Week 5 – Q&A time – Knowledge Integration and Project Planning: Data, Inequality and Society (2022-2023)

Due to the UCU strike, I have not been able to attend the Ethical Data Futures course, so this week I have been concentrating on self-study of some of the guidance in the handbook,I have summarised four key points of knowledge and tried to give my own view.

What are the ethical implications of data collection and analysis in the context of artificial intelligence (AI) and machine learning (ML)?

As AI and ML continue to advance, the amount of data collected and analyzed is increasing exponentially. This raises ethical concerns about how this data is being used and whether it is being used in a fair and just manner. Questions also arise about who has access to this data and how it can be used to make decisions that affect individuals and society as a whole.

How can we ensure that data is used ethically and responsibly, especially in the context of big data and data-driven decision making?

With the rise of big data and data-driven decision making, there is a need for ethical guidelines and regulations to ensure that data is being used in a responsible and ethical manner. This raises questions about how we can design ethical frameworks for data collection, analysis, and use, and how we can ensure that these frameworks are being followed.

What are the potential consequences of biases in data and how can we mitigate these biases?

Data biases can occur at various stages of data collection and analysis, leading to unfair and unjust decisions that can have far-reaching consequences. This raises questions about how we can identify and mitigate biases in data, and how we can design algorithms and systems that are free from bias.

How can we ensure that individuals have control over their personal data and that it is being used in a transparent and responsible manner?

The rise of data-driven technologies has led to concerns about how personal data is being collected, analyzed, and used. This raises questions about how we can ensure that individuals have control over their personal data and how we can design systems that are transparent and accountable in their use of personal data.