Diversity in Computing

BACK: Reproductive Futures and Designer Babies

The Shift from “Big Computing” to “Personal Computing”

Electronic communication: wireless telegraphy, telephony, radio, television, computing.

Rapid Technological changes were considered ‘revolutions.’ Traditionally, it is difficult to retain full control of the market for a long period of time–things are constantly changing and improving.

Computers were a large large box–what was the point of having my own? That was something for banks or research facilities. What am I going to do with just a bunch of number crunching machines? The problem was less about technological limitations but more of lack of imaginations.

Personal computing emerged not because of advances in transistors or some technology–it was prompted by a cultural change. There was a conscious effort to transform the social meaning of computing. The right technologies often came out, unused–but those which survived were those that had social significance in people’s lives (personal calculators).

Stewart Brand’s “Spacewar!” article shows that these machines can be used for playing games–meaning that people who have access to these machines have the ability to play games.

There is now a counter-culture movement, a do it yourself, high-tech hippies from the Silicon Valley. People want access to ways to be able to go where you need, get information, and be able to know things on your own.

Ted Nelson

You can and must understand computers now! New freedoms through computer screens–minorities can have this freedom too. They’re going to shape the way we live, so you really need to know how it works! This was against the centralization of computers by IBM.

Microprocessors were developed for a general purpose computer. Dartmouth College legitimizes free access with a personal/interactive programming language. The size of those giant boxes into a microchip. All of these made the push towards personal computing. “You can build your own computer!!” Inexpensive computers and marketing helped people realize that these can be personal!

Making Arguments with Data

Why are arguments based on quantification persuasive? People are persuasive when they’re objective–but what does that mean? Under which conditions do we seek it? Which conditions do numbers become powerful?

“Objectivity” makes us think of machines, numbers, fairness, representation. “Give equal weight to all the arguments.”

Rise of Quantification in Science: Galileo

He argues that only the quantifiable properties are real. He makes arguments, which quantify the life world. We have changed the way we think about science after his work. The world we see around us aren’t real unless we can quantify it.

This makes arguments universal. Numbers are a technology of distance–it travels well. It minimizes the need for personal trust and helps to produce knowledge independent of the particular people who make it. In this way, we can build science as a global network.

Condorcet: From Science to the Public Discourse

The socio-economic structures of the Regime in 18th Century France was super irrational. Quantitative data and mathematical methods (which were authoritative in science) were weapons in fighting the Regime. This drives out ignorance, prejudice, and elites.

Calculations will replace all forms of decision making–it was a tool for the outsiders, those who lack authority.

French State Engineers (19th Century)

Civil Engineers were needed for the modernization of the country. Schools had intense mathematical training and their activity was backed by the state. Data and economic rationality led to a process of standardization (metric system).

Mathematics wasn’t a tool of revolution, but it was a way to impose on those who didn’t use it. A lot of mathematical decisions about public works were controversial–people defended the interest of the central state against those of local elites.

But numbers need to be interpreted–they aren’t powerful by themselves. We need people that are able to judge what they mean. These engineers are in a position of authority and they become the technocratic elite. There is no higher authority in scientific/technological means. This also meant that they weren’t fully accountable.

Other countries looked quite different. In the US, arguments (with numbers) were constantly challenged. Cost-benefit analysis becomes a set of rationalized economic principles, open to public scrutiny. Eventual success replaces personal trust. Engineers don’t have the ultimate say, they have to justify their decisions. There is more accountability than authority here.

In Italy, there was intense opposition at the local conflicts. There was lack of trust in the engineer’s arguments, as well as lack of trust in data-based arguments. As such, there was only partial success.

Power is still concentrated in the hands of traditional political and intellectual elites–these judgements don’t need quantitative data.

Those “Silly” numbers.

The Italian Government presented to the EU its Budget Law for approval. The EU didn’t approve it because of the risk. The EU thought that it was dangerous, but the Italian government rejected the data because they didn’t think outside strangers should force policy decisions upon the Italian people. They don’t question the numbers. They argue that such quantitative data shouldn’t be relevant when it comes to making decisions about the livelihood of the people they govern. Political and economic choices are not necessarily best shaped by data.

NEXT: Expertise, Public Engagement, Democracy