SSB 5956
In CommitteeSenate
AI use/student discipline
Addressing artificial intelligence, student discipline, and surveillance in public schools.
This status may be delayed. See Action History below for the latest updates.
How does a bill become law?
- Introduced: The bill is filed and assigned a number.
- Committee: A subject-matter committee holds hearings, takes public testimony, and decides whether to advance the bill.
- Floor Vote: The full chamber (House or Senate) debates and votes on the bill.
- Opposite Chamber: The bill repeats the committee and floor vote process in the other chamber.
- Governor: The Governor reviews the bill and decides whether to sign or veto it.
- Signed: The bill has been signed into law.
AI Analysis
This bill bans the use of artificial intelligence and automated systems to make or influence student discipline decisions in Washington’s public schools, especially those that generate risk scores or use biometric data to infer sensitive traits. It ensures human judgment remains central to discipline, restricts data sharing with law enforcement, and requires state agencies to develop new guidance and model policies for schools.
- Prohibits AI or automated systems from being the sole or deciding factor in student discipline decisions (e.g., suspension, expulsion, emergency removal).
- Bans predictive “risk scores” and watchlists for individual students based on AI or surveillance data related to misconduct, gang affiliation, or future disciplinary issues.
- Prohibits use of biometric data (e.g., facial recognition, voiceprints, gait) to infer sensitive traits like mental health, sexual orientation, or gender identity—except for limited employee access or federal requirements.
- Limits sharing student data with law enforcement—only when required by law or when there is an imminent risk of serious physical harm, and only the minimum necessary information may be shared.
- Requires human oversight of AI and automated systems in discipline, and directs the Office of the Superintendent of Public Instruction to update guidance and the Washington State School Directors’ Association to create a model policy by February 1, 2027.
- Bars facial recognition use for student surveillance in schools, and expands existing state restrictions on government use of facial recognition to include schools.
Who is affected
- K–12 public school students — Students may not be disciplined, suspended, expelled, or otherwise disciplined based solely on AI-generated risk scores, surveillance data, or biometric analysis; protections are added for students in groups historically overrepresented in discipline, including Black, Indigenous, students of color, students with disabilities, and LGBTQ students.
- Public school districts and charter schools — School districts must stop using AI tools for student discipline decisions, avoid certain predictive tools, and ensure human oversight of AI systems; they must also adopt new model policies by early 2027.
- State-tribal education compact schools — State-tribal education compact schools must comply with the same prohibitions and requirements as other public schools, including bans on AI-based discipline tools and biometric misuse.
- School employees and contractors — School staff—including teachers, administrators, and security personnel—must ensure discipline decisions include human judgment and cannot rely on automated systems alone; they must also follow new data privacy and disclosure rules.
Pro/Con Analysis
Stronger case for benefits
Potential Benefits (5)
Prevents algorithmic discrimination in discipline by banning AI-generated risk scores and watchlists, which disproportionately impact Black, Indigenous, students of color, students with disabilities, and LGBTQ students—groups already overrepresented in school discipline; this supports equitable treatment and due process.
Rights & LibertiesPeopleRef: Sec. 3(2), Sec. 4(1)(a)Bars use of biometric data to infer sensitive traits (e.g., mental health, gender identity, sexual orientation), protecting students from invasive surveillance and misclassification that could lead to discriminatory discipline or outing without consent.
Rights & LibertiesPeopleRef: Sec. 5(1)Limits data sharing with law enforcement to only when legally required or during imminent serious physical harm, strengthening student privacy and reducing the risk of over-criminalization of minor disciplinary issues.
Rights & LibertiesPeopleRef: Sec. 6(1)(a)Ensures human judgment remains central to discipline decisions, reducing risk of automated overreach and enabling context-sensitive responses (e.g., trauma-informed interventions) that may improve long-term school climate and safety.
Public SafetyPeopleRef: Sec. 3(1), Sec. 7(1)Requires OSPI and WSSDA to develop guidance and model policies in consultation with impacted communities, promoting evidence-based, equity-centered discipline practices and building capacity for trauma-responsive school environments.
EducationPeopleRef: Sec. 9, Sec. 10
Potential Concerns (5)
Reduces ability of schools to use predictive risk tools to identify students at high risk of violent behavior, potentially limiting early intervention for genuine safety threats; this is especially concerning in schools lacking sufficient human resources (e.g., counselors, behavioral specialists) to conduct manual risk assessments effectively.
Public SafetyPeopleRef: Sec. 3(1), Sec. 4(1)(a)Limits law enforcement access to student data during emergencies unless there is an *imminent* likelihood of serious physical harm, which may delay or hinder coordinated emergency response in cases where harm is likely but not yet imminent (e.g., credible threats of school shooting with timeline).
Public SafetyPeopleRef: Sec. 6(1)(b)Requires schools to retain discipline records per existing state law, but imposes no new recordkeeping burden beyond what is already required—no significant fiscal or administrative impact on local governments.
Local GovernmentRef: Sec. 7(2)Mandates OSPI and WSSDA to develop guidance and model policies, but fiscal impact is expected to be covered under existing budgets or federal grants; minimal new cost to districts beyond staff time to adopt/adapt policies.
Local GovernmentRef: Sec. 9, Sec. 10Prohibits facial recognition use for student surveillance in schools, which aligns with existing state restrictions and reduces need for districts to purchase or maintain expensive biometric surveillance infrastructure.
Local GovernmentRef: Sec. 8(8)
Who Is Most Affected
Students—especially those in protected categories (Black, Indigenous, students of color, students with disabilities, LGBTQ)—are protected from algorithmic bias, invasive biometric surveillance, and over-criminalization; discipline decisions will be more individualized and human-centered.
School districts and charter schools must revise discipline policies and vendor contracts, but avoid costly AI surveillance infrastructure; long-term benefits include reduced litigation risk, improved trust with families, and better alignment with equity mandates.
State-tribal education compact schools face the same compliance requirements as other public schools, which may require policy updates but also supports tribal sovereignty by enabling culturally grounded discipline approaches.
School employees gain clearer legal boundaries around AI use and biometric data, reducing liability exposure; however, they may face increased workload in manual oversight and documentation, especially in under-resourced districts.