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[…] $5,000 for (3) months AUDIENCE Distribution list of 2,000 people, including corporate employees of 210+ FPF member companies. List includes senior level privacy executives from a significant number of Fortune 500 companies. Benefits of Sponsorship include: » C ompany name and logo included on LinkedIn Live promotional materials (LI posts, Twitter, a nd YouTube; […]

[…] $5,000 for (3) months AUDIENCE Distribution list of 2,000 people, including corporate employees of 210+ FPF member companies. List includes senior level privacy executives from a significant number of Fortune 500 companies. Benefits of Sponsorship include: » C ompany name and logo included on LinkedIn Live promotional materials (LI posts, Twitter, a nd YouTube; […]

[…] user’s web browser to take actions on their behalf. This could enable a wide range of useful or time-saving tasks, from making restaurant reservations and resolving customer service issues to coding complex systems. At the same time, AI agents raise greater, and sometimes novel, privacy and data protection risks related to the collection and […]

[…] national origin, or insurance statusE.g. Algorithm used to detect skin cancer less accurate for patients with darker skin Physical Safety Differential Access to Safety E.g. Routing of emergency services based on optimizing route efficiency E.g. Missed classification/detection of pedestrians or vehicles due to skin color INDIVIDUAL HARMS COLLECTIVE/ SOCIETAL HARMS The following mitigation practices […]

[…] national origin, or insurance statusE.g. Algorithm used to detect skin cancer less accurate for patients with darker skin Physical Safety Differential Access to Safety E.g. Routing of emergency services based on optimizing route efficiency E.g. Missed classification/detection of pedestrians or vehicles due to skin color INDIVIDUAL HARMS COLLECTIVE/ SOCIETAL HARMS 4 Heightened Risks of […]

[…] national origin, or insurance statusE.g. Algorithm used to detect skin cancer less accurate for patients with darker skin Physical Safety Differential Access to Safety E.g. Routing of emergency services based on optimizing route efficiency E.g. Missed classification/detection of pedestrians or vehicles due to skin color INDIVIDUAL HARMS COLLECTIVE/ SOCIETAL HARMS The following mitigation practices […]

[…] national origin, or insurance statusE.g. Algorithm used to detect skin cancer less accurate for patients with darker skin Physical Safety Differential Access to Safety E.g. Routing of emergency services based on optimizing route efficiency E.g. Missed classification/detection of pedestrians or vehicles due to skin color INDIVIDUAL HARMS COLLECTIVE/ SOCIETAL HARMS 4 Heightened Risks of […]

[…] your school have that may apply? Community dynamics are considered  when constructing any public  communication regarding the incident;  all communication is consistent and  mindful of privacy impacts. What processes does your school have to ensure the privacy of students and minimize harm when communicating? Real-World Example Deepfake non-consensual intimate imagery (NCII) can be generated by face-swapping, replacing one person’s face with another’s face, or digitally “undressing”  a clothed image to appear nude. In the case where NCII involves minors, it may also be considered Child Sexual Abuse Material (CSAM). These deepfakes raise many of the  same issues as non-synthetic NCII and CSAM, though potential ofenders may not appreciate the serious, criminal implications. While many of these deepfakes may be  created and shared outside of school, schools are required to address of-campus behavior that creates a “hostile environment” in the school. Consider how your school  would respond to the below incident as it unfolds.  For more resources visit studentprivacycompass.org/deepfakes IMAGE TThese forgeries can convincingly  alter or create static images of  people, objects, or settings that are entirely or partially  fabricated. Methods like face swapping, morphing, and style transfer are often used.  AUDIO By mimicking vocal traits, audio  deepfakes can convincingly  replicate a person’s voice. They can be used to  fabricate  phone calls, voice messages, or public  addresses. DEEPFAKES PRINCIPAL UPDATE

[…] of deepfakes – video, text, image, and audio – and the varied risks and considerations posed by each in a school setting, from the potential for fabricated phone calls and voice messages impersonating teachers to sharing forged, non-consensual intimate imagery (NCII). “Deepfakes create complicated ethical and security challenges for K-12 schools that will only […]

[…] $5,000 for (3) months AUDIENCE Distribution list of 2,000 people, including corporate employees of 210+ FPF member companies. List includes senior level privacy executives from a significant number of Fortune 500 companies. Benefits of Sponsorship include: » C ompany name and logo included on LinkedIn Live promotional materials (LI posts, Twitter, a nd YouTube; […]