1.6 Impact of Digital Tech Flashcards
OCR GCSE Computer Science J277
Impact
Technology impacts our lives in both positive and negative ways.
Information is easily accessible and can be exchanged on an almost immediate basis. This has changed how much personal information is shared.
It also means that it is important to be considerate of all users’ needs, for example when choosing colours for a company website.
Identifying impacts allows us to make better decisions as we develop and use new technologies.
Awareness of impact can help avoid introducing personal biases into systems, which could affect users.
Morals
are the internal principles that an individual uses to make decisions about what is right and wrong. Your ‘personal compass’.
These principles are not always shared by all members of a community, but they often originate from commonly held beliefs and are reinforced through interaction with other people.
Ethics
Refer to what is right and wrong and how people should behave.
Ethics are shared morals that a particular group of people recognise as necessary to ensure that the group behaves positively based on its own context.
Codes of conduct, rules, laws, standards etc.
Society
A society is one or more groups of people that exist with shared beliefs, practices, and ethics.
Culture
The shared beliefs, practices, and ethics of a group of people within a society is known as a group’s culture.
Therefore, a society can be multicultural, being made up of more than one group, each with distinct beliefs, practices, and ethics, with some of those also shared with other cultures within the society.
Cultural Issues
Refers to the ideas, behaviour, beliefs and values of a group of people.
Cultural issues relate to how computers have impacted our lives, including:
The widespread use of ‘disposable’ devices
The ways in which people interact with each other (social media)
Changes in workplace
Replacing human roles in organisations
Widespread data collection about individuals
Access to entertainment and social interaction
Workforce monitoring
Employment
Technology has changed the type of work available and introduced new ways that people can work in existing jobs.
Technology has also enabled the continuation of work in conditions previously impossible (such as the remote working response to the coronavirus pandemic in 2020).
It has affected employees’ work-based interactions and changed the way that we communicate, with videoconferencing becoming a normal experience for many employees.
Ethical & Cultural Issues
Ethical and cultural issues stemming from the use of computers and digital devices include:
Providing a means of access to inappropriate or illegal content
Safety decisions and judgements made by machines, for example, self-driving vehicles
Social platforms or media that enable cyberbullying, trolling or sexting
Social pressure to be online and purchase more of the latest technology
Not everyone can pay for digital devices or access broadband internet. This leads to a ‘digital divide’
The ‘always on’ culture and an increase in the reliance on computers in the workplace is leading to an increase in eyestrain and RSI (Repetitive Strain Injury) from prolonged use of screens and keyboards
The ‘right’ level of censorship and monitoring of computer usage and viewable content. These decisions may be made by parents, companies or by entire nations.
Employment impact and ethical considerations
The culture of many organisations has changed to enable remote working practices.
Employees can work from anywhere and teams can be entirely dependent on virtual interactions, or use a hybrid approach with opportunities to meet up with co-workers to prevent individuals from feeling isolated.
If the employer has got it right, the workforce responds by feeling empowered, valued, and, above all, happy at work, improving the organisation’s productivity.
Automated Decision Making
Computer programs can complete a task by making decisions based on conditions set by a human.
If the conditions are not set correctly or they do not represent all possible situations, the program may not be suitable for its intended task. This may result in people being unfairly advantaged or disadvantaged.
Examples of this have been seen in:
recruitment processes, where people with particular characteristics have been treated unfairly,
policing, where existing equality issues have been amplified.
UAVS / Drones
UAV = Unmanned Aerial Vehicle, or drone
There are plans for 165 miles of drone superhighway that will link airspace over the Midlands and the south of England.
This will enable a range of activities, such as the delivery of vaccines and blood samples and support for search and rescue missions, to be carried out using drones piloted by computers.
AI and Machine Learning
Unlike automatic systems, autonomous machines are self-sufficient and require no human intervention. They can learn and adjust to their changing environment.
Artificial intelligence and machine learning are the branches of computer science that are used in the development of autonomous machines.
Artificial Intelligence
The research and development of computer systems that determine the relationships between inputs and output to make predictions, instead of following programmed instructions.
Machine Learning
Algorithms that learn the relationship between inputs and outputs in order to make predictions.
Autonomous Vehicles
Driverless cars will be able to communicate with each other and use data from their environment to reduce accidents and make traffic jams a thing of the past.
However, there are several examples of accidents that have been caused by decisions made by autonomous cars.
Sometimes this is because insufficient training data has been used. It is difficult to produce adequate conditions that the cars can use to determine what they should consider to be a hazard.
Lethal Autonomous Weapons
Weapons that can make decisions about a battlefield environment and strike targets without human intervention are known as autonomous weapons, although it is questionable whether these machines are truly ‘autonomous’.
Although there are claims that they can reduce civilian casualties, there are concerns that ‘autonomous’ weapons may target civilians in error.
Bias
A bias is a disproportionate balance in favour of or against an idea or thing.
People often associate bias with being for or against an individual, a group, or a belief, usually in a way that is closed-minded, prejudicial, or unfair.
Algorithmic Bias
However, in science and engineering fields, a bias can also be a systematic error.
The measure of error that shows how far away the actual output is from the predicted output is called algorithmic bias.
If the error is significant, the model has not reflected the real-world relationship between the input data and what the model predicts. The model is therefore said to have prediction bias — favouring one output over others.
Ethical Bias
AI that has algorithmic bias (prediction bias) can output a prediction that has ethical bias.
Automation promises efficiency and fairness because individual programmers and their morals, or teams of programmers and their ethics, are removed from the decision-making.
Echo Chamber
Machine learning is used to analyse huge data sets to find patterns and make decisions on what sort of content you might like to see on social media.
The cultural impact of this is that people with similar interests and views will be shown similar content that they all ‘like’.
This ‘echo chamber’ effect, with individuals’ views being reinforced as they are all shown similar content, can prevent people in the society from having access to diverse views, limiting their experience and understanding of other cultures.
Negative Environmental Issues
The negative environmental impacts of widespread computer use include:
Large global energy requirements to run computer systems and data centres
The use of rare and non-renewable metals and minerals
Some components are made from toxic materials which are a hazard to the environment and human health if not disposed of properly
Upgrade Culture
The length of time for which we use each individual piece of technology has become very short.
Upgrade culture is a term used to refer to the cycle that sees most of us replacing our most trusted devices every few years with the latest products.
Where do you see your role in this process as a consumer?
Is it unethical to want to upgrade your phone after only a few years of use?
Should phone companies slow their development, and would this reduce innovation?