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Look behind the curtain: Don't be dazzled by claims of 'artificial intelligence'

#artificialintelligence

We are presently living in an age of "artificial intelligence" -- but not how the companies selling "AI" would have you believe. According to Silicon Valley, machines are rapidly surpassing human performance on a variety of tasks from mundane, but well-defined and useful ones like automatic transcription to much vaguer skills like "reading comprehension" and "visual understanding." According to some, these skills even represent rapid progress toward "Artificial General Intelligence," or systems which are capable of learning new skills on their own. Given these grand and ultimately false claims, we need media coverage that holds tech companies to account. Far too often, what we get instead is breathless "gee whiz" reporting, even in venerable publications like The New York Times.


The New Intelligence Game

#artificialintelligence

The relevance of the video is that the browser identified the application being used by the IAI as Google Earth and, according to the OSC 2006 report, the Arabic-language caption reads Islamic Army in Iraq/The Military Engineering Unit – Preparations for Rocket Attack, the video was recorded in 5/1/2006, we provide, in Appendix A, a reproduction of the screenshot picture made available in the OSC report. Now, prior to the release of this video demonstration of the use of Google Earth to plan attacks, in accordance with the OSC 2006 report, in the OSC-monitored online forums, discussions took place on the use of Google Earth as a GEOINT tool for terrorist planning. On August 5, 2005 the user "Al-Illiktrony" posted a message to the Islamic Renewal Organization forum titled A Gift for the Mujahidin, a Program To Enable You to Watch Cities of the World Via Satellite, in this post the author dedicated Google Earth to the mujahidin brothers and to Shaykh Muhammad al-Mas'ari, the post was replied in the forum by "Al-Mushtaq al-Jannah" warning that Google programs retain complete information about their users. This is a relevant issue, however, there are two caveats, given the amount of Google Earth users, it may be difficult for Google to flag a jihadist using the functionality in time to prevent an attack plan, one possible solution would be for Google to flag computers based on searched websites and locations, for instance to flag computers that visit certain critical sites, but this is a problem when landmarks are used, furthermore, and this is the second caveat, one may not use one's own computer to produce the search or even mask the IP address. On October 3, 2005, as described in the OSC 2006 report, in a reply to a posting by Saddam Al-Arab on the Baghdad al-Rashid forum requesting the identification of a roughly sketched map, "Almuhannad" posted a link to a site that provided a free download of Google Earth, suggesting that the satellite imagery from Google's service could help identify the sketch.


Technology Ethics in Action: Critical and Interdisciplinary Perspectives

arXiv.org Artificial Intelligence

This special issue interrogates the meaning and impacts of "tech ethics": the embedding of ethics into digital technology research, development, use, and governance. In response to concerns about the social harms associated with digital technologies, many individuals and institutions have articulated the need for a greater emphasis on ethics in digital technology. Yet as more groups embrace the concept of ethics, critical discourses have emerged questioning whose ethics are being centered, whether "ethics" is the appropriate frame for improving technology, and what it means to develop "ethical" technology in practice. This interdisciplinary issue takes up these questions, interrogating the relationships among ethics, technology, and society in action. This special issue engages with the normative and contested notions of ethics itself, how ethics has been integrated with technology across domains, and potential paths forward to support more just and egalitarian technology. Rather than starting from philosophical theories, the authors in this issue orient their articles around the real-world discourses and impacts of tech ethics--i.e., tech ethics in action.


A Science Journalist's Journey to Understand AI

#artificialintelligence

As a teenager, I discovered a worn copy of the book Gödel, Escher, Bach: An Eternal Golden Braid by Douglas Hofstadter on a bookshelf at home. It still had a computer punch card in it that my Mom had used as a bookmark, back when she briefly worked as a programmer in the early 1980s. Reading that book was like falling into another world. I found myself thinking about the mind and computers in brand new ways. I learned about Alan Turing's work for the first time.


Sports Illustrated Swimsuit model Brooks Nader reveals the secret behind her sheer, daring looks

FOX News

Fox News Flash top entertainment and celebrity headlines are here. Check out what clicked this week in entertainment. Brooks Nader is inviting you to go through her clothes. The Sports Illustrated Swimsuit model is opening up her closet on Wardrobe, a luxury and vintage clothing retail app that has collaborated with fellow SI Swimsuit stars Marquita Pring and Olivia Culpo. It allows users to browse through the collections of sought-after influencers and borrow whatever they like.


Why Computers Don't Need to Match Human Intelligence

#artificialintelligence

With continuing advances in machine learning, it makes less and less sense to compare AI to the human mind.


Gartner : Increase Human and Machine Intelligence Through Reciprocal Augmentation …

#artificialintelligence

In the "out of the loop" model, advanced analytics and machine learning take over full decision making and execution. Humans take a supervisory role, …


An overview of event extraction and its applications

arXiv.org Artificial Intelligence

With the rapid development of information technology, online platforms have produced enormous text resources. As a particular form of Information Extraction (IE), Event Extraction (EE) has gained increasing popularity due to its ability to automatically extract events from human language. However, there are limited literature surveys on event extraction. Existing review works either spend much effort describing the details of various approaches or focus on a particular field. This study provides a comprehensive overview of the state-of-the-art event extraction methods and their applications from text, including closed-domain and open-domain event extraction. A trait of this survey is that it provides an overview in moderate complexity, avoiding involving too many details of particular approaches. This study focuses on discussing the common characters, application fields, advantages, and disadvantages of representative works, ignoring the specificities of individual approaches. Finally, we summarize the common issues, current solutions, and future research directions. We hope this work could help researchers and practitioners obtain a quick overview of recent event extraction.


Knowledge Graph informed Fake News Classification via Heterogeneous Representation Ensembles

arXiv.org Artificial Intelligence

Increasing amounts of freely available data both in textual and relational form offers exploration of richer document representations, potentially improving the model performance and robustness. An emerging problem in the modern era is fake news detection -- many easily available pieces of information are not necessarily factually correct, and can lead to wrong conclusions or are used for manipulation. In this work we explore how different document representations, ranging from simple symbolic bag-of-words, to contextual, neural language model-based ones can be used for efficient fake news identification. One of the key contributions is a set of novel document representation learning methods based solely on knowledge graphs, i.e. extensive collections of (grounded) subject-predicate-object triplets. We demonstrate that knowledge graph-based representations already achieve competitive performance to conventionally accepted representation learners. Furthermore, when combined with existing, contextual representations, knowledge graph-based document representations can achieve state-of-the-art performance. To our knowledge this is the first larger-scale evaluation of how knowledge graph-based representations can be systematically incorporated into the process of fake news classification.


Interpretive Blindness

arXiv.org Artificial Intelligence

We model here an epistemic bias we call \textit{interpretive blindness} (IB). IB is a special problem for learning from testimony, in which one acquires information only from text or conversation. We show that IB follows from a co-dependence between background beliefs and interpretation in a Bayesian setting and the nature of contemporary testimony. We argue that a particular characteristic contemporary testimony, \textit{argumentative completeness}, can preclude learning in hierarchical Bayesian settings, even in the presence of constraints that are designed to promote good epistemic practices.