Goto

Collaborating Authors

Results


Tinder's parent company is suing Google over in-app billing

Mashable

Online dating juggernaut Match Group is suing Google, alleging that its Android apps are being forced to use the tech giant's in-app payment system -- thus allowing Google to extract royalties for such transactions. Match Group owns numerous popular dating apps and websites, including Hinge, OkCupid, Tinder, and PlentyOfFish. The issue comes down to Google's outsized influence and control over Android app distribution, as well as its requirements for allowing apps on the Google Play Store. According to Match Group's federal court filing, over 90 percent of Android app downloads are handled through the Google Play Store. Thus, if developers want to reach enough users for their Android app to be sustainable, there's practically no way around putting it on Google's app store.


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.


Tinder launches significant redesign to its sexual violence reporting system

Mashable

Tinder is changing the way it handles reports of sexual violence and harassment with the aim of providing better support for survivors. The dating app worked with U.S. anti-sexual assault organisation RAINN (Rape, Abuse & Incest National Network) to develop the redesign of this trauma-informed reporting process, which aims to give survivors "more agency over what step they want to take next," per a press release from the company. The new changes include significant improvements to the reporting process, improved access to survivor resources, and education for internal teams at Tinder. A new screen has been introduced in the reporting process asking "are you or the person involved in a safe place?" and recommends contacting local authorities if required. It's now easier to report someone you've unmatched from.


Explainable AI for B5G/6G: Technical Aspects, Use Cases, and Research Challenges

arXiv.org Artificial Intelligence

When 5G began its commercialisation journey around 2020, the discussion on the vision of 6G also surfaced. Researchers expect 6G to have higher bandwidth, coverage, reliability, energy efficiency, lower latency, and, more importantly, an integrated "human-centric" network system powered by artificial intelligence (AI). Such a 6G network will lead to an excessive number of automated decisions made every second. These decisions can range widely, from network resource allocation to collision avoidance for self-driving cars. However, the risk of losing control over decision-making may increase due to high-speed data-intensive AI decision-making beyond designers and users' comprehension. The promising explainable AI (XAI) methods can mitigate such risks by enhancing the transparency of the black box AI decision-making process. This survey paper highlights the need for XAI towards the upcoming 6G age in every aspect, including 6G technologies (e.g., intelligent radio, zero-touch network management) and 6G use cases (e.g., industry 5.0). Moreover, we summarised the lessons learned from the recent attempts and outlined important research challenges in applying XAI for building 6G systems. This research aligns with goals 9, 11, 16, and 17 of the United Nations Sustainable Development Goals (UN-SDG), promoting innovation and building infrastructure, sustainable and inclusive human settlement, advancing justice and strong institutions, and fostering partnership at the global level.


Ethical and social risks of harm from Language Models

arXiv.org Artificial Intelligence

This paper aims to help structure the risk landscape associated with large-scale Language Models (LMs). In order to foster advances in responsible innovation, an in-depth understanding of the potential risks posed by these models is needed. A wide range of established and anticipated risks are analysed in detail, drawing on multidisciplinary expertise and literature from computer science, linguistics, and social sciences. We outline six specific risk areas: I. Discrimination, Exclusion and Toxicity, II. Information Hazards, III. Misinformation Harms, V. Malicious Uses, V. Human-Computer Interaction Harms, VI. Automation, Access, and Environmental Harms. The first area concerns the perpetuation of stereotypes, unfair discrimination, exclusionary norms, toxic language, and lower performance by social group for LMs. The second focuses on risks from private data leaks or LMs correctly inferring sensitive information. The third addresses risks arising from poor, false or misleading information including in sensitive domains, and knock-on risks such as the erosion of trust in shared information. The fourth considers risks from actors who try to use LMs to cause harm. The fifth focuses on risks specific to LLMs used to underpin conversational agents that interact with human users, including unsafe use, manipulation or deception. The sixth discusses the risk of environmental harm, job automation, and other challenges that may have a disparate effect on different social groups or communities. In total, we review 21 risks in-depth. We discuss the points of origin of different risks and point to potential mitigation approaches. Lastly, we discuss organisational responsibilities in implementing mitigations, and the role of collaboration and participation. We highlight directions for further research, particularly on expanding the toolkit for assessing and evaluating the outlined risks in LMs.


Tinder Owner To Pay Founders $441 Mn To Settle Valuation Lawsuit

International Business Times

The company that owns Tinder will pay $441 million to the popular dating app's founders to settle a dispute over the valuation of stock options, documents showed Wednesday. The suit filed in New York in 2018 contended that Tinder owner Match Group, and its then parent firm InterActiveCorp, schemed to dramatically drive down the value of stock options and then eliminate them altogether. Co-creators Sean Rad, Justin Mateen and Jonathan Badeen alleged Match and IAC relied on bogus figures to arrive at a valuation of $3 billion in 2017 -- when Tinder was actually worth more than four times that. Tinder's owner is paying the app's founders millions to settle a lawsuit Photo: AFP / Aamir QURESHI Created in 2012, Tinder now has more than 10 million paying users who can quickly scroll through possible romantic matches, and then swipe left or right to signal interest. With options on about 20 percent of Tinder's stock, the founders and their early employees felt they had been shortchanged by several billion dollars.


Virginia Tech player indicted in Tinder date's beating death

FOX News

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. A suspended Virginia Tech linebacker accused in the fatal beating of a Tinder match has been indicted on a charge of second-degree murder. Isimemen Etute, 18, who is accused in the death of 40-year-old Jerry Smith in May, was indicted by a grand jury Tuesday, The Roanoke Times reported. A hearing is scheduled Nov. 18.


Trustworthy AI: From Principles to Practices

arXiv.org Artificial Intelligence

Fast developing artificial intelligence (AI) technology has enabled various applied systems deployed in the real world, impacting people's everyday lives. However, many current AI systems were found vulnerable to imperceptible attacks, biased against underrepresented groups, lacking in user privacy protection, etc., which not only degrades user experience but erodes the society's trust in all AI systems. In this review, we strive to provide AI practitioners a comprehensive guide towards building trustworthy AI systems. We first introduce the theoretical framework of important aspects of AI trustworthiness, including robustness, generalization, explainability, transparency, reproducibility, fairness, privacy preservation, alignment with human values, and accountability. We then survey leading approaches in these aspects in the industry. To unify the current fragmented approaches towards trustworthy AI, we propose a systematic approach that considers the entire lifecycle of AI systems, ranging from data acquisition to model development, to development and deployment, finally to continuous monitoring and governance. In this framework, we offer concrete action items to practitioners and societal stakeholders (e.g., researchers and regulators) to improve AI trustworthiness. Finally, we identify key opportunities and challenges in the future development of trustworthy AI systems, where we identify the need for paradigm shift towards comprehensive trustworthy AI systems.


Socially Responsible AI Algorithms: Issues, Purposes, and Challenges

Journal of Artificial Intelligence Research

In the current era, people and society have grown increasingly reliant on artificial intelligence (AI) technologies. AI has the potential to drive us towards a future in which all of humanity flourishes. It also comes with substantial risks for oppression and calamity. Discussions about whether we should (re)trust AI have repeatedly emerged in recent years and in many quarters, including industry, academia, healthcare, services, and so on. Technologists and AI researchers have a responsibility to develop trustworthy AI systems. They have responded with great effort to design more responsible AI algorithms. However, existing technical solutions are narrow in scope and have been primarily directed towards algorithms for scoring or classification tasks, with an emphasis on fairness and unwanted bias. To build long-lasting trust between AI and human beings, we argue that the key is to think beyond algorithmic fairness and connect major aspects of AI that potentially cause AI’s indifferent behavior. In this survey, we provide a systematic framework of Socially Responsible AI Algorithms that aims to examine the subjects of AI indifference and the need for socially responsible AI algorithms, define the objectives, and introduce the means by which we may achieve these objectives. We further discuss how to leverage this framework to improve societal well-being through protection, information, and prevention/mitigation. This article appears in the special track on AI & Society.