100 research outputs found
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The Partnership Press: Lessons for Platform-Publisher Collaborations as Facebook and News Outlets Team to Fight Misinformation
In December 2016, shortly after the US presidential election, Facebook and five US news and fact-checking organizationsâABC News, Associated Press, FactCheck.org, PolitiFact, and Snopesâentered a partnership to combat misinformation. Motivated by a variety of concerns and values, relying on different understandings of misinformation, and with a diverse set of stakeholders in mind, they created a collaboration designed to leverage the partnersâ different forms of cultural power, technological skill, and notions of public service.
Concretely, the partnership centers around managing a flow of stories that may be considered false. Hereâs how it works: through a proprietary process that mixes algorithmic and human intervention, Facebook identifies candidate stories; these stories are then served to the five news and fact-checking partners through a partners-only dashboard that ranks stories according to popularity. Partners independently choose stories from the dashboard, do their usual fact-checking work, and append their fact-checks to the storiesâ entries in the dashboards. Facebook uses these fact-checks to adjust whether and how it shows potentially false stories to its users.
Variously seen as a public relations stunt, a new type of collaboration, or an unavoidable coupling of organizations through circumstances beyond eitherâs exclusive control, the partnership emerged as a key example of platform-publisher collaboration. This report contextualizes the partnership, traces its dynamics through a series of interviews, and uses it to motivate a general set of questions that future platform press partnerships might ask themselves before collaborating
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Probably Speech, Maybe Free: Toward a Probabilistic Understanding of Online Expression and Platform Governance
Considering the cost of applying a probablistic statistical framework to First Amendment questions on digital platform
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Controlling the Conversation: The Ethics of Social Platforms and Content Moderation
With social platformsâ prevailing dominance, there are numerous debates around who owns information, content, and the audience itself: the publisher, or the platform where the content is discoveredâor not discovered, as the case may be. Platforms rely heavily on algorithms to decide what to surface to their users across the globe, and they also rely on algorithms to decide what content is taken down. Meanwhile, publishers are making similar decisions on a significantly smaller scale, and not necessarily algorithmically or quite as generically. But how are any of these decisions made? And what are the various factors taken into account to ensure that the decision-making is fair and ethical?
On February 23, 2018, the Tow Center for Digital Journalism at Columbia University and the Annenberg Innovation Lab at USC Annenberg School for Communication and Journalism hosted a Policy Exchange Forum followed by a conference on the topic of âControlling the Conversation: The Ethics of Social Platforms and Content.â
The Policy Exchange Forum was a closed-group discussion that followed the Chatham House Rule. The discussion broadly focused on three topics: âEthics of Moderationâ, âModeration Toolsâ, and âTechnological Challenges.
New way to encourage written literacy through oral language
Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2001.Includes bibliographical references (leaves [160]-165).This thesis presents a new approach and a new interface to let children practice written literacy skills using oral language. Specifically, I argue that language composition is learned by practicing a set of cognitive skills that are independent of the medium in which the linguistic meaning is represented. Furthermore, I claim that tangible, technology-enhanced toys with specific features can support the development of these skills through open-ended language play. To investigate this claim, I developed a new model of composition, called the TellTale Composition Model, to address aspects of both oral and written language. This model supports the following features of children's language play: voice; structure; reference; reflection and revision; and sharing and discussion. A new toy, called TellTale, was built to support this composition model. Three studies were conducted to evaluate both its usability and the model's validity. The findings indicate that a toy that lets children create, segment, organize and link oral language through play with a tangible toy in a social setting helps them practice important cognitive skills crucial for later literacy. Preliminary data also suggest that such a toy can help identify children's language learning disabilities and the linguistic strategies used by children of different socio-economic strata. Both TellTale and the composition model on which its design was based suggest several new ways digital media can let children become engaged and skillful authors.Michael J. Ananny.S.M
DĂA DE MUERTOS Y HALLOWEEN DE LA FACULTAD DE QUĂMICA 2017.
La comunidad estudiantil del Organismo AcadĂ©mico Facultad de QuĂmica, el martes 31 de octubre de 2017, a docentes, administrativos y autoridades, expone abiertamente su talento de participante creativo grupal en el concurso DĂA DE MUERTOS Y HALLOWEEN ESTUDIANTIL EN INGLĂS-ESPAĂOL, que organiza la maestra y coordinadora de InglĂ©s, maestra en nuevas tecnologĂas aplicadas a la educaciĂłn Sara Ananny Iturbe Peñaloza
Paywallsâ Impact on Local News Websitesâ Traffic and Their Civic and Business Implications
Empowerment or Engagement? Digital Health Technologies for Mental Healthcare
We argue that while digital health technologies (e.g. artificial intelligence, smartphones, and virtual reality) present significant opportunities for improving the delivery of healthcare, key concepts that are used to evaluate and understand their impact can obscure significant ethical issues related to patient engagement and experience. Specifically, we focus on the concept of empowerment and ask whether it is adequate for addressing some significant ethical concerns that relate to digital health technologies for mental healthcare. We frame these concerns using five key ethical principles for AI ethics (i.e. autonomy, beneficence, non-maleficence, justice, and explicability), which have their roots in the bioethical literature, in order to critically evaluate the role that digital health technologies will have in the future of digital healthcare
Making Sense of Blockchain Applications:A Typology for HCI
Blockchain is an emerging infrastructural technology that is proposed to fundamentally transform the ways in which people transact, trust, collaborate, organize and identify themselves. In this paper, we construct a typology of emerging blockchain applications, consider the domains in which they are applied, and identify distinguishing features of this new technology. We argue that there is a unique role for the HCI community in linking the design and application of blockchain technology towards lived experience and the articulation of human values. In particular, we note how the accounting of transactions, a trust in immutable code and algorithms, and the leveraging of distributed crowds and publics around vast interoperable databases all relate to longstanding issues of importance for the field. We conclude by highlighting core conceptual and methodological challenges for HCI researchers beginning to work with blockchain and distributed ledger technologies
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Ethical principles in machine learning and artificial intelligence: cases from the field and possible ways forward
Decision-making on numerous aspects of our daily lives is being outsourced to machine-learning algorithms and artificial intelligence (AI), motivated by speed and efficiency in the decision process. Machine learning (ML) approaches - one of the typologies of algorithms underpinning artificial intelligence - are typically developed as black boxes. The implication is that ML code scripts are rarely scrutinised; interpretability is usually sacrificed in favour of usability and effectiveness. Room for improvement in practices associated with programme development have also been flagged along other dimensions, including inter alia fairness, accuracy, accountability, and transparency. In this contribution, the production of guidelines and dedicated documents around these themes is discussed. The following applications of AI-driven decision making are outlined: a) Risk assessment in the criminal justice system, and b) autonomous vehicles, highlighting points of friction across ethical principles. Possible ways forward towards the implementation of governance on AI are finally examined
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Lets Talk about Race: Identity, Chatbots, and AI
Why is it so hard for chatbots to talk about race? This work explores how the biased contents of databases, the syntactic focus of natural language processing, and the opaque nature of deep learning algorithms cause chatbots difficulty in handling race-talk. In each of these areas, the tensions between race and chatbots create new opportunities for people and machines. By making the abstract and disparate qualities of this problem space tangible, we can develop chatbots that are more capable of handling race-talk in its many forms. Our goal is to provide the HCI community with ways to begin addressing the question, how can chatbots handle race-talk in new and improved ways
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