• Algorithms: a list of steps to follow in order to solve a problem: most relevant for AI-related work is algorithms written in code that tell computers how to do something; Very important to note the difference between an ordinary algorithm, which only completes the task it was programmed for, and a machine-learning algorithm, which can generate new data, and grow with that.
• Artificial intelligence: there is lack of a generally agreed upon definition, but AI is usually used to refer to getting machines to think on a ‘deep’ level, modifying and refining their own programming over time (after processing huge data sets and “feedback loops”) rather than simply running through static routines and programs over time. The most basic technical definition of AI would be a self-refining program structured as a massive collection of Bayesian trees, mapping all possible outputs and choosing between them probabilistically. (DK)
• Machine learning: “Machine Learning is the science of getting computers to learn and act like humans do, and improve their learning over time in autonomous fashion, by feeding them data and information in the form of observations and real-world interactions. (Source); Machine learning is a subset of Artificial intelligence. The terms machine learning, algorithms, and artificial intelligence cannot be used interchangeably
• Machine learning algorithms: algorithms that use principles of machine-learning to learn from data and come to an answer without having explicit instructions
• Bots — Algorithms impersonating humans, similar but distinct from “trolls” who are (often paid) actors impersonating other humans
• troll/bot farms: An organization or company whose employees or members attempt to create conflict and disruption in an online community by posting deliberately inflammatory or provocative comments. These farms can be hired to generate online conflict or trigger flame wars. A common strategy deployed is to create a concern troll, a false flag pseudonym created by a user whose actual point of view is opposed to the one that the troll claims to hold. The concern troll posts in Web forums devoted to its declared point of view and attempts to sway the group’s actions or opinions while claiming to share their goals, but with professed “concerns”. The goal is to sow fear, uncertainty and doubt within the group
• Data Analytics (sometimes referred to as “Data Science”) – the complex toolkit for making analysis and decisions on the basis of huge data sets (“Big Data“), whether for academic, governmental, or private-sector purposes. Increasingly Data Scientists are becoming more central to the executive decision-making of corporations and governments across industries and contexts. Traditionally, Data Analytics (in any context) are only as useful or as neutral or as reliable as their data sets and its provenance: data accrued over decades in an institutional context generally will bestow analyses based on them with the biases and weaknesses not only of decades of data-collecting but also of that institution, its staffing, its time and place…
• Concrete example: “So it used to be that life insurance companies made black men pay more for life insurance than white men simply because they were going to die sooner. That lasted for a long time before the regulators in question were like – wait a second – that’s racist.” (Source)
• Some data sets are “harvested” from the main institutions of the “freemium” internet (free services or free-for-most-users services that analyze huge amount of traffic) – others, like geographical information, are largely crowdsourced, while others are cobbled together from commercially-available data like credit histories, shopping habit profiles, etc.
• voter rolls (raw data of most profiling, like Cambridge Analytica) are huge data sets of all registered or voting voters across multiple elections in a given district, which until a few years ago were readily available in many states, often without even being anonymized or having personally-identifying information obscured.
  

Advanced topics in Artificial Intelligence

• dark ads, different kinds of paid social media work, including “user-generated” content made by paid human or bot agents
• viral content, etc (“bought trends”) – see the gaming section below
• “process laundering” – delegating to an AI or algo the work that you don’t want individual discretion for and potentially liability
• predictive policing – using big data (simple algos or AI) to flag “likely” criminals, “gang affiliates” (as opposed to members), or other classes of people for differential treatment
  • arguments against “profiling” largely apply– “profiling” is using police discretion
  • predictive policing sometimes seen as “laundered” profiling/discrimination
  • another example is using AI content moderation to monitor and remove content that violates copyright or other policies instead of doing it with human moderators- a use much discussed in terms of Article 13 the EU’s pending Copyright directive

New Media core concepts

• deepfakes: manipulated images, video, and audio generated by sophisticated applications of machine learning- but also still, at this point, detectable by machine learning and other techniques and tools (for more see here) (DK)
• Different forms of engagement: affective (“subliminal”, emotional, psychological, rational, ideological): Affect: “Affect arises in the midst of in-between-ness: in the capacities to act and be acted upon. Affect is an impingement or extrusion of a momentary or sometimes more sustained state of relation as well as the passage (and the duration of passage) of forces or intensities. That is, affect is found in those intensities that pass body-to-body (human, non-human, part-body, and otherwise), in those resonances that circulate about, between and sometimes stick to bodies and worlds, and in the very passages or variations between these intensities and resonances themselves”. Gregory J. Seigworth and Melissa Gregg
• The attention economy – as much of the business model of the Internet for the last twenty years has monetized based on metrics of clicks, page views, and traffic, the metaphor of attention as “currency” in a virtual market for literal or figurative “attention” has taken hold on the media space and its economics.
• Clickbait is a text or thumbnail link that is designed to entice users to follow that link and read, view, or listen to the linked piece of online content.. Click-bait headlines typically aim to exploit the “curiosity gap”, providing just enough information to make readers of news websites curious, but not enough to satisfy their curiosity without clicking through to the linked content Clickbait feeds on the general lack of attention that defines online strolling
• Memes: Memes are multimodal artifacts remixed by countless participants, employing popular culture for public commentary
• virality vs memes: A viral message or object must spread without loosing its original idea or content, memes can help or disrupt virality as they transform and alter the message
• flame warfare: Flaming is the online act of posting insults, often laced with profanity or other offensive language on social networking sites. These insults may turn into flame wars where two or more individuals unite to exchange or unite against a third party with verbal attacks. (Wikipedia)
• virtue signaling: is the conspicuous expression of moral values. The term was first used in signalling theory, to describe any behavior that could be used to signal virtue—especially piety among the religious. In recent years, the term has become more commonly used as a pejorative by commentators to criticize what they regard as empty or superficial support of certain political views, and also used within groups to criticize their own members for valuing appearance over action (Wikipedia)
• superposters: “Superposters tend to be ‘more opinionated, more extreme, more engaged, more everything.’” Their influential role further distorts perception of reality. These posters had a significant impact during the anti-refugee violence in Altena, Germany.

New Media Advanced Topics

• content moderation: the process whereby a host of content such as videos, blog posts, status updates, etcetera, determines what content can remain on the platform. The term is generally used to refer to commercial content moderation as done by platforms like Facebook and YouTube. For more information, see the film the Cleaners and UN Special Rapporteur Freedom of Expression David Kayes June 2018 report; Note: working full time (or more than full time) in content moderation may cause emotional distress and even PTSD
• “gaming” algorithms – taking strategic advantage of how content is sorted, aggregated, or spread.
• Search Engine Optimization (SEO), “shareability”, and “trend-friendliness” – all three of these refer to different in the earliest example of this, Google’s search engine ranking mechanisms were relatively transparent, and a whole industry (“SEO”) was spanned re-writing and tweaking online content to get more traffic and attention by optimizing for these algorithms.
• disinformation – deliberately confusing the public by spreading and popularizing false information to influence their thoughts and action
• disinformation taxonomy from First Draft new: Seven types of dis and misinformation (it’s important to not use the blanket term “fake news”)
  

1. satire/parody,
2. false connection (when headlines/caption don’t support content),
3. misleading content,
4. false context (share with false information, such as saying “this photo is from Syria” when it is from Yemen),
5. imposter content (impersonating genuine content),
6. manipulated content (including “doctored” audio or video, selective omissions, etc.)
7. fabricated content

• dismediation – openly or subtly attacking mainstream/traditional media and getting the public to lose the distinction between propaganda and media (relies primarily on imposture content) – Source
• filter bubble: Term derived by Eli Pariser that describes “that personal ecosystem of information that’s been catered by these algorithms to who they think you are…” isolation which result from personalized searches when a website algorithm selectively guesses what information a user would like to see based on information about the user, such as location, past click-behavior and search history. As a result, users become separated from information that disagrees with their viewpoints, effectively isolating them in their own cultural or ideological bubbles.
• “bothsidesism” – the inappropriate framing of a conflict as a difference of opinion or viewpoint between two groups meeting as equals – the most extreme example in recent years has been Trump saying of the Charlottesville demonstration and riots, “You had some very bad people in that group, but you also had people that were very fine people, on both sides,” Trump said. – Source
• Horseshoe theory – in political science and also popular discourse,[1] the horseshoe theory asserts that the far-left and the far-right, rather than being at opposite and opposing ends of a linear political continuum, closely resemble one another, much like the ends of a horseshoe.

• Anselmo’s distinction between “the political” (narrowly political, “mainstream politics” – electoral system, etc) and “politics” (in the broader sense of communities, values, activism, beyond and partially or fully outside of that system) – sometimes called “capital-P” Politics versus “lowercase-p” politics, or formal versus informal politics.
• populism – a form of politics that works primarily/centrally AGAINST the political altogether (in its most extreme forms– i.e. fascism) or AGAINST the centrist/mainstream institutions and parties of the political– “all politicians are crooks except ours”, cynical rejection of political traditions, journalism and academia as institutions of consensus/common frameworks, etc.
• populism tends to cooperate with older forms of autocracy or demagoguery to make the invalidation, overriding, or scrapping of due process more palatable or “commonsensical” to the people
• nationalism – the ideology that the priorities and necessities of the nation (however defined) are at odds with international priorities, or the application of an ostensibly “national” agenda to internal affairs in a way that trumps or rescinds earlier commitments (such as safety nets, economic programs, cultural programs, etc)
• ethnonationalism or ethnic nationalism – the tendency to define the nation as naturally or necessarily coextensive with an ethnic group (usually relying on dubious race science and/or heavy historical revisionism), which also conveniently creates an ethnic other to be united against and scapegoated. “white nationalism” is often used as a shorthand, but it’s worth mentioning that increasingly ethnonationalist movements have deracialized (at least in their outward communications) much of their messaging to refer to “European civilization” and to include high-profile members of color to blur or complicate the simply racial nature of their ethnic identification and their justifications for hardline nationalism.