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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; […]

[…] credit to all residents in specified neighborhoods (“redlining”)E.g. Not presenting certain credit offers to members of certain groups, or unfairly referencing others Differential Pricing of Goods and Services Differential Access to Goods and Services E.g. Raising online prices based on membership in a protected classE.g. Presenting product discounts based on “ethnic affinity” Narrowing of […]

[…] . 1 Overview of 2025 Update Automated analysis of personal data, including through the use of artificial intelligence and machine learning tools, can be used to improve services, advance research, and combat discrimination. However, automated decision-making can also lead to potential harms in higher risk contexts, such as hiring, education, and healthcare, as well […]

[…] credit to all residents in specified neighborhoods (“redlining”)E.g. Not presenting certain credit offers to members of certain groups, or unfairly referencing others Differential Pricing of Goods and Services Differential Access to Goods and Services E.g. Raising online prices based on membership in a protected classE.g. Presenting product discounts based on “ethnic affinity” Narrowing of […]

[…] . 1 Overview of 2025 Update Automated analysis of personal data, including through the use of artificial intelligence and machine learning tools, can be used to improve services, advance research, and combat discrimination. However, automated decision-making can also lead to potential harms in higher risk contexts, such as hiring, education, and healthcare, as well […]

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[…] SB 332 and SB 226 update Utah’s Artificial Intelligence Policy Act (SB 149), which took effect May 1, 2024. The AIPA requires entities using consumer-facing generative AI services to interact with individuals within regulated professions (those requiring a state-granted license such as accountants, psychologists, and nurses) to disclose that individuals are interacting with generative […]

[…] 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 […]