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Poor quality or unrepresentative data can lead to inaccurate or unethical outcomes in computer vision models. Case Studies: Flawed facial recognition systems used in law enforcement, biased datasets affecting credit scoring systems.

The use of computer vision technology can lead to invasions of privacy, such as unauthorized surveillance or data collection. Case Studies: Clearview AI scraping online images for facial recognition database, retail stores using facial recognition for targeted advertising.

Computer vision systems can inherit biases present in their training data or design, leading to unfair treatment of certain groups. Case Studies: Gender Shades project revealing biases in gender classification, biased facial analysis software against people of color.

Determining who is responsible for the actions of computer vision systems can be challenging. Case Studies: Accidents involving autonomous vehicles, erroneous outputs from medical diagnosis systems.

The displacement of jobs due to computer vision and other AI technologies raises ethical concerns. Case Studies: Job losses in sectors like retail and transportation due to automation, societal impact of rapid technological change.

Computer vision can create realistic deepfakes that facilitate the spread of misinformation. Case Studies: Deepfake videos in political disinformation campaigns, creation of non-existent people's images for fraudulent purposes.

Widespread use of computer vision for surveillance can lead to mass monitoring and threaten civil liberties. Case Studies: China's social credit system, use of drones for crowd monitoring during protests.

Collection and analysis of images and videos by computer vision systems can occur without the consent of the individuals captured. Case Studies: Use of facial recognition without consent in public spaces, non-consensual analysis of social media photos.

As computer vision automates more decisions, it can remove human judgment and oversight, leading to ethical issues. Case Studies: Autonomous vehicle decision-making dilemmas, automated hiring tools excluding candidates without human review.