An online service provider (OSP) can, for example, be an Internet service provider, an email provider, a news provider (press), an entertainment provider (music, movies), a search engine, an e-commerce site, an online banking site, a health site, an official government site, social media, a wiki, or a Usenet newsgroup. In its original more limited definition, it referred only to a commercial computer communication service in which paid members could dial via a computer modem the service's private computer network and access various services and information resources such as bulletin board systems, downloadable files and programs, news articles, chat rooms, and electronic mail services. The term "online service" was also used in references to these dial-up services. The traditional dial-up online service differed from the modern Internet service provider in that they provided a large degree of content that was only accessible by those who subscribed to the online service, while ISP mostly serves to provide access to the Internet and generally provides little if any exclusive content of its own. In the U.S., the Online Copyright Infringement Liability Limitation Act (OCILLA) portion of the U.S. Digital Millennium Copyright Act has expanded the legal definition of online service in two different ways for different portions of the law. It states in section 512(k)(1): (A) As used in subsection (a), the term "service provider" means an entity offering the transmission, routing, or providing of connections for digital online communications, between or among points specified by a user, of material of the user's choosing, without modification to the content of the material as sent or received. (B) As used in this section, other than subsection (a), the term "service provider" means a provider of online services or network access, or the operator of facilities therefore, and includes an entity described in subparagraph (A). These broad definitions make it possible for numerous web businesses to benefit from the OCILLA. == History == The first commercial online services went live in 1969. CompuServe (owned in the 1980s and 1990s by H&R Block) and The Source (for a time owned by The Reader's Digest) are considered the first major online services created to serve the market of personal computer users. Utilizing text-based interfaces and menus, these services allowed anyone with a modem and communications software to use email, chat, news, financial and stock information, bulletin boards, special interest groups (SIGs), forums and general information. Subscribers could exchange email only with other subscribers of the same service. (For a time a service called DASnet carried mail among several online services, and CompuServe, MCI Mail, and other services experimented with X.400 protocols to exchange email until the Internet rendered these outmoded.) Other text-based online services followed such as Delphi, GEnie and MCI Mail. The 1980s also saw the rise of independent Computer Bulletin Boards, or BBSes. (Online services are not BBSes. An online service may contain an electronic bulletin board, but the term "BBS" is reserved for independent dialup, microcomputer-based services that are usually single-user systems.) The commercial services used pre-existing packet-switched (X.25) data communications networks, or the services' own networks (as with CompuServe). In either case, users dialed into local access points and were connected to remote computer centers where information and services were located. As with telephone service, subscribers paid by the minute, with separate day-time and evening/weekend rates. As the use of computers that supported color and graphics, such the Atari 8-bit computers, Commodore 64, TI-99/4A, Apple II, and early IBM PC compatibles, increased, online services gradually developed framed or partially graphical information displays. Early services such as CompuServe added increasingly sophisticated graphics-based front end software to present their information, though they continued to offer text-based access for those who needed or preferred it. In 1985 Viewtron, which began as a Videotex service requiring a dedicated terminal, introduced software allowing home computer owners access. Beginning in the mid-1980s graphics based online services such as PlayNET, Prodigy, and Quantum Link (aka Q-Link) were developed. Quantum Link, which was based on Commodore-only Playnet software, later developed AppleLink Personal Edition, PC-Link (based on Tandy's DeskMate), and Promenade (for IBM), all of which (including Q-Link) were later combined as America Online. These online services presaged the web browser that would change global online life 10 years later. Before Quantum Link, Apple computer had developed its own service, called AppleLink, which was mostly a support network targeted at Apple dealers and developers. Later, Apple offered the short-lived eWorld, targeted at Mac consumers and based on the Mac version of the America Online software. Beginning in 1992, the Internet, which had previously been limited to government, academic, and corporate research settings, was opened to commercial entities. The first online service to offer Internet access was DELPHI, which had developed TCP/IP access much earlier, in connection with an environmental group that rated Internet access. The explosion of popularity of the World Wide Web in 1994 accelerated the development of the Internet as an information and communication resource for consumers and businesses. The sudden availability of low- to no-cost email and appearance of free independent web sites broke the business model that had supported the rise of the early online service industry. CompuServe, BIX, AOL, DELPHI, and Prodigy gradually added access to Internet e-mail, Usenet newsgroups, ftp, and to web sites. At the same time, they moved from usage-based billing to monthly subscriptions. Similarly, companies that paid to have AOL host their information or early online stores began to develop their own web sites, putting further stress on the economics of the online industry. Only the largest services like AOL (which later acquired CompuServe, just as CompuServe acquired The Source) were able to make the transition to the Internet-centric world. A new class of online service provider arose to provide access to the Internet, the internet service provider or ISP. Internet-only service providers like UUNET, The Pipeline, Panix, Netcom, the World, EarthLink, and MindSpring provided no content of their own, concentrating their efforts on making it easy for nontechnical users to install the various software required to "get online" before consumer operating systems came internet-enabled out of the box. In contrast to the online services' multitiered per-minute or per-hour rates, many ISPs offered flat-fee, unlimited access plans. Independent companies sprang up to offer access and packages to compete with the big networks (eg, the-wire.com, 1994 in Toronto and bway.net 1995 in New York). These providers first offered access through telephone and modem, just as did the early online services providers. By the early 2000s, these independent ISPs had largely been supplanted by high speed and broadband access through cable and phone companies, as well as wireless access. The importance of the online services industry was vital in "paving the road" for the information superhighway. When Mosaic and Netscape were released in 1994, they had a ready audience of more than 10 million people who were able to download their first web browser through an online service. Though ISPs quickly began offering software packages with setup to their customers, this brief period gave many users their first online experience. Two online services in particular, Prodigy and AOL, are often confused with the Internet, or the origins of the Internet. Prodigy's Chief Technical Officer said in 1999: "Eleven years ago, the Internet was just an intangible dream that Prodigy brought to life. Now it is a force to be reckoned with." Despite that statement, neither service provided the back bone for the Internet, nor did either start the Internet. == Online service interfaces == The first online service used a simple text-based interface in which content was largely text only and users made choices via a command prompt. This allowed just about any computer with a modem and terminal communications program the ability to access these text-based online services. CompuServe would later offer, with the advent of the Apple Macintosh and Microsoft Windows-based PCs, a GUI interface program for their service. This provided a very rudimentary GUI interface. CompuServe continued to offer text-only access for those needing it. Online services like Prodigy and AOL developed their online service around a GUI and thus unlike CompuServe's early GUI-based software, these online services provided a more robust GUI interface. Early GUI-base
Outline of natural language processing
Natural language processing is computer activity in which computers are entailed to analyze, understand, alter, or generate natural language. This includes the automation of any or all linguistic forms, activities, or methods of communication, such as conversation, correspondence, reading, written composition, dictation, publishing, translation, lip reading, and so on. Natural-language processing is also the name of the branch of computer science, artificial intelligence, and linguistics concerned with enabling computers to engage in communication using natural language(s) in all forms, including but not limited to speech, print, writing, and signing. The following outline is provided as an overview of and topical guide to natural-language processing: == Natural-language processing == Natural-language processing can be described as all of the following: A field of science – systematic enterprise that builds and organizes knowledge in the form of testable explanations and predictions about the universe. An applied science – field that applies human knowledge to build or design useful things. A field of computer science – scientific and practical approach to computation and its applications. A branch of artificial intelligence – intelligence of machines and robots and the branch of computer science that aims to create it. A subfield of computational linguistics – interdisciplinary field dealing with the statistical or rule-based modeling of natural language from a computational perspective. An application of engineering – science, skill, and profession of acquiring and applying scientific, economic, social, and practical knowledge, in order to design and also build structures, machines, devices, systems, materials and processes. An application of software engineering – application of a systematic, disciplined, quantifiable approach to the design, development, operation, and maintenance of software, and the study of these approaches; that is, the application of engineering to software. A subfield of computer programming – process of designing, writing, testing, debugging, and maintaining the source code of computer programs. This source code is written in one or more programming languages (such as Java, C++, C#, Python, etc.). The purpose of programming is to create a set of instructions that computers use to perform specific operations or to exhibit desired behaviors. A subfield of artificial intelligence programming – A type of system – set of interacting or interdependent components forming an integrated whole or a set of elements (often called 'components' ) and relationships which are different from relationships of the set or its elements to other elements or sets. A system that includes software – software is a collection of computer programs and related data that provides the instructions for telling a computer what to do and how to do it. Software refers to one or more computer programs and data held in the storage of the computer. In other words, software is a set of programs, procedures, algorithms and its documentation concerned with the operation of a data processing system. A type of technology – making, modification, usage, and knowledge of tools, machines, techniques, crafts, systems, methods of organization, in order to solve a problem, improve a preexisting solution to a problem, achieve a goal, handle an applied input/output relation or perform a specific function. It can also refer to the collection of such tools, machinery, modifications, arrangements and procedures. Technologies significantly affect human as well as other animal species' ability to control and adapt to their natural environments. A form of computer technology – computers and their application. NLP makes use of computers, image scanners, microphones, and many types of software programs. Language technology – consists of natural-language processing (NLP) and computational linguistics (CL) on the one hand, and speech technology on the other. It also includes many application oriented aspects of these. It is often called human language technology (HLT). == Prerequisite technologies == The following technologies make natural-language processing possible: Communication – the activity of a source sending a message to a receiver Language – Speech – Writing – Computing – Computers – Computer programming – Information extraction – User interface – Software – Text editing – program used to edit plain text files Word processing – piece of software used for composing, editing, formatting, printing documents Input devices – pieces of hardware for sending data to a computer to be processed Computer keyboard – typewriter style input device whose input is converted into various data depending on the circumstances Image scanners – == Subfields of natural-language processing == Information extraction (IE) – field concerned in general with the extraction of semantic information from text. This covers tasks such as named-entity recognition, coreference resolution, relationship extraction, etc. Ontology engineering – field that studies the methods and methodologies for building ontologies, which are formal representations of a set of concepts within a domain and the relationships between those concepts. Speech processing – field that covers speech recognition, text-to-speech and related tasks. Statistical natural-language processing – Statistical semantics – a subfield of computational semantics that establishes semantic relations between words to examine their contexts. Distributional semantics – a subfield of statistical semantics that examines the semantic relationship of words across a corpora or in large samples of data. == Related fields == Natural-language processing contributes to, and makes use of (the theories, tools, and methodologies from), the following fields: Automated reasoning – area of computer science and mathematical logic dedicated to understanding various aspects of reasoning, and producing software which allows computers to reason completely, or nearly completely, automatically. A sub-field of artificial intelligence, automatic reasoning is also grounded in theoretical computer science and philosophy of mind. Linguistics – scientific study of human language. Natural-language processing requires understanding of the structure and application of language, and therefore it draws heavily from linguistics. Applied linguistics – interdisciplinary field of study that identifies, investigates, and offers solutions to language-related real-life problems. Some of the academic fields related to applied linguistics are education, linguistics, psychology, computer science, anthropology, and sociology. Some of the subfields of applied linguistics relevant to natural-language processing are: Bilingualism / Multilingualism – Computer-mediated communication (CMC) – any communicative transaction that occurs through the use of two or more networked computers. Research on CMC focuses largely on the social effects of different computer-supported communication technologies. Many recent studies involve Internet-based social networking supported by social software. Contrastive linguistics – practice-oriented linguistic approach that seeks to describe the differences and similarities between a pair of languages. Conversation analysis (CA) – approach to the study of social interaction, embracing both verbal and non-verbal conduct, in situations of everyday life. Turn-taking is one aspect of language use that is studied by CA. Discourse analysis – various approaches to analyzing written, vocal, or sign language use or any significant semiotic event. Forensic linguistics – application of linguistic knowledge, methods and insights to the forensic context of law, language, crime investigation, trial, and judicial procedure. Interlinguistics – study of improving communications between people of different first languages with the use of ethnic and auxiliary languages (lingua franca). For instance by use of intentional international auxiliary languages, such as Esperanto or Interlingua, or spontaneous interlanguages known as pidgin languages. Language assessment – assessment of first, second or other language in the school, college, or university context; assessment of language use in the workplace; and assessment of language in the immigration, citizenship, and asylum contexts. The assessment may include analyses of listening, speaking, reading, writing or cultural understanding, with respect to understanding how the language works theoretically and the ability to use the language practically. Language pedagogy – science and art of language education, including approaches and methods of language teaching and study. Natural-language processing is used in programs designed to teach language, including first- and second-language training. Language planning – Language policy – Lexicography – Literacies – Pragmatics – Second-language acquisition – Stylistics – Translation – Comp
Stephanie Dinkins
Stephanie Dinkins (born 1964) is a transdisciplinary American artist based in Brooklyn, New York. She creates art about artificial intelligence (AI) as it intersects race, gender, and history. Her aim is to "create a unique culturally attuned AI entity in collaboration with coders, engineers and in close consultation with local communities of color that reflects and is empowered to work toward the goals of its community." Dinkins projects include Conversations with Bina48, a series of conversations between Dinkins and the first social, artificially intelligent humanoid robot BINA48 who looks like a black woman and Not the Only One, a multigenerational artificially intelligent memoir trained off of three generations of Dinkins's family. == Early life and education == Dinkins was born in Perth Amboy, New Jersey to Black American parents who raised her in Staten Island, New York. She credits her grandmother with teaching her how to think about art as a social practice, saying "my grandmother . . . was a gardener and the garden was her art . . . that was a community practice." Dinkins attended the International Center of Photography School in New York City in 1995, where she completed the general studies in photography certificate program. Dinkins received a MFA in photography from the Maryland Institute College of Art in 1997 She completed the Independent Study Program at the Whitney Museum of American Art in 1998. == Career == Dinkins is the Yayoi Kusama Professor of Art at Stony Brook University in New York. == Activism == Dinkins advocates for co-creation within a social practice art framework, so that vulnerable communities understand how to use technology to their advantage, instead of being subjected to their use. This is exemplified in her works such as Project al-Khwarzmi, a series of workshops entitled PAK POP-UP at the nonprofit community center Recess in Brooklyn, NY. The workshops involved collaborating with youth in the criminal justice system and uplifting the voices of vulnerable communities in determining how technologies are created and utilized. Dinkins warns of the dangers to members of minority groups that are absent from the creation of the computer algorithms that now affect their lives. == Art == Dinkins's practice employs technologies including, but not limited to, new media such as artificial intelligence and machine learning. Dinkins uses oral history techniques of interviewing to craft community-authored narratives and databases which inform the subjects of her work and serve as acts of social intervention or protest. === Conversations with Bina48 (2014–present) === Dinkins began working on Conversations with Bina48 in 2014. For the series, Dinkins recorded her conversations with BINA48, a social robot that resembles a middle-aged black woman. Dinkins mirrors Bina48 while they discuss identity and technological singularity. In 2010, Hanson Robotics, an engineering and robotics company known for its development of humanoid robots, developed and released BINA48. Bina48 is a robot modeled after the memories, beliefs, attitudes, commentary and mannerisms of Bina Aspen Rothblatt, the spousal partner of Martine Rothblatt. Both Bina and Martine Rothblatt own Bina48 under their organization, the Terasem Movement Foundation. Five years after Bina48 was released, Dinkins came across a YouTube video of Bina48. She asked, "how did a black woman become the most advanced of the technologies at the time?" Her questioning led her to travel to Lincoln, Vermont (the site of the Terasem Movement Foundation) where she conducted a series of interviews with Bina48 and engaged the robot in conversations pertaining to race, intimacy and the nature of being. The conversations suggest opportunities for complementing human existence with artificially intelligent agents that have an identity and history, but also show artificial intelligence's current limitations. Although it is based on a black woman, Dinkins found that Bina48 was shaped by the biases of its white, male creators. === Project al Kwarizmi (PAK) (2017–present) === Project al Kwarizmi (PAK) was a series of pop up workshops in Brooklyn, NY at Eyebeam and Recess; Manhattan, New York at Google; and Durham, North Carolina at Duke University. The workshops were centered for "communities of color that use art as a vehicle to help citizens understand how algorithms, the artificially intelligent systems they underpin, and big data impact their lives and empowers them to do something about it. Project al-Khwarizmi uses art and aesthetics as the common language to help citizens understand what algorithms and artificial intelligent systems are, and where these systems already impact our daily lives." === Not the Only One (N'TOO) (2018–present) === Not the only one (N’TOO) is a voice-interactive chatbot that was trained with data from members of her family to tell a multi-generational story. Dinkins described Not The Only One (NTOO or N'TOO) as an "experimental" multigenerational memoir of one Black American family told from the "mind" of an artificial intelligence of evolving intellect. N'TOO uses a recursive neural network, a deep learning algorithm. It is a voice-interactive AI robot designed, trained, and aligned with the needs and ideals of black and brown people who are drastically underrepresented in the tech sector. NTOO can also be described as a "physically embodied artificially intelligent agent that senses and acts on its world." == Exhibitions == Dinkins's work is exhibited internationally at various public, private, community, and institutional venues, including the Whitney Museum of American Art, the de Young Museum, the Philadelphia Museum of Art, the Studio Museum in Harlem;, Museum of Contemporary Photography, the Long Island Museum of American Art, History, and Carriages, the International Center of Photography in New York, Herning Kunstmuseum in Herning, Denmark, The Barbican in London, UK, Islip Art Museum, Wave Hill, Taller Boricua, the Queens Museum, and the corner of Putnam and Malcolm X Blvd in Bedford Stuyvesant, Brooklyn, New York. She has presented her work in symposia at the Museum of Modern Art, amongst other venues. == Future Histories Studio == Dinkins is the founder and director of Future Histories Studio, a research laboratory for arts-centered inquiry and production based at Stony Brook University. The studio was established with support from the Mellon Foundation as part of the Digital Inquiry, Speculation, Collaboration, and Optimism (DISCO) network. Future Histories Studio operates as an interdisciplinary hub exploring the intersections of art, technology, race, and storytelling through collaborative and practice-based research. Its activities include exhibitions, workshops, and public programs that examine the social and cultural implications of emerging technologies, particularly artificial intelligence and data systems. == Awards and recognition == Dinkins is the recipient of many awards, including: the 2023 LG Guggenheim Award, an international art prize established as part of a long-term global partnership between LG Group and the Solomon R. Guggenheim Museum to recognize groundbreaking artists in technology-based art; a Berggruen Institute artist fellowship; a Sundance New Frontiers Story Lab fellowship; a Soros Equality Fellowship; a Lucas Artists fellowship; a Creative Capital grant; a Bell Labs artist residency; a Blade of Grass fellowship; and a Data & Society fellowship. == Media coverage == Dinkins appeared in episode six of the HBO television series Random Acts of Flyness directed by Terence Nance, where she described her conversations with BINA48. == Other activities == Dinkins was part of the juries that selected Shu Lea Cheang for the LG Guggenheim Award in 2024.
Fuzzy associative matrix
A fuzzy associative matrix expresses fuzzy logic rules in tabular form. These rules usually take two variables as input, mapping cleanly to a two-dimensional matrix, although theoretically a matrix of any number of dimensions is possible. From the perspective of neuro-fuzzy systems, the mathematical matrix is called a "Fuzzy associative memory" because it stores the weights of the perceptron. == Applications == In the context of game AI programming, a fuzzy associative matrix helps to develop the rules for non-player characters. Suppose a professional is tasked with writing fuzzy logic rules for a video game monster. In the game being built, entities have two variables: hit points (HP) and firepower (FP): This translates to: IF MonsterHP IS VeryLowHP AND MonsterFP IS VeryWeakFP THEN Retreat IF MonsterHP IS LowHP AND MonsterFP IS VeryWeakFP THEN Retreat IF MonsterHP IS MediumHP AND MonsterFP is VeryWeakFP THEN Defend Multiple rules can fire at once, and often will, because the distinction between "very low" and "low" is fuzzy. If it is more "very low" than it is low, then the "very low" rule will generate a stronger response. The program will evaluate all the rules that fire and use an appropriate defuzzification method to generate its actual response. An implementation of this system might use either the matrix or the explicit IF/THEN form. The matrix makes it easy to visualize the system, but it also makes it impossible to add a third variable just for one rule, so it is less flexible. == Identify a rule set == There is no inherent pattern in the matrix. It appears as if the rules were just made up, and indeed they were. This is both a strength and a weakness of fuzzy logic in general. It is often impractical or impossible to find an exact set of rules or formulae for dealing with a specific situation. For a sufficiently complex game, a mathematician would not be able to study the system and figure out a mathematically accurate set of rules. However, this weakness is intrinsic to the realities of the situation, not of fuzzy logic itself. The strength of the system is that even if one of the rules is wrong, even greatly wrong, other rules that are correct are likely to fire as well and they may compensate for the error. This does not mean a fuzzy system should be sloppy. Depending on the system, it might get away with being sloppy, but it will underperform. While the rules are fairly arbitrary, they should be chosen carefully. If possible, an expert should decide on the rules, and the sets and rules should be tested vigorously and refined as needed. In this way, a fuzzy system is like an expert system. (Fuzzy logic is used in many true expert systems, as well.)
Megami Tensei
Megami Tensei, marketed internationally as Shin Megami Tensei (formerly Revelations), is a Japanese media franchise created by Aya Nishitani, Kouji "Cozy" Okada, Ginichiro Suzuki, and Kazunari Suzuki. Primarily developed and published by Atlus, the franchise consists of multiple subseries and covers multiple role-playing video game genres including tactical role-playing, action role-playing, and massively multiplayer online role-playing. The first two titles in the series were published by Namco (now Bandai Namco Entertainment), but have been almost always published by Atlus in Japan and North America since the release of Shin Megami Tensei. For Europe, Atlus publishes the games through third-party companies. The series was originally based on Digital Devil Story, a science fiction novel series by Aya Nishitani. The series takes its name from the first book's subtitle. Most Megami Tensei titles are stand-alone entries with their own stories and characters. Recurring elements include plot themes, a story shaped by the player's choices, and the ability to fight using and often recruit creatures (demons, Personas) to aid the player in battle. Elements of philosophy, religion, occultism, and science fiction have all been incorporated into the series at different times. While not maintaining as high a profile as series such as Final Fantasy and Dragon Quest, it is highly popular in Japan and maintains a strong cult following in the West, finding critical and commercial success. The series has become well known for its artistic direction, challenging gameplay, and music, but raised controversy over its mature content, dark themes, and use of Christian religious imagery. Additional media include manga adaptations, anime films, and television series. In Japan, some games in the series do not use the "Megami Tensei" title, such as the Persona sub-series. Many of the early games in the series were not localized due to potentially controversial content including religious references, and later due to their age. English localizations have used the "Shin Megami Tensei" moniker since the release of Shin Megami Tensei: Nocturne in 2004. == Titles == === Games === The first installment in the franchise, Digital Devil Story: Megami Tensei, was released on September 11, 1987. The following entries have nearly always been unrelated to each other except in carrying over thematic and gameplay elements. The Megami Tensei games, and the later Shin Megami Tensei titles form the core of the series, while other subseries such as Persona, Devil Children, and Devil Summoner are spin-offs marketed as part of the franchise. There are also stand-alone spin-off titles. ==== Main series ==== Two entries were released for the Famicom: Digital Devil Story: Megami Tensei in 1987, and Digital Devil Story: Megami Tensei II in 1990. The two titles are unrelated to each other in terms of story, and each introduced the basic gameplay and story mechanics that would come to define the series. Three entries were released for the Super Famicom: Shin Megami Tensei in 1992, followed byShin Megami Tensei II in 1994, and Shin Megami Tensei If..., released later in the same year. Shin Megami Tensei III: Nocturne was released in 2003 for the PlayStation 2. Its Maniax Edition director's cut was released in Japan and North America in 2004, and in Europe in 2005. The numeral was dropped for its North American release, and its title changed to Shin Megami Tensei: Lucifer's Call in Europe. Shin Megami Tensei IV for the Nintendo 3DS was released in 2013 in Japan and North America, and a year later in Europe as a digital-only release. Another game set in the same universe, Shin Megami Tensei IV: Apocalypse, was released for the 3DS in February 2016 in Japan. Shin Megami Tensei V was released on the Nintendo Switch in 2021. An enhanced version of the game titled Shin Megami Tensei V: Vengeance was released in June 2024 for Microsoft Windows, Nintendo Switch, PlayStation 4, PlayStation 5, Xbox One and Xbox Series X/S. In addition to the main series, there are also numerous spin-offs. Shin Megami Tensei: Nine, was released for the Xbox in 2002. Originally designed as a massively multiplayer online role-playing game (MMORPG), it was later split into a dual single-player and multiplayer package, and the single-player version released first. The online version was delayed and eventually cancelled as the developers could not manage the required online capacities using Xbox Live. Shin Megami Tensei: Imagine, a true MMOROG released for Microsoft Windows, was released in 2007 in Japan, 2008 in North America, and 2009 in Europe. Western service was terminated in 2014 when Marvelous USA, the game's then-handlers, shut down their PC Online game department. Shin Megami Tensei: Strange Journey was released for the Nintendo DS in 2009 in Japan and 2010 in North America. Its Japanese service ended in May 2016. A smartphone game, Shin Megami Tensei: Liberation Dx2, was released in 2018. ==== Persona ==== The Persona series is the largest and most popular spin-off from the Megami Tensei series. The first entry in the series, Megami Ibunroku Persona (originally released overseas as Revelations: Persona), was released in 1996 in Japan and North America. The first Persona 2 title, Innocent Sin, was released in 1999 in Japan. The second game, Eternal Punishment, was released in 2000 in Japan and North America. Persona 3 was released in 2006 in Japan, 2007 in North America, and 2008 in Europe. Its sequel, Persona 4, was released in 2008 in Japan and North America, and in 2009 in Europe. A sixth entry in the series, Persona 5, was released in Japan on September 15, 2016, and was released in North America and Europe on April 4, 2017, to critical acclaim. The series also features spin-offs, including Persona Q: Shadow of the Labyrinth and Persona Q2: New Cinema Labyrinth, two fighting games Persona 4 Arena and its sequel Arena Ultimax as well as the crossover fighting game BlazBlue: Cross Tag Battle, tactical role-playing game Persona 5 Tactica, action role-playing game Persona 5 Strikers and rhythm games Persona 4: Dancing All Night, Persona 3: Dancing in Moonlight, and Persona 5: Dancing in Starlight. While Persona 3 and 4 used the Shin Megami Tensei moniker in the West, it was dropped for the Persona 4 Arena duology and Persona 4 Golden as it would have made the titles too long to be practical. ==== Devil Summoner ==== The Devil Summoner subseries began in 1995 with the release of Shin Megami Tensei: Devil Summoner. It was followed by Devil Summoner: Soul Hackers in 1997, then followed by Soul Hackers 2, released in 2022. Two action role-playing prequels set in 1920s Tokyo were also developed, which revolve around demon summoner Raidou Kuzunoha: Raidou Kuzunoha vs. the Soulless Army was released in 2006, and Raidou Kuzunoha vs. King Abaddon was released in 2008. ==== Other spin-offs ==== Aside from Persona and Devil Summoner, there are other spin-off series covering multiple genres. After the release of Shin Megami Tensei II, Atlus began focusing work on building spin-offs and subseries that would form part of the Megami Tensei franchise. Shortly after Nocturne's release, a duology titled Digital Devil Saga (Digital Devil Saga: Avatar Tuner in Japan) was created based around similar systems to Nocturne, and was also intended as a more accessible gaming experience. Two tactical role-playing games have been developed by Atlus for the DS under the Devil Survivor moniker: the original Devil Survivor and Devil Survivor 2. Both have received expanded ports for the 3DS. Other subseries include Last Bible, a series aimed at a younger audience and using a pure fantasy setting; Devil Children, which was inspired by the popular Pokémon series; and Majin Tensei, a series of strategy games. Two notable stand-alone spin-offs are action spin-off Jack Bros. and Tokyo Mirage Sessions ♯FE, a crossover with Intelligent Systems' Fire Emblem series. === Related media === Several titles in the franchise have received anime and manga adaptations. Persona 3 received both a four-part theatrical adaptation (#1 Spring of Birth, #2 Midsummer Knight's Dream, #3 Falling Down, #4 Winter of Rebirth), and a spin-off series titled Persona: Trinity Soul. Persona 4 received two adaptations: Persona 4: The Animation, based on the original game, and Persona 4: The Golden Animation, based on its expanded PlayStation Vita port. A live-action television series based on the original Devil Summoner was broadcast between 1997 and 1998. Devil Survivor 2 also received an anime adaptation of the same name, and the Devil Children series received two anime adaptations. Multiple Shin Megami Tensei and Persona titles have received manga and CD drama adaptations. Action figures and merchandise related to Persona have also been produced. == Common elements == Despite most games in the series taking place in different continuities, they do share certain elements
Algorithmic bias
Algorithmic bias describes systematic and repeatable harmful tendency in a computerized sociotechnical system to create "unfair" outcomes, such as "privileging" one category over another in ways that may or may not be different from the intended function of the algorithm. Bias can emerge from many factors, including intentionally biased design decisions or the unintended or unanticipated use or decisions relating to the way data is coded, collected, selected or used to train the algorithm. For example, algorithmic bias has been observed in search engine results and social media platforms. This bias can have impacts ranging from privacy violations to reinforcing social biases of race, gender, sexuality, and ethnicity. The study of algorithmic bias is most concerned with algorithms that reflect "systematic and unfair" discrimination. This bias has only recently been addressed in legal frameworks, such as the European Union's General Data Protection Regulation (enforced in 2018) and the Artificial Intelligence Act (proposed in 2021 and adopted in 2024). As algorithms expand their ability to organize society, politics, institutions, and behavior, sociologists have become concerned with the ways in which unanticipated output and manipulation of data can impact the physical world. Because algorithms are often considered to be neutral and unbiased, they can inaccurately project greater authority than human expertise (in part due to the psychological phenomenon of automation bias), and in some cases, reliance on algorithms can displace human responsibility for their outcomes, without last mile thinking. Bias can enter into algorithmic systems as a result of pre-existing cultural, social, or institutional expectations; by how features and labels are chosen; because of technical limitations of their design; or by being used in unanticipated contexts or by audiences who are not considered in the software's initial design. Algorithmic bias has been cited in cases ranging from election outcomes to the spread of online hate speech. It has also arisen in criminal justice, healthcare, and hiring, compounding existing racial, socioeconomic, and gender biases. The relative inability of facial recognition technology to accurately identify darker-skinned faces has been linked to multiple wrongful arrests of black men, an issue stemming from imbalanced datasets. Problems in understanding, researching, and discovering algorithmic bias persist due to the proprietary nature of algorithms, which are typically treated as trade secrets. Even when full transparency is provided, the complexity of certain algorithms poses a barrier to understanding their functioning. Furthermore, algorithms may change, or respond to input or output in ways that cannot be anticipated or easily reproduced for analysis. In many cases, even within a single website or application, there is no single "algorithm" to examine, but a network of many interrelated programs and data inputs, even between users of the same service. A 2021 survey identified multiple forms of algorithmic bias, including historical, representation, and measurement biases, each of which can contribute to unfair outcomes. == Definitions == Algorithms are difficult to define, but may be generally understood as lists of instructions that determine how programs read, collect, process, and analyze data to generate a usable output. For a rigorous technical introduction, see Algorithms. Advances in computer hardware and software have led to an increased capability to process, store and transmit data. This has in turn made the design and adoption of technologies such as machine learning and artificial intelligence technically and commercially feasible. By analyzing and processing data, algorithms are the backbone of search engines, social media websites, recommendation engines, online retail, online advertising, and more. Contemporary social scientists are concerned with algorithmic processes embedded into hardware and software applications because of their political and social impact, and question the underlying assumptions of an algorithm's neutrality. The term algorithmic bias describes systematic and repeatable errors that create unfair outcomes, such as privileging one arbitrary group of users over others. For example, a credit score algorithm may deny a loan without being unfair, if it is consistently weighing relevant financial criteria. If the algorithm recommends loans to one group of users, but denies loans to another set of nearly identical users based on unrelated criteria, and if this behavior can be repeated across multiple occurrences, an algorithm can be described as biased. This bias may be intentional or unintentional (for example, it can come from biased data obtained from a worker that previously did the job the algorithm is going to do from now on). == Methods == Bias can be introduced to an algorithm in several ways. During the assemblage of a dataset, data may be collected, digitized, adapted, and entered into a database according to human-designed cataloging criteria. Next, programmers assign priorities, or hierarchies, for how a program assesses and sorts that data. This requires human decisions about how data is categorized, and which data is included or discarded. Some algorithms collect their own data based on human-selected criteria, which can also reflect the bias of human designers. Other algorithms may reinforce stereotypes and preferences as they process and display "relevant" data for human users, for example, by selecting information based on previous choices of a similar user or group of users. Beyond assembling and processing data, bias can emerge as a result of design. For example, algorithms that determine the allocation of resources or scrutiny (such as determining school placements) may inadvertently discriminate against a category when determining risk based on similar users (as in credit scores). Meanwhile, recommendation engines that work by associating users with similar users, or that make use of inferred marketing traits, might rely on inaccurate associations that reflect broad ethnic, gender, socio-economic, or racial stereotypes. Another example comes from determining criteria for what is included and excluded from results. These criteria could present unanticipated outcomes for search results, such as with flight-recommendation software that omits flights that do not follow the sponsoring airline's flight paths. Algorithms may also display an uncertainty bias, offering more confident assessments when larger data sets are available. This can skew algorithmic processes toward results that more closely correspond with larger samples, which may disregard data from underrepresented populations. == History == === Early critiques === The earliest computer programs were designed to mimic human reasoning and deductions, and were deemed to be functioning when they successfully and consistently reproduced that human logic. In his 1976 book Computer Power and Human Reason, artificial intelligence pioneer Joseph Weizenbaum suggested that bias could arise both from the data used in a program, but also from the way a program is coded. Weizenbaum wrote that programs are a sequence of rules created by humans for a computer to follow. By following those rules consistently, such programs "embody law", that is, enforce a specific way to solve problems. The rules a computer follows are based on the assumptions of a computer programmer for how these problems might be solved. That means the code could incorporate the programmer's imagination of how the world works, including their biases and expectations. While a computer program can incorporate bias in this way, Weizenbaum also noted that any data fed to a machine additionally reflects "human decision making processes" as data is being selected. Finally, he noted that machines might also transfer good information with unintended consequences if users are unclear about how to interpret the results. Weizenbaum warned against trusting decisions made by computer programs that a user doesn't understand, comparing such faith to a tourist who can find his way to a hotel room exclusively by turning left or right on a coin toss. Crucially, the tourist has no basis of understanding how or why he arrived at his destination, and a successful arrival does not mean the process is accurate or reliable. An early example of algorithmic bias resulted in as many as 60 women and ethnic minorities denied entry to St. George's Hospital Medical School per year from 1982 to 1986, based on implementation of a new computer-guidance assessment system that denied entry to women and men with "foreign-sounding names" based on historical trends in admissions. While many schools at the time employed similar biases in their selection process, St. George was most notable for automating said bias through the use of an algorithm, thus gaining the attention of people on a much
Mobile Fortify
Mobile Fortify is a mobile app used by United States Immigration and Customs Enforcement (ICE) on their government-issued phones. The app allows agents to take a photo in order to gather biometrics, including contactless fingerprints and faceprints, for the purpose of identifying an individual and their potential immigration status. The app was created by NEC. == History == In June 2025, use of Mobile Fortify by ICE was uncovered through leaked emails and the user manual, reported by 404 Media. The app is internally developed, and details of the parent company and developer were initially unknown. In January 2026, the DHS's 2025 AI Use Case Inventory revealed the vendor as NEC Corporation, an international conglomerate with subsidiaries in Argentina, Australia, China, India and Malaysia. Later that month, several senators demanded transparency around the app and its origins, and that ICE stop using it. A second letter was sent again in November, after hearing no response to the previous letter from ICE. == Technology == Unlike other facial recognition software, Fortify uses federally linked databases. By contrast, Clearview AI uses public social media databases for biometric scanning. Federal databases include DHS's automated biometric identification system (IDENT), containing more than 270 million biometric records, and Customs and Border Protection's Traveler Verification Service. The State Department's visa and passport photo database, the FBI's National Crime Information Center, National Law Enforcement Telecommunications Systems, and CBP's TECS and Seized Assets and Case Tracing System (SEACATS). == Oversight == Several senators urged ICE to stop using the app for fear of infringing on fourth amendment and first amendment rights, and requested details on who developed the app, when it was deployed, whether the app was tested for accuracy, and policies and practices governing its use. In June 2025, they sent an open letter to Todd Lyons, ICE acting director, signed by senators Cory Booker, Chris Van Hollen, Ed Markey, Bernie Sanders, Adam Schiff, Tina Smith, Elizabeth Warren, and Ron Wyden. On November 3, a second letter was sent to the ICE by senators, after not receiving answers to questions from the previous letter deadlined for October 2. == Criticism == Mobile Fortify, and ICE's use of similar biometric identification technologies (such as Mobile Identify, an app similar to Mobile Fortify to be used by local or regional law enforcement to assist in immigration enforcement ) has faced scrutiny from a variety of digital rights organizations, politicians, and news outlets. The criticism is already considered to potentially be a reason why the similar Mobile Identify app was pulled from the Google Play Store. Facial recognition technologies are known to produce false-positives and generally unreliable results, especially on those with darker skin tones. ICE has already previously mistakenly arrested a U.S. citizen under the belief he was illegally in the country, and later stated that he "could be deported based on biometric confirmation of his identity" prior to his release. U.S. representative Bennie Thompson, ranking member of the House Homeland Security Committee has previously commented that "ICE officials have told us that an apparent biometric match by Mobile Fortify is a ‘definitive’ determination of a person's status and that an ICE officer may ignore evidence of American citizenship—including a birth certificate—if the app says the person is an alien," and that "Mobile Fortify is a dangerous tool in the hands of ICE, and it puts American citizens at risk of detention and even deportation," On January 19, 2026, 404 Media reported on a case where a woman, identified in court documents as "MJMA", was scanned by Mobile Fortify twice in the same interaction, and two entirely different names were provided by the app. According to the Innovation Law Lab, whose attorneys are representing MJMA, both of the names were incorrect. ICE has stated that they will not allow people to decline to be scanned by Mobile Fortify, and that photos taken, even those of U.S. citizens, will be stored for 15 years, something that has been criticized primarily because ICE has not performed a Privacy Impact Assessment (PIA) for Mobile Fortify, the right to decline other forms of biometric verification to the U.S. government is often available under other circumstances, and the 15 year window is viewed as unnecessarily large.