTEMS:
LIMITATIONS OF EXPERT SYSTEMS:
NEURAL NETWORKING:
· Artificial neural networking
· Training Data
Artificial Intelligence and Expert Systems
Sapana Dahal
CSCI 303
Texas A& M University Commerce
Artificial Intelligence (AI) in the current technological crazed world has been on the center stage. AI has commendable gained notable popularity and visibility that is very string in the public domain, business community, Educations and various other special fields. Now the most successful business in the world have not hesitated to fully take advantage of AI to better their products, through presented AI to the consumer in a cheaper state. This is the example Amazon Alexa AI, Apples Siri AI and Microsoft’s Cortana (Kaplan & Haenlein 2019). These are aperfect example of the use of AI to make things easier for the consumer, all these considered to be “personal assistants. Expert Systems (ES) on the other hand are a dominant filed in AI, basically the largest field in AI currently, this is because it offers scientific, commercial and military application of AI. This paper is aimed at looking at and explaining the AI concepts and ES applications that have been able to make the life of every individual in different field easier. Like ROSS the Ai attorney, or the Dendral expert system in medicine. The Implementation of AI technology cannot be ignored in our daily lives cannot be ignored because of the impact that such a technology is bringing to our world. Never have machines been able to mimic the human brain and be able to tackles decision making or problem-solving instance as better or just as the human brain. These aspects have caused a major quagmire of mixed feelings. Mainly because the AI and ESs will make our lives easier bhut at the same time it will step in the place of human experts that will mean they will be replaced. The paper clearly discusses on this fact on how the ESs and Ai are not here to replace the Human experts, especially the white-collar jobs but only to make the.
What Is Artificial Intelligence,How It Is Used and Its Future.pdfMaazUmar3
What Is Artificial Intelligence,How It Is Used in now days and what is Its Future that help the humans also contain full history of artificial intelligence.
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__________Maintenance Bilingual Ed., Self-Contained
__________Transitional Bilingual Ed.
__________One-way Dual Language
__________Pull-out Bilingual Ed.
__________Two-way Dual Language
__________Enrichment Bilingual Education (30 min. per day)
The following programs are designed for ELs who do not live in an area where bilingual ed. is available or do not qualify for bilingual education due to the language they speak. Please rate the following ESL programs on a scale of 1-4 with 1 being the most successful way to teach English and 4 being the least effective program:
__________ESL Pull-out
__________Sheltered Instruction in the regular classroom
__________Total emersion with no language support
__________English enrichment, 30 minutes per day, by classroom teacher
3) Please explain the difference between a 50/50 model and a 90/10 model of Dual Language Education.
4) Why does 2-way Dual Language Education usually have better results than 1-way Dual Language Education?
5) In order to have an effective Dual Language program, there are two important things teachers should not do. What are they?
6) What does it mean to see other cultures not as a deficit but as a difference? Why is this idea important to your classroom?
7) We are required to have many formal assessments in our educational curriculum. However, informal assessment can be much more informative to the teacher of language learners. Please explain why Informal Assessments might be a better way for the teacher to know the true level of the student.
...
Based on Santa Clara University Ethics DialogueEthics .docxrock73
Based on Santa Clara University Ethics Dialogue
Ethics case studies
This is an extra credit assignment that I am offering for the first time this term. In this booklet, you will find 38 separate case studies. You are free to respond to any or all of these cases.
You may earn up to 5 extra credit points per question, based on the complexity of the case and the logic of your response. You may not earn more than 100 points (10 percent of your final grade).
You may find it helpful to read the paper “Four Tough Ethical Dilemmas” prior to responding.
While these are your opinions, citations are not expected; however, if you make use of the work of others, include APA style citations for complete credit.
Either cut and paste the cases you select to a separate file or use this file for your submission. If you use this file to submit a response, please delete those cases to which you are not responding.
Dr. Frick
Case 1: Family Loyalty vs. Meritocracy
A man was appointed president of the newly-acquired Philippine subsidiary of a large American company. He was reviewing the organization with the company's head of human resources. One thing the president noted was that the same names reoccurred frequently in several departments. "It is our tradition," commented the HR head. "Families take care of their own. If one family member gets a good job in a Philippine company, other members of the family apply to join that company and the first member there can help the whole family become successful by helping them get hired and by coaching them to be successful. The company benefits. Our costs of recruiting are lower, we know more about the people we hire, and the commitment to family success results in fewer performance and discipline problems because family members want to please their older relatives."
The president wondered how these practices would be regarded in a large American firm, and whether or not he should take action to change them.
1. Nepotism is not illegal, but is it ethical?
2. If the business is family-owned, does that make a difference?
3. How does national culture affect this discussion?
Case 2: Is the Two-Tier System Ethically Problematic
Employees at a cereal makers plant were “locked-out” from their jobs producing cereal for over 3 months. Company management and the union representing the employees reached a stalemate in negotiations resulting in the lockout. The union claims that the primary issue is the company’s demand of dramatically increasing the number of temporary workers, who would earn $6 less per hour and receive fewer benefits. Critics claim this effectively creates a two-tier system at the plant. Under the current agreement, the company may use temporary workers for up to 30% of the workforce, but the union claims the company is now pushing for 100%. The workers, who have had their health insurance suspended, fear that their jobs will either be replaced entirely by temporary workers, or they will be f ...
Barbara Corcoran Learns Her Heart’s True Desires In her.docxrock73
Barbara Corcoran Learns Her Heart’s True Desires
In her hilarious and lighthearted book, Shark Tales: How I Turned $1,000 Into a
Billion Dollar Business, Barbara Corcoran demonstrates the importance of knowing what
you really want out of life (Corcoran & Littlefield, 2011). As her title suggests, Barbara
founded her real estate company, The Corcoran Group, with only $1,000 and some big
dreams. Shortly after founding the company, Barbara took out a piece of paper and wrote
down some big goals for herself and the company. In 1978, she had only 14 sales agents
working for her, who earned a total of $250,000 in commissions. She set a goal of
doubling the number of agents and the commissions every year. So she put down 28 sales
people for 1979, 56 for 1980, and so on, all the way up to 1,792 salespeople in 1985 with
total commissions of $32,000,000. Barbara was amazed when she saw the fantastic sums
projected for 1985, and of course many people, when they see such amazing sums, would
dismiss the calculations as fantasy But as Barbara put it, she went to work the next day
hustling hard for her $32 million.
Real estate agents are paid largely by commission, which is about as close as you
can get to a pure form of contingent reward for performance. However, Barbara didn’t
rely solely on the commissions to motivate her workers. She threw theme parties and held
numerous social events to build a committed workforce. Good sales agents could always
move to another firm, but not every firm had Barbara’s positive attitude and fun-filled
atmosphere. In the early years of the firm, when money was tight, Barbara and her
relatives did the cooking for the outings and parties, and she found clever ways to
entertain people with skating parties and other lively activities. As the firm became larger
and more profitable, she even hired professional entertainers for the company’s midweek
picnics, which included elephant shows, daring rides on hot air balloons, horses, or
Harley Davidsons, etc. Barbara stated “I built my company on pure fun, and believe that
fun is the most underutilized motivational tool in business today. All of my best ideas
came when I was playing outside the office with the people I worked with” (Corcoran &
Littlefield, 2011, p. 283). What did she get in return for the fun atmosphere? She had the
“most profitable real estate company per person in the United States” (p. 284). By the
time she sold her agency in 2001, she had 1,000 agents working for her, and she had the
largest real estate agency in New York – clearly her motivational strategies attracted a
large number of productive employees.
Barbara Corcoran had sold her firm for $66 million. She thought that would make
her happy, but instead, it made her sad. Although she pretended to be happy with her new
wealth and freedom, she was “secretly miserable” (Corcoran & Littlefield, 2011, p. 232).
She had lost her purpose ...
Bapsi Sidhwa’s Cracking India
1947 Partition
Deepa Mehta’s earth (1998)
Characters
Aamir Khan - Dil Navaz, the Ice Candy Man
Nandita Das - Shanta, the Ayah
Rahul Khanna - Hassan, the Masseur
Maia Sethna - Lenny Sethna
Shabana Azmi - older Lenny, narrator
Kitu Gidwani - Bunty Sethna
Arif Zakaria - Rustom Sethna
Kulbhushan Kharbanda - Imam Din
Kumar Rajendra - Refugee Police
Pavan Malhotra - Butcher
IN Deepa Mehta’s words
I wanted desperately to make CRACKING INDIA into a film, a particular film, EARTH, which would be the second in my trilogy of the elements of Fire, Earth and Water.
Tracing Bapsi was no easy task but persevere we did and soon I was talking to Bapsi on the phone, hoping that the film rights to her book were still available. Two months later, thanks to David Hamilton's unwavering belief in the project, we owned the rights, had development funds, and I was sitting at my kitchen table, writing the screenplay of EARTH.
David and Anne Masson and I had worked together on FIRE and we re-assembled the team to begin the detailed planning of the production.
During this phase Bapsi became a friend and was exceedingly generous with information and old photographs. She would talk with me for hours about what it was like growing up in Lahore during those times. Lenny, after all, was based on Bapsi. In fact, Lenny was Bapsi.
The irony of our situation hasn't escaped Bapsi or myself. Bapsi is from Pakistan and now a US citizen. I'm from India and now living in Canada. If neither of us had moved from our respective homelands, the film just wouldn't have been possible. Pakistan and India, since the Partition of 1947, are sworn enemies. Not only have they fought three major wars against each other, but also, as I write this, both countries talk blithely about their nuclear capabilities and continue their militant aggression against each other across the still- disputed Kashmir border.
Fallen Women in the novel and film
Abducted women like Ayah and Hamdia, Lenny’s new nanny are viewed with suspicion from Lenny.
Page 226
“It isn’t a jail, Lenny baby…it’s a camp for fallen women.”
“What are fallen women?”
“Hai! The questions you ask! Your mother won’t like such talk…Now keep quiet”
“Are you a fallen woman?”
Fallen women – Abducted and raped women
In the aftermath of the 1947 declaration of Indian independence, the roughly drawn new state boundaries triggered what may have been the biggest migration in human history.
Historical consensus supports a figure of 12 million people displaced, although the BBC suggests figures as high as 14.5 million people. An undeclared civil war erupted as communities of Hindus, Muslims, and Sikhs fought one another to establish their own identities in their redefined homelands. And, in the process, the Indian government estimates, 83,000 women were abused and abducted. Others put the number even higher.
“Rather than being raped and abandoned,” Yasmin Khan writes in The Great Partition: The ...
Barriers of therapeutic relationshipThe therapeutic relations.docxrock73
Barriers of therapeutic relationship:
The therapeutic relationship between patient and nurse is often filled with barriers that can generate obstacles for the relationship and, in the end, the health system as a whole (Sfoggia et al.,2014). There are many factors that hinder building a therapeutic relationship: language, professional jargon, communication impairment, and cultural diversity (ibid).
Language:
Language can be an obstacle to nurse-patient communication because a patient may not be able to speak the same language and therefore communication is not possible (Levin,2006). The best way to overcome this barrier is providing a translator who can explain a professional facilitator's message easily to the patient(ibid). For instance, if the nurse only speaks English but the patient is only able to speak Arabic, a translation to the patient of what the professional facilitator is saying leads to less chance of misunderstanding (ibid). Translation also allows a patient to feel comfortable through being able to speak in their own language (ibid).
Medical jargon:
Jargon is a technical language that is comprehended by people in a specific industry or area of work (Leblanc et al.,2014). Health professionals often use jargon to communicate with each other(ibid). For example, T.B. disease stands for tubercle bacillus and HIV stands for human immunodeficiency virus (Mccrary & Christensen,1993). Jargon often makes sense to health professionals but a patient who does not understand these acronyms will not understand such communication, leading to a barrier in therapeutic relationship between patient and health professional (Leblanc et al.,2014).
Communication impairment:
Patients with communication impairment such as blindness, deafness and speech impairment often feel isolated, frustrated and self-conscious (O’Halloran et al.,2009). Some patients are born with such disabilities or have developed them as a result of disease (ibid). Therefore, nurses should provide enough time in order to describe any issue to such patients so that they do not feel uncomfortable or censured by health professionals, who must remain impartial (ibid).
Cultural diversity:
Patients often have various differences (Leblanc et al.,2014).Some of these differences are due to a patient's illness, social status, economic class, education and personality(ibid). However, according to Kirkham (1998), the deepest differences might be cultural diversity. Beheri (2009) points out that many nurses believe if they just treat patients with respect, they will avoid most cultural issues. Nevertheless, avoiding misunderstanding can be achieved through some knowledge of cultural customs, which might help and enable nurses to provide better health care to patients (ibid).
Facilitators of therapeutic relationship:
UNCRPD (2006) states that the most fundamental human right in hospital is communication. Patients are required to be provided with an effective communication method by nurs ...
Barada 2Mohamad BaradaProfessor Andrew DurdinReligions of .docxrock73
Barada 2
Mohamad Barada
Professor Andrew Durdin
Religions of the World Hum 201-02
March 23rd, 2018
References:
1. Rachel. Rachel’s Musings: Buddhism is a Religion. Retrieved from https://www.rabe.org/thoughts-on-buddhism/buddhism-is-a-religion/
2. Winfield, Pamela. The Conversation: Why so many Americans think Buddhism is just a philosophy. Retrieved from https://theconversation.com/why-so-many-americans-think-buddhism-is-just-a-philosophy-89488
Critical Analysis of the religious nature of Buddhism
The religious community often debates on whether Buddhism is categorized as a religion or as philosophical teaching. The answer to the question varies depending on an individual’s point of view. There are three main types of Buddhism practices across the world with each of them having smaller branches with slights variances in their teachings and beliefs. The different styles of Buddhist mainly encompass Theravada Buddhism, Vajrayana Buddhism, and Mahayana Buddhism. The various forms often have deities that are worshipped while others do not. Some often have scriptures while others do not usually believe in any physical form of the Buddhist teachings. The first article is authored by Rachel, a blogger, presenting the argument that Buddhism is a religion (Rachel, 1). On the other hand, the second article authored by Pamela Winfield recognizes Buddhism as a philosophy. Analyzing and comparing the two pieces having divergent views on the religious nature of Buddhism is crucial for understanding whether it is a religion or philosophy.
Summary of the articles
Rachel in her article considers Buddhism as a religion. The author acknowledges the fact that Mahayana Buddhism which is often found in greater part of Asia that includes Japan, Korea, and China often teaches on attaining enlightenment (Rachel, 1). The Mahayana often accept that every individual wishes to ensure the effective attainment of enlightenment and thus end the cycle of rebirth which others recognize as “Karma.” The article proceeds to state that Buddha is the greatest of the deities but is not worshipped. Instead, Buddha often inspires all those who practice doing as he once did. The author states that Buddhism often requires that the individuals that choose the wrong path attempt to re-accomplish these tasks in their next life alongside other punishments imposed on them by karma. The characteristics of this type of Buddhism thus often play a significant role in showing the religious nature of Buddhism. The author concludes by stating that Buddhism often contains all the different elements of a religion. Moreover, the article associates Buddhism with fallacies that characterize other religions and just as dangerous as other religions as well. A quote proves the claim on the dangerous nature of Buddhism that the author uses to summarize the teachings of Buddhism.
On the other hand, Winfield tends to focus on enlightening the readers on some of the aspects of Buddhism that ensures its a ...
Macroeconomics- Movie Location
This will be used as part of your Personal Professional Portfolio once graded.
Objective:
Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
Welcome to TechSoup New Member Orientation and Q&A (May 2024).pdfTechSoup
In this webinar you will learn how your organization can access TechSoup's wide variety of product discount and donation programs. From hardware to software, we'll give you a tour of the tools available to help your nonprofit with productivity, collaboration, financial management, donor tracking, security, and more.
A Strategic Approach: GenAI in EducationPeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
Francesca Gottschalk - How can education support child empowerment.pptxEduSkills OECD
Francesca Gottschalk from the OECD’s Centre for Educational Research and Innovation presents at the Ask an Expert Webinar: How can education support child empowerment?
Embracing GenAI - A Strategic ImperativePeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
Author Francesca Rossi EN Policy Department C Citizens.docx
1. Author: Francesca Rossi EN
Policy Department C: Citizens' Rights and Constitutional
Affairs
European Parliament
PE 571.380
Artificial Intelligence: Potential Benefits and
Ethical Considerations
KEY FINDINGS
complex, ambiguous
information into insight has the potential to reveal long-held
secrets and help solve
some of the world’s most enduring problems.
great care must be
taken in its development
and deployment. To reap the societal benefits of AI systems, we
will first need to trust
them and make sure that they follow the same ethical principles,
moral values,
2. professional codes, and social norms that we humans would
follow in the same
scenario. Research and educational efforts, as well as carefully
designed regulations,
must be put in place to achieve this goal.
actively engaged, both internally
as well as with its collaborators and competitors, in global
discussions about how to
make AI ethical and as beneficial as possible for people as
society.
1. WHAT IS ARTIFICIAL INTELLIGENCE?
The term “artificial intelligence” (AI) has been mentioned for
the first time in 1956 by John
McCarthy during a conference where several scientists decided
to meet to see if machines could
be made intelligent. Since then, AI is usually defined as the
capability of a computer
program to perform tasks or reasoning processes that we usually
associate to intelligence
in a human being. Often it has to do with the ability to make a
good decision even when there
is uncertainty or vagueness, or too much information to handle.
3. As an example, playing chess well, or some complex card
games, is believed to need some
form of intelligence in a human being, as well as choosing the
best diagnosis in a difficult
medical case, or creating something new, such as a
mathematical theorem or even some form
of art, or even driving a car in the middle of a crowded city.
It is clear that this is a strange definition, because it depends on
what we consider being
intelligent in the behaviour of a human being at a certain point
in time. If our belief about
human intelligence changes, and we don't believe any longer
that a certain task requires
intelligence, then a computer program performing that task is no
longer part of AI, it becomes
just another boring computer program.
The term “artificial intelligence” brings to mind to the notion of
replacing human intelligence
with something synthetic. At IBM, we prefer the term
“augmented intelligence”. This means
that we aim to build systems that enhance and scale human
expertise and skills rather than
4. replacing them. We therefore focus on practical applications of
discrete AI capabilities that
assist people in performing well-defined tasks, by exploiting a
wide range of AI-based services.
We also use the term “Cognitive Computing”, to mean a
comprehensive set of capabilities
based on technologies which include AI, but that go far beyond
it. “Cognitive Computing”
Policy Department C: Citizens' Rights and Constitutional
Affairs
2 PE 571.380
comprises the fields of machine learning, reasoning and
decision technologies, language,
speech and vision recognition and processing technologies,
human interface technologies,
distributed and high-performance computing, and new
computing architectures and devices.
When purposefully integrated, these capabilities are designed to
solve a wide range of practical
problems, boost productivity, and foster new discoveries across
many industries.
2. AI IN OUR LIVES
5. There are many examples of the presence of AI in our current
life, that we don’t even know of.
Whenever we buy something with a credit card, an AI algorithm
approves that transaction (or
not). When we use the GPS in our car, the algorithm that finds
the best way to go from where
we are to where we need to go is called the A* algorithm and it
is an essential tool for AI,
present in every AI teaching book. Spam filters are based on
AI. Recommender systems such
as that of Amazon are AI. The Google translate service, which
nowadays is able to translate
from and to more than 70 languages, is based on statistical
machine learning, which is part of
AI. Even web searches, such as those that we ask of Google or
Baidu or other search engines,
rely on AI to give us the web pages that are most relevant to our
query. The face recognition
capability of any of our cameras, shown usually with a green
rectangle around each face we
want to take a picture of, is AI. Siri, the IPhone app that
understands us when we speak and
responds (usually) in a useful way, is based on AI algorithms
for speech understanding.
6. And of course there is the whole branch of robotics, which is
more easily associated with AI
because of the iconic image of humanoid robots that make it
seem that humans have been
reproduced artificially. Of course not all of them are intelligent
in the way we would say a
human is intelligent, but they are usually very good at doing
what they are supposed to in their
environment, from the Roomba robot that cleans the floors of
our houses, to the Baxter robot
that can work together with humans in production chains,
passing through the Kiva warehouse
robots that can take care of the tasks of an entire warehouse and
the companion robots like
Nao, Pepper, Aibo, and Giraff, who can entertain us, talk to us,
and help elderly people to stay
connected to their friends, relatives, and doctors.
The realm of possible uses of AI techniques is enormously vast,
and this is one of the reasons
why many companies have been heavily investing in AI in
recent years. Google is building self-
driving cars and has acquired more than 10 robotics companies,
7. Facebook had opened a whole
new research facility focused only on AI research, Apple has
developed Siri, Microsoft has built
Cortana, a similar personalized assistant, Google has acquired
DeepMind, a UK company whose
long-term aim is to build general AI and has already shown
great potential in winning at the
game of Go the current world champion, and IBM is investing a
huge amount of resources in
applying its Watson cognitive computing system to the medical
domain, to finance, and to
personalized education, just to name a few. This expansion of
AI-based systems and services
is reaching all corners of the globe. In Europe, IBM is
establishing new centres in Munich and
Milan focused on the application of cognitive computing
capabilities to the Internet of Things
and healthcare, respectively.
Self-driving cars are all about AI: they need to be able to see
what happens in the street
(signals, lanes, other cars, pedestrians, traffic lights), they need
to able to predict what other
cars and pedestrian will do, and they need to be able to cope
8. with unforeseen situations. Since
most car accidents are due to human fault, it is estimated that
the adoption of self-driving cars
will save about half of the lives that are usually lost in car
accidents, which totals around 40,000
each year in the US alone. Some of us may be reluctant to hand
over the wheel to an AI system,
but very soon we may wonder why we did not do it sooner!
Watson is an IBM cognitive computing system that won against
the best human champions at
the Jeopardy! game in 2011. To do that, IBM Watson had to
understand spoken language,
make sense of massive amount of text, respond correctly to
questions in many categories, as
well as assess its own confidence in responding to such
questions. The kind of
question/answering capabilities that would be very useful, for
example, in assisting a doctor
Artificial Intelligence: Potential Benefits and Ethical
Considerations
PE 571.380 3
9. when trying to come to the correct diagnosis for a patient and to
propose the best therapy.
Watson puts together many AI results and algorithms, from text
and speech understanding, to
reasoning with uncertainty, to optimization.
IBM is not new to tackling daunting challenges and successfully
addressing them. In 1997, the
Deep Blue computer program won against the world chess
champion Garry Kasparov. This was
very iconic, since chess, as I said above, is one of those
activities that we believe requires a
significant amount of intelligence in a human being. Deep Blue
showed that computers could
do better than the best humans when it comes to certain tasks.
3. AI AND COMPUTING POWER
We have to be careful in labelling all this promising progress as
truly “intelligent.” Humans
need intelligence and good intuition in playing chess because
our brain does not have enough
computing power to make sense of a lot of data. In chess, for
example, it is not possible for
our brain to evaluate all possible sequences of moves of us and
10. our opponent in a very short
time. If we could do that, it would be obvious to us what the
best move is. Contrarily to our
brain, computers can rely on a computing power that, according
to Moore’s law, doubles every
about 18 months. Gordon Moore, co-founder of Intel, in 1965
noticed that this was the trend
in putting transistors into a single chip, and to the amazement of
many, this law has been
followed since then in our computers.
This law means that computer processing power doubles every
18, or, seen from another point
of view, every 18 months we can have a much cheaper computer
with the same speed as the
old one. For example, it has been calculated that an IPhone in
1991 would have cost about
$3,6 million. And this is only for its processor, its memory, and
its connectivity. Today’s smart
phones are more powerful than NASA computers that in 1969
sent a man to the moon. This is
how much computing power has increased over the years.
4. AI AND DATA
11. AI is not all about computing power. Intelligent machines can
also rely on huge amounts of
data, to be used to learn how to make better and better
decisions. This data comes from all of
us. Over the years, Facebook users have uploaded more than
250 billion pictures, and every
day they upload about 350 million more. Every second, we
submit 40,000 Google search
queries, which means 3.5 billion per day and 1.2 trillion per
year. As of today, there are 2
billion people connected to internet, which is estimated to get to
5 billion by 2020. And by that
time, also 50 billion “things” will be connected through the
web: from appliances to traffic
lights, from cars to watches.
5. MACHINES VS HUMANS
No matter how much data and computing power is available to
machines, there are tasks that
are still difficult for machines to perform, but that remain very
easy for humans. Machines and
humans are very complementary. A typical example is
understanding what is depicted in an
12. image.
How do we know that an image contains a cat? Because during
our life we have seen many
examples of cats and non-cats, and at some point we got a very
good idea of how a cat should
look like, so much that we don’t have problems recognizing one
even if we have never seen it
before, and even if it is in a strange position.
Machines need humans to provide them with many examples. A
lot of progress has been made
in this, but we are still working hard to improve their accuracy
in labelling pictures or other
perception capabilities
Policy Department C: Citizens' Rights and Constitutional
Affairs
4 PE 571.380
Other tasks that are very easy for humans are physical and
manipulation tasks such as walking,
running, picking up an object no matter its shape and location.
13. Robots can do this only in
restricted environments. But they are still not able to have the
general physical and
manipulation capabilities even of a 6 year old.
6. AI ETHICS AND TRUST
The ability of AI systems to transform vast amounts of complex,
ambiguous information into
insight has the potential to reveal long-held secrets and help
solve some of the world’s most
enduring problems. AI systems can potentially be used to help
discover insights to treat
disease, predict the weather, and manage the global economy. It
is an undeniably powerful
tool. And like all powerful tools, great care must be taken in its
development and deployment.
However, to reap the societal benefits of AI systems, we will
first need to trust it. The right
level of trust will be earned through repeated experience, in the
same way we learn to trust
that an ATM will register a deposit, or that an automobile will
stop when the brake is applied.
Put simply, we trust things that behave as we expect them to.
14. Trust is built upon accountability. As such, the algorithms that
underpin AI systems need to be
as transparent, or at least interpretable, as possible. In other
words, they need to be able to
explain their behaviour in terms that humans can understand —
from how they interpreted
their input to why they recommended a particular output. To do
this, we recommend all AI
systems should include explanation-based collateral systems.
But trust will also require a system of best practices that can
help guide the safe and ethical
management of AI systems including alignment with social
norms and values; algorithmic
responsibility; compliance with existing legislation and policy;
assurance of the integrity of the
data, algorithms and systems; and protection of privacy and
personal information.
One of the primary reasons for including algorithmic
accountability in any AI system is to
manage the potential for bias in the decision-making process.
This is an important and valid
concern among those familiar with AI. Bias can be introduced
15. both in the data sets that are
used to train an AI system, and by the algorithms that process
that data. At IBM, we believe
that the biases of AI systems can not only be managed, but also
that AI systems themselves
can help eliminate many of the biases that already exist in
human decision-making models
today.
AI systems should function according to values that are aligned
to those of humans, so that
they are accepted by our societies and by the environment in
which they are intended to
function. This is essential not just in autonomous systems, but
also in systems based on
human-machine collaboration, since value misalignment could
preclude or impede effective
teamwork. It is not yet clear what values machines should use,
and how to embed these values
into them. Several ethical theories, defined for humans, are
being considered (deontic,
consequentialist, virtue, etc.) as well as the implications of their
use within a machine, in order
to find the best way to define and adapt values from humans to
16. machines.
In industries like healthcare and finance, the relevant
professional ethical principles are
explicitly encoded and practiced by professionals in the field
already. In AI systems designed
to help professionals in these domains, these best practices and
principles could form the core
of the ethics module for such systems. Ethics modules, however,
should be constantly adapted
to reflect humans’ best practices in their everyday profession.
We envision a future in which every AI system will need to
have its own ethics module to allow
for a fruitful interaction and collaboration with humans in the
environments in which it is used.
This could be achieved by developing an ethics API that can be
adapted to specific professions
and real-life scenarios. It would provide the main principles and
values the AI systems should
base its behaviour on, as well as the capability to dynamically
adapt them over time to tune
them to the real situations that are encountered in that
profession or environment. Such a
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rigorous approach could offer sufficient value alignment
without compromising the full problem-
solving potential of artificial intelligence.
7. IBM AND AI
IBM has been researching, developing and investing in AI
technology for more than 50 years.
In 1997, IBM Deep Blue bested then world chess champion
Garry Kasparov, showing that
innovative AI algorithms and computational power can play a
complex game at super-human
levels. In 2011, IBM Watson won at Jeopardy! against the best
human players, showing that
AI can also perform very well in natural language understanding
and reasoning with
uncertainty.
These are just the tip of the iceberg compared to what IBM has
been achieving over the years
18. in the field of AI. We have been transforming the original
Watson program into a fully fledged
platform and we have exploited it to successfully apply AI to
many industrial sectors, including
healthcare, finance, commerce, education, security, and the
Internet of Things. The whole
company is deeply committed to AI, since we believe strongly
in its potential to benefit society
while transforming our personal and professional lives.
As mentioned above IBM prefer the term “augmented
intelligence” and therefore focuses on
practical applications of AI capabilities that assist people in
performing well-defined tasks, by
exploiting a wide range of AI-based services. With this aim in
mind, IBM researchers, in tight
collaboration with several universities, produce continuous
innovations in area such as machine
learning, knowledge modelling, reasoning and decision
technologies, human interface,
automated perception, data assurance, and computing
infrastructures. Most of these research
efforts cannot be achieved by AI researchers alone.
Collaboration with experts in multiple
19. disciplines — such as psychology, philosophy, sociology, art,
regulation, and law — is crucial.
We believe that new companies, new jobs, and entirely new
markets will be built on the
shoulders of this powerful technology. Moreover, AI systems
will improve access to critical
services for underserved populations. Overall, we anticipate
widespread improvements in the
quality of life.
8. IBM AND AI ETHICS
In order to be fully accepted into society, AI systems need to
have significant social capabilities,
because their presence in our lives has a profound impact on our
emotions and on our decision
making capabilities. Also, AI systems need to understand how
to learn and comply with specific
behavioural principles for aligning with human values. To take
full advantage of the potential
societal benefits of AI, we will need to trust AI, whether we
speak of autonomous systems or,
as is the focus of IBM, of human/machines partnerships. Trust
will be earned over time and via
20. natural interaction modalities. Trust will also require a system
of best practices that can guide
the safe and ethical development and management of AI, a
carefully thought alignment with
social norms and values, algorithmic accountability, compliance
with existing legislation and
policy, and protection of privacy and personal information.
IBM is in the process of developing this system internally, with
our collaborators, and also with
our competitors. More precisely, IBM is engaged in several
efforts – both internally and
externally – to advance our understanding and effecting the
ethical development of artificial
intelligence. They include:
to discuss, advise and
guide the ethical development and deployment of AI systems.
-wide educational curriculum on the ethical
development of cognitive
technologies.
Policy Department C: Citizens' Rights and Constitutional
Affairs
21. 6 PE 571.380
nitive Ethics and Society
research program, a multi-
disciplinary research program for the ongoing exploration of
responsible development of AI
systems aligned with our personal and professional values.
-industry, government and scientific
initiatives and events around
AI and ethics, such as the recently launched Partnership on AI,
the White House Office of
Science and Technology Policy AI workshops, the International
Joint Conference on Artificial
Intelligence, and the conference of the Association for the
Advancement of Artificial
Intelligence.
-hosted engagements with a robust
ecosystem of academics,
researchers, policymakers, NGOs and business leaders on the
ethical implications of AI.
9. IBM AND EUROPE
IBM is an international company with a strong history and
presence in Europe:
22. The IBM Zurich research lab is supported by a multicultural and
interdisciplinary team of a few
hundred people from about 45 nationalities who work in diverse
areas such as chip
technologies, nanotechnology, fibre optics, supercomputing,
data storage, security and privacy,
risk and compliance, business optimization and transformation,
and server systems. The Zurich
lab is involved in many joint projects with universities
throughout Europe, in research programs
established by the European Union and the Swiss government,
and in cooperation agreements
with research institutes of industrial partners.
The recently opened IBM Watson IoT Headquarters in Munich
is applying Watson to the Internet
of Things and helping many companies (from automotive,
insurance, electronics, banks, and
industrial sectors) to transform their business by extending the
power of AI to the billions of
connected devices, sensors and systems that comprise the IoT.
The recently announced IBM Watson Health European Centre of
Excellence, that will be placed
23. within the Human Technopole Lab in Milan, is supporting the
government of Italy’s initiative to
establish an international hub for the advancement of genomics,
big data, aging, and nutrition.
The Centre is expected to provide access to resources and
technology designed to help
accelerate research into new treatment options, promote
personalized medicine, and
encourage discoveries aimed at improving overall public health
management while advancing
sustainable health systems.
10. AI AND POLICIES
AI technology is changing so rapidly, and has so many
applications to the real world, that it is
difficult for any government or regulatory agency to keep up
with them and to meaningfully
and timely guide the deployment of AI systems. However, some
issues like data privacy and
ownership have been considered in the EU, as well as algorithm
transparency and
accountability.
An example is the recently released General Data Protection
24. Regulation, that will take effect as
law across the EU in 2018 and will restrict automated individual
decision-making (that is,
algorithms that make decisions based on user-level predictors)
which "significantly affect"
users. The law will effectively create a so-called "right to
explanation," whereby a user can ask
for an explanation of an algorithmic decision that was made
about them. Another example is
the very recently released USA federal policy on automated
vehicles, that is already in effect.
The main point of all these policies is to make sure that society
can take full advantage of the
capabilities of AI systems while minimizing the possible
undesired consequences on people.
Safety is very important, as well as fairness, inclusiveness, and
equality. These and other
properties should be assured of AI systems, or at least we
should be able to assess the limits
of an intelligent machine, so to not overtrust it. It is therefore
very important the policies and
regulations help society in using AI for the best of all.
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Ethical issues, including safety constraints, are essential in this
respect, since an AI system
that behaves according to our ethical principles and moral
values would allow humans to
interact with it in a safe and meaningful way.
It is clear that a lack of regulations would open the way to
unsafe developments. However, also
excessive regulations would have a cost to society, since they
would not allow us to take
advantage of all the potential benefits that AI can bring, such as
saving lives, curing diseases,
and solving planetary problems.
IBM is eager to work with governments, media, other
companies, regulatory agencies, and
industry sectors in a meaningful discussion on ethical issues of
AI, with the aim of clearly
identifying the potential and limits of AI, and carefully
26. understanding how to harness it for the
best of all.
Policy Department C: Citizens' Rights and Constitutional
Affairs