why we still need cyberpunk

William Gibson penned Neuromancer over thirty years ago, and the 1990’s ended viciously on 9/11. With the exception of cyberfeminism, I wrote off “cyberpunk” as an ethic once we as a society stopped saying “cyber” and replaced the word with “online”.

Yesterday I traced partial assets of an individual I distrusted—and needed the straight dope from—from my laptop. Dating while transgender proves dangerous and a girl must protect herself!

In between I persistently beleaguered Microsoft as a career-long Linux hacker.

Once declared squatter’s rights on a piece of land I identified though data mining.

I walk with the Big Data devils to broadcast my signal, a means to an end. Twitter, Google, Amazon, and Facebook receive my data, and in exchange they amplify my cultural imperative.

And they know where the real value in data lies: Not in the records themselves but in the interconnections between them.

Emergent properties steered by unholy gods.

“Cyber”: Greek for “to steer”.

Steering a boat requires connecting the data: Position, velocity, acceleration, time. State variables alone won’t suffice.

When we get burned by Cambridge Analytica or the Russian Federation, we realize our individual technological vulnerability.

Propaganda is hacking: Implant bias, implant ideas, grow emergent outcomes. Seduction is a system intrusion.

Technological warfare and psychological warfare forever link.

Class war must proceed asymmetrically.

I only trust the Prophets, not the Church, not the State, not the Oligarchs.

And we can be prophets in cyberspace. We can create technology that liberates the world.

We can steer toward our own emergent outcomes.

We can end material scarcity.

Love forward. Program. Network. Build enterprise. Produce art. Write. Love forward.

Jam the system, and prepare to be jammed by the punks that follow you.

The 1990’s are dust, but the “system” still remains cybernetic control. Therefore resistance remains cyberpunk.

bias reinforcement through survey questionnaires

Today I play media theorist and examine how survey questionnaires reinforce survey designers’ biases:

The knowledge that biases emit from survey questionnaires is nothing new. The extreme case, “push-polling”, intentionally guides the questionnaire reader toward a viewpoint, without real interest in their prior opinion. Any survey writer willing to push-poll already understands my concerns about bias (because they are propagandists).

It is the unintended or “honest” biases that concern me here.



Consider for example the common belief that individuals can be categorized as a member of one out of four or five distinct racial groups, a belief reflected in many survey questionnaires that ask respondents to indicate which race they belong to. This is an example of what I call an “honestly” projected bias; the survey writer likely has limited awareness that there is even a problem, and does not expect their respondents to question the belief. In these cases, the bias enters the survey questionnaire through the questionnaire writers’ phrasing and provided options, and is confirmed when each respondent chooses one of the options.

Stepping back, we observe “bias in, bias out” where the belief itself gains strength across the survey process. It strengthens among the respondents as they accept the belief when answering the questions, and strengthens in the mind of the survey creator when they see tacit acceptance of the bias in the responses. At each step, neural pathways supporting the belief become stronger due to exercise.

I’ve mapped this process below, illustrating the cumulative bias amplification by degree of red in the arrows’ color:

While we cannot completely escape projecting our biases through our measurement instruments, I call on questionnaire writers to step back and consider what we might be propagating. We may have to become more creative to limit the damage. (For one example of a creative approach, see my post “a better way to ask about gender in survey questionnaires” for an idea on how to avoid propagating the binary sex/gender bias through survey questionnaires).