Kasiski enlisted in East Prussia’s 33rd Infantry Regiment on 20 March, 1823 at the age of 17. In May 1824, he was promoted to the rank of Master Sergeant, and eight months later was commissioned as a Second Lieutenant in February 1825. It took fourteen years to earn his next promotion when, in May 1839, he advanced to the rank of First Lieutenant. His next advancement was quicker, promoted to Captain in November 1842. Kasiski finally retired from active service with the rank of Major on 17 February 1852.

Between 1860 and 1868 he was the commander of a National Guard battalion.

In 1863, Kasiski published a 95-page book on cryptography, Die Geheimschriften und die Dechiffrierkunst (German, “Secret writing and the Art of Deciphering”). This was the first published account of a procedure for attacking polyalphabetic substitution ciphers, especially the Vigenère cipher (although it is possible Charles Babbage was already aware of a similar method but had kept it secret). The method relied on the analysis of gaps between repeated fragments in the ciphertext; such analysis can give hints as to the length of the key used. This technique is known as Kasiski examination.

The significance of Kasiski’s cryptanalytic work was not widely realised at the time, and he turned his mind to archaeology instead. The later years of his life were spent at Neustettin (Szczecinek); the 11th edition of Encyclopædia Britannica cited a scholarly article by Kasiski in its entry on the town. Historian David Kahn notes, “Kasiski died on May 22, 1881, almost certainly without realizing that he had wrought a revolution in cryptology” (The Codebreakers)

While studying mathematics at Poznań University, Rejewski had attended a secret cryptology course conducted by the Polish General Staff’s Cipher Bureau, which he joined full-time in 1932. The Bureau had achieved little success reading Enigma and in late 1932 set Rejewski to work on the problem. After only a few weeks, he deduced the secret internal wiring of the Enigma. Rejewski and his two mathematician colleagues then developed an assortment of techniques for the regular decryption of Enigma messages. Rejewski’s contributions included devising the cryptologic “card catalog,” derived using his “cyclometer,” and the “cryptologic bomb.”

Five weeks before the German invasion of Poland in 1939, Rejewski and his colleagues presented their results on Enigma decryption to French and British intelligence representatives. Shortly after the outbreak of war, the Polish cryptologists were evacuated to France, where they continued their work in collaboration with the British and French. They were again compelled to evacuate after the fall of France in June 1940, but within months returned to work undercover in Vichy France. After the country was fully occupied by Germany in November 1942, Rejewski and fellow mathematician Henryk Zygalski fled, via Spain, Portugal and Gibraltar, to Britain. There they worked at a Polish Army unit, solving low-level German ciphers. In 1946 Rejewski returned to his family in Poland and worked as an accountant, remaining silent about his cryptologic work until 1967.

The British scientist Richard Dawkins introduced the word “meme” in The Selfish Gene (1976) as a basis for discussion of evolutionary principles in explaining the spread of ideas and cultural phenomena. Examples of memes given in the book included melodies, catch-phrases, beliefs (notably religious beliefs), clothing fashion, and the technology of building arches.

Meme-theorists contend that memes evolve by natural selection (in a manner similar to that of biological evolution) through the processes of variation, mutation, competition, and inheritance influencing an individual entity’s reproductive success. Memes spread through the behaviors that they generate in their hosts. Memes that propagate less prolifically may become extinct, while others may survive, spread, and (for better or for worse) mutate. Theorists point out that memes which replicate the most effectively spread best, and some memes may replicate effectively even when they prove detrimental to the welfare of their hosts.

A field of study called memetics arose in the 1990s to explore the concepts and transmission of memes in terms of an evolutionary model. Criticism from a variety of fronts has challenged the notion that scholarship can examine memes empirically. Some commentators question the idea that one can meaningfully categorize culture in terms of discrete units.

The above definition has emerged from the writings of Douglas Hofstadter (1979), Peter Russell (1983), Tom Atlee (1993), Pierre Lévy (1994), Howard Bloom (1995), Francis Heylighen (1995), Douglas Engelbart, Cliff Joslyn, Ron Dembo, Gottfried Mayer-Kress (2003) and other theorists. Collective intelligence is referred to as Symbiotic intelligence by Norman L. Johnson.

Some figures like Tom Atlee prefer to focus on collective intelligence primarily in humans and actively work to upgrade what Howard Bloom calls “the group IQ”. Atlee feels that collective intelligence can be encouraged “to overcome ‘groupthink’ and individual cognitive bias in order to allow a collective to cooperate on one process—while achieving enhanced intellectual performance.”

Collective intelligence (CI) can also be defined as a form of networking enabled by the rise of communications technology, namely the Internet. Web 2.0 has enabled interactivity and thus, users are able to generate their own content. Collective Intelligence draws on this to enhance the social pool of existing knowledge. Henry Jenkins, a key theorist of new media and media convergence draws on the theory that collective intelligence can be attributed to media convergence and participatory culture. Collective intelligence is not merely a quantitative contribution of information from all cultures, it is also qualitative.

One CI pioneer, George Pór, defined the collective intelligence phenomenon as “the capacity of human communities to evolve towards higher order complexity and harmony, through such innovation mechanisms as differentiation and integration, competition and collaboration.” Tom Atlee and George Pór state that “collective intelligence also involves achieving a single focus of attention and standard of metrics which provide an appropriate threshold of action”. Their approach is rooted in Scientific Community Metaphor.

Levy and de Kerckhove consider CI from a mass communications perspective, focusing on the ability of networked ICT’s to enhance the community knowledge pool. They suggest that these communications tools enable humans to interact and to share and collaborate with both ease and speed (Flew 2008). With the development of the Internet and its widespread use, the opportunity to contribute to community-based knowledge forums, such as Wikipedia, is greater than ever before. These computer networks give participating users the opportunity to store and to retrieve knowledge through the collective access to these databases and allow them to “harness the hive” (Raymond 1998; Herz 2005 in Flew 2008). Researchers^[3] at the MIT Center for Collective Intelligence research and explore collective intelligence of groups of people and computers.

To understand how and why people accept and maintain the social systems that affect them, social psychologists have developed system justification theory. According to system justification theory, people not only want to hold favorable attitudes about themselves (ego-justification) and their own groups (group-justification), but they also want to hold favorable attitudes about the overarching social order (system-justification).

According to system justification theory, this motive is not unique to members of dominant groups, who benefit the most from the current regime; it also affects the thoughts and behaviors of members of groups who are seemingly incurring disadvantages by it (e.g., poor people, racial/ethnic minorities). System justification theory therefore accounts for counter-intuitive evidence that members of disadvantaged groups often support the societal status quo (at least to some degree), often at considerable cost to themselves and to fellow group members.

System justification theory differs from the status quo bias in that it is predominately motivational rather than cognitive. Generally, the status quo bias refers to a tendency to prefer the default or established option when making choices. In contrast, system justification posits that people need and want to see prevailing social systems as fair and just. The motivational component of system justification means that its effects are exacerbated when people are under psychological threat or when they feel their outcomes are especially dependent on the system that is being justified.

Information cascades are fragile because new information can overturn a long-standing behavioral trend. Because people are rational, they realize that their behavior is based on limited information and are willing to change. Thus, even though a thousand people may have chosen one action, a single new piece of information can induce people to subsequently choose a different action.

There are two key conditions in an information cascade model:

1. Sequential decisions with subsequent actors observing decisions (not information) of previous actors.
2. A limited action space (e.g. an adopt/reject decision).

The spiral of silence begins with fear of reprisal or isolation, and escalates from there. Individuals use what is described as “an innate ability” or quasi-statistical sense to gauge public opinion. Mass media plays a large part in determining what the dominant opinion is, since our direct observation is limited to a small percentage of the population. Mass media has an enormous impact on how public opinion is portrayed, and can dramatically impact an individual’s perception about where public opinion lies, whether or not that portrayal is factual. Noelle-Neumann describes the spiral of silence as a dynamic process, in which predictions about public opinion become fact as mass media’s coverage of the majority opinion becomes the status quo, and the minority becomes less likely to speak out. The theory, however, only applies to moral or opinion issues, not issues that can be proven right or wrong using facts.

Study of this effect has shown that after participating in a discussion group, members tend to advocate more extreme positions and call for riskier courses of action than individuals who did not participate in any such discussion. This phenomenon was originally coined risky shift but was found to apply to more than risk, so the replacement term choice shift has been suggested.

In addition, attitudes such as racial and sexual prejudice tend to be reduced (for already low-prejudice individuals) and inflated (for already high-prejudice individuals) after group discussion.

Group polarization has been used to explain the decision-making of a jury, particularly when considering punitive damages in a civil trial. Studies have shown that after deliberating together, mock jury members often decided on punitive damage awards that were either larger or smaller than the amount any individual juror had favoured prior to deliberation. The studies indicated that when the jurors favoured a relatively low award, discussion would lead to an even more lenient result, while if the jury was inclined to impose a stiff penalty, discussion would make it even harsher.

The bandwagon effect is well-documented in behavioral psychology and has many applications. The general rule is that conduct or beliefs spread among people, as fads and trends clearly do, with “the probability of any individual adopting it increasing with the proportion who have already done so”. As more people come to believe in something, others also “hop on the bandwagon” regardless of the underlying evidence. The tendency to follow the actions or beliefs of others can occur because individuals directly prefer to conform, or because individuals derive information from others. Both explanations have been used for evidence of conformity in psychological experiments. For example, social pressure has been used to explain Asch’s conformity experiments, and information has been used to explain Sherif’s autokinetic experiment.

When individuals make rational choices based on the information they receive from others, economists have proposed that information cascades can quickly form in which people decide to ignore their personal information signals and follow the behavior of others. Cascades explain why behavior is fragile—people understand that they are based on very limited information. As a result, fads form easily but are also easily dislodged. Such informational effects have been used to explain political bandwagons.