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Ethical Issues in Data Collection

Having access to vast collections of data has huge implications for society. Coupled with advances in technology, now more than ever before, the human race has the potential to solve more problems and make even more advances. Before anyone gets carried away, however, everyone must remember the Peter Parker principle:
Having access to vast collections of data has huge implications for society. Coupled with advances in technology, now more than ever before, the human race has the potential to solve more problems and make even more advances. Before anyone gets carried away, however, everyone must remember the Peter Parker principle:
With great power comes great responsibility

The Ethics of Data Collection

The ethics of data collection and how it is subsequently processed needs to be considered by everyone involved in projects involving data and that includes machine learning projects. Even in the absence of a legal framework, you still need to think about questions such as:
  • Where will the data be sourced?
  • What methods of collecting data should be used?
  • Is consent needed?
  • Who will store, own and control the data?
  • Are all your actions transparent and open to inspection?
Controversial examples of data collection often involve situations where personal data is collected and processed.

Location Tracking

Google’s location history is one such controversial example relating to the collection of personal data. In 2018, an Associated Press investigation into Google confirmed that “many Google services on Android devices and iPhones store your location data even if you’ve used a privacy setting that says it will prevent Google from doing so”. The report highlighted that by changing a setting to turn Google’s Location History off, you are only stopping Google from adding your movements to its Timeline feature. Other services including maps, weather updates and web searches still enable Google to timestamp and pinpoint your location. Google argue that these services are “opt in” and users have the controls to turn it off in the “Web and App Activity” settings.

How Google Uses Your Data

Google are transparent about how and why they collect this data, which can be found on their local data policy webpage. The data will be processed by their machine learning algorithms to provide you with services that Google thinks will be relevant to you. For example, when you get in a car and open maps, the AI might know where you are likely to want to go based on the time of day and notify you of traffic conditions. When you do a web search, results and advertising are customised by Google’s AI to be more relevant to your location and interests.
One of the ethical issues that this highlights is one of consent. If services that are collecting data are turned on by default, even if you have the ability to disable the data collection, can it be said that consent has been given? Are all companies transparent about what they do with the data and who they share it with? If other companies were able to access the same location data, what could they learn about the user, and how could they use it?

Data and Smart Cities

A smart city is a city that uses electronic devices including sensors to collect data and to use it to improve operations and services in the area. Examples of benefits to those living these cities include:
  • Real-time traffic management, i.e. controlling lights to reduce travel times and emissions
  • Smart bins relaying information on how full they are so that they only get emptied when needed
  • Street lights that turn on only when needed, resulting in energy savings
A illustration of a 'smart city' - a sensor on a streelight is detecting a pedestrian walking, and a traffic light sensor is detecting a travelling car. A recycling lorry is detecting levels of waste in two bins and is picking up the bin which is full.
Data can be fed into machine learning algorithms to help plan for sustainable development of the city. For example, by recording footfall, traffic, and air quality from around the city, machine learning can be used to help identify new routes for public transport.
In principle, the collected data appears to be being used for ethical purposes as the aim of a smart city is to improve the lives of those who access its services. This doesn’t mean that the people collecting and using the data don’t need to factor in ethical considerations, however. Stringent controls need to be in place over who has access to the data and to make sure it is only being used for the purpose the citizens have agreed to.

Laws Governing the Use of Data

Some governments have passed laws to govern the use of identifiable data relating to their citizens, such as the General Data Protection Regulation in the EU and the Data Protection Act in the UK. These laws aim to control how organisations collect and use personal data, as well as outlining the rights their citizens have over how their data is used.

Discussion

Ethical principles are not necessarily universal. We might note, for example, that the United Kingdom is more bound by ethical considerations of data collection and use than some other countries. This could put us at a technological disadvantage. “Ethical drag” might mean a lack of agility in the face of evolving data technologies.
  • To what extent to do you agree with this statement?
Having access to vast collections of data has huge implications for society. Coupled with advances in technology, now more than ever before, the human race has the potential to solve more problems and make even more advances. Before anyone gets carried away, however, everyone must remember the Peter Parker principle:

With great power comes great responsibility

The Ethics of Data Collection

The ethics of data collection and how it is subsequently processed needs to be considered by everyone involved in projects involving data and that includes machine learning projects. Even in the absence of a legal framework, you still need to think about questions such as:
  • Where will the data be sourced?
  • What methods of collecting data should be used?
  • Is consent needed?
  • Who will store, own and control the data?
  • Are all your actions transparent and open to inspection?
Controversial examples of data collection often involve situations where personal data is collected and processed.

Location Tracking

Google’s location history is one such controversial example relating to the collection of personal data. In 2018, an Associated Press investigation into Google confirmed that “many Google services on Android devices and iPhones store your location data even if you’ve used a privacy setting that says it will prevent Google from doing so”. The report highlighted that by changing a setting to turn Google’s Location History off, you are only stopping Google from adding your movements to its Timeline feature. Other services including maps, weather updates and web searches still enable Google to timestamp and pinpoint your location. Google argue that these services are “opt in” and users have the controls to turn it off in the “Web and App Activity” settings.

How Google Uses Your Data

Google are transparent about how and why they collect this data, which can be found on their local data policy webpage. The data will be processed by their machine learning algorithms to provide you with services that Google thinks will be relevant to you. For example, when you get in a car and open maps, the AI might know where you are likely to want to go based on the time of day and notify you of traffic conditions. When you do a web search, results and advertising are customised by Google’s AI to be more relevant to your location and interests.
One of the ethical issues that this highlights is one of consent. If services that are collecting data are turned on by default, even if you have the ability to disable the data collection, can it be said that consent has been given? Are all companies transparent about what they do with the data and who they share it with? If other companies were able to access the same location data, what could they learn about the user, and how could they use it?

Data and Smart Cities

A smart city is a city that uses electronic devices including sensors to collect data and to use it to improve operations and services in the area. Examples of benefits to those living these cities include:
  • Real-time traffic management, i.e. controlling lights to reduce travel times and emissions
  • Smart bins relaying information on how full they are so that they only get emptied when needed
  • Street lights that turn on only when needed, resulting in energy savings
A illustration of a 'smart city' - a sensor on a streelight is detecting a pedestrian walking, and a traffic light sensor is detecting a travelling car. A recycling lorry is detecting levels of waste in two bins and is picking up the bin which is full.
Data can be fed into machine learning algorithms to help plan for sustainable development of the city. For example, by recording footfall, traffic, and air quality from around the city, machine learning can be used to help identify new routes for public transport.
In principle, the collected data appears to be being used for ethical purposes as the aim of a smart city is to improve the lives of those who access its services. This doesn’t mean that the people collecting and using the data don’t need to factor in ethical considerations, however. Stringent controls need to be in place over who has access to the data and to make sure it is only being used for the purpose the citizens have agreed to.

Laws Governing the Use of Data

Some governments have passed laws to govern the use of identifiable data relating to their citizens, such as the General Data Protection Regulation in the EU and the Data Protection Act in the UK. These laws aim to control how organisations collect and use personal data, as well as outlining the rights their citizens have over how their data is used.

Discussion

Ethical principles are not necessarily universal. We might note, for example, that the United Kingdom is more bound by ethical considerations of data collection and use than some other countries. This could put us at a technological disadvantage. “Ethical drag” might mean a lack of agility in the face of evolving data technologies.
  • To what extent to do you agree with this statement?
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