The Four Kinds of Issue in Computing

Overview

Recall questions on the individual, social, legal and cultural framing, why the risks are only half the story, and the reach of digital technology.

What you need to know

Answer each one before you reveal it.

Questions from this subtopic

Each one with the model answer underneath.

1. 1

   The consequences of computing are usually sorted into four kinds of issue: individual, social, legal and cultural. What does each label pick out?

   Model answer

   Individual issues are moral ones — they concern the effect on a particular person and what it is right or wrong to do to them, for example whether a person's location history should be recorded. Social issues are ethical ones — they concern effects on groups and on society as a whole, for example whether automated hiring changes who gets work. Legal issues concern what the law actually permits, requires or forbids, which is not always the same as what is right. Cultural issues concern the shared values, expectations and practices of a group or society, which differ from place to place — a level of public photography that is unremarkable in one community may be experienced as an intrusion in another. The same system usually raises several kinds at once, and they can pull in different directions.

2. 2

   Why is it a mistake to talk only about the risks of computing?

   Model answer

   Because the same developments create opportunities as well as risks, and an honest assessment has to weigh both. Digital technology has widened access to information and education, allowed people separated by distance to communicate cheaply, supported medical diagnosis and drug discovery, made government data open to scrutiny, given small businesses global reach, and allowed groups with little money or power to organise and publish. Any judgement about a system that lists only the harms, or only the benefits, is incomplete.

3. 3

   How have computing and digital technology changed the way information moves through society?

   Model answer

   Communication used to be either one-to-one and private (letter, telephone) or one-to-many and controlled by a small number of publishers and broadcasters. Digital networks make one-to-many publishing available to almost anyone at almost no cost, make many-to-many conversation ordinary, and make the flow instantaneous and international. Information also now flows in directions it previously did not: from individuals back to the companies and states whose systems they use. Because the flows are cheap, fast and recorded, their scale is far larger than anything the earlier arrangements allowed.

4. 4

   Digital technology has transformed the capacity to do three things with information about people. What are they?

   Model answer

   To monitor behaviour; to amass and analyse personal information; and to distribute, publish, communicate and disseminate that information. They are worth separating because a system may do only one of them, and each raises its own questions — a system might watch without storing, store without analysing, or analyse without ever passing the results on.

5. 5

   Give concrete examples of how computing has increased the capacity to monitor behaviour.

   Model answer

   Mobile phones report their position to the network and to apps; travel and payment cards record where and when they were used; CCTV and automatic number plate recognition track movement in public space; websites log every page requested, and analytics scripts record scrolling and clicks; workplace software can log keystrokes, application use and driver routes; fitness trackers and smart meters record activity inside the home. The change is not that watching became possible but that it became continuous, automatic and cheap, so it is now the default rather than something a person has to decide to do.

6. 6

   What is meant by the capacity to amass and analyse personal information, and why does amassing matter even when each individual item looks harmless?

   Model answer

   Amassing means collecting and retaining very large quantities of data about people, often gathered as a by-product of some other service; analysing means using software — increasingly machine learning — to find patterns in it. It matters because aggregation changes what the data reveals. A single shop purchase, a single journey or a single search says almost nothing, but the whole record of them can indicate health conditions, religion, political views, relationships and daily routine, none of which the person ever disclosed. Data sets can also be combined, so information given for one purpose can be joined to another, and supposedly anonymous records can sometimes be re-identified by matching an unusual combination of details against a second data set.

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