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we need other ways for humans to learn about the world and interact with each other, healthier ways, less commercial and addictive ways. We should explicitly build out public forums, we should subsidize journalism, we should enhance our public support for universities, museums & libraries.

The Global Battle for Attention and Authority – Have We Already Lost? https://scholarlykitchen.sspnet.org/2018/06/14/global-battle-attention-authority-already-lost/

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“ancient rituals are technologies that have been debugged, fine-tuned, and time-tested over millennia. They evolved to respond to human needs, and in their crystallized form, they contain deep insights into those needs. By jettisoning the rituals, we also jettison the wisdom they house. ... [a ritual] situates your experience within a larger framework of moral imperatives, and makes demands of you, including that you be of service to others. ... “We need to take a breath ... and think about the wider implications of commodifying our spiritual life this way.”

https://www.theatlantic.com/technology/archive/2018/05/ritual-design-lab-secular-atheist/559535/

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“The problem with this ethics paradigm in corporate strategies is that ethical values such as fairness or inclusiveness have no widely agreed-upon meaning. The inherent nebulousness of such ethical principles makes them rather unhelpful to ensure ‘good’ corporate behavior. When is certain behavior ‘unfair’? And, more importantly, to whom are corporations accountable in case of ‘violations’ of these ethical principles (if these principles can be ‘violated’ at all)?”

https://points.datasociety.net/artificial-intelligence-whats-human-rights-got-to-do-with-it-4622ec1566d5

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data ethics can be defined as the branch of ethics that studies and evaluates moral problems related to data (including generation, recording, curation, processing, dissemination, sharing and use), algorithms (including artificial intelligence, artificial agents, machine learning and robots) and corresponding practices (including responsible innovation, programming, hacking and professional codes), in order to formulate and support morally good solutions (e.g. right conducts or right values). This means that the ethical challenges posed by data science can be mapped within the conceptual space delineated by three axes of research: the ethics of data, the ethics of algorithms and the ethics of practices.

http://rsta.royalsocietypublishing.org/content/374/2083/20160360

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“Essentially, the privacy rules that govern companies around the world are built around three major ethics: 1) Do not lie; 2) Do not harm; and 3) Follow the Fair Information Practices, or “the FIPs.” The rules that are built around these three ethics fail to adequately address how the design of information technologies affects people and can frustrate the goals of privacy law.”

https://www.linkedin.com/pulse/should-privacy-law-regulate-technological-design-interview-solove

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Libraries are lifelines in the modern world. They provide access to knowledge and technology; they are places where people apply for jobs, file taxes, get warm during the winter, cool off in the summer, and escape the apprehension and frenzy of daily life.  Few institutions have had as profound an impact on American society.  Now, perhaps as a result of the Bard-Brooklyn Public Library partnership, these iconic institutions will become places where men and women who have been marginalized and left behind--immigrants, the homeless, veterans, the formerly incarcerated, and the family members of incarcerated people--can start their journeys toward a more secure future and a better life.

Public Libraries are Reinventing Access to Higher Education | The Andrew W. Mellon Foundation https://mellon.org/resources/shared-experiences-blog/public-libraries-are-reinventing-access-higher-education/

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human moderators were still the reigning gatekeepers for information on the Internet’s most popular sites. ... AI can’t understand the context of speech and, since most categories for problematic speech are poorly defined [by necessity], having humans determine context is not only necessary but desirable.

https://www.washingtonpost.com/news/the-switch/wp/2018/04/11/ai-will-solve-facebooks-most-vexing-problems-mark-zuckerberg-says-just-dont-ask-when-or-how/?noredirect=on&utm_term=.41fdfb01b4f6

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“the three key ideals that tech companies should be prioritizing are: promoting genuine trust (through greater transparency and less manipulation), respecting obscurity (the ability for people to be more selective when sharing personal information in public and semipublic spaces), and treating dignity as sacrosanct (by fostering genuine autonomy and not treating illusions of user control as the real deal).”

https://t.co/C1R6XbAtYO

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“we need to start developing a networked response to this networked landscape. And it starts by understanding different ways of constructing knowledge.”

https://points.datasociety.net/you-think-you-want-media-literacy-do-you-7cad6af18ec2?gi=396cfe4abb48

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“In relation to the Internet and the changes it has already brought in our society, my feeling is that although we don’t know really where it’s heading because it’s too early in the change, we’ve had one stroke of luck. The stroke of luck was that, as a species, we’ve conducted this experiment once before. We’re living through a transformation of our information environment. This happened once before, and we know quite a lot about it. It was kicked off in 1455 by Johannes Gutenberg and his invention of printing by movable type.”

“The State of Informed Bewilderment” https://www.edge.org/conversation/john_naughton-the-state-of-informed-bewilderment

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there is widespread recognition in the academy and beyond that getting at the truth is difficult, that the construction of what counts as truthful is indeed contestable and contested and that debunking falsehood requires critical skills and moral commitment to truth-seeking.

https://firstdraftnews.org/wp-content/uploads/2018/03/The-Disinformation-Ecosystem-20180207-v2.pdf

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I came away from these conversations thinking that one big challenge for this generation is determining how to take good things that are happening on the local level and translate them to the national level, where the problems are. I was also struck by pervasive but subtle hunger for a change in the emotional tenor of life. “We’re more connected but we’re more apart,” one student lamented. Again and again, students expressed a hunger for social and emotional bonding, for a shift from guilt and accusation toward empathy. “How do you create relationship?” one student asked. That may be the longing that undergirds all others.

https://www.nytimes.com/2018/02/26/opinion/millennials-college-hopeful.html

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“Consider that holy grail of learning outcomes, critical thinking — what the philosopher John Dewey called the ability “to maintain the state of doubt and to carry on systematic and protracted inquiry.” Teaching it is not a cheap or efficient process. It does not come from trying to educate the most students at the lowest possible cost or from emphasizing short, quantifiable, standardized assignments at the expense of meandering, creative and difficult investigation.

Producing thoughtful, talented graduates is not a matter of focusing on market-ready skills. It’s about giving students an opportunity that most of them will never have again in their lives: the chance for serious exploration of complicated intellectual problems, the gift of time in an institution where curiosity and discovery are the source of meaning.

That’s how we produce the critical thinkers American employers want to hire.”

https://www.nytimes.com/2018/02/23/opinion/sunday/colleges-measure-learning-outcomes.html

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We argue that calls for explainable machines have failed to recognize the connection between intuition and evaluation and the limitations of such an approach. A belief in the value of explanation for justification assumes that if only a model is explained, problems will reveal themselves intuitively. Machine learning, however, can uncover relationships that are both non-intuitive and legitimate, frustrating this mode of normative assessment. If justification requires understanding why the model's rules are what they are, we should seek explanations of the process behind a model's development and use, not just explanations of the model itself. This Article illuminates the explanation-intuition dynamic and offers documentation as an alternative approach to evaluating machine learning models.

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3126971

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we make the five following recommendations for the future of media literacy work: ■ Develop a coherent understanding of the media environment. With new technologies and new rhetorical techniques, existing programs should be updated. ■ Improve cross-disciplinary collaboration. Media literacy is often seen as a narrow, pedagogical  eld. But work from other disciplines – social psychology, political science, sociology – is producing new research and  ndings that could greatly bene t media literacy. ■ Leverage the current media crisis to consolidate stakeholders. The new attention on “fake news” could allow for new cross-disciplinary collaboration and therefore greater coherence within the  eld. ■ Prioritize the creation of a national media literacy evidence base. A centralized and stable base of evaluation data would make more accurate assessment possible. Though there are many potential political challenges to such an evidence base. ■ Develop curricula for addressing action in addition to interpretation. With the increased use of social media, literacy efforts need to be able to address user behavior in addition to interpretation.

https://www.datasociety.net/pubs/oh/DataAndSociety_Media_Literacy_2018.pdf