{"id":45357,"topic":"ai","source":"FIRE | Foundation for Individual Rights and Expression","title":"Don’t let California turn universities into AI gatekeepers - FIRE | Foundation for Individual Rights and Expression","url":"https://www.fire.org/news/dont-let-california-turn-universities-ai-gatekeepers","url_hash":"1f90eb513b01b49e64a25e9e02b77cbe6637bb19","author":"","summary":"Don’t let California turn universities into AI gatekeepers FIRE | Foundation for Individual Rights and Expression","content":"Universities exist to advance knowledge through cutting-edge research and by training the next generation of thought leaders. Artificial intelligence is a growing part of that work. Yet a bill moving quickly through the California State Legislature threatens to place political constraints on its reach as a tool for research and exploration.\nAssembly Bill 2392 would require the California State University and the Chancellor of the California Community Colleges to convene a working group and establish procurement standards for generative AI — or GenAI — in line with certain state requirements. These requirements include ensuring that GenAI tools are evaluated for “potential harms, misuses, abuses, and bias,” and ensuring they will not produce “harmful” or “illegal” content. Although the bill provides a few examples of covered content, such as “disordered eating,” they don’t cure the underlying issue: these terms have no settled meaning and often depend on contested political and social judgments, making this mandate as broad as it is subjective.\nAnd while universities have a legitimate interest in prohibiting and responding to unlawful uses of their resources, vague anti-bias and anti-harm restrictions could prompt institutions to procure watered-down GenAI that avoids controversial ideas.\nCalifornia can ensure responsible GenAI use in higher education without undermining its educational and research potential through restrictions that cause it to deny, obscure, and avoid sensitive issues or “biased” answers.\nImagine a professor using GenAI to identify statistical correlations between crime and mental illness — research that might raise uncomfortable conclusions about institutionalization, homelessness, and public safety. She won’t get very far with GenAI that finds support for institutionalization stigmatizing and avoids “harmful” outputs. This tool might avoid such sensitive correlations or qualify answers so heavily that analysis becomes difficult. These system reluctances could permeate other delicate subjects like extremism, poverty, sex and gender, and race.\nThis is particularly unacceptable at universities, which are supposed to encourage students and faculty to confront difficult truths about our society and ourselves. In this way, members of the campus community educate themselves and push the boundaries of human knowledge. But that process short circuits if the tools provided by universities prevent unvarnished truth seeking.\nThese concerns extend beyond research. A philosophy student can explore an unpopular worldview by engaging GenAI in a back-and-forth debate. Such exercises are not only common in higher education, but indispensable to rigorous inquiry. It’s one way to avoid what John Stuart Mill called the “dead dogma” problem, where people continue to profess a belief without understanding or being able to defend the reasons for it. GenAI systems are ready-made devil’s advocates — available on demand to every student. But they can’t fill this role if they are trained to avoid the arguments students need to confront.\nApplying First Amendment principles to AI-generated expression is both a natural extension of those principles and a necessary step to prevent those principles’ weakening in other applications, including in areas like newspapers and video games.\nTo be clear, nothing in this bill directly prevents people from using non-procured GenAI. However, university policies may only allow school-approved GenAI systems in various contexts, including when working with student records, unpublished research, sensitive data, or information subject to confidentiality obligations. If AB 2392’s standards cause schools to procure heavily limited tools, many people on campus will be left with AI systems incapable of facilitating intellectual pursuits.\nCalifornia can ensure responsible GenAI use in higher education without undermining its educational and research potential through restrictions that cause it to deny, obscure, and avoid sensitive issues or “biased” answers. Lawmakers, for example, can order public institutions to provide training on the lawful use of GenAI or how to use AI effectively. These steps do not require restrictions that may limit a GenAI system’s ability to explore controversial or sensitive subjects.\nHigher education should be empowering today’s experts and tomorrow’s leaders to break new ground across a wide array of subjects. 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Artificial intelligence is a growing part of that work. Yet a bill moving quickly through the California State Legislature threatens to place political constraints on its reach as a tool for research and exploration.\nAssembly Bill 2392 would require the California State University and the Chancellor of the California Community Colleges to convene a working group and establish procurement standards for generative AI — or GenAI — in line with certain state requirements. These requirements include ensuring that GenAI tools are evaluated for “potential harms, misuses, abuses, and bias,” and ensuring they will not produce “harmful” or “illegal” content. Although the bill provides a few examples of covered content, such as “disordered eating,” they don’t cure the underlying issue: these terms have no settled meaning and often depend on contested political and social judgments, making this mandate as broad as it is subjective.\nAnd while universities have a legitimate interest in prohibiting and responding to unlawful uses of their resources, vague anti-bias and anti-harm restrictions could prompt institutions to procure watered-down GenAI that avoids controversial ideas.\nCalifornia can ensure responsible GenAI use in higher education without undermining its educational and research potential through restrictions that cause it to deny, obscure, and avoid sensitive issues or “biased” answers.\nImagine a professor using GenAI to identify statistical correlations between crime and mental illness — research that might raise uncomfortable conclusions about institutionalization, homelessness, and public safety. She won’t get very far with GenAI that finds support for institutionalization stigmatizing and avoids “harmful” outputs. This tool might avoid such sensitive correlations or qualify answers so heavily that analysis becomes difficult. These system reluctances could permeate other delicate subjects like extremism, poverty, sex and gender, and race.\nThis is particularly unacceptable at universities, which are supposed to encourage students and faculty to confront difficult truths about our society and ourselves. In this way, members of the campus community educate themselves and push the boundaries of human knowledge. But that process short circuits if the tools provided by universities prevent unvarnished truth seeking.\nThese concerns extend beyond research. A philosophy student can explore an unpopular worldview by engaging GenAI in a back-and-forth debate. Such exercises are not only common in higher education, but indispensable to rigorous inquiry. It’s one way to avoid what John Stuart Mill called the “dead dogma” problem, where people continue to profess a belief without understanding or being able to defend the reasons for it. GenAI systems are ready-made devil’s advocates — available on demand to every student. But they can’t fill this role if they are trained to avoid the arguments students need to confront.\nApplying First Amendment principles to AI-generated expression is both a natural extension of those principles and a necessary step to prevent those principles’ weakening in other applications, including in areas like newspapers and video games.\nTo be clear, nothing in this bill directly prevents people from using non-procured GenAI. However, university policies may only allow school-approved GenAI systems in various contexts, including when working with student records, unpublished research, sensitive data, or information subject to confidentiality obligations. If AB 2392’s standards cause schools to procure heavily limited tools, many people on campus will be left with AI systems incapable of facilitating intellectual pursuits.\nCalifornia can ensure responsible GenAI use in higher education without undermining its educational and research potential through restrictions that cause it to deny, obscure, and avoid sensitive issues or “biased” answers. Lawmakers, for example, can order public institutions to provide training on the lawful use of GenAI or how to use AI effectively. These steps do not require restrictions that may limit a GenAI system’s ability to explore controversial or sensitive subjects.\nHigher education should be empowering today’s experts and tomorrow’s leaders to break new ground across a wide array of subjects. 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Although the bill provides a few examples of covered content, such as “disordered eating,” they don’t cure the underlying issue: these terms have no settled meaning and often depend on contested political and social judgments, making this mandate as broad as it is subjective.\nAnd while universities have a legitimate interest in prohibiting and responding to unlawful uses of their resources, vague anti-bias and anti-harm restrictions could prompt institutions to procure watered-down GenAI that avoids controversial ideas.\nCalifornia can ensure responsible GenAI use in higher education without undermining its educational and research potential through restrictions that cause it to deny, obscure, and avoid sensitive issues or “biased” answers.\nImagine a professor using GenAI to identify statistical correlations between crime and mental illness — research that might raise uncomfortable conclusions about institutionalization, homelessness, and public safety. She won’t get very far with GenAI that finds support for institutionalization stigmatizing and avoids “harmful” outputs. This tool might avoid such sensitive correlations or qualify answers so heavily that analysis becomes difficult. These system reluctances could permeate other delicate subjects like extremism, poverty, sex and gender, and race.\nThis is particularly unacceptable at universities, which are supposed to encourage students and faculty to confront difficult truths about our society and ourselves. In this way, members of the campus community educate themselves and push the boundaries of human knowledge. But that process short circuits if the tools provided by universities prevent unvarnished truth seeking.\nThese concerns extend beyond research. A philosophy student can explore an unpopular worldview by engaging GenAI in a back-and-forth debate. Such exercises are not only common in higher education, but indispensable to rigorous inquiry. It’s one way to avoid what John Stuart Mill called the “dead dogma” problem, where people continue to profess a belief without understanding or being able to defend the reasons for it. GenAI systems are ready-made devil’s advocates — available on demand to every student. But they can’t fill this role if they are trained to avoid the arguments students need to confront.\nApplying First Amendment principles to AI-generated expression is both a natural extension of those principles and a necessary step to prevent those principles’ weakening in other applications, including in areas like newspapers and video games.\nTo be clear, nothing in this bill directly prevents people from using non-procured GenAI. However, university policies may only allow school-approved GenAI systems in various contexts, including when working with student records, unpublished research, sensitive data, or information subject to confidentiality obligations. 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Although the bill provides a few examples of covered content, such as “disordered eating,” they don’t cure the underlying issue: these terms have no settled meaning and often depend on contested political and social judgments, making this mandate as broad as it is subjective.\nAnd while universities have a legitimate interest in prohibiting and responding to unlawful uses of their resources, vague anti-bias and anti-harm restrictions could prompt institutions to procure watered-down GenAI that avoids controversial ideas.\nCalifornia can ensure responsible GenAI use in higher education without undermining its educational and research potential through restrictions that cause it to deny, obscure, and avoid sensitive issues or “biased” answers.\nImagine a professor using GenAI to identify statistical correlations between crime and mental illness — research that might raise uncomfortable conclusions about institutionalization, homelessness, and public safety. She won’t get very far with GenAI that finds support for institutionalization stigmatizing and avoids “harmful” outputs. This tool might avoid such sensitive correlations or qualify answers so heavily that analysis becomes difficult. These system reluctances could permeate other delicate subjects like extremism, poverty, sex and gender, and race.\nThis is particularly unacceptable at universities, which are supposed to encourage students and faculty to confront difficult truths about our society and ourselves. In this way, members of the campus community educate themselves and push the boundaries of human knowledge. But that process short circuits if the tools provided by universities prevent unvarnished truth seeking.\nThese concerns extend beyond research. A philosophy student can explore an unpopular worldview by engaging GenAI in a back-and-forth debate. Such exercises are not only common in higher education, but indispensable to rigorous inquiry. It’s one way to avoid what John Stuart Mill called the “dead dogma” problem, where people continue to profess a belief without understanding or being able to defend the reasons for it. GenAI systems are ready-made devil’s advocates — available on demand to every student. But they can’t fill this role if they are trained to avoid the arguments students need to confront.\nApplying First Amendment principles to AI-generated expression is both a natural extension of those principles and a necessary step to prevent those principles’ weakening in other applications, including in areas like newspapers and video games.\nTo be clear, nothing in this bill directly prevents people from using non-procured GenAI. However, university policies may only allow school-approved GenAI systems in various contexts, including when working with student records, unpublished research, sensitive data, or information subject to confidentiality obligations. If AB 2392’s standards cause schools to procure heavily limited tools, many people on campus will be left with AI systems incapable of facilitating intellectual pursuits.\nCalifornia can ensure responsible GenAI use in higher education without undermining its educational and research potential through restrictions that cause it to deny, obscure, and avoid sensitive issues or “biased” answers. Lawmakers, for example, can order public institutions to provide training on the lawful use of GenAI or how to use AI effectively. These steps do not require restrictions that may limit a GenAI system’s ability to explore controversial or sensitive subjects.\nHigher education should be empowering today’s experts and tomorrow’s leaders to break new ground across a wide array of subjects. 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These requirements include ensuring that GenAI tools are evaluated for “potential harms, misuses, abuses, and bias,” and ensuring they will not produce “harmful” or “illegal” content. Although the bill provides a few examples of covered content, such as “disordered eating,” they don’t cure the underlying issue: these terms have no settled meaning and often depend on contested political and social judgments, making this mandate as broad as it is subjective.\nAnd while universities have a legitimate interest in prohibiting and responding to unlawful uses of their resources, vague anti-bias and anti-harm restrictions could prompt institutions to procure watered-down GenAI that avoids controversial ideas.\nCalifornia can ensure responsible GenAI use in higher education without undermining its educational and research potential through restrictions that cause it to deny, obscure, and avoid sensitive issues or “biased” answers.\nImagine a professor using GenAI to identify statistical correlations between crime and mental illness — research that might raise uncomfortable conclusions about institutionalization, homelessness, and public safety. She won’t get very far with GenAI that finds support for institutionalization stigmatizing and avoids “harmful” outputs. This tool might avoid such sensitive correlations or qualify answers so heavily that analysis becomes difficult. These system reluctances could permeate other delicate subjects like extremism, poverty, sex and gender, and race.\nThis is particularly unacceptable at universities, which are supposed to encourage students and faculty to confront difficult truths about our society and ourselves. In this way, members of the campus community educate themselves and push the boundaries of human knowledge. But that process short circuits if the tools provided by universities prevent unvarnished truth seeking.\nThese concerns extend beyond research. A philosophy student can explore an unpopular worldview by engaging GenAI in a back-and-forth debate. Such exercises are not only common in higher education, but indispensable to rigorous inquiry. It’s one way to avoid what John Stuart Mill called the “dead dogma” problem, where people continue to profess a belief without understanding or being able to defend the reasons for it. GenAI systems are ready-made devil’s advocates — available on demand to every student. But they can’t fill this role if they are trained to avoid the arguments students need to confront.\nApplying First Amendment principles to AI-generated expression is both a natural extension of those principles and a necessary step to prevent those principles’ weakening in other applications, including in areas like newspapers and video games.\nTo be clear, nothing in this bill directly prevents people from using non-procured GenAI. However, university policies may only allow school-approved GenAI systems in various contexts, including when working with student records, unpublished research, sensitive data, or information subject to confidentiality obligations. 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