“You can sway a thousand men by appealing to their prejudices quicker than you can convince one man by logic."
—ROBERT A. HEINLEIN”
"A defining trait of post-truth politics is that campaigners continue to repeat their talking points, even when media outlets, experts in the field in question, and others provide proof that contradicts these talking points."
- Altnews (Indian politics),
- Social Media hoax slayer (link),
- Factchecker,
- Snopes,
- politifact (US politics),
- Boom,
- Crash course: Media Literacy (link to playlist)
- (00) Preview,
- (01) Introduction,
- (02) History - 01,
- (03) History - 02,
- (04) Media and the mind,
- (05) Media and money,
- (06) Influence and persuasion,
- (07) Online advertising,
- (08) Media ownership,
- (09) Media policy and you,
- (10) Darker side of media,
- (11) Media skills,
- (12) Future literacies.
- Crash course: Navigating Digital Information (link to playlist)
- Preview (Ep 0),
- Introduction (Ep 1),
- Fact Checking (Ep 2),
- Lateral reading (Ep 3),
- Deciding who to trust (Ep 4),
- Using wikipedia (Ep 5),
- Evaluating evidence (Ep 6),
- Evaluating photos and videos (Ep 7),
- Data and infographics (Ep 8),
- Click restraint (Ep 9),
- Social media (Ep 10).
- Books:
- Post-Truth by Lee Mcintyre,
- The death of truth by Kakutani,
- The death of expertise by Tom Nichols,
- The misinformation age by Calin O'Connor and James Weatherall,
- Why Learn History (When It’s Already on Your Phone) by Sam Wineburg,
- Antisocial Media: How Facebook Disconnects Us and Undermines Democracy Hardcover – 12 Jun 2018 by Siva Vaidhyanathan;
- How to Win an Indian Election: What political parties don't want you to know by Shivam Shankar Singh;
- World Without Mind: The Existential Threat of Big Tech Hardcover
- A field guide to lies and statistics by Daniel Levitin
- Why fiction trumps truth by Yuval Noah Harari: https://www.nytimes.com/2019/
05/24/opinion/why-fiction- trumps-truth.html, - Jordan Peterson on political tribalism: https://www.youtube.com/watch?v=yo3gOoOSdhY
- https://www.nytimes.com/2019/01/29/books/review/roger-mcnamee-zucked.html
- The rise and rise of fake news in India (article by Soumya Shankar),
- Journalism's fall from grace:
- Journalistic ethics, standards and policies:
- New-York Times: ethical journalism,
- Journalism ethics,
- The Washington Post: policies and standards,
- Journalism ethics;
- 2016 US presidential elections:
- Fake news in 2016 US elections,
- Netflix documentary: Get me Roger Stone;
- Learn how to perform advanced search and look for sources online: here;
- Courses:
- https://www.callingbullshit.org/
- https://thegoldstandardsite.wordpress.com/2019/04/19/course-on-bullshit-detection/
- Logical fallacies: see e.g. here;
- Facebook (Last week tonight with John Oliver);
- Scientific studies (Last week tonight with John Oliver);
- Deep Fake;
- Why obvious lies make great propaganda;
- Manufacturing consent: Media and propaganda;
- Election campaign and consumer marketing;
- https://www.technologyreview.com/s/614083/the-worlds-top-deepfake-artist-is-wrestling-with-the-monster-he-created/
- It is useful to be aware of the following:
- Opinion vs reporting
- Propaganda,
- Cult of personality,
- Smear Campaign,
- Post truth politics,
- Sensationalism,
- Clickbait,
- Yellow journalism,
- Media manipulation, Public opinion, Perception management, Promotion, Personal branding
- Having a different opinion/viewpoint/perspective/political philosophy is different from being biased (unfair favouritism),
- It is also useful to be aware of some other, related big picture issues:
- Capitalism and the dangers of unchecked capitalism (e.g. Atlantic slave trade),
- Capitalism -> consumerism, advertising and promotion,
- Hedonism;
- Romanticism;
- collectivism vs individualism;
- totalitarianism;
- Ted talks
- "Navigating Through the Sea of Information in Digital Era" (link),
- "How a handful of tech companies control billions of minds every day: Tristan Harris" (link)
- The Social Dilemma: https://en.m.wikipedia.org/wiki/The_Social_Dilemma
- https://en.m.wikipedia.org/wiki/Attention_economy
- Deep fake
- Deepfakes by Nina Schick
- https://en.wikipedia.org/wiki/Synthetic_media
- Cobrapost sting operations:
- Trending topics at twitter and IT cell: Pratik Sinha's Rancho act;
- Ravish Kumar speech: https://thewire.in/media/when-media-turns-against-the-citizen-citizens-must-play-the-role-of-the-media
- https://archive.org/stream/TheBurdenOfSkepticism-CarlSagan/sagan-skeptism_djvu.txt
- Recent articles:
- heres-what-it-will-take-to-win-the-battle-against-fake-news,
- how indians perceive fake news,
- https://thewire.in/media/vast-far-right-disinformation-networks-discovered-in-eu,
- https://scroll.in/article/927971/theres-no-winning-against-fake-news-but-that-doesnt-mean-we-should-stop-trying
- https://thewire.in/world/indonesia-fake-news-digital-literacy
- https://thewire.in/tech/can-an-ai-fact-checker-solve-indias-fake-news-problem
- https://thewire.in/communalism/mob-lynchings-whatsapp-fake-news
- https://thewire.in/tech/whatsapp-automated-spam-behaviour-elections-india-study
- https://thewire.in/politics/top-whatsapp-official-warns-indian-political-parties-to-behave
- What's trending? Understanding unintended biases in the contents presented to users:
- Abstract of talk by Prof Niloy Ganguly (IIT-Kh): "Due to the enormous amount of information being carried over online systems today, no user can access all such information. Therefore, to help the users, all major online organizations deploy information retrieval (content recommendation, search or ranking) systems to find important information. Current information retrieval systems have to make certain design choices. For example, news recommendation systems need to decide on the quality of recommended news stories, how much emphasis to give to a story’s long-term importance over its recency or freshness etc. Similarly, retrieval systems over user generated contents (e.g., in social media like Facebook and Twitter) need to take into account the content posted by heterogeneous user groups. However, such design choices can introduce unintended biases in the contents presented to the users. For example, the recommended contents may have poor quality or less news value, or the news discourse may get hijacked by hyper-active demographic groups. In this work, we want to systematically measure the effect of such design choices in the retrieval systems (recommendation systems in particular), and build alternate retrieval systems that mitigate the biases in the recommendation output."
- https://scroll.in/article/918579/beware-indian-social-media-influencers-promoting-brands-they-may-be-restoring-to-fakery
- Specific cases:
- Here's a link to a short summary of the famous and fascinating story of Elizabeth Holmes (https://en.wikipedia.org/
wiki/Elizabeth_Holmes) and the company she founded Theranos (https://en.wikipedia.org/ wiki/Theranos). She founded the company in 2003 (at the age of 19) and raised insane amount of money by making claims which the experts were always skeptical about. Eventually, she was celeb as the youngest and wealthiest self-made female billionaire by the media. As of now, she is facing charges which can send her to prison for 20 years.The world is full of frauds and we just believe them because we are floored by their personalities while the mass media plays along (and because we ignore the boring sounding experts, who know that people are being fooled by great speeches and attractive looks).But this keeps happening: from routine astrologers to Ramdev baba or MSG baba claiming that they have a cure for cancer (which several decades of actual research hasn't been able to arrive at) to some politician claiming that he is the saviour of the country (while the experts uncovering his lies are called urban naxals or anti-nationals). - Additionally: what the internet is doing to us:
No comments:
New comments are not allowed.