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Ethical Considerations in Computer Vision
Computer Vision enables machines to see and interpret the
visual world through images and videos. While powerful, it
raises following important ethical concerns:
Informed Consent
Computer Vision datasets are more often derived from the
internet or public spaces without the knowledge of individuals.
It is ethical to inform individuals that their data is being collected. However, the challenges are
identifying them and obtaining consent.
Voluntary Participation
It is ethical to collect data in a computer vision project with participants' permission. However,
content collected from social media or CCTV footage lacks this voluntary participation ethic.
Do No Harm
Computer Vision can sometimes cause problems if it makes mistakes, treats people unfairly, or is
used in the wrong way. That’s why it is important to check and test the data carefully to make sure
it is fair for everyone. This is especially important in areas like hospitals, police work, and job hiring.
Confidentiality
Many pictures and videos used to train AI are shared online without hiding people’s faces or
details. This can be unsafe. To keep data safe, it should be locked with special codes (encryption),
only shared with people who are allowed (access control), and stored in secure places where
others can’t easily get to it.
Anonymity
It’s hard to keep people completely anonymous in videos and apps that use faces. To address
this, synthetic datasets should be used, and in addition to removing names, visual data must
also be protected from identification.
Only Assess Relevant Components
Some computer systems gather more
Voluntary
information than they actually need. Informed Participation Do No Harm
Consent
This is not right. Good ethics means that
systems should only collect the data that
is necessary and not go too far or try to Confidentiality Anonymity Only Assess
Relevant
judge people based on extra details. Components
AI and Ethical Considerations 53

