Due to an error in a facial recognition system created by the startup clearview ai an innocent woman in the US spent 5 months in jail.

Judges tend to place complete trust in #ai generated results, while developers avoid responsibility because there is no malicious intent in their actions

Despite the real threat of unlawful arrests, law enforcement systems around the world are unlikely to abandon algorithms

#algorithmicbias #aiethics

https://edition.cnn.com/2026/03/29/us/angela-lipps-ai-facial-recognition

Police used AI facial recognition to arrest a Tennessee woman for crimes committed in a state she says she’s never visited

A Tennessee grandmother spent more than five months in jail after police used an AI facial recognition tool to link her to crimes committed in North Dakota – a state she says she’d never been to before.

CNN

Data collection is not the biggest problem. Interpretation is.
A version of you is constantly being assembled — cleaner, simpler, more usable than you actually are.

Measured.
Sorted.
Packaged.

That’s the moment the mirror stops reflecting and starts rewriting.

And once the model matters more than the person, complexity quietly disappears.

#DigitalIdentity #AlgorithmicPower #DataPolitics #DataProtection #AIEthics #Technology&Society #Democracy #DigitalGovernance #AlgorithmicBias

Teaching AI Ethics: Bias and Discrimination

This is the first post in a series exploring the nine areas of AI ethics outlined in this original post. Each post will go into detail on the ethical concern as well as providing practical ways to discuss these issues in a variety of subject areas. UPDATE: Here's a pre-post-script to this post which raises an important point about bias in image generation. It comes from a DM conversation and subsequent comment on the post on LinkedIn: Excellent comment via Lori Mazor on the image with this […]

https://leonfurze.com/2023/03/06/teaching-ai-ethics-bias-and-discrimination/

Teaching AI Ethics: Environment

This is the second post in a series exploring the nine areas of AI ethics outlined in this original post. Each post goes into detail on the ethical concern and provides practical ways to discuss these issues in a variety of subject areas. For the first post on bias and discrimination, click here. The original post Teaching AI Ethics provided an overview of nine areas of ethical concern with AI. Although I primarily work with generative AI like text and image generation, many of these can be […]

https://leonfurze.com/2023/03/13/teaching-ai-ethics-environment/

Teaching AI Ethics: Truth and Academic Integrity

This is the third post in a series exploring the nine areas of AI ethics outlined in this original post. Each post goes into detail on the ethical concern and provides practical ways to discuss these issues in a variety of subject areas. For the previous post on Environmental concerns, click here. The concept of "truth" is a significant ethical issue related to AI systems like ChatGPT. Since its launch in November, there have been two main concerns: first, the likelihood of AI models […]

https://leonfurze.com/2023/03/21/teaching-ai-ethics-truth-and-academic-integrity/

Teaching AI Ethics: Copyright

This is the 4th post in a series exploring the nine areas of AI ethics outlined in this original post. Each post goes into detail on the ethical concern and provides practical ways to discuss these issues in a variety of subject areas. For the previous post on Truth, click here. This is the first in the 'intermediate' level of posts for Teaching AI Ethics. At this level, the concepts start to become more complex. This might be because the information is harder to access, or because the ideas […]

https://leonfurze.com/2023/04/04/teaching-ai-ethics-copyright/

Teaching AI Ethics: Privacy

This is the fifth post in a series exploring the nine areas of AI ethics outlined in this original post. Each post goes into detail on the ethical concern and provides practical ways to discuss these issues in a variety of subject areas. For the previous post on copyright, click here. There are growing concerns about the impact of Artificial Intelligence technologies on our privacy. AI systems are often "black boxes", making it hard to understand how they arrive at their decisions and […]

https://leonfurze.com/2023/04/10/teaching-ai-ethics-privacy/

Teaching AI Ethics: Datafication

This is the sixth post in a series exploring the nine areas of AI ethics outlined in this original post. Each post goes into detail on the ethical concern and provides practical ways to discuss these issues in a variety of subject areas. For the previous post on privacy, click here. "Datafication" is a term used to describe how all aspects of our lives are being turned into datapoints. Whether through the collection of our likes, shares, and ratings on social media and streaming apps, or […]

https://leonfurze.com/2023/04/16/teaching-ai-ethics-datafication/

Teaching AI Ethics: Affect Recognition

This is the seventh post in a series exploring the nine areas of AI ethics outlined in this original post. Each post goes into detail on the ethical concern and provides practical ways to discuss these issues in a variety of subject areas. For the previous post on datafication, click here. As artificial intelligence continues to develop and influence different aspects of our lives, its role in education is becoming increasingly important. One particularly controversial implementation of AI […]

https://leonfurze.com/2023/05/15/teaching-ai-ethics-affect-recognition/

Teaching AI Ethics: Human Labour

This is the eighth post in a series exploring the nine areas of AI ethics outlined in this original post. Each post goes into detail on the ethical concern and provides practical ways to discuss these issues in a variety of subject areas. For the previous post on affect recognition, click here. When people think of Artificial Intelligence, the image that often springs to mind is that of sentient machines or shiny metallic robots, a depiction heavily influenced by popular culture. This […]

https://leonfurze.com/2023/05/22/teaching-ai-ethics-human-labour/