Artificial intelligence is the simulation of human decision making. Artificial affectivity is the simulation of human emotion. Emotion has historically been underrated in artificial intelligence. Without emotion, otherwise rational human beings cannot make decisions. Tellingly, the classic test for artificial intelligence, the Turing Test, is a test of software's performance in conversation rather than at number crunching.
Joseph Weizenbaum's "Eliza" system of the late 1960s featured a simulated Rogerian psychoanalyst ("Doctor", which most people just call Eliza). Kenneth Colby's early 1970s "Parry" simulated the conversation of a paranoid schizophrenic. Parry had a simulation of beliefs and mental state, but Doctor just echoed back the words of its user. Both manage to build an emotional rapport with their conversation partners until they make a mistake and break the user's suspension of disbelief.
Modelling human personalities and emotions as hierarchies of related concepts has a long history in psychology. But the various proposed taxonomies disagree even on what a basic emotion is, so there is a lot of work remaining to be done before we can describe emotion in a robust manner. This hasn't prevented these models being used outside of psychology.
You may have done a personality type test during a job interview, or for fun on the Web. Writers can buy books describing personality traits types to flesh out the characters in their stories. The pen-and-paper role-playing games that followed Dungeons & Dragons in the 1970s eventually added systems for modelling personality and the life stories that influence it. Few adopted scientific models although an article in "Challenge" magazine did so rigorously.
Rosalid Picard's 2000 book "Affective Computing" presented examples of emotional models and rule-based computer simulation of them to both parse human emotions and represent computer output using them. The Sims, the most popular computer game of all time in the early 2000s, contained a simple emotional simulation for each game character.
A switch from rule-based expert systems to internet-data-processing statistical methods can be seen in affective computing as well as in artificial intelligence. The best example of this is Jonathan Harris and Sep Kamvar's project "We Feel Fine" which extracts statements of the form "I feel X" from blog posts along with information about who has made this stament, when and where. This affective sample of the blogosphere is then made available for other software to use through an API.
The DGRs use We Feel Fine's API to set their inner emotional state. They search for users that match their demographic information, then (if they find a match) they choose words as tags that represent how they express or act on that emotion. The DGRs are not artificial intelligences, they do not make practical decisions on the basis of a disembodied and disinterested emulation of human intellect. They are artificial affectivities. To ask whether they actually feel is like asking whether a submarine can swim (to borrow Edsger Dijkstra's response to the question of whether computers can think). They are performative, functional equivalents to human emoting within the limited affective bandwidth of microblogging.
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