It’s tempting to believe that communicating on the Web is faceless, bodiless, and genderless. Indeed, this notion formed part of the basis of cyberfeminism, which envisioned a post-body, post-gender future inhabited by cyborgs. Without physical cues, an Internet user could be free to be anyone or anything without consequence.  While this may have been true 20 years ago (when this comic was published), it sadly is no longer. Persistent identities and data trackers which follow your digital footprint aside, communication itself is not as anonymous as one may think.  In social psychology, such a programme has been able to categorise samples of discourse by gender with an 80% success rate, lending further credence to theories of gender-based difference in language use.

There is also evidence to suggest that the ways in which men and women use the Web might also be different, as well as the possibility that using the Web can affect people differently according to their gender. High exposure to and use of the Internet has been linked with poor body image and desire for thinness in teenage girls. Additionally, highly explicit content has been made available to all, including children and adolescents. Exposure to pornography and other sexual media has the potential to communicate to teenagers, particularly boys, as well as reinforcing gender stereotypes such as objectification of women and masculinisation of men.

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Creating artificial intelligence or an artificial mind has been a preoccupation of computer science (and science fiction) for decades, since the concept was introduced by scientists such as Alan Turing and John McCarthy. The original idea was built on the assumption that the human brain functioned like a machine – a body made up of small working components which individually were not conscious but together make a mind. Cartesian philosophy also provided tentative encouragement, as to Descartes being a person meant simply to be “a thing that thinks”, as well as which doubts, perceives, affirms, denies, wills, does not will, that imagines also, and which feels” – an array of qualifiers which largely translate to the kind of stimulus responses which machines are perfectly capable of.

However the belief that this could translate simply into machine code has proven rather naive, for various reasons.  Humans are capable of not just storing massive amounts of information, but are able to retrieve and use it “with remarkable efficiency” (Brookshear, 2012: 485). Although storing data is not a huge challenge for machines, understanding it as information in a wider context (as ‘knowledge)’ is. This brings us to the Web, and a more nuanced understanding of intelligence. The Web, and to a greater extent the Semantic Web, gives computer scientists the opportunity to work with a vast store of connected, contextualised information. Results derived from using this network do not attempt to mimic the human brain, but instead create results that are similar to human abilities, and yet are achieved in a different way (a constructionist rather than mimetic understanding of intelligence). The real and achievable aim with this is not to be able emulate what a human do in a given situation, but rather to solve a problem as well as possible.

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