Artificial Intelligence: The Promise, the Myth, and a Dose of RealityDagmar Monett
Keynote at the 33. Bremer Universitäts-Gespräche Data Science - Wunderwelt oder alter Wein in neuen Schläuchen (engl. Data science - Wonderworld or old wine in new bottles), October 7th, 2021, Universität Bremen, Germany.
Explainable AI : Machine Learning for Humans - AI Paris2018Domitille Leriche
Interpretability is the Success Key Factor when opting for Artificial Intelligence. Bleckwen, a French fintech specialized in Artificial Intelligence for fraud prevention, presents how explanable AI can be applied to its models.
www.bleckwen.ai
True Artificial Intelligence Will Change Everything Russia.AI
We are delighted to republish slides presented by professor Jürgen Schmidhuber at GTC Conference in Amsterdam.
The presentation covers evolution of deep learning since efforts of A. G. Ivakhnenko till the most recent achievement in curiosity-driven skills acquisition.
Slides contains a wealth of useful information including references and links.
ARTIFICIAL INTELLIGENCE AND ITS IMPACT ON THE FOURTH INDUSTRIAL REVOLUTION: A...ijaia
Artificial Intelligence may revolutionize everything during the so-called fourth industrial revolution, which carries several emerging technologies and could progress without precedents in human history due to its speed and scope. Government, academia, industry, and civil society show interest in understanding the multidimensional impact of the emerging industrial revolution; however, its development is hard to predict. Experts consider emerging technologies could bring tremendous benefits to humanity; at the same time, they could pose an existential risk. This paper reviews the development and trends in AI, as well as the benefits, risks, and strategies in the field. During the course of the emerging industrial revolution, the common good may be achieved in a collaborative environment of shared interests and the hardest work will be the implementation and monitoring of projects at a global scale.
Artificial Intelligence: The Promise, the Myth, and a Dose of RealityDagmar Monett
Keynote at the 33. Bremer Universitäts-Gespräche Data Science - Wunderwelt oder alter Wein in neuen Schläuchen (engl. Data science - Wonderworld or old wine in new bottles), October 7th, 2021, Universität Bremen, Germany.
Explainable AI : Machine Learning for Humans - AI Paris2018Domitille Leriche
Interpretability is the Success Key Factor when opting for Artificial Intelligence. Bleckwen, a French fintech specialized in Artificial Intelligence for fraud prevention, presents how explanable AI can be applied to its models.
www.bleckwen.ai
True Artificial Intelligence Will Change Everything Russia.AI
We are delighted to republish slides presented by professor Jürgen Schmidhuber at GTC Conference in Amsterdam.
The presentation covers evolution of deep learning since efforts of A. G. Ivakhnenko till the most recent achievement in curiosity-driven skills acquisition.
Slides contains a wealth of useful information including references and links.
ARTIFICIAL INTELLIGENCE AND ITS IMPACT ON THE FOURTH INDUSTRIAL REVOLUTION: A...ijaia
Artificial Intelligence may revolutionize everything during the so-called fourth industrial revolution, which carries several emerging technologies and could progress without precedents in human history due to its speed and scope. Government, academia, industry, and civil society show interest in understanding the multidimensional impact of the emerging industrial revolution; however, its development is hard to predict. Experts consider emerging technologies could bring tremendous benefits to humanity; at the same time, they could pose an existential risk. This paper reviews the development and trends in AI, as well as the benefits, risks, and strategies in the field. During the course of the emerging industrial revolution, the common good may be achieved in a collaborative environment of shared interests and the hardest work will be the implementation and monitoring of projects at a global scale.
History of AI, Current Trends, Prospective TrajectoriesGiovanni Sileno
Talk given at the 2nd Winter Academy on Artificial Intelligence and International Law of the Asser Institute. The birth of AI: Dartmouth workshop. The biggest AI waves: classic symbolic AI (reasoning, knowledge systems, problem-solving), machine learning (induction). Current problems: explainability, trustworthyness, impact and transformation on society and people, the rise of artificially dumber systems.
I made this presentation in my 7th semester of B.Tech as per academic curriculum.
Took help from several videos from youtube and studied some IBM publications.
Cognitive Era is at the dawn. It does not make machines intelligent but instead it allows them to develop cognisance and learn by themselves as we humans do.
I am fascinated and looking forward to contribute my existence in this great thought of almighty came into human mind.
Guys! You could get a nice introduction from this presentation and explain it to others and even it could be used for your academic homework.
Goodluck! GODSPEED!
This is the second edition of Machine Learning and Language. If it seems to be almost identical to the initial version, which focused on a different area of science, that's the point...
The generation of digital content has undergone a great increase in recent years due to the
development of new technologies that allow the creation of content quickly and easily. A further step in this
evolution is the generation of contents by automatic systems without human intervention. Thus, for decadesit has
been developing models for the Natural Language Generation (NLG) that allow the transformation of content to
the form of narratives. At present, there are several systems that enable the generation in text format. In this
paper we present the Narrative system, which allows the generation of text narratives from different sources,
and which are indistinguishable for user from those made by a human being.
Defin
ing artificial intelligence is no easy matter. Since the mid
-
20th century when it
was first
recognized
as a specific field of research, AI has always been envisioned as
an evolving boundary, rather than a settled research field. Fundamentally, it refers
to
a programme whose ambitious objective is to understand and reproduce human
cognition; creating cognitive processes comparable to those found in human beings.
Therefore, we are naturally dealing with a wide scope here, both in terms of the
technical proced
ures that can be employed and the various disciplines that can be
called upon: mathematics, information technology, cognitive sciences, etc. There is
a great variety of approaches when it comes to AI: ontological, reinforcement
learning, adversarial learni
ng and neural networks, to name just a few. Most of them
have been known for decades and many of the algorithms used today were
developed in the ’60s and ’70s.
Since the 1956 Dartmouth conference, artificial intelligence has alternated between
periods of
great enthusiasm and disillusionment, impressive progress and frustrating
failures. Yet, it has relentlessly pushed back the limits of what was only thought to
be achievable by human beings. Along the way, AI research has achieved significant
successes: o
utperforming human beings in complex games (chess, Go),
understanding natural language, etc. It has also played a critical role in the history
of mathematics and information technology. Consider how many softwares that we
now take for granted once represen
ted a major breakthrough in AI: chess game
apps, online translation programmes, etc
Deep Learning Explained: The future of Artificial Intelligence and Smart Netw...Melanie Swan
This talk provides an overview of an important emerging artificial intelligence technology, deep learning neural networks. Deep learning is a branch of computer science focused on machine learning algorithms that model and make predictions about data. A key distinction is that deep learning is not merely a software program, but a new class of information technology that is changing the concept of the modern technology project by replacing hard-coded software with a capacity to learn and execute tasks. In the future, deep learning smart networks might comprise a global computational infrastructure tackling real-time data science problems such as global health monitoring, energy storage and transmission, and financial risk assessment.
Artificial Intelligence Future |Impact Of Artificial Intelligence On SocietyYashShah445
the content has artificial intelligence Artificial intelligence is helping farmers, doctors and rescue workers improve their positive impact on society. ... While fear of the negative consequences remain, AI is proving it can bring about enormous societal benefits.
Inventing Things tTht Matter to the World; Inventing Things tht that Matter to the WOrld; Inventing Things That Matter to the WOrld; Inventing Things That Matter to the World (correct)
Driven by the rapid progress in Artificial Intelligence (AI) research, intelligent machines are gaining the ability to learn, improve and make calculated decisions in ways that will enable them to perform tasks previously thought to rely solely on human experience, creativity, and ingenuity. As a result, we will in the near future see large parts of our lives influenced by AI.
AI innovation will also be central to the achievement of the United Nations' Sustainable Development Goals (SDGs) and will help solving humanity's grand challenges by capitalizing on the unprecedented quantities of data now being generated on sentiment behavior, human health, commerce, communications, migration and more.
With large parts of our lives being influenced by AI, it is critical that government, industry, academia and civil society work together to evaluate the opportunities presented by AI, ensuring that AI benefits all of humanity. Responding to this critical issue, ITU and the XPRIZE Foundation organized AI for Good Global Summit in Geneva, 7-9 June, 2017 in partnership with a number of UN sister agencies. The Summit aimed to accelerate and advance the development and democratization of AI solutions that can address specific global challenges related to poverty, hunger, health, education, the environment, and others.
The Summit provided a neutral platform for government officials, UN agencies, NGO's, industry leaders, and AI experts to discuss the ethical, technical, societal and policy issues related to AI, offer reccommendations and guidance, and promote international dialogue and cooperation in support of AI innovation.
Please visit the AI for Good Global Summit page for more resources: https://www.itu.int/en/ITU-T/AI/Pages/201706-default.aspx
If you would like to speak, partner or sponsor the 2018 edition of the summit, please contact: ai@itu.int
In this unit, students will explore contemporary scientific media and art forms to understand what the advent of artificial intelligence (AI) might mean for the future of humankind.
History of AI, Current Trends, Prospective TrajectoriesGiovanni Sileno
Talk given at the 2nd Winter Academy on Artificial Intelligence and International Law of the Asser Institute. The birth of AI: Dartmouth workshop. The biggest AI waves: classic symbolic AI (reasoning, knowledge systems, problem-solving), machine learning (induction). Current problems: explainability, trustworthyness, impact and transformation on society and people, the rise of artificially dumber systems.
I made this presentation in my 7th semester of B.Tech as per academic curriculum.
Took help from several videos from youtube and studied some IBM publications.
Cognitive Era is at the dawn. It does not make machines intelligent but instead it allows them to develop cognisance and learn by themselves as we humans do.
I am fascinated and looking forward to contribute my existence in this great thought of almighty came into human mind.
Guys! You could get a nice introduction from this presentation and explain it to others and even it could be used for your academic homework.
Goodluck! GODSPEED!
This is the second edition of Machine Learning and Language. If it seems to be almost identical to the initial version, which focused on a different area of science, that's the point...
The generation of digital content has undergone a great increase in recent years due to the
development of new technologies that allow the creation of content quickly and easily. A further step in this
evolution is the generation of contents by automatic systems without human intervention. Thus, for decadesit has
been developing models for the Natural Language Generation (NLG) that allow the transformation of content to
the form of narratives. At present, there are several systems that enable the generation in text format. In this
paper we present the Narrative system, which allows the generation of text narratives from different sources,
and which are indistinguishable for user from those made by a human being.
Defin
ing artificial intelligence is no easy matter. Since the mid
-
20th century when it
was first
recognized
as a specific field of research, AI has always been envisioned as
an evolving boundary, rather than a settled research field. Fundamentally, it refers
to
a programme whose ambitious objective is to understand and reproduce human
cognition; creating cognitive processes comparable to those found in human beings.
Therefore, we are naturally dealing with a wide scope here, both in terms of the
technical proced
ures that can be employed and the various disciplines that can be
called upon: mathematics, information technology, cognitive sciences, etc. There is
a great variety of approaches when it comes to AI: ontological, reinforcement
learning, adversarial learni
ng and neural networks, to name just a few. Most of them
have been known for decades and many of the algorithms used today were
developed in the ’60s and ’70s.
Since the 1956 Dartmouth conference, artificial intelligence has alternated between
periods of
great enthusiasm and disillusionment, impressive progress and frustrating
failures. Yet, it has relentlessly pushed back the limits of what was only thought to
be achievable by human beings. Along the way, AI research has achieved significant
successes: o
utperforming human beings in complex games (chess, Go),
understanding natural language, etc. It has also played a critical role in the history
of mathematics and information technology. Consider how many softwares that we
now take for granted once represen
ted a major breakthrough in AI: chess game
apps, online translation programmes, etc
Deep Learning Explained: The future of Artificial Intelligence and Smart Netw...Melanie Swan
This talk provides an overview of an important emerging artificial intelligence technology, deep learning neural networks. Deep learning is a branch of computer science focused on machine learning algorithms that model and make predictions about data. A key distinction is that deep learning is not merely a software program, but a new class of information technology that is changing the concept of the modern technology project by replacing hard-coded software with a capacity to learn and execute tasks. In the future, deep learning smart networks might comprise a global computational infrastructure tackling real-time data science problems such as global health monitoring, energy storage and transmission, and financial risk assessment.
Artificial Intelligence Future |Impact Of Artificial Intelligence On SocietyYashShah445
the content has artificial intelligence Artificial intelligence is helping farmers, doctors and rescue workers improve their positive impact on society. ... While fear of the negative consequences remain, AI is proving it can bring about enormous societal benefits.
Inventing Things tTht Matter to the World; Inventing Things tht that Matter to the WOrld; Inventing Things That Matter to the WOrld; Inventing Things That Matter to the World (correct)
Driven by the rapid progress in Artificial Intelligence (AI) research, intelligent machines are gaining the ability to learn, improve and make calculated decisions in ways that will enable them to perform tasks previously thought to rely solely on human experience, creativity, and ingenuity. As a result, we will in the near future see large parts of our lives influenced by AI.
AI innovation will also be central to the achievement of the United Nations' Sustainable Development Goals (SDGs) and will help solving humanity's grand challenges by capitalizing on the unprecedented quantities of data now being generated on sentiment behavior, human health, commerce, communications, migration and more.
With large parts of our lives being influenced by AI, it is critical that government, industry, academia and civil society work together to evaluate the opportunities presented by AI, ensuring that AI benefits all of humanity. Responding to this critical issue, ITU and the XPRIZE Foundation organized AI for Good Global Summit in Geneva, 7-9 June, 2017 in partnership with a number of UN sister agencies. The Summit aimed to accelerate and advance the development and democratization of AI solutions that can address specific global challenges related to poverty, hunger, health, education, the environment, and others.
The Summit provided a neutral platform for government officials, UN agencies, NGO's, industry leaders, and AI experts to discuss the ethical, technical, societal and policy issues related to AI, offer reccommendations and guidance, and promote international dialogue and cooperation in support of AI innovation.
Please visit the AI for Good Global Summit page for more resources: https://www.itu.int/en/ITU-T/AI/Pages/201706-default.aspx
If you would like to speak, partner or sponsor the 2018 edition of the summit, please contact: ai@itu.int
In this unit, students will explore contemporary scientific media and art forms to understand what the advent of artificial intelligence (AI) might mean for the future of humankind.
It is technology and a branch of computer science that studies and develops intelligent machines and software. Major AI researchers and textbooks define the field as "the study and design of intelligent agents", where an intelligent agent is a system that perceives its environment and takes actions that maximize its chances of success. John McCarthy, who coined the term in 1955, defines it as "The science and engineering of making intelligent machines".
Presentation given at the HEA Social Sciences learning and teaching summit 'Exploring the implications of ‘the era of big data’ for learning and teaching'.
A blog post outlining the issues discussed at the summit is available via: http://bit.ly/1lCBUIB
Slides from a series of talks for the IET's IoT India Congress and some associated events - SRM Chennai, PES Bengaluru, Srishti Bengaluru. I used different subsets of the slides in each talk - this is the whole deck.
Introduction to PhilosophyFall 2017Essay Exam 2Due Date Tues.docxnormanibarber20063
Introduction to Philosophy
Fall 2017
Essay Exam 2
Due Date Tuesday November 7
1000 words
Essays in Unit 2
Gilbert Ryle, “Descartes’s Myth”
John Searle, “Can Computers Think?”
David Chalmers, “The Hard Problem of Consciousness”
Here are some general directions before you read the questions. You only answer 1 prompt, but in each question you are asked to agree or disagree with the position in the reading that starts the question. In doing so you are giving reasons to agree or disagree and that must be more than simply repeating what is in the exposition.
The completed essay must be 1000 words; your discussion should be roughly 800 for the expository part and 200 words for critical assessment part. I emphasize that this separate word count is rough, so the critical assessment could be longer. But keep in mind that there must be content in any critical assessment. If it is just filler beyond 200 words, then that will not improve your essay.
Choose 1 of the following
1. Discuss Ryle’s criticism of Descartes’s mind-body dualism and how Ryle supports his criticism. Discuss your critical assessment of Ryle (i.e., reasons for agreeing or disagreeing).
2. Discuss Searle’s position on strong AI and how he defends it. Discuss your critical assessment of Searle (i.e., reasons for agreeing or disagreeing).
3. Discuss Chalmers position on consciousness and how he defends it. Discuss your critical assessment of Chalmers (i.e., reasons for agreeing or disagreeing).
Chapter 28 TECHNOLOGY AND SOCIALITY IN THE NEW MILLENNIUM: CURRENT CHALLENGES FOR THE HUMAN SERVICE GENERALIST
EUGENE M. DeROBERTIS AND ROBERT SALDARINI
Human services can be characterized as a broad social movement designed to counterbalance the emphasis on rugged individualism in American culture (Cimmino, 1999, p. 13). Thus, part and parcel of the human service orientation toward helping others is the notion that human service generalists place “a portion of responsibility on society for creating conditions that reduce opportunities for people to be successful by perpetuating social problems” (p. 14). Among the myriad challenges that human service generalists address in their work are problems involving the development of the self within the social context (p. 10). As is well known, Maslow’s (1968) hierarchy of needs speaks to the importance of interpersonal relations in self-development with his articulation of needs for love and belongingness, esteem, and self-actualization. Hansell’s motivation theory also addresses the need for a co-constitution of the self by noting that humans need intimacy, closeness, belonging, self-identity, and social roles (Schmolling and Burger, 1989). Accordingly, it is in the interest of competent service delivery for human service workers to be aware of burgeoning trends in the interpersonal dimension of our lives that pose new challenges to a healthy social climate and optimal self-development. Such trends can be found in the ever-increasing rel.
Introduction to Human Computer Interface (HCI)Edneil Jocusol
This topic is based on the article published by Whitworth and Ahmad in Interaction-Design. It covers topics such as Evolution of Computing Systems, Computing Level (in terms of Mechanical, Informational, Psychological, and Socio-Technical Systems), Human Physiological Needs, and Design Level Combination.
The study adds a new viewpoint to the scaling deep context and presents a concrete starting point of the scaling deep strategy by linking it with the creation of common ground.
Let's Get Digital, Digital 🎶: Using Digital Humanities to Embrace Data FuzzinessLeah Henrickson
Presented as a virtual guest lecture at Iona College (12 April 2022). Uses the concept of data fuzziness to argue that we should embrace complexity in our research, showing how we might apply digital humanities methods to do so.
Note that some slides are animated and do not present accurately on SlideShare.
Game-based Learning as a Suitable Approach for Teaching Digital Ethical Think...Dagmar Monett
Slides of the talk at the 15th annual International Technology, Education and Development Conference, INTED 2021 (a virtual conference), March 8th-9th, 2021.
University-Industry Collaboration's Next Level: A Comparative Study as Basis ...Dagmar Monett
Slides of the talk at the 15th annual International Technology, Education and Development Conference, INTED 2021 (virtual conference), March 8th-9th, 2021.
The Changing Landscape of Digital Technologies for Learning Dagmar Monett
Slides of the talk at the 20th European Conference on e-Learning, ECEL 2021 (virtual conference), Academic Conferences International Ltd., October 29th, 2021.
Will Robots Take all the Jobs? Not yet.Dagmar Monett
Slides of the talk at the 3rd European Conference on the Impact of Artificial Intelligence and Robotics, ECIAIR 2021 (a virtual conference), November 18th, 2021.
Erfahrungen aus Projektbasiertes Lernen im Informatik Studium - The Missing p...Dagmar Monett
Talk at the Workshop "Hochschulübergreifender Praxisaustausch: Entrepreneurship in der Lehre", organized by BENHU, The Berlin Entrepreneurship Network of Universities and Businesses, at the Alexander von Humboldt Institute for Internet and Society, Berlin, 25 January 2018.
Teaching Students Collaborative Requirements Engineering. Case Study Red:WireDagmar Monett
Slides of the talk at the 18th International Conference on Parallel, Distributed Systems and Software Engineering, ICPDSSE 2016, Rome, Italy, May 02-03, 2016.
E-Learning Adoption in a Higher Education Setting: An Empirical StudyDagmar Monett
Slides of the talk at the Multidisciplinary Academic Conference on Education, Teaching and Learning 2015, MAC-ETL 2015, Prague, Czech Republic, 4-6 December 2015.
Evolving Lesson Plans to Assist Educators: From Paper-Based to Adaptive Lesso...Dagmar Monett
Slides of the talk at the Multidisciplinary Academic Conference on Education, Teaching and Learning 2015, MAC-ETL 2015, Prague, Czech Republic, 4-6 December 2015.
Methods for Validating and Testing Software Requirements (lecture slides)Dagmar Monett
Online lecture at the School of Computer Science, University of Hertfordshire, Hatfield, UK, as part of the 11th Europe Week from 2nd to 6th March 2015.
Modelling Software Requirements: Important diagrams and templates (lecture sl...Dagmar Monett
Online lecture at the School of Computer Science, University of Hertfordshire, Hatfield, UK, as part of the 11th Europe Week from 2nd to 6th March 2015.
Requirements Engineering Methods for Documenting Requirements (lecture slides)Dagmar Monett
Online lecture at the School of Computer Science, University of Hertfordshire, Hatfield, UK, as part of the 11th Europe Week from 2nd to 6th March 2015.
Requirements Engineering Techniques for Eliciting Requirements (lecture slides)Dagmar Monett
Online lecture at the School of Computer Science, University of Hertfordshire, Hatfield, UK, as part of the 11th Europe Week from 2nd to 6th March 2015.
A Structured Approach to Requirements Analysis (lecture slides)Dagmar Monett
Online lecture at the School of Computer Science, University of Hertfordshire, Hatfield, UK, as part of the 11th Europe Week from 2nd to 6th March 2015.
Walking the path from the MOOC to my classroom: My collection of methods and ...Dagmar Monett
These are the slides I prepared as part of a peer assessed assignment when attending the Coursera MOOC "Foundations of Teaching for Learning 1: Introduction" (see https://www.coursera.org/course/teach1 for more).
I hope other educators can benefit from the ideas I share here.
Understanding the Cuban Blogosphere: Retrospective and Perspectives based on ...Dagmar Monett
Invited talk at the Interdisciplinary Workshop “UNDER CONSTRUCTION. Analyzing Postcolonial Weblogs with Literary and Computational Methods”, University of Heidelberg, Germany
Genetic Algorithms and Ant Colony Optimisation (lecture slides)Dagmar Monett
Online lecture at the School of Computer Science, University of Hertfordshire, Hatfield, UK, as part of the 10th Europe Week from 3rd to 7th March 2014.
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
Safalta Digital marketing institute in Noida, provide complete applications that encompass a huge range of virtual advertising and marketing additives, which includes search engine optimization, virtual communication advertising, pay-per-click on marketing, content material advertising, internet analytics, and greater. These university courses are designed for students who possess a comprehensive understanding of virtual marketing strategies and attributes.Safalta Digital Marketing Institute in Noida is a first choice for young individuals or students who are looking to start their careers in the field of digital advertising. The institute gives specialized courses designed and certification.
for beginners, providing thorough training in areas such as SEO, digital communication marketing, and PPC training in Noida. After finishing the program, students receive the certifications recognised by top different universitie, setting a strong foundation for a successful career in digital marketing.
Normal Labour/ Stages of Labour/ Mechanism of LabourWasim Ak
Normal labor is also termed spontaneous labor, defined as the natural physiological process through which the fetus, placenta, and membranes are expelled from the uterus through the birth canal at term (37 to 42 weeks
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...Levi Shapiro
Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
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!
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.
Exploiting Artificial Intelligence for Empowering Researchers and Faculty, In...Dr. Vinod Kumar Kanvaria
Exploiting Artificial Intelligence for Empowering Researchers and Faculty,
International FDP on Fundamentals of Research in Social Sciences
at Integral University, Lucknow, 06.06.2024
By Dr. Vinod Kumar Kanvaria
1.4 modern child centered education - mahatma gandhi-2.pptx
Coming to terms with intelligence in machines
1. My slides are available for you at:
Coming to terms with
intelligence in machines
Prof. Dr. Dagmar Monett
Computer Science Dept., Berlin School of Economics and Law
dagmar.monett-diaz@hwr-berlin.de
https://www.slideshare.net/dmonett/monett-2021-atd
Keynote, Nov. 16, 2021
5. 5
@dmonett
“The long-term dream of AI is to
build machines that have the
that people
have—to build machines that are
self-aware, conscious and
autonomous in the same way
that people like you and me are.”
Wooldridge, M. (2020). The Road to Conscious Machines: The Story of AI. UK: Pelican Random House.
6. 6
@dmonett
“Intelligence measures an agent’s ability
to achieve goals in a wide range of
environments.” (Legg & Hutter, 2007)
Fogel, D. B. (2006). Defining Artificial Intelligence. In Evolutionary Computation: Toward a New Philosophy of Machine Intelligence.
Third Edition, pp. 1-32. The Institute of Electrical and Electronics Engineers, Inc., IEEE Press.
Legg, S. and Hutter, M. (2007). Universal Intelligence: A Definition of Machine Intelligence. Minds and Machines, 17(4):391-444,
Springer.
McCarthy, J. (2007). What is Artificial Intelligence? Computer Science Department, School of Engineering, Stanford University.
Wang, P. (2008). What Do You Mean by "AI"? In P. Wang, B. Goertzel, and S. Franklin (eds.), Artificial General Intelligence 2008,
Proceedings of the First AGI Conference, Frontiers in Artificial Intelligence and Applications, 171:362-373. IOS Press Amsterdam,
The Netherlands.
“[Artificial Intelligence is] the science and
engineering of making intelligent
machines. ... It is related to the similar task
of using computers to understand human
intelligence.” (McCarthy, 2007)
“Intelligence is] the capability of a system
to adapt its behavior to meet its goals in a
range of environments.” (Fogel, 2006)
Four examples of AI definitions
“The essence of intelligence is the
principle of adapting to the environment
while working with insufficient
knowledge and resources.” (Wang, 2008)
8. 8
@dmonett
“
, the one
“available through
the newspapers,
books and films.”
Collins, H. (2018). Artifictional Intelligence: Against Humanity’s Surrender to Computers. Cambridge, UK: Polity Press.
9. 9
@dmonett
“If you rely on movies and science
fiction (and even some popular non-
fiction) for your view of AI, you will
be afraid of AI becoming conscious,
turning malevolent, and trying to
enslave or kill us all. But given
,
this is not what most people in the AI
community worry about.”
Mitchell, M. (2019). Artificial Intelligence: A Guide for Thinking Humans. UK: Pelican Random House.
10. 10
@dmonett
“Neither deep learning
nor other forms of
second-wave AI, nor any
proposals yet advanced
for third-wave,
.”
Smith, B. C. (2019). The Promise of Artificial Intelligence: Reckoning and Judgment. Cambridge, MA: The MIT Press.
11. 11
@dmonett
“The myth is not that true AI is
possible. As to that, the future of AI
is a scientific unknown.
–that we have
already embarked on the path that
will lead to human-level AI, and then
superintelligence. We have not.”
Larson, E. J. (2021). The Myth of Artificial Intelligence: Why computers can’t think the way we do. Cambridge, MA: Berlknap,
Harvard University Press.
12. 12
@dmonett
“The reality of AI for
the foreseeable
future
to the
grand dream.”
Wooldridge, M. (2020). The Road to Conscious Machines: The Story of AI. UK: Pelican Random House.
14. 14
@dmonett
No consensus
Journal editors (1921). Intelligence and Its Measurement: A Symposium. Journal of Educational Psychology, Vol 12(3), 123-147.
Detterman, D. K. (1986). Qualitative Integration: The Last Word? In R. J. Sternberg and D. K. Detterman (eds.), What is intelligence?
Contemporary Viewpoints on its Nature and Definition, pp. 163-166. Norwood, NJ: Ablex.
Chollet, F. (2019). The Measure of Intelligence. arXiv:1911.01547 [cs.AI].
“There is very great disagreement concerning the concept of
intelligence.” (Journal editors 1921)
“[A] substantial disagreement on a single definition still abounds.”
(Detterman 1986)
“It is a testimony to the immaturity of our field that the question of
what we mean when we talk about intelligence still doesn’t have a
satisfying answer.” (Chollet 2019)
15. 15
@dmonett
“The lack of specificity allows journalists, entrepreneurs, and
marketing departments to say virtually anything they want.”
(Lipton, 2018)
“[T]he public knowledge and understanding on AI [...] is
suffering from a lack of transparency as to capabilities and
thus impacts of AI.” (Nemitz, 2018)
“[A] lack of clarity in terms of definitions and objectives seems
to have plagued the [AI] field right back to its origins in the
1950s. This makes tracing [its] evolution . . . a difficult task.”
(AI in the UK, 2018, p. 156)
No consensus and its consequences
http://approximatelycorrect.com/2018/06/05/ai-ml-ai-swirling-nomenclature-slurried-thought/
http://dx.doi.org/10.1098/rsta.2018.0089
https://publications.parliament.uk/pa/ld201719/ldselect/ldai/100/100.pdf
18. 18
@dmonett
5 (14) educational psychologists define intelligence
[ is …]
… the power of good responses from the point of view
of truth or facts; (Thorndike, 1921)
… the ability to carry on abstract thinking; (Terman , 1921)
… having learned or ability to learn to adjust oneself to
the environment; (Colvin , 1921)
… the capacity for knowledge; (Henmon, 1921)
… the capacity to acquire capacity. (Woodrow, 1921)
As referred to in Lanz, P. (2000). The Concept of Intelligence in Psychology and Philosophy. In Cruse, H., Dean, J., and Ritter, H. (eds.)
Prerational Intelligence: Adaptive Behavior and Intelligent Systems Without Symbols and Logic, Vol. 1, 19-30, Springer.
19. 19
@dmonett
14
Educational Psychology
USA, Europe
Prediction of behavior
14
Only definitions of human
intelligence
25
Diverse Psychologies
(educational, cognitive,
behavioral, social, cross-
cultural, etc.)
USA, Europe
Understanding of behavior
25
Mostly definitions of human
intelligence
Participants
Primary
affiliation
Countries
Focus
Definitions
Type of
definitions
Symposium Symposium
1921 1986
Defining (A)I: A comparison
20. 20
@dmonett
16 (25) leading psychologists define intelligence
[ is] an elusive concept (Estes, 1986); an illusory unified capacity
(Horn, 1986); a cognitive proficiency (Glaser, 1986); a polymorphous set of qualities
elusive to define, explain, and measure (Brown, 1986); a pluralistic (Anastasi, 1986),
context-dependent concept (Anastasi, 1986; Sternberg, 1986); a medley of important
events, a mixture of different things (Horn, 1986); a finite set of independent
abilities operating as a complex system (Detterman, 1986); the sum total of all
cognitive processes (Das, 1986); a collective term for demonstrated, mental
individual differences (Hunt, 1986); mental self-government (Sternberg, 1986); a
judgement or attribution that people do, and not a quality residing in the
individual (Goodnow, 1986); a hypothetical (Zigler, 1986), culture-bound, ethnocentric,
and excessively narrow (Berry, 1986), societal construct, a concept in the mind of
a society at large (Carroll, 1986).
A summary of some of the definitions that are included in Sternberg, R. J. and Detterman, D. K. (1986). What is intelligence?
Contemporary Viewpoints on its Nature and Definition. Norwood, NJ: Ablex.
21. 21
@dmonett
AGISI survey
14
Educational Psychology
USA, Europe
Prediction of behavior
14
Only definitions of human
intelligence
25
Diverse Psychologies
(educational, cognitive,
behavioral, social, cross-
cultural, etc.)
USA, Europe
Understanding of behavior
25
Mostly definitions of human
intelligence
567 (academia: 79.7%)
Computer Science,
Engineering, Biology,
Neurosciences, Philosophy,
Cognitive Science, etc.
57+ countries
Computation of behavior
343 (+ 4128 opinions)
Explicit distinction human vs.
machine intelligence
Participants
Primary
affiliation
Countries
Focus
Definitions
Type of
definitions
Symposium Symposium
1921 1986 2019
Defining (A)I: A comparison
22. 22
@dmonett
24.7.2017—25.7.2019 57+ 184+
Academia (N=452, 79.7%)
Industry (N=116, 20.5%)
Researchers (N=435, 76.7%)
Educators (N=197, 34.7%)
Developers, Engineers (N=90, 15.9%)
567 responses
4,128
opinions
343 new,
suggested
definitions
9x2 definitions of (human/machine)
intelligence to agree upon
AGISI survey Defining (machine) Intelligence
(Partial results) Monett, D. and Lewis, C. W. P. (2018). Getting clarity by defining Artificial Intelligence—A Survey. In Müller, Vincent C.
(Ed.), Philosophy and Theory of Artificial Intelligence 2017. SAPERE 44 (pp. 212-214). Berlin: Springer.
See http://agisi.org/Survey_intelligence.html
24. 24
@dmonett
A widely accepted definition of intelligence
Gottfredson, L. S. (1997a). Mainstream science on intelligence: An editorial with 52 signatories,
history, and bibliography. Intelligence, 24: 13-23.
As cited in Haier, R. J. (2017). The Neuroscience of Intelligence. New York: Cambridge University
Press.
Most accepted definition, AGISI survey
25. 25
@dmonett
1 target article on defining AI (Wang, 2019)
20 commentaries from leading AI experts
1 extended answer from target author
Wang, P. (2019). On Defining Artificial Intelligence. Journal of Artificial General
Intelligence, 10(2), 1–37.
Monett, D., Lewis, C. W. P., & Thórisson, K. R. (eds.) (2020). Special Issue “On Defining
Artificial Intelligence.” Journal of Artificial General Intelligence, 11(2), 1–100.
But still no general consensus in the AI community!
26. 26
@dmonett
“ .
Rather, artificial intelligence is both
embodied and material, made from
natural resources, fuel, human labor,
infrastructures, logistics, histories, and
classifications. AI systems are not
autonomous, rational, or able to discern
anything without extensive,
computationally intensive training with
large datasets or predefined rules and
rewards.”
Crawford, K. (2021). Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence. Yale University Press.
29. 29
@dmonett
Monett, D., & Lemke, C. (2021). AI-ware: Bridging AI and Software Engineering for responsible and sustainable intelligent artefacts.
In van Giffen, B., Koehler, J., Brenner, W., & Albayrak, C. A., Managing Artificial Intelligence (pp. 66-73), Workshop Paper Series,
INFORMATIK 2021, Institute of Information Management, University of St. Gallen. A workshop co-located with INFORMATIK 2021,
the 51st Annual Conference of the German Informatics Society (GI), September 29th - October 1st, 2021, in Berlin and online.
Soft-
ware
AI-
ware
30. 30
@dmonett
(Monett & Lemke, 2021)
AI-
ware
The need to be aware of what AI is and is not,
its subfields, as well as a critical appraisal of
where does applying AI make sense at all.
The conjunction of AI and Software
Engineering, mainly –but not only– the former
learning from the variety of well-established
techniques and good practices from the latter,
at the same time extending them.
31. 31
@dmonett
research agenda & Responsible AI
(Monett & Lemke, 2021)
Societal and
ethical
perspective
Algorithmic
perspective
Data-oriented
perspective
Framework-
based
perspective
Economics
perspective
Interdisciplinary
perspective
41. 41
@dmonett
“Did you assess how your
system behaves in
unexpected situations
and environments?”
Cartoon created at www.projectcartoon.com
(Trustworthy AI assessment list, 2019)
42. 42
@dmonett
“Did you consider the
potential impact or safety
risk to the environment
or to animals?”
Cartoon created at www.projectcartoon.com
(Trustworthy AI assessment list, 2019)
43. 43
@dmonett
“In case the AI system
features a chat bot or
conversational system,
are the human end users
made aware of the fact
that they are interacting
with a non-human
agent?”
Cartoon created at www.projectcartoon.com
(Trustworthy AI assessment list, 2019)
44. 44
@dmonett
“Did you consider ways to
develop the AI system or
train the model without
or with minimal use of
potentially sensitive or
personal data?”
Cartoon created at www.projectcartoon.com
(Trustworthy AI assessment list, 2019)
45. 45
@dmonett
“Did you consider
diversity and
representativeness of
users in the data?
Did you test for specific
populations or
problematic use cases?”
Cartoon created at www.projectcartoon.com
(Trustworthy AI assessment list, 2019)
46. 46
@dmonett
“Did you put in place
mechanisms that
facilitate the system’s
auditability by internal
and/or independent
actors?”
Cartoon created at www.projectcartoon.com
(Trustworthy AI assessment list, 2019)
47. Put it
on your backlog!
That’s how RAI gets done.
@dmonett